“Prospects for Quantum Enhancement with Diabatic Quantum Annealing” [2008.09913], by E.J. Crosson and D.A. Lidar.

“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]

“Boundaries of quantum supremacy via random circuit sampling”, [2005.02464], by A. Zlokapa, S. Boixo, and D. A. Lidar

“Quantum adiabatic machine learning with zooming”, [1908.04480], by A. Zlokapa, A. Mott, J-R. Vlimant, J. Job, D. Lidar and M. Spiropulu

“Charged particle tracking with quantum annealing-inspired optimization”, [1908.04475], by A. Zlokapa, A. Anand, J-R. Vlimant, J. Duarte, J. Job, D. Lidar and M. Spiropulu

“On the computational complexity of curing non-stoquastic Hamiltonians”, Nature Comm. **10**, 1571 (2019), by M. Marvian, D. A. Lidar and I. Hen [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]

“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]

“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 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]

“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

“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]

“Optimally Stopped Optimization”, Phys. Rev. Applied **6**, 054016 (2016), by W. Vinci 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]

“When Diabatic Trumps Adiabatic in Quantum Optimization”, [1505.01249], by S. Muthukrishnan, T. Albash, and D.A. Lidar

“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”,Phys. Rev. A **92**, 042310 (2015), by W. Vinci, T. Albash, G. Paz-Silva, I. Hen, and D. A. Lidar [link]

“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]

“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]

“Evidence for 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.A. Lidar, J. Martinis, and M. Troyer. [link][sup-mat]

“Analysis of Generalized Grover Quantum Search Algorithms Using Recursion Equations”, Phys. Rev. A **63**, 012310 (2001), by E. Biham, O. Biham, D. Biron, M. Grassl, D.A. Lidar, and D. Shapira [pdf]

“Calculating the Thermal Rate Constant with Exponential Speedup on a Quantum Computer”, Phys. Rev. E **59**, 2429 (1999), by D.A. Lidar and H. Wang [pdf]

“Grovers Quantum Search Algorithm for Arbitrary Initial Amplitude Distribution”, Phys. Rev. A **60**, 2742 (1999), by E. Biham, O. Biham, D. Biron, M. Grassl, and D.A. Lidar [pdf]

“Simulating Ising Spin Glasses on a Quantum Computer”, Phys. Rev. E **56**, 3661 (1997), , by D.A. Lidar and O. Biham [pdf]

“Accuracy Versus Run Time in an Adiabatic Quantum Search”, Phys. Rev. A **82**, 052305 (2010), by A.T. Rezakhani, A.K. Pimachev, and D.A. Lidar. [link]

“Adiabatic Quantum Algorithm for Search Engine Ranking”, Phys. Rev. Lett. **108**, 230506 (2012), by S. Garnerone, P. Zanardi, and D.A. Lidar [link][sup-mat]

“An Implementation of the Deutsch-Jozsa Algorithm on Molecular Vibronic Coherences Through Four-Wave Mixing: a Theoretical Study”, Chem. Phys. Lett. **360**, 459 (2002), by Z. Bihary, D.R. Glenn, D.A. Lidar, and V.A. Apkarian [pdf]

“Classical Ising Model Test for Quantum Circuits”, New J. Physics **12**, 075026 (2010), by J. Geraci and D.A. Lidar [link]

“Encoding a Qubit into Multilevel Subspaces”, New J. Phys. **8**, 35 (2006), by M. Grace, C. Brif, H. Rabitz, I. Walmsley, R. Kosut, and D.A. Lidar [link]

“On the Exact Evaluation of Certain Instances of the Potts Partition Function by Quantum Computers”, Commun. Math. Phys279, **3**, 735-768 (2008), by J. Geraci and D.A. Lidar [link]

“On the Quantum Computational Complexity of the Ising Spin Glass Partition Function and of Knot Invariants”, New J. Phys. **6**, 167 (2004), by D. Lidar [pdf]

“Polynomial-Time Simulation of Pairing Models on a Quantum Computer”, Phys. Rev. Lett. **89**, 057904 (2002), by L.-A. Wu, M.S. Byrd, and D.A. Lidar [pdf]

“Quantum Adiabatic Brachistochrone”, Phys. Rev. Lett. **103**, 080502 (2009), by A.T. Rezakhani, W.J. Kuo, A. Hamma, D.A. Lidar, and P. Zanardi. [link]

“Quantum Adiabatic Machine Learning”, Quantum Info. Process. **12**, 2027 (2013), by K. Pudenz and D.A. Lidar. [link]

“Quantum Malware”, Quant. Info. Processing **5**, 69 (2006), by L.A. Wu and D.A. Lidar [link]

“Reply to: “Comment on `Polynomial-Time Simulation of Pairing Models on a Quantum Computer’””, Phys. Rev. Lett. **90**, 249804 (2003), by L.-A. Wu, M.S. Byrd, and D.A. Lidar [pdf]

“Simple Proof of Equivalence Between Adiabatic Quantum Computation and the Circuit Model”, Phys. Rev. Lett. **99**, 070502 (2007), by A. Mizel, D.A. Lidar, and M. Mitchell [link]