Publications

Sadaf, A, Mathieson, L & Musial, K 2023, 'Effects of Global and Local Network Structure on Number of Driver Nodes in Complex Networks' in Lecture Notes in Social Networks, Springer Nature Switzerland, pp. 81-98.
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This book offers an excellent source of knowledge for readers who are interested in keeping up with the developments in the field of cyber security and social media analysis.

Acharya, R, Aleiner, I, Allen, R, Andersen, TI, Ansmann, M, Arute, F, Arya, K, Asfaw, A, Atalaya, J, Babbush, R, Bacon, D, Bardin, JC, Basso, J, Bengtsson, A, Boixo, S, Bortoli, G, Bourassa, A, Bovaird, J, Brill, L, Broughton, M, Buckley, BB, Buell, DA, Burger, T, Burkett, B, Bushnell, N, Chen, Y, Chen, Z, Chiaro, B, Cogan, J, Collins, R, Conner, P, Courtney, W, Crook, AL, Curtin, B, Debroy, DM, Del Toro Barba, A, Demura, S, Dunsworth, A, Eppens, D, Erickson, C, Faoro, L, Farhi, E, Fatemi, R, Flores Burgos, L, Forati, E, Fowler, AG, Foxen, B, Giang, W, Gidney, C, Gilboa, D, Giustina, M, Grajales Dau, A, Gross, JA, Habegger, S, Hamilton, MC, Harrigan, MP, Harrington, SD, Higgott, O, Hilton, J, Hoffmann, M, Hong, S, Huang, T, Huff, A, Huggins, WJ, Ioffe, LB, Isakov, SV, Iveland, J, Jeffrey, E, Jiang, Z, Jones, C, Juhas, P, Kafri, D, Kechedzhi, K, Kelly, J, Khattar, T, Khezri, M, Kieferová, M, Kim, S, Kitaev, A, Klimov, PV, Klots, AR, Korotkov, AN, Kostritsa, F, Kreikebaum, JM, Landhuis, D, Laptev, P, Lau, K-M, Laws, L, Lee, J, Lee, K, Lester, BJ, Lill, A, Liu, W, Locharla, A, Lucero, E, Malone, FD, Marshall, J, Martin, O, McClean, JR, McCourt, T, McEwen, M, Megrant, A, Meurer Costa, B, Mi, X, Miao, KC, Mohseni, M, Montazeri, S, Morvan, A, Mount, E, Mruczkiewicz, W, Naaman, O, Neeley, M, Neill, C, Nersisyan, A, Neven, H, Newman, M, Ng, JH, Nguyen, A, Nguyen, M, Niu, MY, O’Brien, TE, Opremcak, A, Platt, J, Petukhov, A, Potter, R, Pryadko, LP, Quintana, C, Roushan, P, Rubin, NC, Saei, N, Sank, D, Sankaragomathi, K, Satzinger, KJ, Schurkus, HF, Schuster, C, Shearn, MJ, Shorter, A, Shvarts, V, Skruzny, J, Smelyanskiy, V, Smith, WC, Sterling, G, Strain, D, Szalay, M, Torres, A, Vidal, G, Villalonga, B, Vollgraff Heidweiller, C, White, T, Xing, C, Yao, ZJ, Yeh, P, Yoo, J, Young, G, Zalcman, A, Zhang, Y & Zhu, N 2023, 'Suppressing quantum errors by scaling a surface code logical qubit', Nature, vol. 614, no. 7949, pp. 676-681.
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AbstractPractical quantum computing will require error rates well below those achievable with physical qubits. Quantum error correction1,2 offers a path to algorithmically relevant error rates by encoding logical qubits within many physical qubits, for which increasing the number of physical qubits enhances protection against physical errors. However, introducing more qubits also increases the number of error sources, so the density of errors must be sufficiently low for logical performance to improve with increasing code size. Here we report the measurement of logical qubit performance scaling across several code sizes, and demonstrate that our system of superconducting qubits has sufficient performance to overcome the additional errors from increasing qubit number. We find that our distance-5 surface code logical qubit modestly outperforms an ensemble of distance-3 logical qubits on average, in terms of both logical error probability over 25 cycles and logical error per cycle ((2.914 ± 0.016)% compared to (3.028 ± 0.023)%). To investigate damaging, low-probability error sources, we run a distance-25 repetition code and observe a 1.7 × 10−6 logical error per cycle floor set by a single high-energy event (1.6 × 10−7 excluding this event). We accurately model our experiment, extracting error budgets that highlight the biggest challenges for future systems. These results mark an experimental demonstration in which quantum error correction begins to improve performance with increasing qubit number, illuminating the path to reaching the logical error rates required for computation.

Andersen, TI, Lensky, YD, Kechedzhi, K, Drozdov, IK, Bengtsson, A, Hong, S, Morvan, A, Mi, X, Opremcak, A, Acharya, R, Allen, R, Ansmann, M, Arute, F, Arya, K, Asfaw, A, Atalaya, J, Babbush, R, Bacon, D, Bardin, JC, Bortoli, G, Bourassa, A, Bovaird, J, Brill, L, Broughton, M, Buckley, BB, Buell, DA, Burger, T, Burkett, B, Bushnell, N, Chen, Z, Chiaro, B, Chik, D, Chou, C, Cogan, J, Collins, R, Conner, P, Courtney, W, Crook, AL, Curtin, B, Debroy, DM, Del Toro Barba, A, Demura, S, Dunsworth, A, Eppens, D, Erickson, C, Faoro, L, Farhi, E, Fatemi, R, Ferreira, VS, Burgos, LF, Forati, E, Fowler, AG, Foxen, B, Giang, W, Gidney, C, Gilboa, D, Giustina, M, Gosula, R, Dau, AG, Gross, JA, Habegger, S, Hamilton, MC, Hansen, M, Harrigan, MP, Harrington, SD, Heu, P, Hilton, J, Hoffmann, MR, Huang, T, Huff, A, Huggins, WJ, Ioffe, LB, Isakov, SV, Iveland, J, Jeffrey, E, Jiang, Z, Jones, C, Juhas, P, Kafri, D, Khattar, T, Khezri, M, Kieferová, M, Kim, S, Kitaev, A, Klimov, PV, Klots, AR, Korotkov, AN, Kostritsa, F, Kreikebaum, JM, Landhuis, D, Laptev, P, Lau, K-M, Laws, L, Lee, J, Lee, KW, Lester, BJ, Lill, AT, Liu, W, Locharla, A, Lucero, E, Malone, FD, Martin, O, McClean, JR, McCourt, T, McEwen, M, Miao, KC, Mieszala, A, Mohseni, M, Montazeri, S, Mount, E, Movassagh, R, Mruczkiewicz, W, Naaman, O, Neeley, M, Neill, C, Nersisyan, A, Newman, M, Ng, JH, Nguyen, A, Nguyen, M, Niu, MY, O’Brien, TE, Omonije, S, Petukhov, A, Potter, R, Pryadko, LP, Quintana, C, Rocque, C, Rubin, NC, Saei, N, Sank, D, Sankaragomathi, K, Satzinger, KJ, Schurkus, HF, Schuster, C, Shearn, MJ, Shorter, A, Shutty, N, Shvarts, V, Skruzny, J, Smith, WC, Somma, R, Sterling, G, Strain, D, Szalay, M, Torres, A, Vidal, G, Villalonga, B, Heidweiller, CV, White, T, Woo, BWK, Xing, C, Yao, ZJ, Yeh, P, Yoo, J, Young, G, Zalcman, A, Zhang, Y, Zhu, N, Zobrist, N, Neven, H, Boixo, S, Megrant, A, Kelly, J, Chen, Y, Smelyanskiy, V, Kim, E-A, Aleiner, I & Roushan, P 2023, 'Non-Abelian braiding of graph vertices in a superconducting processor', Nature, vol. 618, no. 7964, pp. 264-269.
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AbstractIndistinguishability of particles is a fundamental principle of quantum mechanics1. For all elementary and quasiparticles observed to date—including fermions, bosons and Abelian anyons—this principle guarantees that the braiding of identical particles leaves the system unchanged2,3. However, in two spatial dimensions, an intriguing possibility exists: braiding of non-Abelian anyons causes rotations in a space of topologically degenerate wavefunctions4–8. Hence, it can change the observables of the system without violating the principle of indistinguishability. Despite the well-developed mathematical description of non-Abelian anyons and numerous theoretical proposals9–22, the experimental observation of their exchange statistics has remained elusive for decades. Controllable many-body quantum states generated on quantum processors offer another path for exploring these fundamental phenomena. Whereas efforts on conventional solid-state platforms typically involve Hamiltonian dynamics of quasiparticles, superconducting quantum processors allow for directly manipulating the many-body wavefunction by means of unitary gates. Building on predictions that stabilizer codes can host projective non-Abelian Ising anyons9,10, we implement a generalized stabilizer code and unitary protocol23to create and braid them. This allows us to experimentally verify the fusion rules of the anyons and braid them to realize their statistics. We then study the prospect of using the anyons for quantum computation and use braiding to create an entangled state of anyons encoding three logical qubits. Our work provides new insights about non-Abelian braiding and, through the future inclusion of error correction to achieve topological protection, could open a path towards fault-tolerant quantum computing.

Biswas, K, Shivakumara, P, Pal, U, Lu, T, Blumenstein, M & Lladós, J 2023, 'Classification of aesthetic natural scene images using statistical and semantic features', Multimedia Tools and Applications, vol. 82, no. 9, pp. 13507-13532.
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Cao, MX & Tomamichel, M 2023, 'Comments on “Channel Coding Rate in the Finite Blocklength Regime”: On the Quadratic Decaying Property of the Information Rate Function', IEEE Transactions on Information Theory, vol. 69, no. 9, pp. 5528-5531.
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Chen, K, Wang, Q, Long, P & Ying, M 2023, 'Unitarity Estimation for Quantum Channels.', IEEE Trans. Inf. Theory, vol. 69, no. 8, pp. 5116-5134.
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Cheng, H-C, Winter, A & Yu, N 2023, 'Discrimination of Quantum States Under Locality Constraints in the Many-Copy Setting', Communications in Mathematical Physics, vol. 404, no. 1, pp. 151-183.
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Devitt, SJ 2023, 'How do we quantify the utility of quantum algorithms?', Research Directions: Quantum Technologies, vol. 1, pp. 1-4.
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Quantum computing advantage emerges not from brute force power, but from subtle differences in information processing that can occur for key bottleneck subroutines. In 2019, the Google Quantum AI team performed a landmark experiment demonstrating quantum computational supremacy (Arute et al., 2019) where they performed a quantum computation that, at the time, could not be done on a classical supercomputer. This was remarkable because it was achieved by a processor with only 53 qubits, an observation that emerged from theoretical work which identified that quantum computers could have a massive advantage for certain specially designed benchmarking tasks (Boixo et al., 2018; Bremner et al., 2016).

Fan, J, Li, J, Wang, Y, Li, Y, Hsieh, M-H & Du, J 2023, 'Partially Concatenated Calderbank-Shor-Steane Codes Achieving the Quantum Gilbert-Varshamov Bound Asymptotically', IEEE Transactions on Information Theory, vol. 69, no. 1, pp. 262-272.
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Fang, K, Zhao, J, Li, X, Li, Y & Duan, R 2023, 'Quantum NETwork: from theory to practice', Science China Information Sciences, vol. 66, no. 8.
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Fang, W & Ying, M 2023, 'SymPhase: Phase Symbolization for Fast Simulation of Stabilizer Circuits.', CoRR, vol. abs/2311.03906.

Grochow, J & Qiao, Y 2023, 'On the Complexity of Isomorphism Problems for Tensors, Groups, and Polynomials I: Tensor Isomorphism-Completeness', SIAM Journal on Computing, vol. 52, no. 2, pp. 568-617.
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Hoke, JC, Ippoliti, M, Rosenberg, E, Abanin, D, Acharya, R, Andersen, TI, Ansmann, M, Arute, F, Arya, K, Asfaw, A, Atalaya, J, Bardin, JC, Bengtsson, A, Bortoli, G, Bourassa, A, Bovaird, J, Brill, L, Broughton, M, Buckley, BB, Buell, DA, Burger, T, Burkett, B, Bushnell, N, Chen, Z, Chiaro, B, Chik, D, Cogan, J, Collins, R, Conner, P, Courtney, W, Crook, AL, Curtin, B, Dau, AG, Debroy, DM, Del Toro Barba, A, Demura, S, Di Paolo, A, Drozdov, IK, Dunsworth, A, Eppens, D, Erickson, C, Farhi, E, Fatemi, R, Ferreira, VS, Burgos, LF, Forati, E, Fowler, AG, Foxen, B, Giang, W, Gidney, C, Gilboa, D, Giustina, M, Gosula, R, Gross, JA, Habegger, S, Hamilton, MC, Hansen, M, Harrigan, MP, Harrington, SD, Heu, P, Hoffmann, MR, Hong, S, Huang, T, Huff, A, Huggins, WJ, Isakov, SV, Iveland, J, Jeffrey, E, Jiang, Z, Jones, C, Juhas, P, Kafri, D, Kechedzhi, K, Khattar, T, Khezri, M, Kieferová, M, Kim, S, Kitaev, A, Klimov, PV, Klots, AR, Korotkov, AN, Kostritsa, F, Kreikebaum, JM, Landhuis, D, Laptev, P, Lau, K-M, Laws, L, Lee, J, Lee, KW, Lensky, YD, Lester, BJ, Lill, AT, Liu, W, Locharla, A, Martin, O, McClean, JR, McEwen, M, Miao, KC, Mieszala, A, Montazeri, S, Morvan, A, Movassagh, R, Mruczkiewicz, W, Neeley, M, Neill, C, Nersisyan, A, Newman, M, Ng, JH, Nguyen, A, Nguyen, M, Niu, MY, O’Brien, TE, Omonije, S, Opremcak, A, Petukhov, A, Potter, R, Pryadko, LP, Quintana, C, Rocque, C, Rubin, NC, Saei, N, Sank, D, Sankaragomathi, K, Satzinger, KJ, Schurkus, HF, Schuster, C, Shearn, MJ, Shorter, A, Shutty, N, Shvarts, V, Skruzny, J, Smith, WC, Somma, R, Sterling, G, Strain, D, Szalay, M, Torres, A, Vidal, G, Villalonga, B, Heidweiller, CV, White, T, Woo, BWK, Xing, C, Yao, ZJ, Yeh, P, Yoo, J, Young, G, Zalcman, A, Zhang, Y, Zhu, N, Zobrist, N, Neven, H, Babbush, R, Bacon, D, Boixo, S, Hilton, J, Lucero, E, Megrant, A, Kelly, J, Chen, Y, Smelyanskiy, V, Mi, X, Khemani, V & Roushan, P 2023, 'Measurement-induced entanglement and teleportation on a noisy quantum processor', Nature, vol. 622, no. 7983, pp. 481-486.
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AbstractMeasurement has a special role in quantum theory1: by collapsing the wavefunction, it can enable phenomena such as teleportation2 and thereby alter the ‘arrow of time’ that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space–time3–10 that go beyond the established paradigms for characterizing phases, either in or out of equilibrium11–13. For present-day noisy intermediate-scale quantum (NISQ) processors14, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping9,15–17 to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling3,4 to measurement-induced teleportation18. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.

Huang, Z, Shivakumara, P, Kaljahi, MA, Kumar, A, Pal, U, Lu, T & Blumenstein, M 2023, 'Writer age estimation through handwriting', Multimedia Tools and Applications, vol. 82, no. 11, pp. 16033-16055.
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Handwritten image-based writer age estimation is a challenging task due to the various writing styles of different individuals, use of different scripts, varying alignment, etc. Unlike age estimation using face recognition in biometrics, handwriting-based age classification is reliable and inexpensive because of the plain backgrounds of documents. This paper presents a novel model for deriving the phase spectrum based on the Harmonic Wavelet Transform (HWT) for age classification on handwritten images from 11 to 65 years. This includes 11 classes with an interval of 5 years. In contrast to the Fourier transform, which provides a noisy phase spectrum due to loss of time variations, the proposed HWT-based phase spectrum retains time variations of phase and magnitude. As a result, the proposed HWT-based phase spectrum preserves vital information of changes in handwritten images. In order to extract such information, we propose new phase statistics-based features for age classification based on the understanding that as age changes, writing style also changes. The features and the input images are fed to a VGG-16 model for age classification. The proposed method is tested on our own dataset and three standard datasets, namely, IAM-2, KHATT and that of Basavaraja et al. to demonstrate the effectiveness of the proposed model compared to the existing methods in terms of classification rate. The results of the proposed and existing methods on different datasets show that the proposed method outperforms the existing methods in terms of classification rate.

Lee, T & Shraibman, A 2023, 'Around the log-rank conjecture', Israel Journal of Mathematics, vol. 256, no. 2, pp. 441-477.
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Liu, CL, Yagi, Y, Kamiya, T, Blumenstein, M, Lu, H, Yang, W & Cho, SB 2023, 'Preface for ACPR 2023 Proceedings', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14406 LNCS, pp. v-vi.

Liu, K, Lyu, S, Shivakumara, P, Blumenstein, M & Lu, Y 2023, 'A New Few-Shot Learning-Based Model for Prohibited Objects Detection in Cluttered Baggage X-Ray Images Through Edge Detection and Reverse Validation', IEEE Signal Processing Letters, vol. 30, pp. 1607-1611.
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Mohanty, N, Behera, BK & Ferrie, C 2023, 'Analysis of the Vehicle Routing Problem Solved via Hybrid Quantum Algorithms in the Presence of Noisy Channels', IEEE Transactions on Quantum Engineering, vol. 4, pp. 1-14.
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O’Brien, TE, Anselmetti, G, Gkritsis, F, Elfving, VE, Polla, S, Huggins, WJ, Oumarou, O, Kechedzhi, K, Abanin, D, Acharya, R, Aleiner, I, Allen, R, Andersen, TI, Anderson, K, Ansmann, M, Arute, F, Arya, K, Asfaw, A, Atalaya, J, Bardin, JC, Bengtsson, A, Bortoli, G, Bourassa, A, Bovaird, J, Brill, L, Broughton, M, Buckley, B, Buell, DA, Burger, T, Burkett, B, Bushnell, N, Campero, J, Chen, Z, Chiaro, B, Chik, D, Cogan, J, Collins, R, Conner, P, Courtney, W, Crook, AL, Curtin, B, Debroy, DM, Demura, S, Drozdov, I, Dunsworth, A, Erickson, C, Faoro, L, Farhi, E, Fatemi, R, Ferreira, VS, Flores Burgos, L, Forati, E, Fowler, AG, Foxen, B, Giang, W, Gidney, C, Gilboa, D, Giustina, M, Gosula, R, Grajales Dau, A, Gross, JA, Habegger, S, Hamilton, MC, Hansen, M, Harrigan, MP, Harrington, SD, Heu, P, Hoffmann, MR, Hong, S, Huang, T, Huff, A, Ioffe, LB, Isakov, SV, Iveland, J, Jeffrey, E, Jiang, Z, Jones, C, Juhas, P, Kafri, D, Khattar, T, Khezri, M, Kieferová, M, Kim, S, Klimov, PV, Klots, AR, Korotkov, AN, Kostritsa, F, Kreikebaum, JM, Landhuis, D, Laptev, P, Lau, K-M, Laws, L, Lee, J, Lee, K, Lester, BJ, Lill, AT, Liu, W, Livingston, WP, Locharla, A, Malone, FD, Mandrà, S, Martin, O, Martin, S, McClean, JR, McCourt, T, McEwen, M, Mi, X, Mieszala, A, Miao, KC, Mohseni, M, Montazeri, S, Morvan, A, Movassagh, R, Mruczkiewicz, W, Naaman, O, Neeley, M, Neill, C, Nersisyan, A, Newman, M, Ng, JH, Nguyen, A, Nguyen, M, Niu, MY, Omonije, S, Opremcak, A, Petukhov, A, Potter, R, Pryadko, LP, Quintana, C, Rocque, C, Roushan, P, Saei, N, Sank, D, Sankaragomathi, K, Satzinger, KJ, Schurkus, HF, Schuster, C, Shearn, MJ, Shorter, A, Shutty, N, Shvarts, V, Skruzny, J, Smith, WC, Somma, RD, Sterling, G, Strain, D, Szalay, M, Thor, D, Torres, A, Vidal, G, Villalonga, B, Vollgraff Heidweiller, C, White, T, Woo, BWK, Xing, C, Yao, ZJ, Yeh, P, Yoo, J, Young, G, Zalcman, A, Zhang, Y, Zhu, N, Zobrist, N, Bacon, D, Boixo, S, Chen, Y, Hilton, J, Kelly, J, Lucero, E, Megrant, A, Neven, H, Smelyanskiy, V, Gogolin, C, Babbush, R & Rubin, NC 2023, 'Purification-based quantum error mitigation of pair-correlated electron simulations', Nature Physics, vol. 19, no. 12, pp. 1787-1792.
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AbstractAn important measure of the development of quantum computing platforms has been the simulation of increasingly complex physical systems. Before fault-tolerant quantum computing, robust error-mitigation strategies were necessary to continue this growth. Here, we validate recently introduced error-mitigation strategies that exploit the expectation that the ideal output of a quantum algorithm would be a pure state. We consider the task of simulating electron systems in the seniority-zero subspace where all electrons are paired with their opposite spin. This affords a computational stepping stone to a fully correlated model. We compare the performance of error mitigations on the basis of doubling quantum resources in time or in space on up to 20 qubits of a superconducting qubit quantum processor. We observe a reduction of error by one to two orders of magnitude below less sophisticated techniques such as postselection. We study how the gain from error mitigation scales with the system size and observe a polynomial suppression of error with increased resources. Extrapolation of our results indicates that substantial hardware improvements will be required for classically intractable variational chemistry simulations.

Patil, G, Shivakumara, P, Gornale, SS, Pal, U & Blumenstein, M 2023, 'A new robust approach for altered handwritten text detection', Multimedia Tools and Applications, vol. 82, no. 14, pp. 20925-20949.
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Pira, L & Ferrie, C 2023, 'An invitation to distributed quantum neural networks', Quantum Machine Intelligence, vol. 5, no. 2.
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AbstractDeep neural networks have established themselves as one of the most promising machine learning techniques. Training such models at large scales is often parallelized, giving rise to the concept of distributed deep learning. Distributed techniques are often employed in training large models or large datasets either out of necessity or simply for speed. Quantum machine learning, on the other hand, is the interplay between machine learning and quantum computing. It seeks to understand the advantages of employing quantum devices in developing new learning algorithms as well as improving the existing ones. A set of architectures that are heavily explored in quantum machine learning are quantum neural networks. In this review, we consider ideas from distributed deep learning as they apply to quantum neural networks. We find that the distribution of quantum datasets shares more similarities with its classical counterpart than does the distribution of quantum models, though the unique aspects of quantum data introduce new vulnerabilities to both approaches. We review the current state of the art in distributed quantum neural networks, including recent numerical experiments and the concept of circuit-cutting.

Qiao, Y 2023, 'Turán and Ramsey Problems for Alternating Multilinear Maps', Discrete Analysis, vol. 2023.
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Guided by the connections between hypergraphs and exterior algebras, we study Turán and Ramsey type problems for alternating multilinear maps. This study lies at the intersection of combinatorics, group theory, and algebraic geometry, and has origins in the works of Lovász (Proc. Sixth British Combinatorial Conf., 1977), Buhler, Gupta, and Harris (J. Algebra, 1987), and Feldman and Propp (Adv. Math., 1992). Our main result is a Ramsey theorem for alternating bilinear maps. Given s, t ∈ N, s, t ≥ 2, and an alternating bilinear map ϕ: V × V → U with dim(V) ≥ s ·t4, we show that there exists either a dimension-s subspaceW ≤ V such that dim(span(ϕ(W,W))) = 0, or a dimension-t subspaceW ≤ V such that dim(span(ϕ(W,W))) = (t2). This result has natural group-theoretic (for finite p-groups) and geometric (for Grassmannians) implications, and leads to new Ramsey-type questions for varieties of groups and Grassmannians.

Quyet Truong, D, Choo, Y, Akther, N, Roobavannan, S, Norouzi, A, Gupta, V, Blumenstein, M, Vinh Nguyen, T & Naidu, G 2023, 'Selective rubidium recovery from seawater with metal-organic framework incorporated potassium cobalt hexacyanoferrate nanomaterial', Chemical Engineering Journal, vol. 454, pp. 140107-140107.
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Ramakrishnan, N, Tomamichel, M & Berta, M 2023, 'Moderate Deviation Expansion for Fully Quantum Tasks', IEEE Transactions on Information Theory, vol. 69, no. 8, pp. 5041-5059.
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Rambach, M, Youssry, A, Tomamichel, M & Romero, J 2023, 'Efficient quantum state tracking in noisy environments', Quantum Science and Technology, vol. 8, no. 1, pp. 015010-015010.
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Abstract Quantum state tomography, which aims to find the best description of a quantum state—the density matrix, is an essential building block in quantum computation and communication. Standard techniques for state tomography are incapable of tracking changing states and often perform poorly in the presence of environmental noise. Although there are different approaches to solve these problems theoretically, experimental demonstrations have so far been sparse. Our approach, matrix-exponentiated gradient (MEG) tomography, is an online tomography method that allows for state tracking, updates the estimated density matrix dynamically from the very first measurements, is computationally efficient, and converges to a good estimate quickly even with very noisy data. The algorithm is controlled via a single parameter, its learning rate, which determines the performance and can be tailored in simulations to the individual experiment. We present an experimental implementation of MEG tomography on a qutrit system encoded in the transverse spatial mode of photons. We investigate the performance of our method on stationary and evolving states, as well as significant environmental noise, and find fidelities of around 95% in all cases.

Tian, J, Sun, X, Du, Y, Zhao, S, Liu, Q, Zhang, K, Yi, W, Huang, W, Wang, C, Wu, X, Hsieh, M-H, Liu, T, Yang, W & Tao, D 2023, 'Recent Advances for Quantum Neural Networks in Generative Learning', IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1-20.
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Wang, Q, Zhang, Z, Chen, K, Guan, J, Fang, W, Liu, J & Ying, M 2023, 'Quantum Algorithm for Fidelity Estimation.', IEEE Trans. Inf. Theory, vol. 69, no. 1, pp. 273-282.
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For two unknown mixed quantum states ρ and σ in an N-dimensional Hilbert space, computing their fidelity F (ρ, σ) is a basic problem with many important applications in quantum computing and quantum information, for example verification and characterization of the outputs of a quantum computer, and design and analysis of quantum algorithms. In this paper, we propose a quantum algorithm that solves this problem in poly(log(N), r, 1/ϵ) time, where r is the lower rank of ρ and σ, and ϵ is the desired precision, provided that the purifications of ρ and σ are prepared by quantum oracles. This algorithm exhibits an exponential speedup over the best known algorithm (based on quantum state tomography) which has time complexity polynomial in N.

White, T, Opremcak, A, Sterling, G, Korotkov, A, Sank, D, Acharya, R, Ansmann, M, Arute, F, Arya, K, Bardin, JC, Bengtsson, A, Bourassa, A, Bovaird, J, Brill, L, Buckley, BB, Buell, DA, Burger, T, Burkett, B, Bushnell, N, Chen, Z, Chiaro, B, Cogan, J, Collins, R, Crook, AL, Curtin, B, Demura, S, Dunsworth, A, Erickson, C, Fatemi, R, Burgos, LF, Forati, E, Foxen, B, Giang, W, Giustina, M, Grajales Dau, A, Hamilton, MC, Harrington, SD, Hilton, J, Hoffmann, M, Hong, S, Huang, T, Huff, A, Iveland, J, Jeffrey, E, Kieferová, M, Kim, S, Klimov, PV, Kostritsa, F, Kreikebaum, JM, Landhuis, D, Laptev, P, Laws, L, Lee, K, Lester, BJ, Lill, A, Liu, W, Locharla, A, Lucero, E, McCourt, T, McEwen, M, Mi, X, Miao, KC, Montazeri, S, Morvan, A, Neeley, M, Neill, C, Nersisyan, A, Ng, JH, Nguyen, A, Nguyen, M, Potter, R, Quintana, C, Roushan, P, Sankaragomathi, K, Satzinger, KJ, Schuster, C, Shearn, MJ, Shorter, A, Shvarts, V, Skruzny, J, Smith, WC, Szalay, M, Torres, A, Woo, BWK, Yao, ZJ, Yeh, P, Yoo, J, Young, G, Zhu, N, Zobrist, N, Chen, Y, Megrant, A, Kelly, J & Naaman, O 2023, 'Readout of a quantum processor with high dynamic range Josephson parametric amplifiers', Applied Physics Letters, vol. 122, no. 1, pp. 014001-014001.
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We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in which the active nonlinear element is implemented using an array of rf-SQUIDs. The device is matched to the 50 Ω environment with a Klopfenstein-taper impedance transformer and achieves a bandwidth of 250–300 MHz with input saturation powers up to −95 dBm at 20 dB gain. A 54-qubit Sycamore processor was used to benchmark these devices, providing a calibration for readout power, an estimation of amplifier added noise, and a platform for comparison against standard impedance matched parametric amplifiers with a single dc-SQUID. We find that the high power rf-SQUID array design has no adverse effect on system noise, readout fidelity, or qubit dephasing, and we estimate an upper bound on amplifier added noise at 1.6 times the quantum limit. Finally, amplifiers with this design show no degradation in readout fidelity due to gain compression, which can occur in multi-tone multiplexed readout with traditional JPAs.

Ying, M & Zhang, Z 2023, 'Quantum Recursive Programming with Quantum Case Statements.', CoRR, vol. abs/2311.01725.

Youssry, A, Paz-Silva, GA & Ferrie, C 2023, 'Noise detection with spectator qubits and quantum feature engineering', New Journal of Physics, vol. 25, no. 7, pp. 073004-073004.
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Abstract Designing optimal control pulses that drive a noisy qubit to a target state is a challenging and crucial task for quantum engineering. In a situation where the properties of the quantum noise affecting the system are dynamic, a periodic characterization procedure is essential to ensure the models are updated. As a result, the operation of the qubit is disrupted frequently. In this paper, we propose a protocol that addresses this challenge by making use of a spectator qubit to monitor the noise in real-time. We develop a machine-learning-based quantum feature engineering approach for designing the protocol. The complexity of the protocol is front-loaded in a characterization phase, which allow real-time execution during the quantum computations. We present the results of numerical simulations that showcase the favorable performance of the protocol.

Yu, N 2023, 'Almost Tight Sample Complexity Analysis of Quantum Identity Testing by Pauli Measurements', IEEE Transactions on Information Theory, vol. 69, no. 8, pp. 5060-5068.
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Yu, N 2023, 'Structured Theorem for Quantum Programs and its Applications', ACM Transactions on Software Engineering and Methodology, vol. 32, no. 4, pp. 1-35.
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This article proves a structured program theorem for flowchart quantum programs. The theorem states that any flowchart quantum program is equivalent to a single quantum program that repeatedly executes a quantum measurement and a subprogram, so long as the measurement outcome is true. Moreover, their expected runtime, variance, and general moments are the same. This theorem simplifies the quantum program’s verification significantly. – We derive an analytical characterization of the termination problem for quantum programs in polynomial time. Our procedure is more efficient and accurate with much simpler techniques than the analysis of this problem, as described in [ 29 ]. – We compute the expected runtime analytically and exactly for quantum programs in polynomial time. This result improves the methods based on the weakest precondition calculus for the question recently developed in [ 31 , 34 ]. – We show that a single loop rule is a relatively complete Hoare logic for quantum programs after applying our structured theorem. Although using fewer rules, our method verifies a broad...

Basheer, A, Feng, Y, Ferrie, C & Li, S 1970, 'Alternating Layered Variational Quantum Circuits Can Be Classically Optimized Efficiently Using Classical Shadows', Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023, pp. 6770-6778.
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Variational quantum algorithms (VQAs) are the quantum analog of classical neural networks (NNs). A VQA consists of a parameterized quantum circuit (PQC) which is composed of multiple layers of ansatzes (simpler PQCs, which are an analogy of NN layers) that differ only in selections of parameters. Previous work has identified the alternating layered ansatz as potentially a new standard ansatz in near-term quantum computing. Indeed, shallow alternating layered VQAs are easy to implement and have been shown to be both trainable and expressive. In this work, we introduce a training algorithm with an exponential reduction in training cost of such VQAs. Moreover, our algorithm uses classical shadows of quantum input data, and can hence be run on a classical computer with rigorous performance guarantees. We demonstrate 2–3 orders of magnitude improvement in the training cost using our algorithm for the example problems of finding state preparation circuits and the quantum autoencoder.

Gavriel, J, Herr, D, Shaw, A, Bremner, MJ, Paler, A & Devitt, SJ 1970, 'Transversal Injection: Using the Surface Code to Prepare Non-Pauli Eigenstates', 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), IEEE.
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Guan, J, Fang, W, Huang, M & Ying, M 1970, 'Detecting Violations of Differential Privacy for Quantum Algorithms.', CoRR.

Halder, A, Shivakumara, P, Pal, U, Lu, T & Blumenstein, M 1970, 'A New Transformer-Based Approach for Text Detection in Shaky and Non-shaky Day-Night Video', Pattern Recognition, Asian Conference on Pattern Recognition, Springer Nature Switzerland, Kitakyushu, Japan, pp. 30-44.
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Text detection in shaky and non-shaky videos is challenging because of variations caused by day and night videos. In addition, moving objects, vehicles, and humans in the video make the text detection problems more challenging in contrast to text detection in normal natural scene images. Motivated by the capacity of the transformer, we propose a new transformer-based approach for detecting text in both shaky and non-shaky day-night videos. To reduce the effect of object movement, poor quality, and other challenges mentioned above, the proposed work explores temporal frames for obtaining activation frames based on similarity and dissimilarity measures. For estimating similarity and dissimilarity, our method extracts luminance, contrast, and structural features. The activation frames are fed to the transformer which comprises an encoder, decoder, and feed-forward network for text detection in shaky and non-shaky day-night video. Since it is the first work, we create our own dataset for experimentation. To show the effectiveness of the proposed method, experiments are conducted on a standard dataset called the ICDAR-2015 video dataset. The results on our dataset and standard dataset show that the proposed model is superior to state-of-the-art methods in terms of recall, precision, and F-measure.

Hong, X, Huang, W-J, Chien, W-C, Feng, Y, Hsieh, M-H, Li, S, Yeh, C-S & Ying, M 1970, 'Decision Diagrams for Symbolic Verification of Quantum Circuits.', QCE, IEEE, pp. 970-977.

Ivanyos, G & Qiao, Y 1970, 'On the orbit closure intersection problems for matrix tuples under conjugation and left-right actions', Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 4115-4126.
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Let G be a linear algebraic group acting on the vector space V. Given v, v′ ∈ V, the orbit closure intersection problem asks to decide if the orbit closures of v and v′ under G intersect. Due to connections with polynomial identity testing, the orbit closure intersection problems for the conjugation and left-right actions on matrix tuples received considerable attention in computational complexity and computational invariant theory, as seen in the works of Forbes-Shpilka (RANDOM 2013), Allen-Zhu-Garg-Li-Oliveira-Wigderson (STOC 2018), and Derksen-Makam (Algebra & Number Theory 2020). In this paper, we present new algorithms for the orbit closure problem for the conjugation and left-right actions on matrix tuples. The main novel feature is that in the case of intersecting orbit closures, our algorithm outputs cosets of one-parameter subgroups that drive the matrix tuples to a tuple in the intersection of the orbit closures.

Li, S, Nguyen, KD, Clare, Z & Feng, Y 1970, 'Single-Qubit Gates Matter for Optimising Quantum Circuit Depth in Qubit Mapping', 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), IEEE.
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Liu, A, Han, Q, Xia, L & Yu, N 1970, 'Accelerating Voting by Quantum Computation', Proceedings of Machine Learning Research, pp. 1274-1283.
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Studying the computational complexity and designing fast algorithms for determining winners under voting rules are classical and fundamental questions in computational social choice. In this paper, we accelerate voting by leveraging quantum computation: we propose a quantum-accelerated voting algorithm that can be applied to any anonymous voting rule. We show that our algorithm can be quadratically faster than any classical algorithm (based on sampling with replacement) under a wide range of common voting rules, including positional scoring rules, Copeland, and single transferable voting (STV). Precisely, our quantum-accelerated voting algorithm outputs the correct winner with high probability in (Equation presented) time, where n is the number of votes and MoV is margin of victory, the smallest number of voters to change the winner. In contrast, any classical voting algorithm based on sampling with replacement requires (Equation presented) time under a large class of voting rules. Our theoretical results are supported by experiments under plurality, Borda, Copeland, and STV.

Liu, S, Benchasattabuse, N, Morgan, DQC, Hajdušek, M, Devitt, SJ & Van Meter, R 1970, 'A Substrate Scheduler for Compiling Arbitrary Fault-Tolerant Graph States', 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), IEEE.
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Sadaf, A, Mathieson, L, Bródka, P & Musial, K 1970, 'Maximising Influence Spread in Complex Networks by Utilising Community-Based Driver Nodes as Seeds', Springer Nature Switzerland, pp. 126-141.
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Wang, W, Shen, T, Blumenstein, M & Long, G 1970, 'Improving Open-Domain Answer Sentence Selection by Distributed Clients with Privacy Preservation', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature Switzerland, pp. 15-29.
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Open-domain answer sentence selection (OD-AS2), as a practical branch of open-domain question answering (OD-QA), aims to respond to a query by a potential answer sentence from a large-scale collection. A dense retrieval model plays a significant role across different solution paradigms, while its success depends heavily on sufficient labeled positive QA pairs and diverse hard negative sampling in contrastive learning. However, it is hard to satisfy such dependencies in a privacy-preserving distributed scenario, where in each client, fewer in-domain pairs and a relatively small collection cannot support effective dense retriever training. To alleviate this, we propose a brand-new learning framework for Privacy-preserving Distributed OD-AS2, dubbed PDD-AS2. Built upon federated learning, it consists of a client-customized query encoding for better personalization and a cross-client negative sampling for learning effectiveness. To evaluate our learning framework, we first construct a new OD-AS2 dataset, called Fed-NewsQA, based on NewsQA to simulate distributed clients with different genre/domain data. Experiment results show that our learning framework can outperform its baselines and exhibit its personalization ability.

Devitt, SJ & Langford, NK Standards Australia 2023, At the Intersection between Quantum Communication Networks and Standardisation, pp. 1-47, Sydney, Australia.

Langford, NK & Devitt, SJ Standards Australia 2023, At the Intersection Between Scalable Quantum Computing and Standardisation, pp. 1-42, Sydney, Australia.

Langford, NK & Devitt, SJ Standards Australia 2023, Quantum Education, Training and Literacy: Laying Good Foundations for the Future Quantum Industry, Sydney, Australia.

Langford, NK & Devitt, SJ Standards Australia 2023, Quantum Technologies and Standardisation Globally and in Australia, Sydney, Australia.

Allcock, J, Bao, J, Belovs, A, Lee, T & Santha, M 2023, 'On the quantum time complexity of divide and conquer'.

Beigi, S & Tomamichel, M 2023, 'Lower Bounds on Error Exponents via a New Quantum Decoder'.

Berta, M & Tomamichel, M 2023, 'Entanglement monogamy via multivariate trace inequalities'.

Brahmachari, S, Rubboli, R & Tomamichel, M 2023, 'A fixed-point algorithm for matrix projections with applications in quantum information'.

Bremner, MJ, Cheng, B & Ji, Z 2023, 'IQP Sampling and Verifiable Quantum Advantage: Stabilizer Scheme and Classical Security'.

Cervero-Martín, E & Tomamichel, M 2023, 'Device independent security of quantum key distribution from monogamy-of-entanglement games'.

Chapman, A, Elman, SJ & Mann, RL 2023, 'A Unified Graph-Theoretic Framework for Free-Fermion Solvability'.

Chen, K-C, Apers, S & Hsieh, M-H 2023, '(Quantum) complexity of testing signed graph clusterability'.

Cheng, MH, Chen, Y-C, Wang, Q, Bartsch, V, Kim, MS, Hu, A & Hsieh, M-H 2023, 'Unleashing Quantum Simulation Advantages: Hamiltonian Subspace Encoding for Resource Efficient Quantum Simulations'.

Farooq, MU, Fritz, T, Haapasalo, E & Tomamichel, M 2023, 'Matrix majorization in large samples'.

Figueroa-Romero, P, Papič, M, Auer, A, Hsieh, M-H, Modi, K & Vega, ID 2023, 'Operational Markovianization in Randomized Benchmarking'.

Hirche, C & Tomamichel, M 2023, 'Quantum Rényi and $f$-divergences from integral representations'.

Hu, Y & Tomamichel, M 2023, 'Fundamental limits on quantum cloning from the no-signalling principle'.

Li, S, Nguyen, KD, Clare, Z & Feng, Y 2023, 'Single-Qubit Gates Matter for Optimising Quantum Circuit Depth in Qubit Mapping'.

Lipka-Bartosik, P, Chubb, CT, Renes, JM, Tomamichel, M & Korzekwa, K 2023, 'Quantum dichotomies and coherent thermodynamics beyond first-order asymptotics'.

Lo, Y-F, Lee, Y-C & Hsieh, M-H 2023, 'Capacity Bounds for Vertically-Drifted First Arrival Position Channels under a Covariance Constraint'.

Ouyang, Y, Goswami, K, Romero, J, Sanders, BC, Hsieh, M-H & Tomamichel, M 2023, 'Approximate reconstructability of quantum states and noisy quantum secret sharing schemes'.

Rubboli, R, Takagi, R & Tomamichel, M 2023, 'Mixed-state additivity properties of magic monotones based on quantum relative entropies for single-qubit states and beyond'.

Wills, A, Hsieh, M-H & Strelchuk, S 2023, 'Efficient Algorithms for All Port-Based Teleportation Protocols'.

Wills, A, Lin, T-C & Hsieh, M-H 2023, 'General Distance Balancing for Quantum Locally Testable Codes'.

Wills, A, Lin, T-C & Hsieh, M-H 2023, 'Tradeoff Constructions for Quantum Locally Testable Codes'.