Publications

Cotta, C, Mathieson, L & Moscato, P 2018, 'Memetic Algorithms' in Resende, MGC, Marti, R & Pardalos, PM (eds), Handbook of Heuristics, Springer International Publishing, Switzerland, pp. 607-638.
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© Springer International Publishing AG, part of Springer Nature 2018. All rights reserved. Memetic algorithms provide one of the most effective and flexible metaheuristic approaches for tackling hard optimization problems. Memetic algorithms address the difficulty of developing high-performance universal heuristics by encouraging the exploitation of multiple heuristics acting in concert, making use of all available sources of information for a problem. This approach has resulted in a rich arsenal of heuristic algorithms and metaheuristic frameworks for many problems. This chapter discusses the philosophy of the memetic paradigm, lays out the structure of a memetic algorithm, develops several example algorithms, surveys recent work in the field, and discusses the possible future directions of memetic algorithms.

Liu, S, Wang, X, Zhou, L, Guan, J, Li, Y, He, Y, Duan, R & Ying, M 2018, 'Q|SI⟩ : A Quantum Programming Environment.' in Jones, CB, Wang, J & Zhan, N (eds), Symposium on Real-Time and Hybrid Systems, Springer, Switzerland, pp. 133-164.
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© Springer Nature Switzerland AG 2018. This paper describes a quantum programming environment, named Q| SI⟩, to support quantum programming using a quantum extension of the while -language. Embedded in the.Net framework, the Q| SI⟩ platform includes a quantum while -language compiler and a suite of tools to simulate quantum computation, optimize quantum circuits, analyze and verify quantum programs. This paper demonstrates Q| SI⟩ in use. Quantum behaviors are simulated on classical platforms with a combination of components and the compilation procedures for different back-ends are described in detail. Q| SI⟩ bridges the gap between quantum hardware and software. As a scalable framework, this platform allows users to code and simulate customized functions, optimize them for a range of quantum circuits, analyze the termination of a quantum program, and verify the program’s correctness (The software of Q| SI⟩ is available at http://www.qcompiler.com.).

Anshu, A, Berta, M, Jain, R & Tomamichel, M 2018, 'Partially smoothed information measures', IEEE Trans. Inf. Theory, vol. 66, pp. 5022-5036.
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Smooth entropies are a tool for quantifying resource trade-offs in (quantum)information theory and cryptography. In typical bi- and multi-partite problems,however, some of the sub-systems are often left unchanged and this is notreflected by the standard smoothing of information measures over a ball ofclose states. We propose to smooth instead only over a ball of close stateswhich also have some of the reduced states on the relevant sub-systems fixed.This partial smoothing of information measures naturally allows to give morerefined characterizations of various information-theoretic problems in theone-shot setting. In particular, we immediately get asymptotic second-ordercharacterizations for tasks such as privacy amplification against classicalside information or classical state splitting. For quantum problems like statemerging the general resource trade-off is tightly characterized by partiallysmoothed information measures as well.

Anshu, A, Hsieh, M-H & Jain, R 2018, 'Noisy quantum state redistribution with promise and the Alpha-bit', IEEE Transactions on Information Theory (IEEE-TIT), Volume: 66, Issue: 12, 2020, vol. 66, no. 12, pp. 7772-7786.
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We consider a variation of the well-studied quantum state redistributiontask, in which the starting state is known only to the receiver Bob and not tothe sender Alice. We refer to this as quantum state redistribution with aone-sided promise. In addition, we consider communication from Alice to Bobover a noisy channel $\mathcal{N}$, instead of the noiseless channel, as isusually considered in state redistribution. We take a natural approach towardsthe solution of this problem where we 'embed' the promise as part of the stateand then invoke known protocols for quantum state redistribution composed withknown protocols for transfer of quantum information over noisy channels. Usingour approach, we are able to reproduce the Alpha-bit capacities with or withoutentanglement assistance in Ref. [ArXiv:1706.09434], using known protocols forquantum state redistribution and quantum communication over noisy channels.Furthermore, we generalize the entanglement assisted classical Alpha-bitcapacity, showing that any quantum state redistribution protocol can be used asa black box to simulate classical communication.

Anshu, A, Hsieh, M-H & Jain, R 2018, 'Quantifying Resources in General Resource Theory with Catalysts', Physical Review Letters, vol. 121, no. 19.
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© 2018 American Physical Society. A question that is commonly asked in all areas of physics is how a certain property of a physical system can be used to achieve useful tasks and how to quantify the amount of such a property in a meaningful way. We answer this question by showing that, in a general resource-theoretic framework that allows the use of free states as catalysts, the amount of 'resources' contained in a given state, in the asymptotic scenario, is equal to the regularized relative entropy of a resource of that state. While we need to place a few assumptions on our resource-theoretical framework, it is still sufficiently general, and its special cases include quantum resource theories of entanglement, coherence, asymmetry, athermality, nonuniformity, and purity. As a by-product, our result also implies that the amount of noise one has to inject locally to erase all the entanglement contained in an entangled state is equal to the regularized relative entropy of entanglement.

Babbush, R, Berry, DW, Sanders, YR, Kivlichan, ID, Scherer, A, Wei, AY, Love, PJ & Aspuru-Guzik, A 2018, 'Exponentially more precise quantum simulation of fermions in the configuration interaction representation', Quantum Science and Technology, vol. 3, no. 1, pp. 015006-015006.
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We present a quantum algorithm for the simulation of molecular systems that is asymptotically more efficient than all previous algorithms in the literature in terms of the main problem parameters. As in Babbush et al (2016 New Journal of Physics 18, 033032), we employ a recently developed technique for simulating Hamiltonian evolution using a truncated Taylor series to obtain logarithmic scaling with the inverse of the desired precision. The algorithm of this paper involves simulation under an oracle for the sparse, first-quantized representation of the molecular Hamiltonian known as the configuration interaction (CI) matrix. We construct and query the CI matrix oracle to allow for on-the-fly computation of molecular integrals in a way that is exponentially more efficient than classical numerical methods. Whereas second-quantized representations of the wavefunction require qubits, where N is the number of single-particle spin-orbitals, the CI matrix representation requires qubits, where is the number of electrons in the molecule of interest. We show that the gate count of our algorithm scales at most as .

Berry, DW, Kieferová, M, Scherer, A, Sanders, YR, Low, GH, Wiebe, N, Gidney, C & Babbush, R 2018, 'Improved techniques for preparing eigenstates of fermionic Hamiltonians', npj Quantum Information, vol. 4, no. 1.
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AbstractModeling low energy eigenstates of fermionic systems can provide insight into chemical reactions and material properties and is one of the most anticipated applications of quantum computing. We present three techniques for reducing the cost of preparing fermionic Hamiltonian eigenstates using phase estimation. First, we report a polylogarithmic-depth quantum algorithm for antisymmetrizing the initial states required for simulation of fermions in first quantization. This is an exponential improvement over the previous state-of-the-art. Next, we show how to reduce the overhead due to repeated state preparation in phase estimation when the goal is to prepare the ground state to high precision and one has knowledge of an upper bound on the ground state energy that is less than the excited state energy (often the case in quantum chemistry). Finally, we explain how one can perform the time evolution necessary for the phase estimation based preparation of Hamiltonian eigenstates with exactly zero error by using the recently introduced qubitization procedure.

Cao, Y, Romero, J, Olson, JP, Degroote, M, Johnson, PD, Kieferová, M, Kivlichan, ID, Menke, T, Peropadre, B, Sawaya, NPD, Sim, S, Veis, L & Aspuru-Guzik, A 2018, 'Quantum Chemistry in the Age of Quantum Computing', Chemical Reviews, vol. 119, no. 19.
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Practical challenges in simulating quantum systems on classical computershave been widely recognized in the quantum physics and quantum chemistrycommunities over the past century. Although many approximation methods havebeen introduced, the complexity of quantum mechanics remains hard to appease.The advent of quantum computation brings new pathways to navigate thischallenging complexity landscape. By manipulating quantum states of matter andtaking advantage of their unique features such as superposition andentanglement, quantum computers promise to efficiently deliver accurate resultsfor many important problems in quantum chemistry such as the electronicstructure of molecules. In the past two decades significant advances have beenmade in developing algorithms and physical hardware for quantum computing,heralding a revolution in simulation of quantum systems. This article is anoverview of the algorithms and results that are relevant for quantum chemistry.The intended audience is both quantum chemists who seek to learn more aboutquantum computing, and quantum computing researchers who would like to exploreapplications in quantum chemistry.

Cheng, H-C, Hanson, EP, Datta, N & Hsieh, M-H 2018, 'Non-Asymptotic Classical Data Compression with Quantum Side Information', IEEE Transactions on Information Theory, vol. 67, no. 2, pp. 902-930.
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In this paper, we analyze classical data compression with quantum sideinformation (also known as the classical-quantum Slepian-Wolf protocol) in theso-called large and moderate deviation regimes. In the non-asymptotic setting,the protocol involves compressing classical sequences of finite length $n$ anddecoding them with the assistance of quantum side information. In the largedeviation regime, the compression rate is fixed, and we obtain bounds on theerror exponent function, which characterizes the minimal probability of erroras a function of the rate. Devetak and Winter showed that the asymptotic datacompression limit for this protocol is given by a conditional entropy. For anyprotocol with a rate below this quantity, the probability of error converges toone asymptotically and its speed of convergence is given by the strong converseexponent function. We obtain finite blocklength bounds on this function, anddetermine exactly its asymptotic value. In the moderate deviation regime forthe compression rate, the latter is no longer considered to be fixed. It isallowed to depend on the blocklength $n$, but assumed to decay slowly to theasymptotic data compression limit. Starting from a rate above this limit, wedetermine the speed of convergence of the error probability to zero and showthat it is given in terms of the conditional information variance. Our resultscomplement earlier results obtained by Tomamichel and Hayashi, in which theyanalyzed the so-called small deviation regime of this protocol.

Chitambar, E, Fortescue, B & Hsieh, M-H 2018, 'The Conditional Common Information in Classical and Quantum Secret Key Distillation', IEEE Transactions on Information Theory, vol. 64, no. 11, pp. 7381-7394.
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© 2018 IEEE. In this paper, we consider two extensions of the Gács-Körner common information to three variables, the conditional common information (cCI) and the coarse-grained conditional common information (ccCI). Both quantities are shown to be useful technical tools in the study of classical and quantum resource transformations. In particular, the ccCI is shown to have an operational interpretation as the optimal rate of secret key extraction from an eavesdropped classical source pXYZ when Alice (X) and Bob (Y) are unable to communicate but share common randomness with the eavesdropper Eve (Z). Moving to the quantum setting, we consider two different ways of generating a tripartite quantum state from classical correlations pXYZ : 1) coherent encodings ∑xyz√pxyz|xyz〉 and 2) incoherent encodings ∑xyzpxyz|xyz〉〈xyz|. We study how well can Alice and Bob extract secret key from these quantum sources using quantum operations compared with the extraction of key from the underlying classical sources pXYZ using classical operations. While the power of quantum mechanics increases Alice and Bob's ability to generate shared randomness, it also equips Eve with a greater arsenal of eavesdropping attacks. Therefore, it is not obvious who gains the greatest advantage for distilling secret key when replacing a classical source with a quantum one. We first demonstrate that the classical key rate of pXYZ is equivalent to the quantum key rate for an incoherent quantum encoding of the distribution. For coherent encodings, we next show that the classical and quantum rates are generally incomparable, and in fact, their difference can be arbitrarily large in either direction. Finally, we introduce a 'zoo' of entangled tripartite states all characterized by the conditional common information of their encoded probability distributions. Remarkably, for these states almost all entanglement measures, such as Alice and Bob's entanglement cost, squashed entanglement, and relative ...

Chou, K-P, Prasad, M, Wu, D, Sharma, N, Li, D-L, Lin, Y-F, Blumenstein, M, Lin, W-C & Lin, C-T 2018, 'Robust Feature-Based Automated Multi-View Human Action Recognition System', IEEE Access, vol. 6, pp. 15283-15296.
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© 2013 IEEE. Automated human action recognition has the potential to play an important role in public security, for example, in relation to the multiview surveillance videos taken in public places, such as train stations or airports. This paper compares three practical, reliable, and generic systems for multiview video-based human action recognition, namely, the nearest neighbor classifier, Gaussian mixture model classifier, and the nearest mean classifier. To describe the different actions performed in different views, view-invariant features are proposed to address multiview action recognition. These features are obtained by extracting the holistic features from different temporal scales which are modeled as points of interest which represent the global spatial-temporal distribution. Experiments and cross-data testing are conducted on the KTH, WEIZMANN, and MuHAVi datasets. The system does not need to be retrained when scenarios are changed which means the trained database can be applied in a wide variety of environments, such as view angle or background changes. The experiment results show that the proposed approach outperforms the existing methods on the KTH and WEIZMANN datasets.

Chubb, CT, Tomamichel, M & Korzekwa, K 2018, 'Moderate deviation analysis of majorisation-based resource interconversion', Phys. Rev. A, vol. 99, no. 3, p. 032332.
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We consider the problem of interconverting a finite amount of resourceswithin all theories whose single-shot transformation rules are based on amajorisation relation, e.g. the resource theories of entanglement and coherence(for pure state transformations), as well as thermodynamics (forenergy-incoherent transformations). When only finite resources are available weexpect to see a non-trivial trade-off between the rate $r_n$ at which $n$copies of a resource state $\rho$ can be transformed into $nr_n$ copies ofanother resource state $\sigma$, and the error level $\varepsilon_n$ of theinterconversion process, as a function of $n$. In this work we derive theoptimal trade-off in the so-called moderate deviation regime, where the rate ofinterconversion $r_n$ approaches its optimum in the asymptotic limit ofunbounded resources ($n\to\infty$), while the error $\epsilon_n$ vanishes inthe same limit. We find that the moderate deviation analysis exhibits aresonance behaviour which implies that certain pairs of resource states can beinterconverted at the asymptotically optimal rate with negligible error, evenin the finite $n$ regime.

Combes, J, Ferrie, C, Leifer, MS & Pusey, MF 2018, 'Why protective measurement does not establish the reality of the quantum state', Quantum Studies: Mathematics and Foundations, vol. 5, no. 2, pp. 189-211.
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Das, A, Suwanwiwat, H, Ferrer, MA, Pal, U & Blumenstein, M 2018, 'Thai automatic signature verification system employing textural features', IET Biometrics, vol. 7, no. 6, pp. 615-627.
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© The Institution of Engineering and Technology 2018. This study focuses on a comprehensive study of Automatic Signature Verification (ASV) for off-line Thai signatures; an investigation was carried out to characterise the challenges in Thai ASV and to baseline the performance of Thai ASV employing baseline features, being Local Binary Pattern, Local Directional Pattern, Local Binary and Directional Patterns combined (LBDP), and the baseline shape/feature-based hidden Markov model. As there was no publicly available Thai signature database found in the literature, the authors have developed and proposed a database considering real-world signatures from Thailand. The authors have also identified their latent challenges and characterised Thai signature-based ASV. The database consists of 5,400 signatures from 100 signers. Thai signatures could be bi-script in nature, considering the fact that a single signature can contain only Thai or Roman characters or contain both Roman and Thai, which poses an interesting challenge for script-independent SV. Therefore, along with the baseline experiments, the investigation on the influence and nature of bi-script ASV was also conducted. From the equal error rates and Bhattacharyya distance, the score achieved in the experiments indicate that the Thai SV scenario is a script-independent problem. The open research area on this subject of research has also been addressed.

Dickel, C, Wesdorp, JJ, Langford, NK, Peiter, S, Sagastizabal, R, Bruno, A, Criger, B, Motzoi, F & DiCarlo, L 2018, 'Chip-to-chip entanglement of transmon qubits using engineered measurement fields', Physical Review B, vol. 97, no. 6.
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© 2018 American Physical Society. While the on-chip processing power in circuit QED devices is growing rapidly, an open challenge is to establish high-fidelity quantum links between qubits on different chips. Here, we show entanglement between transmon qubits on different cQED chips with 49% concurrence and 73% Bell-state fidelity. We engineer a half-parity measurement by successively reflecting a coherent microwave field off two nearly identical transmon-resonator systems. By ensuring the measured output field does not distinguish |01) from |10), unentangled superposition states are probabilistically projected onto entangled states in the odd-parity subspace. We use in situ tunability and an additional weakly coupled driving field on the second resonator to overcome imperfect matching due to fabrication variations. To demonstrate the flexibility of this approach, we also produce an even-parity entangled state of similar quality, by engineering the matching of outputs for the |00) and |11) states. The protocol is characterized over a range of measurement strengths using quantum state tomography showing good agreement with a comprehensive theoretical model.

Du, Y, Hsieh, M-H, Liu, T & Tao, D 2018, 'A Grover-search Based Quantum Learning Scheme for Classification', New J. Phys., vol. 23, no. 2, p. 023020.
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The hybrid quantum-classical learning scheme provides a prominent way toachieve quantum advantages on near-term quantum devices. A concrete exampletowards this goal is the quantum neural network (QNN), which has been developedto accomplish various supervised learning tasks such as classification andregression. However, there are two central issues that remain obscure when QNNis exploited to accomplish classification tasks. First, a quantum classifierthat can well balance the computational cost such as the number of measurementsand the learning performance is unexplored. Second, it is unclear whetherquantum classifiers can be applied to solve certain problems that outperformtheir classical counterparts. Here we devise a Grover-search based quantumlearning scheme (GBLS) to address the above two issues. Notably, most existingQNN-based quantum classifiers can be seamlessly embedded into the proposedscheme. The key insight behind our proposal is reformulating the classificationtasks as the search problem. Numerical simulations exhibit that GBLS canachieve comparable performance with other quantum classifiers under variousnoise settings, while the required number of measurements is dramaticallyreduced. We further demonstrate a potential quantum advantage of GBLS overclassical classifiers in the measure of query complexity. Our work providesguidance to develop advanced quantum classifiers on near-term quantum devicesand opens up an avenue to explore potential quantum advantages in variousclassification tasks.

Du, Y, Hsieh, M-H, Liu, T & Tao, D 2018, 'The Expressive Power of Parameterized Quantum Circuits', Phys. Rev. Research, vol. 2, no. 3, p. 033125.
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Parameterized quantum circuits (PQCs) have been broadly used as a hybridquantum-classical machine learning scheme to accomplish generative tasks.However, whether PQCs have better expressive power than classical generativeneural networks, such as restricted or deep Boltzmann machines, remains an openissue. In this paper, we prove that PQCs with a simple structure alreadyoutperform any classical neural network for generative tasks, unless thepolynomial hierarchy collapses. Our proof builds on known results from tensornetworks and quantum circuits (in particular, instantaneous quantum polynomialcircuits). In addition, PQCs equipped with ancillary qubits for post-selectionhave even stronger expressive power than those without post-selection. Weemploy them as an application for Bayesian learning, since it is possible tolearn prior probabilities rather than assuming they are known. We expect thatit will find many more applications in semi-supervised learning where priordistributions are normally assumed to be unknown. Lastly, we conduct severalnumerical experiments using the Rigetti Forest platform to demonstrate theperformance of the proposed Bayesian quantum circuit.

Gour, G, Jennings, D, Buscemi, F, Duan, R & Marvian, I 2018, 'Quantum majorization and a complete set of entropic conditions for quantum thermodynamics', Nature Communications, vol. 9, no. 1.
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AbstractWhat does it mean for one quantum process to be more disordered than another? Interestingly, this apparently abstract question arises naturally in a wide range of areas such as information theory, thermodynamics, quantum reference frames, and the resource theory of asymmetry. Here we use a quantum-mechanical generalization of majorization to develop a framework for answering this question, in terms of single-shot entropies, or equivalently, in terms of semi-definite programs. We also investigate some of the applications of this framework, and remarkably find that, in the context of quantum thermodynamics it provides the first complete set of necessary and sufficient conditions for arbitrary quantum state transformations under thermodynamic processes, which rigorously accounts for quantum-mechanical properties, such as coherence. Our framework of generalized thermal processes extends thermal operations, and is based on natural physical principles, namely, energy conservation, the existence of equilibrium states, and the requirement that quantum coherence be accounted for thermodynamically.

Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'A local and scalable lattice renormalization method for ballistic quantum computation', npj Quantum Information, vol. 4, no. 1, pp. 1-8.
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AbstractA recent proposal has shown that it is possible to perform linear-optics quantum computation using a ballistic generation of the lattice. Yet, due to the probabilistic generation of its cluster state, it is not possible to use the fault-tolerant Raussendorf lattice, which requires a lower failure rate during the entanglement-generation process. Previous work in this area showed proof-of-principle linear-optics quantum computation, while this paper presents an approach to it which is more practical, satisfying several key constraints. We develop a classical measurement scheme that purifies a large faulty lattice to a smaller lattice with entanglement faults below threshold. A single application of this method can reduce the entanglement error rate to 7% for an input failure rate of 25%. Thus, we can show that it is possible to achieve fault tolerance for ballistic methods.

Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'Lattice surgery on the Raussendorf lattice', Quantum Science and Technology, vol. 3, no. 3, pp. 035011-035011.
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© 2018 IOP Publishing Ltd. Lattice surgery is a method to perform quantum computation fault-tolerantly by using operations on boundary qubits between different patches of the planar code. This technique allows for universal planar code computation without eliminating the intrinsic two-dimensional nearest-neighbor properties of the surface code that eases physical hardware implementations. Lattice surgery approaches to algorithmic compilation and optimization have been demonstrated to be more resource efficient for resource-intensive components of a fault-tolerant algorithm, and consequently may be preferable over braid-based logic. Lattice surgery can be extended to the Raussendorf lattice, providing a measurement-based approach to the surface code. In this paper we describe how lattice surgery can be performed on the Raussendorf lattice and therefore give a viable alternative to computation using braiding in measurement-based implementations of topological codes.

Huber, S, Koenig, R & Tomamichel, M 2018, 'Jointly constrained semidefinite bilinear programming with an application to Dobrushin curves', IEEE Trans Inf Theory, vol. 56, no. 5, pp. 2934-2950.
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We propose a branch-and-bound algorithm for minimizing a bilinear functionalof the form \[ f(X,Y) = \mathrm{tr}((X\otimesY)Q)+\mathrm{tr}(AX)+\mathrm{tr}(BY) , \] of pairs of Hermitian matrices$(X,Y)$ restricted by joint semidefinite programming constraints. Thefunctional is parametrized by self-adjoint matrices $Q$, $A$ and $B$. Thisproblem generalizes that of a bilinear program, where $X$ and $Y$ belong topolyhedra. The algorithm converges to a global optimum and yields upper andlower bounds on its value in every step. Various problems in quantuminformation theory can be expressed in this form. As an example application, wecompute Dobrushin curves of quantum channels, giving upper bounds on classicalcoding with energy constraints.

Ivanyos, G, Kulkarni, R, Qiao, Y, Santha, M & Sundaram, A 2018, 'On the complexity of trial and error for constraint satisfaction problems', Journal of Computer and System Sciences, vol. 92, pp. 48-64.
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© 2017 Elsevier Inc. In 2013 Bei, Chen and Zhang introduced a trial and error model of computing, and applied to some constraint satisfaction problems. In this model the input is hidden by an oracle which, for a candidate assignment, reveals some information about a violated constraint if the assignment is not satisfying. In this paper we initiate a systematic study of constraint satisfaction problems in the trial and error model, by adopting a formal framework for CSPs, and defining several types of revealing oracles. Our main contribution is to develop a transfer theorem for each type of the revealing oracle. To any hidden CSP with a specific type of revealing oracle, the transfer theorem associates another CSP in the normal setting, such that their complexities are polynomial-time equivalent. This in principle transfers the study of a large class of hidden CSPs to the study of normal CSPs. We apply the transfer theorems to get polynomial-time algorithms or hardness results for several families of concrete problems.

Ivanyos, G, Qiao, Y & Subrahmanyam, KV 2018, 'Constructive non-commutative rank computation is in deterministic polynomial time', computational complexity, vol. 27, no. 4, pp. 561-593.
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© 2018, Springer International Publishing AG, part of Springer Nature. We extend the techniques developed in Ivanyos et al. (Comput Complex 26(3):717–763, 2017) to obtain a deterministic polynomial-time algorithm for computing the non-commutative rank of linear spaces of matrices over any field. The key new idea that causes a reduction in the time complexity of the algorithm in Ivanyos et al. (2017) from exponential time to polynomial time is a reduction procedure that keeps the blow-up parameter small, and there are two methods to implement this idea: the first one is a greedy argument that removes certain rows and columns, and the second one is an efficient algorithmic version of a result of Derksen & Makam (Adv Math 310:44–63, 2017b), who were the first to observe that the blow-up parameter can be controlled. Both methods rely crucially on the regularity lemma from Ivanyos et al. (2017). In this note, we improve that lemma by removing a coprime condition there.

Korzekwa, K, Chubb, CT & Tomamichel, M 2018, 'Avoiding irreversibility: engineering resonant conversions of quantum resources', Phys. Rev. Lett., vol. 122, no. 11, p. 110403.
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We identify and explore the intriguing property of resource resonance arisingwithin resource theories of entanglement, coherence and thermodynamics. Whilethe theories considered are reversible asymptotically, the same is generallynot true in realistic scenarios where the available resources are bounded. Thefinite-size effects responsible for this irreversibility could potentiallyprohibit small quantum information processors or thermal machines fromachieving their full potential. Nevertheless, we show here that by carefullyengineering the resource interconversion process any such losses can be greatlysuppressed. Our results are predicted by higher order expansions of thetrade-off between the rate of resource interconversion and the achievedfidelity, and are verified by exact numerical optimizations of appropriateapproximate majorization conditions.

Kounalakis, M, Dickel, C, Bruno, A, Langford, NK & Steele, GA 2018, 'Tuneable hopping and nonlinear cross-Kerr interactions in a high-coherence superconducting circuit', npj Quantum Information, vol. 4, no. 1.
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AbstractAnalog quantum simulations offer rich opportunities for exploring complex quantum systems and phenomena through the use of specially engineered, well-controlled quantum systems. A critical element, increasing the scope and flexibility of such experimental platforms, is the ability to access and tune in situ different interaction regimes. Here, we present a superconducting circuit building block of two highly coherent transmons featuring in situ tuneable photon hopping and nonlinear cross-Kerr couplings. The interactions are mediated via a nonlinear coupler, consisting of a large capacitor in parallel with a tuneable superconducting quantum interference device (SQUID). We demonstrate the working principle by experimentally characterising the system in the single-excitation and two-excitation manifolds, and derive a full theoretical model that accurately describes our measurements. Both qubits have high coherence properties, with typical relaxation times in the range of 15 to 40 μs at all bias points of the coupler. Our device could be used as a scalable building block in analog quantum simulators of extended Bose-Hubbard and Heisenberg XXZ models, and may also have applications in quantum computing such as realising fast two-qubit gates and perfect state transfer protocols.

Lanese, I & Devitt, S 2018, 'Preface for the special issue of the 8th Conference on Reversible Computation (RC 2016)', Science of Computer Programming, vol. 151, pp. 1-1.
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Lu, S, Huang, S, Li, K, Li, J, Chen, J, Lu, D, Ji, Z, Shen, Y, Zhou, D & Zeng, B 2018, 'Separability-entanglement classifier via machine learning', Physical Review A, vol. 98, no. 1.
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© 2018 American Physical Society. The problem of determining whether a given quantum state is entangled lies at the heart of quantum information processing. Despite the many methods - such as the positive partial transpose criterion and the k-symmetric extendibility criterion - to tackle this problem, none of them enables a general, practical solution due to the problem's NP-hard complexity. Explicitly, separable states form a high-dimensional convex set of vastly complicated structures. In this work, we build a different separability-entanglement classifier underpinned by machine learning techniques. We use standard tools from machine learning to learn the entanglement feature of arbitrary given quantum states. We perform substantial numerical tests on two-qubit and two-qutrit systems, and the results indicate that our method can outperform the existing methods in generic cases in terms of both speed and accuracy. This opens up avenues to explore quantum entanglement via the machine learning approach.

Luo, Y, Li, Y & Hsieh, M-H 2018, 'Inequivalent Multipartite Coherence Classes and New Coherence Monotones', Phys. Rev. A, vol. 99, no. 4, p. 042306.
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Quantum coherence has received significant attention in recent years, but itsstudy is mostly conducted in single party settings. In this paper, wegeneralize important results in multipartite entanglement theory to theircounterparts in quantum coherence theory. First, we give a necessary andsufficient condition for when two pure multipartite states are equivalent underlocal quantum incoherent operations and classical communication (LICC), i.e.,two states can be deterministically transformed to each other under LICCoperations. Next, we investigate and give the conditions in which such atransformation succeeds only stochastically. Different from entanglement casefor two-qubit states, we find that the SLICC equivalence classes are infinite.Moreover, it's possible that there are some classes of states in multipartiteentanglement can convert into each other, while, they cannot convert into eachother in multipartite coherence. In order to show the difference among SLICCclasses, we introduce two coherence monotones: accessible coherence and sourcecoherence, following the logistics given in [\emph{Phys.~Rev.~Lett. 115,~150502(2015)}]. These coherence monotones have a straightforward operationalinterpretation, namely, the accessible coherence characterizes the proficiencyof a state to generate other states via quantum incoherent operations, whilethe source coherence characterizes the set of states that can be reached viaquantum incoherent operations acting on the given state of interest.

Luthi, F, Stavenga, T, Enzing, OW, Bruno, A, Dickel, C, Langford, NK, Rol, MA, Jespersen, TS, Nygård, J, Krogstrup, P & DiCarlo, L 2018, 'Evolution of Nanowire Transmon Qubits and Their Coherence in a Magnetic Field', Physical Review Letters, vol. 120, no. 10.
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We present an experimental study of flux- and gate-tunable nanowire transmons with state-of-the-art relaxation time allowing quantitative extraction of flux and charge noise coupling to the Josephson energy. We evidence coherence sweet spots for charge, tuned by voltage on a proximal side gate, where first order sensitivity to switching two-level systems and background 1/f noise is minimized. Next, we investigate the evolution of a nanowire transmon in a parallel magnetic field up to 70 mT, the upper bound set by the closing of the induced gap. Several features observed in the field dependence of qubit energy relaxation and dephasing times are not fully understood. Using nanowires with a thinner, partially covering Al shell will enable operation of these circuits up to 0.5 T, a regime relevant for topological quantum computation and other applications.

Mann, RL & Bremner, MJ 2018, 'Approximation Algorithms for Complex-Valued Ising Models on Bounded Degree Graphs', Quantum, vol. 3, p. 162.
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We study the problem of approximating the Ising model partition function withcomplex parameters on bounded degree graphs. We establish a deterministicpolynomial-time approximation scheme for the partition function when theinteractions and external fields are absolutely bounded close to zero.Furthermore, we prove that for this class of Ising models the partitionfunction does not vanish. Our algorithm is based on an approach due to Barvinokfor approximating evaluations of a polynomial based on the location of thecomplex zeros and a technique due to Patel and Regts for efficiently computingthe leading coefficients of graph polynomials on bounded degree graphs.Finally, we show how our algorithm can be extended to approximate certainoutput probability amplitudes of quantum circuits.

Paler, A & Devitt, SJ 2018, 'Specification format and a verification method of fault-tolerant quantum circuits', Physical Review A, vol. 98, no. 2, pp. 1-9.
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© 2018 American Physical Society. Quantum computations are expressed in general as quantum circuits, which are specified by ordered lists of quantum gates. The resulting specifications are used during the optimization and execution of the expressed computations. However, the specification format makes it difficult to verify that optimized or executed computations still conform to the initial gate list specifications: showing the computational equivalence between two quantum circuits expressed by different lists of quantum gates is exponentially complex in the worst case. In order to solve this issue, this work presents a derivation of the specification format tailored specifically for fault-tolerant quantum circuits. The circuits are considered a form consisting entirely of single qubit initializations, cnot gates, and single qubit measurements (ICM form). This format allows, under certain assumptions, to efficiently verify optimized (or implemented) computations. Two verification methods based on checking stabilizer circuit structures are presented.

Peng, H, Zheng, Y, Blumenstein, M, Tao, D & Li, J 2018, 'CRISPR/Cas9 cleavage efficiency regression through boosting algorithms and Markov sequence profiling', Bioinformatics, vol. 34, no. 18, pp. 3069-3077.
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AbstractMotivationCRISPR/Cas9 system is a widely used genome editing tool. A prediction problem of great interests for this system is: how to select optimal single-guide RNAs (sgRNAs), such that its cleavage efficiency is high meanwhile the off-target effect is low.ResultsThis work proposed a two-step averaging method (TSAM) for the regression of cleavage efficiencies of a set of sgRNAs by averaging the predicted efficiency scores of a boosting algorithm and those by a support vector machine (SVM). We also proposed to use profiled Markov properties as novel features to capture the global characteristics of sgRNAs. These new features are combined with the outstanding features ranked by the boosting algorithm for the training of the SVM regressor. TSAM improved the mean Spearman correlation coefficiencies comparing with the state-of-the-art performance on benchmark datasets containing thousands of human, mouse and zebrafish sgRNAs. Our method can be also converted to make binary distinctions between efficient and inefficient sgRNAs with superior performance to the existing methods. The analysis reveals that highly efficient sgRNAs have lower melting temperature at the middle of the spacer, cut at 5’-end closer parts of the genome and contain more ‘A’ but less ‘G’ comparing with inefficient ones. Comprehensive further analysis also demonstrates that our tool can predict an sgRNA’s cutting efficiency with consistently good performance no matter it is expressed from an U6 promoter in cells or from a T7 promoter in vitro.Availability and implementationOnline tool is available at http://www.aai-bioinfo.com/CRISPR/. Python and Matlab source codes are freely available at https://github.com/penn-hui/TSAM.Supplementary information

Quadeer, M, Tomamichel, M & Ferrie, C 2018, 'Minimax quantum state estimation under Bregman divergence', Quantum, vol. 3, p. 126.
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We investigate minimax estimators for quantum state tomography under generalBregman divergences. First, generalizing the work of Komaki et al.$\href{http://dx.doi.org/10.3390/e19110618}{\textrm{[Entropy 19, 618 (2017)]}}$for relative entropy, we find that given any estimator for a quantum state,there always exists a sequence of Bayes estimators that asymptotically performat least as well as the given estimator, on any state. Second, we show thatthere always exists a sequence of priors for which the corresponding sequenceof Bayes estimators is asymptotically minimax (i.e. it minimizes the worst-caserisk). Third, by re-formulating Holevo's theorem for the covariant stateestimation problem in terms of estimators, we find that any covariantmeasurement is, in fact, minimax (i.e. it minimizes the worst-case risk).Moreover, we find that a measurement is minimax if it is only covariant under aunitary 2-design. Lastly, in an attempt to understand the problem of findingminimax measurements for general state estimation, we study the qubit case indetail and find that every spherical 2-design is a minimax measurement.

Salek, F, Anshu, A, Hsieh, M-H, Jain, R & Fonollosa, JR 2018, 'One-shot Capacity bounds on the Simultaneous Transmission of Classical and Quantum Information', IEEE Transactions on Information Theory ( Volume: 66, Issue: 4, April 2020 ), vol. 66, no. 4, pp. 2141-2164.
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We study the communication capabilities of a quantum channel under the mostgeneral channel model known as the one-shot model. Unlike classical channelsthat can only be used to transmit classical information (bits), a quantumchannel can be used for transmission of classical information, quantuminformation (qubits) and simultaneous transmission of classical and quantuminformation. In this work, we investigate the one-shot capabilities of aquantum channel for simultaneously transmitting of bits and qubits. Thisproblem was studied in the asymptotic regime for a memoryless channel and aregularized characterization of the capacity region was reported. It is knownthat the transmission of private classical information is closely related tothe problem of quantum information transmission. We resort to this idea andfind achievable and converse bounds on the simultaneous transmission of thepublic and private classical information. then by shifting the classicalprivate rate to the quantum information rate, the obtained rate regions will betranslated into rate regions of thThis in turn, leads to a rate region forsimulttaneous transmission of classical and quantum information. In the case ofasymptotic i.i.d. setting, our one-shot result is evaluated to the knownresults in the literature. Our main tools used in the achievability proofs areposition-based decoding and convex-split lemma.

Stapelberg, NJC, Pratt, R, Neumann, DL, Shum, DHK, Brandis, S, Muthukkumarasamy, V, Stantic, B, Blumenstein, M & Headrick, JP 2018, 'From feedback loop transitions to biomarkers in the psycho-immune-neuroendocrine network: Detecting the critical transition from health to major depression', Neuroscience & Biobehavioral Reviews, vol. 90, pp. 1-15.
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Stewart, RA, Nguyen, K, Beal, C, Zhang, H, Sahin, O, Bertone, E, Vieira, AS, Castelletti, A, Cominola, A, Giuliani, M, Giurco, D, Blumenstein, M, Turner, A, Liu, A, Kenway, S, Savić, DA, Makropoulos, C & Kossieris, P 2018, 'Integrated intelligent water-energy metering systems and informatics: Visioning a digital multi-utility service provider', Environmental Modelling & Software, vol. 105, pp. 94-117.
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© 2018 Elsevier Ltd Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. Providers that can install low-cost integrative systems will reap the benefits of derived operational synergies and access to mass markets not bounded by historical city, state or country limits. This paper provides a vision of the required transformative process and features of an integrated multi-utility service provider covering the system architecture, opportunities and benefits, impediments and strategies, and business opportunities. The heart of the paper is focused on demonstrating data modelling processes and informatics opportunities for contemporaneously collected demand data, through illustrative examples and four informative water-energy nexus case studies. Finally, the paper provides an overview of the transformative R&D priorities to realise the vision.

Taranto, P, Pollock, FA, Milz, S, Tomamichel, M & Modi, K 2018, 'Quantum Markov Order', Phys. Rev. Lett., vol. 122, no. 14, p. 140401.
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We formally extend the notion of Markov order to open quantum processes byaccounting for the instruments used to probe the system of interest atdifferent times. Our description recovers the classical Markov order propertyin the appropriate limit: when the stochastic process is classical and theinstruments are non-invasive, \emph{i.e.}, restricted to orthogonal, projectivemeasurements. We then prove that there do not exist non-Markovian quantumprocesses that have finite Markov order with respect to all possibleinstruments; the same process exhibits distinct memory effects with respect todifferent probing instruments. This naturally leads to a relaxed definition ofquantum Markov order with respect to specified sequences of instruments. Thememory effects captured by different choices of instruments vary dramatically,providing a rich landscape for future exploration.

Vijayan, MK, Chitambar, E & Hsieh, M-H 2018, 'One-shot assisted concentration of coherence', Journal of Physics A: Mathematical and Theoretical 51.41 (2018): 414001, vol. 51, no. 41.
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We find one-shot bounds for concentration of maximally coherent states in theso called assisted scenario. In this setting, Bob is restricted to performingincoherent operations on his quantum system, however he is assisted by Alice,who holds a purification of Bob's state and can send classical data to him. Wefurther show that in the asymptotic limit our one-shot bounds recover thepreviously computed rate of asymptotic assisted concentration.

Youssry, A, Ferrie, C & Tomamichel, M 2018, 'Efficient online quantum state estimation using a matrix-exponentiated gradient method', New J. Phys., vol. 21, no. 3, p. 033006.
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In this paper, we explore an efficient online algorithm for quantum stateestimation based on a matrix-exponentiated gradient method previously used inthe context of machine learning. The state update is governed by a learningrate that determines how much weight is given to the new measurement resultsobtained in each step. We show convergence of the running state estimate inprobability to the true state for both noiseless and noisy measurements. Wefind that in the latter case the learning rate has to be chosen adaptively anddecreasing to guarantee convergence beyond the noise threshold. As a practicalalternative we then propose to use running averages of the measurementstatistics and a constant learning rate to overcome the noise problem. Theproposed algorithm is numerically compared with batch maximum-likelihood andleast-squares estimators. The results show a superior performance of the newalgorithm in terms of accuracy and runtime complexity.

Zhang, C, Gao, X, Hsieh, M-H, Hang, H & Tao, D 2018, 'Matrix Infinitely Divisible Series: Tail Inequalities and Their Applications', pp., vol. 10, no. 2, pp. 9-1117.
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In this paper, we study tail inequalities of the largest eigenvalue of amatrix infinitely divisible (i.d.) series, which is a finite sum of fixedmatrices weighted by i.d. random variables. We obtain several types of tailinequalities, including Bennett-type and Bernstein-type inequalities. Thisallows us to further bound the expectation of the spectral norm of a matrixi.d. series. Moreover, by developing a new lower-bound function for$Q(s)=(s+1)\log(s+1)-s$ that appears in the Bennett-type inequality, we derivea tighter tail inequality of the largest eigenvalue of the matrix i.d. seriesthan the Bernstein-type inequality when the matrix dimension is high. Theresulting lower-bound function is of independent interest and can improve anyBennett-type concentration inequality that involves the function $Q(s)$. Theclass of i.d. probability distributions is large and includes Gaussian andPoisson distributions, among many others. Therefore, our results encompass theexisting work \cite{tropp2012user} on matrix Gaussian series as a special case.Lastly, we show that the tail inequalities of a matrix i.d. series haveapplications in several optimization problems including the chance constrainedoptimization problem and the quadratic optimization problem with orthogonalityconstraints. In addition, we also use the resulting tail bounds to show thatrandom matrices constructed from i.d. random variables satisfy the restrictedisometry property (RIP) when it acts as a measurement matrix in compressedsensing.

Zhang, J, Devitt, SJ, You, JQ & Nori, F 2018, 'Holonomic surface codes for fault-tolerant quantum computation', Physical Review A, vol. 97, no. 2.
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© 2018 American Physical Society. Surface codes can protect quantum information stored in qubits from local errors as long as the per-operation error rate is below a certain threshold. Here we propose holonomic surface codes by harnessing the quantum holonomy of the system. In our scheme, the holonomic gates are built via auxiliary qubits rather than the auxiliary levels in multilevel systems used in conventional holonomic quantum computation. The key advantage of our approach is that the auxiliary qubits are in their ground state before and after each gate operation, so they are not involved in the operation cycles of surface codes. This provides an advantageous way to implement surface codes for fault-tolerant quantum computation.

Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'A Study on Idiosyncratic Handwriting with Impact on Writer Identification', 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, Niagara Falls, NY, USA, pp. 193-198.
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© 2018 IEEE. In this paper, we study handwriting idiosyncrasy in terms of its structural eccentricity. In this study, our approach is to find idiosyncratic handwritten text components and model the idiosyncrasy analysis task as a machine learning problem supervised by human cognition. We employ the Inception network for this purpose. The experiments are performed on two publicly available databases and an in-house database of Bengali offline handwritten samples. On these samples, subjective opinion scores of handwriting idiosyncrasy are collected from handwriting experts. We have analyzed the handwriting idiosyncrasy on this corpus which comprises the perceptive ground-truth opinion. We also investigate the effect of idiosyncratic text on writer identification by using the SqueezeNet. The performance of our system is promising.

Adak, C, Chaudhuri, BB & Blumenstein, M 1970, 'Cognitive Analysis for Reading and Writing of Bengali Conjuncts', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil, pp. 1-7.
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© 2018 IEEE. In this paper, we study the difficulties arising in reading and writing of Bengali conjunct characters by human-beings. Such difficulties appear when the human cognitive system faces certain obstructions in effortlessly reading/writing. In our computer-based investigation, we consider the reading/writing difficulty analysis task as a machine learning problem supervised by human perception. To this end, we employ two distinct models: (a) an auto-derived feature-based Inception network and (b) a hand-crafted feature-based SVM (Support Vector Machine). Two commonly used Bengali printed fonts and three contemporary handwritten databases are used for collecting subjective opinion scores from human readers/writers. On this corpus, which contains the perceptive ground-truth opinion of reading/writing complications, we have undertaken to conduct the experiments. The experimental results obtained on various types of conjunct characters are promising.

Adak, C, Marinai, S, Chaudhuri, BB & Blumenstein, M 1970, 'Offline Bengali Writer Verification by PDF-CNN and Siamese Net', 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), IEEE, Vienna, Austria, pp. 381-386.
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© 2018 IEEE. Automated handwriting analysis is a popular area of research owing to the variation of writing patterns. In this research area, writer verification is one of the most challenging branches, having direct impact on biometrics and forensics. In this paper, we deal with offline writer verification on complex handwriting patterns. Therefore, we choose a relatively complex script, i.e., Indic Abugida script Bengali (or, Bangla) containing more than 250 compound characters. From a handwritten sample, the probability distribution functions (PDFs) of some handcrafted features are obtained and input to a convolutional neural network (CNN). For such a CNN architecture, we coin the term 'PDFCNN', where handcrafted feature PDFs are hybridized with auto-derived CNN features. Such hybrid features are then fed into a Siamese neural network for writer verification. The experiments are performed on a Bengali offline handwritten dataset of 100 writers. Our system achieves encouraging results, which sometimes exceed the results of state-of-The-Art techniques on writer verification.

Ahadi, A, Lister, R & Mathieson, L 1970, 'Syntax error based quantification of the learning progress of the novice programmer', Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE '18: 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, ACM, Larnaca, Cyprus, pp. 10-14.
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© 2018 Association for Computing Machinery. Recent data-driven research has produced metrics for quantifying a novice programmer’s error profile, such as Jadud’s error quotient. However, these metrics tend to be context dependent and contain free parameters. This paper reviews the caveats of such metrics and proposes a more general approach to developing a metric. The online implementation of the proposed metric is publicly available at http://online-analysis-demo.herokuapp.com/.

Alaei, F, Alaei, A, Pal, U & Blumenstein, M 1970, 'Evaluation of Gist Operator for Document Image Retrieval', 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), IEEE, Vienna, Austria, pp. 369-374.
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© 2018 IEEE. As digitised documents normally contain a large variety of structures, a page segmentation-and layout-free method for document image retrieval is preferable. In this research work, therefore, wavelet transform as a transform-based approach is initially used to provide different under-sampled images from the original image. Then, GIST operator, as a feature extraction technique, is employed to extract a set of global features from the original image as well as the sub-images obtained from the wavelet transform. Moreover, the column-wise variances of the values in each sub-image are computed and they are then concatenated to obtain another set of features. Considering each feature set, locality-sensitive hashing is employed to compute similarity distances between a query and the document images in the database. Finally, a classifier fusion technique using the mean function is taken into account to provide a document image retrieval result. The combination of these features and a clustering score fusion strategy provides higher document image retrieval accuracy. Two different databases of the document image are considered for experimentation. The results obtained from the experimental study are detailed and the results are encouraging.

Anshu, A, Gavinsky, D, Jain, R, Kundu, S, Lee, T, Mukhopadhyay, P, Santha, M & Sanyal, S 1970, 'A composition theorem for randomized query complexity', Leibniz International Proceedings in Informatics, LIPIcs.
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Let the randomized query complexity of a relation for error probability be denoted by R. We prove that for any relation f (0, 1)n × R and Boolean function g : (0, 1) m (0, 1), R 1/3(f g n) = R 4/9(f). R1/2-1/n4 (g), where f g n is the relation obtained by composing f and g. We also show using an XOR lemma that R 1/3 f gO(log n)n = log n. R 4/9(f). R1/3(g), where g O (log n) is the function obtained by composing the XOR function on O(log n) bits and g.

Cheng, H-C, Gao, L & Hsieh, M-H 1970, 'Properties of Noncommutative Renyi and Augustin Information', Communications in Mathematical Physics volume, IEEE International Symposium on Information Theory, IEEE, Paris, France, pp. 501-544.
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R\'enyi and Augustin information are generalizations of mutual informationdefined via the R\'enyi divergence, playing a significant role in evaluatingthe performance of information processing tasks by virtue of its connection tothe error exponent analysis. In quantum information theory, there are threegeneralizations of the classical R\'enyi divergence -- the Petz's, sandwiched,and log-Euclidean versions, that possess meaningful operational interpretation.However, the associated quantum R\'enyi and Augustin information are much lessexplored compared with their classical counterpart, and lacking crucialproperties hinders applications of these quantities to error exponent analysisin the quantum regime. The goal of this paper is to analyze fundamentalproperties of the R\'enyi and Augustin information from a noncommutativemeasure-theoretic perspective. Firstly, we prove the uniform equicontinuity forall three quantum versions of R\'enyi and Augustin information, and it henceyields the joint continuity of these quantities in order and prior inputdistributions. Secondly, we establish the concavity of the scaled R\'enyi andAugustin information in the region of $s\in(-1,0)$ for both Petz's and thesandwiched versions. This completes the open questions raised by Holevo [IEEETrans.~Inf.~Theory, 46(6):2256--2261, 2000], and Mosonyi and Ogawa[Commun.~Math.~Phys., 355(1):373--426, 2017]. For the applications, we showthat the strong converse exponent in classical-quantum channel coding satisfiesa minimax identity, which means that the strong converse exponent can beattained by the best constant composition code. The established concavity isfurther employed to prove an entropic duality between classical datacompression with quantum side information and classical-quantum channel coding,and a Fenchel duality in joint source-channel coding with quantum sideinformation.

Cheng, H-C, Hanson, EP, Datta, N & Hsieh, M-H 1970, 'Duality between source coding with quantum side information and c-q channel coding', IEEE International Symposium on Information Theory - Proceedings, IEEE International Symposium on Information Theory, IEEE, Paris, France, pp. 1142-1146.
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In this paper, we establish an interesting duality between two differentquantum information-processing tasks, namely, classical source coding withquantum side information, and channel coding over c-q channels. The dualityrelates the optimal error exponents of these two tasks, generalizing theclassical results of Ahlswede and Dueck. We establish duality both at theoperational level and at the level of the entropic quantities characterizingthese exponents. For the latter, the duality is given by an exact relation,whereas for the former, duality manifests itself in the following sense: anoptimal coding strategy for one task can be used to construct an optimal codingstrategy for the other task. Along the way, we derive a bound on the errorexponent for c-q channel coding with constant composition codes which might beof independent interest.

Cheng, H-C, Hanson, EP, Datta, N & Hsieh, M-H 1970, 'Error Exponents and Strong Converse Exponents for Classical Data Compression with Quantum Side Information', 2018 IEEE International Symposium on Information Theory (ISIT), 2018 IEEE International Symposium on Information Theory (ISIT), IEEE, Vail, CO, USA, pp. 2162-2166.
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© 2018 IEEE. In this paper, we analyze classical data compression with quantum side information (also known as the classical-quantum Slepian- Wolf protocol) in the so-called large and moderate deviation regimes. In the non-asymptotic setting, the protocol involves compressing classical sequences of finite length n and decoding them with the assistance of quantum side information. In the large deviation regime, the compression rate is fixed, and we obtain bounds on the error exponent function, which characterizes the minimal probability of error as a function of the rate. Devetak and Winter showed that the asymptotic data compression limit for this protocol is given by a conditional entropy. For any protocol with a rate below this quantity, the probability of error converges to one asymptotically and its speed of convergence is given by the strong converse exponent function. We obtain finite blocklength bounds on this function, and determine exactly its asymptotic value, thus improving on previous results by Tomamichel. In the moderate deviation regime for the compression rate, the latter is no longer considered to be fixed. It is allowed to depend on the blocklength n, but assumed to decay slowly to the asymptotic data compression limit. Starting from a rate above this limit, we determine the speed of convergence of the error probability to zero and show that it is given in terms of the conditional information variance. Our results complement earlier results obtained by Tomamichel and Hayashi, in which they analyzed the so-called small deviation regime of this protocol.

Das, A, Pal, U, Ferrer, MA, Blumenstein, M, Stepec, D, Rot, P, Emersic, Z, Peer, P & Struc, V 1970, 'SSBC 2018: Sclera Segmentation Benchmarking Competition', 2018 International Conference on Biometrics (ICB), 2018 International Conference on Biometrics (ICB), IEEE, Gold Coast, QLD, Australia, pp. 303-308.
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© 2018 IEEE. This paper summarises the results of the Sclera Segmentation Benchmarking Competition (SSBC 2018). It was organised in the context of the 11th IAPR International Conference on Biometrics (ICB 2018). The aim of this competition was to record the developments on sclera segmentation in the cross-sensor environment (sclera trait captured using multiple acquiring sensors). Additionally, the competition also aimed to gain the attention of researchers on this subject of research. For the purpose of benchmarking, we have developed two datasets of sclera images captured using different sensors. The first dataset was collected using a DSLR camera and the second one was collected using a mobile phone camera. The first dataset is the Multi-Angle Sclera Dataset (MASD version 1), which was used in the context of the previous versions of sclera segmentation competitions. The images in the second dataset were captured using.a mobile phone rear camera of 8-megapixel. As baseline manual segmentation mask of the sclera images from both the datasets were developed. Precision and recall-based statistical measures were employed to evaluate the effectiveness of the submitted segmentation technique and to rank them. Six algorithms were submitted towards the segmentation task. This paper analyses the results produced by these algorithms/system and defines a way forward for this subject of research. Both the datasets along with some of the accompanying ground truth/baseline mask will be freely available for research purposes upon request to authors by email.

Das, A, Sengupta, A, Saqib, M, Pal, U & Blumenstein, M 1970, 'More Realistic and Efficient Face-Based Mobile Authentication using CNNs', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil, pp. 1-8.
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© 2018 IEEE. In this work, we propose a more realistic and efficient facebased mobile authentication technique using CNNs. This paper discusses and explores an inevitable problem of using face images for mobile authentication, taken from varying distances with a front/selfie camera of the mobile phone. Incidentally, once an individual comes towards a certain distance from the camera, the face images get large and appear over-sized. Simultaneously sharp features of some portions of the face, such as forehead, cheek, and chin are changed completely. As a result, the face features change and the impact increases exponentially once the individual crosses a certain distance and gradually approaches towards the front camera. This work proposes a solution (achieving better accuracy and facial features, whereby face images were cropped and aligned around its close bounding box) to mitigate the aforementioned identified gap. The work investigated different frontier face detection and recognition techniques to justify the proposed solution. Among all the employed methods evaluated, CNNs worked best. For a quantitative comparison of the proposed method, manually cropped face images/annotations of the face images along with their close boundary were prepared. In turn, we have developed a database considering the above-mentioned scenario for 40 individuals, which will be publicly available for academic research purposes. The experimental results achieved indicate a successful implementation of the proposed method and the performance of the proposed technique is also found to be superior in comparison to the existing state-of-the-art.

Du, Y, Liu, T, Li, Y, Duan, R & Tao, D 1970, 'Quantum Divide-and-Conquer Anchoring for Separable Non-negative Matrix Factorization', Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}, International Joint Conferences on Artificial Intelligence Organization, Stockholm, Sweden, pp. 2093-2099.
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It is NP-complete to find non-negative factors W and H with fixed rank r from a non-negative matrix X by minimizing ||X-WH^Τ ||^2. Although the separability assumption (all data points are in the conical hull of the extreme rows) enables polynomial-time algorithms, the computational cost is not affordable for big data. This paper investigates how the power of quantum computation can be capitalized to solve the non-negative matrix factorization with the separability assumption (SNMF) by devising a quantum algorithm based on the divide-and-conquer anchoring (DCA) scheme [Zhou et al., 2013]. The design of quantum DCA (QDCA) is challenging. In the divide step,  the random projections in  DCA is completed by a quantum algorithm for linear operations, which achieves the exponential speedup. We then  devise a heuristic post-selection procedure which extracts the information of anchors stored in the quantum states efficiently. Under a plausible assumption, QDCA performs efficiently, achieves the quantum speedup, and is beneficial for high dimensional problems.

Fan, J, Hsieh, M-H, Chen, H, Chen, H & Li, Y 1970, 'Construction and Performance of Quantum Burst Error Correction Codes for Correlated Errors', IEEE International Symposium on Information Theory - Proceedings, IEEE International Symposium on Information Theory, IEEE, Vail, CO, USA, pp. 2336-2340.
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In practical communication and computation systems, errors occurpredominantly in adjacent positions rather than in a random manner. In thispaper, we develop a stabilizer formalism for quantum burst error correctioncodes (QBECC) to combat such error patterns in the quantum regime. Ourcontributions are as follows. Firstly, we derive an upper bound for thecorrectable burst errors of QBECCs, the quantum Reiger bound (QRB). This boundgeneralizes the quantum Singleton bound for standard quantum error correctioncodes (QECCs). Secondly, we propose two constructions of QBECCs: one byheuristic computer search and the other by concatenating two quantum tensorproduct codes (QTPCs). We obtain several new QBECCs with better parameters thanexisting codes with the same coding length. Moreover, some of the constructedcodes can saturate the quantum Reiger bounds. Finally, we perform numericalexperiments for our constructed codes over Markovian correlated depolarizingquantum memory channels, and show that QBECCs indeed outperform standard QECCsin this scenario.

Fang, K, Wang, X, Tomamichel, M & Berta, M 1970, 'Quantum Channel Simulation and the Channel's Smooth Max-Information', IEEE Transactions on Information Theory, International Symposium on Information Theory, IEEE, Vail, CO, USA, pp. 2129-2140.
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We study the general framework of quantum channel simulation, that is, theability of a quantum channel to simulate another one using different classes ofcodes. First, we show that the minimum error of simulation and the one-shotquantum simulation cost under no-signalling assisted codes are given bysemidefinite programs. Second, we introduce the channel's smoothmax-information, which can be seen as a one-shot generalization of the mutualinformation of a quantum channel. We provide an exact operationalinterpretation of the channel's smooth max-information as the one-shot quantumsimulation cost under no-signalling assisted codes, which significantlysimplifies the study of channel simulation and provides insights and bounds forthe case under entanglement-assisted codes. Third, we derive the asymptoticequipartition property of the channel's smooth max-information; i.e., itconverges to the quantum mutual information of the channel in the independentand identically distributed asymptotic limit. This implies the quantum reverseShannon theorem in the presence of no-signalling correlations. Finally, weexplore the simulation cost of various quantum channels.

Gavinsky, D, Lee, T, Santha, M & Sanyal, S 1970, 'A composition theorem for randomized query complexity via max conflict complexity', Leibniz International Proceedings in Informatic, International Colloquium on Automata, Languages, and Programming, Dagstuhl Publishing, Greece, pp. 1-13.
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Let $R_\epsilon(\cdot)$ stand for the bounded-error randomized querycomplexity with error $\epsilon > 0$. For any relation $f \subseteq \{0,1\}^n\times S$ and partial Boolean function $g \subseteq \{0,1\}^m \times \{0,1\}$,we show that $R_{1/3}(f \circ g^n) \in \Omega(R_{4/9}(f) \cdot\sqrt{R_{1/3}(g)})$, where $f \circ g^n \subseteq (\{0,1\}^m)^n \times S$ isthe composition of $f$ and $g$. We give an example of a relation $f$ andpartial Boolean function $g$ for which this lower bound is tight. We prove our composition theorem by introducing a new complexity measure, themax conflict complexity $\bar \chi(g)$ of a partial Boolean function $g$. Weshow $\bar \chi(g) \in \Omega(\sqrt{R_{1/3}(g)})$ for any (partial) function$g$ and $R_{1/3}(f \circ g^n) \in \Omega(R_{4/9}(f) \cdot \bar \chi(g))$; thesetwo bounds imply our composition result. We further show that $\bar \chi(g)$ isalways at least as large as the sabotage complexity of $g$, introduced byBen-David and Kothari.

Ivanyos, G & Qiao, Y 1970, 'Algorithms based on *-algebras, and their applications to isomorphism of polynomials with one secret, group isomorphism, and polynomial identity testing', Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms, Symposium on Discrete Algorithm, Society for Industrial and Applied Mathematics, New Orleans, LA, USA, pp. 2357-2376.
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© Copyright 2018 by SIAM. We consider two basic algorithmic problems concerning tuples of (skew-)symmetric matrices. The first problem asks to decide, given two tuples of (skew-)symmetric matrices (B1; : : : ;Bm) and (C1; : : : ;Cm), whether there exists an invertible matrix A such that for every i 2 f1; : : : ;mg, AtBiA = Ci. We show that this problem can be solved in randomized polynomial time over finite fields of odd size, the reals, and the complex numbers. The second problem asks to decide, given a tuple of square matrices (B1; : : : ;Bm), whether there exist invertible matrices A and D, such that for every i 2 f1; : : : ;mg, ABiD is (skew-)symmetric. We show that this problem can be solved in deterministic polynomial time over fields of characteristic not 2. For both problems we exploit the structure of the underlying α-algebras (algebras with an involutive antiautomorphism), and utilize results and methods from the module isomorphism problem. Applications of our results range from multivariate cryptography, group isomorphism, to polynomial identity testing. Specifically, these results imply efficient algorithms for the following problems. (1) Test isomorphism of quadratic forms with one secret over a finite field of odd size. This problem belongs to a family of problems that serves as the security basis of certain authentication schemes proposed by Patarin (Eurocrypt 1996). (2) Test isomorphism of p-groups of class 2 and exponent p (p odd) with order p' in time polynomial in the group order, when the commutator subgroup is of order pO( p '). (3) Deterministically reveal two families of singularity witnesses caused by the skew-symmetric structure. This represents a natural next step for the polynomial identity testing problem, in the direction set up by the recent resolution of the non-commutative rank problem (Garg-Gurvits-Oliveira-Wigderson, FOCS 2016; Ivanyos-Qiao-Subrahmanyam, ITCS 2017).

Jain, R, Klauck, H, Kundu, S, Lee, T, Santha, M, Sanyal, S & Vihrovs, J 1970, 'Quadratically Tight Relations for Randomized Query Complexity', Springer International Publishing, pp. 207-219.
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Ji, Z, Liu, Y-K & Song, F 1970, 'Pseudorandom Quantum States', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Annual International Cryptology Conference, Springer International Publishing, Santa Barbara, CA, USA, pp. 126-152.
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© International Association for Cryptologic Research 2018. We propose the concept of pseudorandom quantum states, which appear random to any quantum polynomial-time adversary. It offers a computational approximation to perfectly random quantum states analogous in spirit to cryptographic pseudorandom generators, as opposed to statistical notions of quantum pseudorandomness that have been studied previously, such as quantum t-designs analogous to t-wise independent distributions. Under the assumption that quantum-secure one-way functions exist, we present efficient constructions of pseudorandom states, showing that our definition is achievable. We then prove several basic properties of pseudorandom states, which show the utility of our definition. First, we show a cryptographic no-cloning theorem: no efficient quantum algorithm can create additional copies of a pseudorandom state, when given polynomially-many copies as input. Second, as expected for random quantum states, we show that pseudorandom quantum states are highly entangled on average. Finally, as a main application, we prove that any family of pseudorandom states naturally gives rise to a private-key quantum money scheme.

Lee, T, Ray, M & Santha, M 1970, 'Strategies for quantum races', 10th Innovations in Theoretical Computer Science, Innovations in Theoretical Computer Science, Schloss Dagstuhl, UCSD.
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We initiate the study of quantum races, games where two or more quantumcomputers compete to solve a computational problem. While the problem ofdueling algorithms has been studied for classical deterministic algorithms, thequantum case presents additional sources of uncertainty for the players. Theforemost among these is that players do not know if they have solved theproblem until they measure their quantum state. This question of `when tomeasure?' presents a very interesting strategic problem. We develop agame-theoretic model of a multiplayer quantum race, and find an approximateNash equilibrium where all players play the same strategy. In the two-partycase, we further show that this strategy is nearly optimal in terms of payoffamong all symmetric Nash equilibria. A key role in our analysis of quantumraces is played by a more tractable version of the game where there is nopayout on a tie; for such races we completely characterize the Nash equilibriain the two-party case. One application of our results is to the stability of the Bitcoin protocolwhen mining is done by quantum computers. Bitcoin mining is a race to solve acomputational search problem, with the winner gaining the right to create a newblock. Our results inform the strategies that eventual quantum miners shoulduse, and also indicate that the collision probability---the probability thattwo miners find a new block at the same time---would not be too high in thecase of quantum miners. Such collisions are undesirable as they lead to forkingof the Bitcoin blockchain.

Leung, D, Nayak, A, Shayeghi, A, Touchette, D, Yao, P & Yu, N 1970, 'Capacity approaching coding for low noise interactive quantum communication', Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC '18: Symposium on Theory of Computing, ACM, Los Angeles, CA, USA, pp. 926-939.
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© 2018 Copyright held by the owner/author(s). We consider the problem of implementing two-party interactive quantum communication over noisy channels, a necessary endeavor if we wish to fully reap quantum advantages for communication. For an arbitrary protocol with n messages, designed for noiseless qudit channels (where d is arbitrary), our main result is a simulation method that fails with probability less than 2−Θ(nϵ) and uses a qudit channel n 1 + Θ times, of which an fraction can be corrupted adversarially. The simulation is thus capacity achieving to leading order, and we conjecture that it is optimal up to a constant factor in the term. Furthermore, the simulation is in a model that does not require pre-shared resources such as randomness or entanglement between the communicating parties. Perhaps surprisingly, this outperforms the best known overhead of 1 + O log log ϵ1 in the corresponding classical model, which is also conjectured to be optimal [Haeupler, FOCS’14]. Our work also improves over the best previously known quantum result where the overhead is a non-explicit large constant [Brassard et al., FOCS’14] for low .

Li, JJ, Kowalski, T, Renz, J & Li, S 1970, 'Combining binary constraint networks in qualitative reasoning', Frontiers in Artificial Intelligence and Applications, European Conference on Artificial Intelligence, IOS Press, Patras, Greece, pp. 515-519.
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Constraint networks in qualitative spatial and temporal reasoning are always complete graphs. When one adds an extra element to a given network, previously unknown constraints are derived by intersections and compositions of other constraints, and this may introduce inconsistency to the overall network. Likewise, when combining two consistent networks that share a common part, the combined network may become inconsistent. In this paper, we analyse the problem of combining these binary constraint networks and develop certain conditions to ensure combining two networks will never introduce an inconsistency for a given spatial or temporal calculus. This enables us to maintain a consistent world-view while acquiring new information in relation with some part of it. In addition, our results enable us to prove other important properties of qualitative spatial and temporal calculi in areas such as representability and complexity.

Rahman, JS, Li, J, Xie, J, Fogelman, S & Blumenstein, M 1970, 'Connectivity Based Method for Clustering Microbial Communities from Metagenomics Data of Water and Soil Samples', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil, pp. 1-8.
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© 2018 IEEE. Understanding microbial community structure of metagenomics water and soil samples is a key process in discovering functions and impact of microorganisms on human and animal health. Evolution of Next Generation Sequencing (NGS) technology has encouraged researchers to sequence large quantity of microbial data from environmental sources. Clustering marker gene sequences into Operational Taxonomic Units (OTU) is the most significant task in microbial community analysis. Several methods have been developed over the years to improve OTU picking strategies. However, building strongly connected OTUs is a major issue in majority of these methods. Herein we present ConClust, a novel method for clustering OTUs that is based on quantifying connectivity among the sequences. Experimental analysis on two synthetic datasets and two real world datasets from water and soil samples demonstrate that our method can mine robust OTUs. Our method can be highly benelicial to study functions of known and unknown microbes and analyze their positive and negative effect on the environment as well as human and animal health.

Razzak, MI, Saris, RA, Blumenstein, M & Xu, G 1970, 'Robust 2D Joint Sparse Principal Component Analysis With F-Norm Minimization For Sparse Modelling: 2D-RJSPCA', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil.
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Salek, F, Anshu, A, Hsieh, M-H, Jain, R & Fonollosa, JR 1970, 'One-shot Capacity Bounds on the Simultaneous Transmission of Public and Private Information Over Quantum Channels', 2018 IEEE International Symposium on Information Theory (ISIT), 2018 IEEE International Symposium on Information Theory (ISIT), IEEE, Vail, CO, USA, pp. 296-300.
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© 2018 IEEE. We aim to study the optimal rates of transmission of public and private classical information over a quantum channel in the most general channel model. To this end, we discuss a scenario in which a quantum channel is being used only once, i.e., one-shot regime is considered. A quantum channel can be used to send classical information (bits) either publicly or privately and for either case, one-shot bounds have been reported in the literature. This paper investigates the one-shot capacity capabilities of a quantum channel for simultaneous transmission of public and private information. We derive an achievable rate region in the form of a tradeoff between public and private rates. We also provide converse bounds assessing the ' of our achievable rates. Our main tools used in the achievability proofs are position-based decoding and convex-split lemma.

Saqib, M, Daud Khan, S, Sharma, N, Scully-Power, P, Butcher, P, Colefax, A & Blumenstein, M 1970, 'Real-Time Drone Surveillance and Population Estimation of Marine Animals from Aerial Imagery', 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, Auckland, New Zealand.
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© 2018 IEEE. Video analysis is being rapidly adopted by marine biologists to asses the population and migration of marine animals. Manual analysis of videos by human observers is labor intensive and prone to error. The automatic analysis of videos using state-of-the-art deep learning object detectors provides a cost-effective way for the study of marine animals population and their ecosystem. However, there are many challenges associated with video analysis such as background clutter, illumination, occlusions, and deformation. Due to the high-density of objects in the images and sever occlusion, current state-of-the-art object often results in multiple detections. Therefore, customized Non-Maxima-Suppression is proposed after the detections to suppress false positives which significantly improves the counting and mean average precision of the detections. An end-to-end deep learning framework of Faster-RCNN [1] was adopted for detections with base architectures of VGG16 [2], VGGM [3] and ZF [4].

Saqib, M, Khan, SD, Sharma, N & Blumenstein, M 1970, 'Person Head Detection in Multiple Scales Using Deep Convolutional Neural Networks', 2018 International Joint Conference on Neural Networks (IJCNN), 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, Rio de Janeiro, Brazil.
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© 2018 IEEE. Person detection is an important problem in computer vision with many real-world applications. The detection of a person is still a challenging task due to variations in pose, occlusions and lighting conditions. The purpose of this study is to detect human heads in natural scenes acquired from a publicly available dataset of Hollywood movies. In this work, we have used state-of-the-art object detectors based on deep convolutional neural networks. These object detectors include region-based convolutional neural networks using region proposals for detections. Also, object detectors that detect objects in the single-shot by looking at the image only once for detections. We have used transfer learning for fine-tuning the network already trained on a massive amount of data. During the fine-tuning process, the models having high mean Average Precision (mAP) are used for evaluation of the test dataset. Experimental results show that Faster R-CNN [18] and SSD MultiBox [13] with VGG16 [21] perform better than YOLO [17] and also demonstrate significant improvements against several baseline approaches.

Sharma, N, Mandal, R, Sharma, R, Pal, U & Blumenstein, M 1970, 'Signature and Logo Detection using Deep CNN for Document Image Retrieval', 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, Niagara Falls, NY, USA, pp. 416-422.
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© 2018 IEEE. Signature and logo as a query are important for content-based document image retrieval from a scanned document repository. This paper deals with signature and logo detection from a repository of scanned documents, which can be used for document retrieval using signature or logo information. A large intra-category variance among signature and logo samples poses challenges to traditional hand-crafted feature extraction-based approaches. Hence, the potential of deep learning-based object detectors namely, Faster R-CNN and YOLOv2 were examined for automatic detection of signatures and logos from scanned administrative documents. Four different network models namely ZF, VGG16, VGG-M, and YOLOv2 were considered for analysis and identifying their potential in document image retrieval. The experiments were conducted on the publicly available 'Tobacco-800' dataset. The proposed approach detects Signatures and Logos simultaneously. The results obtained from the experiments are promising and at par with the existing methods.

Sharma, N, Scully-Power, P & Blumenstein, M 1970, 'Shark Detection from Aerial Imagery Using Region-Based CNN, a Study', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Australasian Joint Conference on Artificial Intelligence, Springer International Publishing, Wellington, New Zealand, pp. 224-236.
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© Springer Nature Switzerland AG 2018. Shark attacks have been a very sensitive issue for Australians and many other countries. Thus, providing safety and security around beaches is very fundamental in the current climate. Safety for both human beings and underwater creatures (sharks, whales, etc.) in general is essential while people continue to visit and use the beaches heavily for recreation and sports. Hence, an efficient, automated and real-time monitoring approach on beaches for detecting various objects (e.g. human activities, large fish, sharks, whales, surfers, etc.) is necessary to avoid unexpected casualties and accidents. The use of technologies such as drones and machine learning techniques are promising directions in such challenging circumstances. This paper investigates the potential of Region-based Convolutional Neural Networks (R-CNN) for detecting various marine objects, and Sharks in particular. Three network architectures namely Zeiler and Fergus (ZF), Visual Geometry Group (VGG16), and VGG_M were considered for analysis and identifying their potential. A dataset consisting of 3957 video frames were used for experiments. VGG16 architecture with faster-R-CNN performed better than others, with an average precision of 0.904 for detecting Sharks.

Suwanwiwat, H, Das, A, Pal, U & Blumenstein, M 1970, 'ICFHR 2018 Competition on Thai Student Signatures and Name Components Recognition and Verification (TSNCRV2018)', 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, Niagara Falls, NY, USA, pp. 500-505.
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© 2018 IEEE. This paper summarises the results of the competition on the 1st Thai Student Signature and Name Components Recognition and Verification (TSNCRV 2018). It was organised in the context of the 16th International Conference on Frontiers in Handwriting Recognition (ICFHR 2018). The aim of this competition was to record the development and gain attention on Thai student signatures and name component recognition and verification. Two different types of datasets were used for the competition: The first dataset contains Thai student signatures and the second dataset contains Thai student name components. Signatures and name components from 100 volunteers each were included in the competition datasets. For Thai signature dataset, there are 30 genuine signatures, 12 skilled and 12 simple forgeries for each writer. For Thai name components, there are 30 genuine and 12 skilfully forged name components for each writer. For both the datasets the individuals were asked to write their name/signature in the given space on a white piece of paper for number of time (with a pause between each 10 samples). The skilled forgers were asked practice emitting the original signature for certain number of times till they fill skilled to forge. Five teams from distinguish labs submitted their systems. This paper analysed the results produced by these algorithms/systems using a performance measure and defined a way forward for this subject of research. Both the datasets along with some of the accompanying ground truth/baseline mask will be made freely available for research purposes via the TC10/TC11.

Wang, X, Fang, K & Tomamichel, M 1970, 'On Finite Blocklength Converse Bounds for Classical Communication Over Quantum Channels', 2018 IEEE International Symposium on Information Theory (ISIT), 2018 IEEE International Symposium on Information Theory (ISIT), IEEE, Vail, CO, USA, pp. 2157-2161.
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© 2018 IEEE. We explore several new converse bounds for classical communication over quantum channels in the finite blocklength regime. First, we show that the Matthews-Wehner meta-converse bound for entanglement-assisted classical communication can be achieved by activated, no-signalling assisted codes, suitably generalizing a result for classical channels. Second, we derive a new meta-converse on the amount of information unassisted codes can transmit over a single use of a quantum channel. We further show that this meta-converse can be evaluated via semidefinite programming. As an application, we provide a second-order analysis of classical communication over quantum erasure channels.

Wu, D, Sharma, N & Blumenstein, M 1970, 'An End-to-End Hierarchical Classification Approach for Similar Gesture Recognition', 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), IEEE, New Zealand, pp. 73-78.
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© 2018 IEEE. Human action recognition from the RGB video is widely applied on varies real applications. Many works have been done by researchers in computer vision and machine learning area to address the challenges and complexity involved in video-based human action recognition. Deep learning approaches including Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) have been introduced in the human action recognition research area. However, due to the drawbacks of the CNNs, recognizing actions with similar gestures and describing complex actions is still very challenging. Hence, an end-to-end hierarchical classification architecture has been proposed in this paper to resolve the confusion between similar gesture. The proposed approach firstly classifies the whole dataset and generates the accuracy for each class in stage 1. Based on the confusion matrix obtained from stage-1, the approach combines the most confused similar gesture pairs into one class, and classify them along with all other class, in the stage-2. In stage 3, similar gesture pairs will be classified by binary classifiers, which will increase the performance of each class and the overall accuracy. We apply and evaluate the developed models to recognize the similar human actions on the both KTH and UCF101 dataset. The result shows that the proposed approach can boost the classification performance on both the datasets. The proposed architecture is robust and any classification technique can be used in stage 1 and stage 2.

Wu, D, Sharma, N & Blumenstein, M 1970, 'Similar Gesture Recognition using Hierarchical Classification Approach in RGB Videos', 2018 Digital Image Computing: Techniques and Applications (DICTA), 2018 Digital Image Computing: Techniques and Applications (DICTA), IEEE, Canberra, Australia.
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© 2018 IEEE. Recognizing human actions from the video streams has become one of the very popular research areas in computer vision and deep learning in the recent years. Action recognition is wildly used in different scenarios in real life, such as surveillance, robotics, healthcare, video indexing and human-computer interaction. The challenges and complexity involved in developing a video-based human action recognition system are manifold. In particular, recognizing actions with similar gestures and describing complex actions is a very challenging problem. To address these issues, we study the problem of classifying human actions using Convolutional Neural Networks (CNN) and develop a hierarchical 3DCNN architecture for similar gesture recognition. The proposed model firstly combines similar gesture pairs into one class, and classify them along with all other class, as a stage-1 classification. In stage-2, similar gesture pairs are classified individually, which reduces the problem to binary classification. We apply and evaluate the developed models to recognize the similar human actions on the HMDB51 dataset. The result shows that the proposed model can achieve high performance in comparison to the state-of-the-art methods.

Wu, X, Shivakumara, P, Zhu, L, Zhang, H, Shi, J, Lu, T, Pal, U & Blumenstein, M 1970, 'Fourier Transform based Features for Clean and Polluted Water Image Classification', 2018 24th International Conference on Pattern Recognition (ICPR), 2018 24th International Conference on Pattern Recognition (ICPR), IEEE, Beijing, China, pp. 1707-1712.
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© 2018 IEEE. Water image classification is challenging because water images of ocean or river share the same properties with images of polluted water such as fungus, waste and rubbish. In this paper, we present a method for classifying clean and polluted water images. The proposed method explores Fourier transform based features for extracting texture properties of clean and polluted water images. Fourier spectrum of each input image is divided into several sub-regions based on angle and spatial information. For each region over the spectrum, the proposed method extracts mean and variance features using intensity values, which results in a feature matrix. The feature matrix is then passed to an SVM classifier for the classification of clean and polluted water images. Experimental results on classes of clean and polluted water images show that the proposed method is effective. Furthermore, a comparative study with the state-of-the-art method shows that the proposed method outperforms the existing method in terms of classification rate, recall, precision and F-measure.

Xie, W, Wang, X & Duan, R 1970, 'Converse Bounds for Classical Communication Over Quantum Broadcast Channels and Quantum Multi-Access Channels', 2018 IEEE International Symposium on Information Theory (ISIT), 2018 IEEE International Symposium on Information Theory (ISIT), IEEE, Vail, CO, USA, pp. 2341-2345.
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© 2018 IEEE. We explore the classical communication over quantum channels with one sender and two receivers, or with two senders and one receiver, in both one-shot and asymptotic regimes. First, for the quantum broadcast channel (QBC) and the quantum multi-access channel (QMAC), we study the classical communication assisted by no-signalling and positive-partial-transpose-preserving codes, and obtain efficiently computable one-shot bounds to assess the performance of classical communication. Second, we consider the asymptotic communication capability of communication over the QBC and QMAC. We derive an efficiently computable strong converse bound for the capacity region, which behaves better than the previous semidefinite programming strong converse bound for point-to-point channels. Third, we obtain a converse bound on the one-shot capacity region based on the hypothesis testing divergence between the given channel and a certain class of subchannels. As applications, we analyze the communication performance for some basic network channels, including the classical broadcast channels and a specific class of quantum broadcast channels.

Zhang, M, Gao, Y, Sun, C & Blumenstein, M 1970, 'Matching Pursuit Based on Kernel Non-Second Order Minimization', 2018 25th IEEE International Conference on Image Processing (ICIP), 2018 25th IEEE International Conference on Image Processing (ICIP), IEEE, Athens, Greece, pp. 3858-3862.
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© 2018 IEEE. The orthogonal matching pursuit (OMP) is an important sparse approximation algorithm to recover sparse signals from compressed measurements. However, most MP algorithms are based on the mean square error(MSE) to minimize the recovery error, which is suboptimal when there are outliers. In this paper, we present a new robust OMP algorithm based on kernel non-second order statistics (KNS-OMP), which not only takes advantages of the outlier resistance ability of correntropy but also further extends the second order statistics based correntropy to a non-second order similarity measurement to improve its robustness. The resulted framework is more accurate than the second order ones in reducing the effect of outliers. Experimental results on synthetic and real data show that the proposed method achieves better performances compared with existing methods.

Bannink, T, Briët, J, Buhrman, H, Labib, F & Lee, T 2018, 'Bounding quantum-classical separations for classes of nonlocal games'.
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We bound separations between the entangled and classical values for severalclasses of nonlocal $t$-player games. Our motivating question is whether thereis a family of $t$-player XOR games for which the entangled bias is $1$ but forwhich the classical bias goes down to $0$, for fixed $t$. Answering thisquestion would have important consequences in the study of multi-partycommunication complexity, as a positive answer would imply an unboundedseparation between randomized communication complexity with and withoutentanglement. Our contribution to answering the question is identifying severalgeneral classes of games for which the classical bias can not go to zero whenthe entangled bias stays above a constant threshold. This rules out thepossibility of using these games to answer our motivating question. Apreviously studied set of XOR games, known not to give a positive answer to thequestion, are those for which there is a quantum strategy that attains value 1using a so-called Schmidt state. We generalize this class to mod-$m$ games andshow that their classical value is always at least $\frac{1}{m} + \frac{m-1}{m}t^{1-t}$. Secondly, for free XOR games, in which the input distribution is ofproduct form, we show $\beta(G) \geq \beta^*(G)^{2^t}$ where $\beta(G)$ and$\beta^*(G)$ are the classical and entangled biases of the game respectively.We also introduce so-called line games, an example of which is a slightmodification of the Magic Square game, and show that they can not give apositive answer to the question either. Finally we look at two-player uniquegames and show that if the entangled value is $1-\epsilon$ then the classicalvalue is at least $1-\mathcal{O}(\sqrt{\epsilon \log k})$ where $k$ is thenumber of outputs in the game. Our proofs use semidefinite-programmingtechniques, the Gowers inverse theorem and hypergraph norms.

Ferrie, C & Blume-Kohout, R 2018, 'Maximum likelihood quantum state tomography is inadmissible'.
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Maximum likelihood estimation (MLE) is the most common approach to quantum state tomography. In this letter, we investigate whether it is also optimal in any sense. We show that MLE is an inadmissible estimator for most of the commonly used metrics of accuracy, i.e., some other estimator is more accurate for every true state. MLE is inadmissible for fidelity, mean squared error (squared Hilbert-Schmidt distance), and relative entropy. We prove that almost any estimator that can report both pure states and mixed states is inadmissible. This includes MLE, compressed sensing (nuclear-norm regularized) estimators, and constrained least squares. We provide simple examples to illustrate why reporting pure states is suboptimal even when the true state is itself pure, and why 'hedging' away from pure states generically improves performance.

Rozpędek, F, Schiet, T, Thinh, LP, Elkouss, D, Doherty, AC & Wehner, S 2018, 'Optimizing practical entanglement distillation'.

Sanders, YR, Low, GH, Scherer, A & Berry, DW 2018, 'Black-box quantum state preparation without arithmetic'.

Thinh, LP, Faist, P, Helsen, J, Elkouss, D & Wehner, S 2018, 'Practical and reliable error bars for quantum process tomography'.

Thinh, LP, Varvitsiotis, A & Cai, Y 2018, 'Structure of the set of quantum correlators via semidefinite programming'.