Journal Articles

“Demonstration of algorithmic quantum speedup”, Phys. Rev. Lett. 130, 210602 (2023) by B. Pokharel and D. A. Lidar [link]

“Boundaries of quantum supremacy via random circuit sampling”, npj Quantum Information, 9, 36 (2023), by A. Zlokapa, S. Boixo, and D. A. Lidar [link]

“Demonstration of Error-Suppressed Quantum Annealing Via Boundary Cancellation”, Phys. Rev. Applied 19 , 034095 (2023), by H. Munoz-Bauza, L. Campos Venuti, and D. A. Lidar [link]

“Quantum adiabatic theorem for unbounded Hamiltonians with a cutoff and its application to superconducting circuits”, Phil. Trans. R. Soc. 381: 20210407 (2023), by E. Mozgunov and D. A. Lidar [link]

“Coherent quantum annealing in a programmable 2,000 qubit Ising chain”, Nat. Phys. (2022), by A. D. King, S. Suzuki, J. Raymond, A. Zucca, T. Lanting, F. Altomare, A. J. Berkley, S. Ejtemaee, E. Hoskinson, S. Huang, E. Ladizinsky, A. J. R. MacDonald, G. Marsden, T. Oh, G. Poulin-Lamarre, M. Reis, C. Rich, Y. Sato, J. D. Whittaker, J. Yao, R. Harris, D. A. Lidar, H. Nishimori, M. H. Amin [link]

“Suppression of crosstalk in superconducting qubits using dynamical decoupling”, Phys. Rev. Applied 18, 024068 (2022), by V. Tripathi, H. Chen, M. Khezri, Ka-Wa Yip, E. M. Levenson-Falk, D. A. Lidar [link]

“Demonstration of long-range correlations via susceptibility measurements in a one-dimensional superconducting Josephson spin chain”, npj Quantum Information 8, 85 (2021), by D. M. Tennant, X. Dai, A. J. Martinez, R. Trappen, D. Melanson, M. A. Yurtalan, Y. Tang, S. Bedkihal, R. Yang, S. Novikov, J. A. Grover, S. M. Disseler, J. I. Basham, R. Das, D. K. Kim, A. J. Melville, B. M. Niedzielski, S. J. Weber, J. L. Yoder, A. J. Kerman, E. Mozgunov, D. A. Lidar & A. Lupascu [link]

“Breakdown of the weak coupling limit in quantum annealing”, Phys. Rev. Applied 17, 054033 (2022), by Y. Bando, Ka-Wa Yip, H. Chen, D. A. Lidar, H. Nishimori [link]

“Predicting non-Markovian superconducting qubit dynamics from tomographic reconstruction”, Phys. Rev. Applied 17, 054018 (2022), by H. Zhang, B. Pokharel, E. M. Levenson-Falk and D. A. Lidar [link]

“HOQST: Hamiltonian Open Quantum System Toolkit”, Communications Physics (2022)5:11, by H. Chen and D. A. Lidar [link]

“Customized quantum annealing schedules”, Phys. Rev. Applied 17, 044005 (2022), by M. Khezri, X. Dai, R. Yang, T. Albash, A. Lupascu, D. A. Lidar [link]

“Standard quantum annealing outperforms adiabatic reverse annealing with decoherence”, Phys. Rev. A 105, 032431 (2022), by G. Passarelli, K.-W. Yip, D.A. Lidar, P. Lucignano [link]

“3-Regular 3-XORSAT Planted Solutions Benchmark of Classical and Quantum Heuristic Optimizers”, Quantum Sci. Technol. 7 025008 (2022), by M. Kowalsky, T. Albash, I. Hen, D. A. Lidar [link]

“Optimal Control for Closed and Open System Quantum Optimization”, Phys. Rev. Applied 16, 054023 (2021), by L. Campos Venuti, D. D’Alessandro and D. A. Lidar [link]

“Charged particle tracking with quantum annealing-inspired optimization”, Quantum Machine Intelligence 3, 27 (2021), by A. Zlokapa, A. Anand, J-R. Vlimant, J. Duarte, J. Job, D. Lidar and M. Spiropulu [link]

“Identification of driver genes for severe forms of COVID-19 in a deeply phenotyped young patient cohort”, Science Translational Medicine (2021), by R. Carapito, R. Li, J. Helms, C. Carapito, S. Gujja, V. Rolli, R. Guimaraes, J. Malagon-Lopez, P. Spinnhirny, R. Mohseninia, A. Hirschler, L. Muller, P. Bastard, A. Gervais, Q. Zhang, F.s Danion, Y. Ruch, M. Schenck-Dhif, O. Collange, T.-N. Chamaraux-Tran, A. Molitor, A. Pichot, A. Bernard, O. Tahar, S. Bibi-Triki, H. Wu, N. Paul, S. Mayeur, A. Larnicol, G. Laumond, J. Frappier, S. Schmidt, A. Hanauer, C. Macquin, T. Stemmelen, M. Simons, X. Mariette, O. Hermine, S. Fafi-Kremer, B. Goichot, B. Drenou, K. Kuteifan, J. Pottecher, P.-M. Mertes, S. Kailasan, J. Aman, E. Pin, P. Nilsson, A. Thomas, A. Viari, D. Sanlaville, F. Schneider, J. Sibilia, P.-L. Tharaux, J.-L. Casanova, Y. Hansmann, D. Lidar, M. Radosavljevic, J.R. Gulcher, F. Meziani, C. Moog, T.W. Chittenden, S. Bahram [link]

“Calibration of flux crosstalk in large-scale flux-tunable superconducting quantum circuits”, PRX Quantum 2, 040313 (2021), by X. Dai, D. M. Tennant, R. Trappen, A. J. Martinez, D. Melanson, M. A. Yurtalan, Y. Tang, S. Novikov, J. A. Grover, S. M. Disseler, J. I. Basham, R. Das, D. K. Kim, A. J. Melville, B. M. Niedzielski, S. J. Weber, J. L. Yoder, D. A. Lidar, and A. Lupascu [link]

“Phase transitions in the frustrated Ising ladder with stoquastic and non-stoquastic catalysts”, Phys. Rev. Research 3 (2021), by K. Takada, S. Sota, S. Yunoki, B. Pokharel, H. Nishimori, D. A. Lidar [link]

“Prospects for quantum enhancement with diabatic quantum annealing”, Nat Rev Phys 3466–489 (2021), by E. J. Crosson and D. A. Lidar [link]

“Quantum processor-inspired machine learning in the biomedical sciences”, Patterns 2, 100246 (2021) by R. Li, S. Gujja, S. Bajaj, O. Gamel, N. Cilfone, J. Gulcher, D. A. Lidar and T. Chittenden [link]

“Low overhead universality and quantum supremacy using only Z-control”, Phys. Rev. Research 3, 033207 (2021), by B. Barch, R. Mohseninia and D. A. Lidar [link]

“Quantum adiabatic machine learning with zooming”, Phys. Rev. A 102, 062405, by A. Zlokapa, A. Mott, J-R. Vlimant, J. Job, D. A. Lidar and M. Spiropulu [link]

“Fast, Lifetime-Preserving Readout for High-Coherence Quantum Annealers”, PRX Quantum 1, 020314, by J. A. Grover, J. I. Basham, A. Marakov, S. M. Disseler, R. T. Hinkey, M. Khalil, Z. A. Stegen, T. Chamberlin, W. DeGottardi, D. J. Clarke, J. R. Medford, J. D. Strand, M. Stoutimore, S. Novikov, D. G. Ferguson, D. A. Lidar, K. M. Zick, A. J. Przybysz [link]

“Limitations of error corrected quantum annealing in improving the performance of Boltzmann machines”, Quantum Science and Technology 5, 045010 (2020), by R. Li, T. Albash and D. A. Lidar [link]

“Why and when is pausing beneficial in quantum annealing?”, Phys. Rev. Applied 14, 014100 (2020),  by H. Chen and D. A. Lidar [link]

“Reverse quantum annealing of the p-spin model with relaxation”, Phys. Rev. A. 101, 022331 (2020), by G. Passarelli, K. Yip, D. A. Lidar, H. Nishimori and P. Lucignano [link]

“Probing the Universality of Topological Defect Formation in a Quantum Annealer: Kibble-Zurek Mechanism and Beyond”, Phys. Rev. Research 2, 033369 (September 2020), by Y. Bando, Y. Susa, H. Oshiyama, N. Shibata, M. Ohzeki, F. J. G´omez-Ruiz, D. A. Lidar, A. del Campo, S. Suzuki, and H. Nishimori [link]

“Analog Errors in Quantum Annealing: Doom and Hope” npj Quantum Information 5, 107 (2019), by A. Pearson, A. Mishra, I. Hen and D. A. Lidar [link]

“Sensitivity of quantum speedup by quantum annealing to a noisy oracle”, Phys. Rev. A 99, 032324 (2019), by S. Muthukrishnan, T. Albash and D. A. Lidar [link]

“Adiabatic Quantum Computation”, Rev. Mod. Phys. 90, 015002 (2018), by T. Albash and D. A. Lidar [link]

“Defining and Detecting Quantum Speedup”, Science 345, 420 (2014), by T.F. Ronnow, Z. Wang, J. Job, S.V. Isakov, D. Wecker, J.M. Martinis, D.A. Lidar, and M. Troyer.[link]

“The Manipulation of Massive Ro-vibronic Superpositions Using Time-Frequency-Resolved Coherent Anti-Stokes Raman Scattering (TFRCARS): from Quantum Control to Quantum Computing”, Chemical Physics 266, 323 (2001), R. Zadoyan, D. Kohen, D.A. Lidar, and V.A. Apkarian [pdf]