2018
“Quantum annealing of the p-spin model under inhomogeneous transverse field driving”, Phys. Rev. A 98, 042326 (2018), by Y. Susa, Y. Yamashiro, M. Yamamoto, I. Hen, D. A. Lidar and H. Nishimori [link]
“Error Reduction in Quantum Annealing using Boundary Cancellation: Only the End Matters”, Phys. Rev. A 98, 022315 (2018) , by L. Campos Venuti and D. A. Lidar [link]
“Reverse annealing for the fully connected p-spin model”, Phys. Rev. A 98, 022314 (2018), by M. Ohkuwa, H. Nishimori and D. A. Lidar [link]
“Finite temperature quantum annealing solving exponentially small gap problem with non-monotonic success probability”, Nature Comm. 9, 2917 (2018), by A. Mishra, T. Albash and D. A. Lidar [link]
“Demonstration of a Scaling Advantage for a Quantum Annealer over Simulated Annealing”, Phys. Rev. X 8, 031016 (2018), by T. Albash and D. A. Lidar [link]
“Test-driving 1000 qubits”, Quantum Science & Technology 3, 030501 (2018). Special issue on “What would you do with 1000 qubits” , by J. Job and D. A. Lidar [link]
“Quantum trajectories for time-dependent adiabatic master equations”, Phys. Rev. A 97, 022116 (2018), by K. W. Yip, T. Albash, D. A. Lidar [link]
“Quantum annealing versus classical machine learning applied to a simplified computational biology problem”, npj Quant. Info. 4, 14 (2018), by R. Y. Li, R. Di Felice, R. Rohs and D. A. Lidar [link]
“Scalable effective temperature reduction for quantum annealers via nested quantum annealing correction”, Phys. Rev. A 97, 022308 (2018), by W. Vinci and D. A. Lidar [link]
“Adiabatic Quantum Computation”, Rev. Mod. Phys. 90, 015002 (2018), by T. Albash and D. A. Lidar [link]
2017
“Off-diagonal expansion quantum Monte Carlo”, Phys. Rev. E 96, 063309 (2017), by T. Albash, G. Wagenbreth and I. Hen [link]
“Temperature Scaling Law for Quantum Annealing Optimizers”, Phys. Rev. Lett. 119, 110502 (2017), by T. Albash, V. Martin-Mayor and I. Hen [link]
“Solving a Higgs optimization problem with quantum annealing for machine learning”, Nature 550, 375 (2017), A. Mott, J. Job, J. R. Vlimant, D. A. Lidar, and M. Spiropulu [link]
“Non-stoquastic Hamiltonians in quantum annealing via geometric phases”, Nature Quant. Info. 3, 38 (2017), by W. Vinci and D. A. Lidar [link]
“Quasi-adiabatic Grover search via the WKB approximation”, Phys. Rev. A 96, 012329 (2017), by S. Muthukrishnan and D. A. Lidar [link]
“Relaxation vs. adiabatic quantum steady state preparation: which wins?”, Phys. Rev. A 95, 042302 (2017), by L. Campos Venuti, T. Albash, M. Marvian, D. A. Lidar, and P. Zanardi [link]
“Error Suppression for Hamiltonian Quantum Computing in Markovian Environments”, Phys. Rev. A 95, 032302 (2017), by M. Marvian and D. A. Lidar [link]
“Quantum annealing correction at finite temperature: ferromagnetic p-spin models”, Phys. Rev. A 95, 022308 (2017), by S. Matsuura, H. Nishimori, W. Vinci, T. Albash, and D. A. Lidar [link]
“Error suppression for Hamiltonian-based quantum computation using subsystem codes”, Phys. Rev. Lett. 118, 030504 (2017), by M. Marvian and D. A. Lidar [link]
2016
“Optimally Stopped Optimization”, Phys. Rev. Applied 6, 054016 (2016), by W. Vinci and D. A. Lidar [link]
“Simulated Quantum Annealing with Two All-to-All Connectivity Schemes”, Phys. Rev. A 94, 022327 (2016), by T. Albash, W. Vinci, and D. A. Lidar [link]
“Eigenstate Tracking in Open Quantum Systems”, Phys. Rev. A 94, 042131 (2016), by J. Jing, M. S. Sarandy, D. A. Lidar, D. W. Luo, and L. A. Wu [link]
“Nested Quantum Annealing Correction”, Nature Quant. Info. 2, 16017 (2016), by W. Vinci, T. Albash, and D. A. Lidar [link]
“Tunneling and speedup in quantum optimization for permutation-symmetric problems”, Phys. Rev. X, 6, 031010 (2016), by S. Muthukrishnan, T. Albash, and D. A. Lidar [link]
“Mean Field Analysis of Quantum Annealing Correction”, Phys. Rev. Lett. 116, 220501 (2016), by S. Matsuura, H. Nishimori, T. Albash, D.A. Lidar [link]
“Adiabaticity in open quantum systems”, Phys. Rev. A 93, 032118 (2016), by L.C. Venuti, T. Albash, D. A. Lidar, and P. Zanardi [link]
“Performance of two different quantum annealing correction codes”, Quant. Info. Proc. 15, 2, pp. 609-636 (2016), by A. Mishra, T. Albash, D.A. Lidar [link]
“Quantum versus simulated annealing in wireless interference network optimization”, Nature Sci. Rep. 25797 (2016), by C. Wang, H. Chen, E. Jonckheere [link]
2015
“Probing for quantum speedup in spin glass problems with planted solutions”, Phys. Rev. A 92, 042325 (2015), by I. Hen, J. Job, T. Albash, T.F. Ronnow, M. Troyer, and D.A. Lidar [link]
“Quantum Annealing Correction with Minor Embedding”, Journal of Physics: Conference Series 640, 012038 (2015), by W. Vinci, T. Albash, G. Paz-Silva, I. Hen, and D. A. Lidar [link]
“Decoherence in adiabatic quantum computation”, Phys. Rev. A 91, 062320 (2015), by T. Albash and D.A. Lidar [pdf]
“Consistency tests of classical and quantum models for a quantum annealer”, Phys. Rev. A 91, 042314 (2015), by T. Albash, W. Vinci, A. Mishra, P.A. Warburton, and D.A. Lidar [pdf]
“Quantum Annealing Correction for Random Ising Problems”, Phys. Rev. A 91, 042302 (2015), by K. Pudenz, T. Albash, and D. Lidar. [pdf]
“Reexamining classical and quantum models for the D-Wave One processor”, The European Physics Journal, Special Topics 224, 111 (special issue on quantum annealing) (2015), by T. Albash, T. Ronnow, M. Troyer, D.A. Lidar [link]
“Performance of the quantum adiabatic algorithm on constraint satisfaction and spin glass problems”, European Physical Journal Special Topics 224, 63-73 (2015), by I. Hen and A. P. Young. [link]
“Quantum gates with controlled adiabatic evolutions”, Phys. Rev. A 91, 022309 (2015), by I. Hen. [pdf]
“Unraveling Quantum Annealers using Classical Hardness”, [1502.02494], by I. Hen and V. Martin-Mayor.
“Reexamination of the evidence for entanglement in the D-Wave processor”, [1506.03539], by T. Albash, I. Hen, F. M. Spedalieri, D. A. Lidar
2014
“Quantum error suppression with commuting Hamiltonians: Two-local is too local”, Phys. Rev. Lett. 113, 260504 (2014), by I. Marvian and D.A. Lidar [pdf]
“Entanglement in a quantum annealing processor”, Phys. Rev. X 4, 021041 (published 29 May 2014), by T. Lanting, A.J. Przybysz, A. Yu. Smirnov, F.M. Spedalieri, M.H. Amin, A.J. Berkley, R. Harris, F. Altomare, S. Boixo, P. Bunyk, N. Dickson, C. Enderud, J.P. Hilton, E. Hoskinson, M.W. Johnson, E. Ladizinsky, N. Ladizinsky, R. Neufeld, T. Oh, I. Perminov, C. Rich, M.C. Thom, E. Tolkacheva, S. Uchaikin, A.B. Wilson and G. Rose. [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]
“MAX 2-SAT with up to 108 Qubits”, New J. Phys. 16, 045006 (2014), by S. Santra, G. Quiroz, G. Ver Steeg, and D.A. Lidar. [link]
“Consistency tests of classical and quantum models for a quantum annealer”, Phys. Rev. A 91, 042314 (2015), by T. Albash, W. Vinci, A. Mishra, P.A. Warburton, and D.A. Lidar [link]
“Evidence of Quantum Annealing with More Than One Hundred Qubits”, Nature Physics 10, 218 (2014), by S. Boixo, T. Ronnow, S. Isakov, Z. Wang, D. Wecker, D.Lidar, J. Martinis, and M. Troyer. [pdf]
“Error-Corrected Quantum Annealing with Hundreds of Qubits”, Nature Communications 5, 3243 (2014), by K. Pudenz, T. Albash, and D. Lidar. [pdf]
“How Fast Can Quantum Annealers Count?”, J. Phys. A: Math. Theor. 47, 235304 (2014), by I. Hen [pdf]
“Continuous-Time Quantum Algorithms for Unstructured Problems”, J. Phys. A: Math. Theor. 47, 045305 (2014), by I. Hen [pdf]
“Period finding with Adiabatic Quantum Computation”, Europhysics Letters 105, 50005 (2014), by I. Hen [pdf]
“Phase Transitions in Planning Problems: Design and Analysis of Parameterized Families of Hard Planning Problems”, AAAI 2014: 2337-2343 (2014), by E. G. Rie el, M. Do, D. Venturelli, I. Hen and J. Franks. [pdf]
“Fourier-transforming with quantum annealers”. Front. Phys. 2, 44 (2014), by I. Hen [link]
“Optimized tomography for pure quantum states”, [1409.1952], by A. Kalev and I. Hen.
2013
“Adiabatic Quantum Optimization with the Wrong Hamiltonian”, Phys. Rev. A 88, 062314 (2013), by K.C. Young, R. Blume-Kohout, D.A. Lidar. [pdf]
“Experimental Signature of Programmable Quantum Annealing”, Nature Communications 4, 2067 (2013), by S. Boixo, T. Albash, F. Spedalieri, N. Chancellor, D. Lidar. [pdf]
“Quantum Adiabatic Machine Learning”, Quantum Info. Process. 12, 2027 (2013), by K. Pudenz and D.A. Lidar. [pdf]
2012
“Quantum Adiabatic Markovian Master Equations”, New J. of Physics 14, 123016 (2012), by T. Albash, S. Boixo, D. Lidar, and P. Zanardi. [pdf]
“Detecting Entanglement with Partial State Information”, Phys. Rev. A 86, 062311 (2012), by F. Spedalieri. [pdf]
“Adiabatic Quantum Algorithm for Search Engine Ranking”, Phys. Rev. Lett. 108, 230506 (2012), by S. Garnerone, P. Zanardi, D. Lidar. [pdf]
“High-Fidelity Adiabatic Quantum Computation via Dynamical Decoupling”, Phys. Rev. A 86, 042333 (2012), by G. Quiroz and D. Lidar. [pdf]
“Excitation Gap from Optimized Correlation Functions in Quantum Monte Carlo Simulations”, Phys. Rev. E 85, 036705 (2012) by I. Hen. [pdf]
“Solving the Graph Isomorphism Problem with a Quantum Annealer”, Phys. Rev. A 86, 042310 (2012), I. Hen and A. P. Young. [pdf]
“The performance of the quantum adiabatic algorithm on 3 Regular 3XORSAT and 3 Regular Max-Cut”, Phys. Rev. A 86, 052334 (2012), E. Farhi, D. Gosset, I. Hen, A. W. Sandvik, P. Shor, A. P. Young, and F. Zamponi. [pdf]