Generalized Grover Search Algorithm for Arbitrary Initial Amplitude Distribution. - David Biron; Ofer Biham; Eli Biham; Markus Grassl; Daniel A. Lidar (QCQC, 1998)

Bang-Bang Operations from a Geometric Perspective. - Mark S. Byrd; Daniel A. Lidar (Quantum Inf. Process., 2002)

Quantum Codes for Simplifying Design and Suppressing Decoherence in Superconducting Phase-Qubits. - Daniel A. Lidar; Lian-Ao Wu; Alexandre Blais (Quantum Inf. Process., 2002)

Dreams Versus Reality: Plenary Debate Session on Quantum Computing. - Derek Abbott; Charles R. Doering; Carlton M. Caves; Daniel M. Lidar; Howard E. Brandt; Alex R. Hamilton; David K. Ferry; Julio Gea-Banacloche; Sergey M. Bezrukov; Laszlo B. Kish (Quantum Inf. Process., 2003)

Consistency of the Adiabatic Theorem. - Marcelo S. Sarandy; Lian-Ao Wu; Daniel A. Lidar (Quantum Inf. Process., 2004)

Editorial: quantum information and quantum control. - Paul Brumer; Daniel A. Lidar; Hoi-Kwong Lo; Aephraim Steinberg (Quantum Inf. Comput., 2005)

Stabilizing qubit coherence via tracking-control. - Daniel A. Lidar; Sara Schneider (Quantum Inf. Comput., 2005)

Quantum Malware. - Lian-Ao Wu; Daniel A. Lidar (Quantum Inf. Process., 2006)

Quantum error correction via convex optimization. - Robert L. Kosut; Daniel A. Lidar (Quantum Inf. Process., 2009)

Channel-optimized quantum error correction. - Soraya Taghavi; Robert L. Kosut; Daniel A. Lidar (IEEE Trans. Inf. Theory, 2010)

Quantum adiabatic machine learning. - Kristen L. Pudenz; Daniel A. Lidar (Quantum Inf. Process., 2013)

Beyond complete positivity. - Jason M. Dominy; Daniel A. Lidar (Quantum Inf. Process., 2016)

A general framework for complete positivity. - Jason M. Dominy; Alireza Shabani; Daniel A. Lidar (Quantum Inf. Process., 2016)

Performance of two different quantum annealing correction codes. - Anurag Mishra; Tameem Albash; Daniel A. Lidar (Quantum Inf. Process., 2016)

Solving a Higgs optimization problem with quantum annealing for machine learning. - Alex Mott; Joshua A. Job; Jean-Roch Vlimant; Daniel A. Lidar; Maria Spiropulu (Nat., 2017)

Evolution prediction from tomography. - Jason M. Dominy; Lorenzo Campos Venuti; Alireza Shabani; Daniel A. Lidar (Quantum Inf. Process., 2017)

Exploring More-Coherent Quantum Annealing. - Sergey Novikov; Robert Hinkey; Steven Disseler; James I. Basham; Tameem Albash; Andrew Risinger; David Ferguson; Daniel A. Lidar; Kenneth M. Zick (ICRC, 2018)

Charged particle tracking with quantum annealing-inspired optimization. - Alexander Zlokapa; Abhishek Anand; Jean-Roch Vlimant; Javier M. Duarte; Joshua A. Job; Daniel A. Lidar; Maria Spiropulu (CoRR, 2019)

Quantum adiabatic machine learning with zooming. - Alexander Zlokapa; Alex Mott; Joshua A. Job; Jean-Roch Vlimant; Daniel A. Lidar; Maria Spiropulu (CoRR, 2019)

Completely positive master equation for arbitrary driving and small level spacing. - Evgeny Mozgunov; Daniel A. Lidar (Quantum, 2020)

Quantum processor-inspired machine learning in the biomedical sciences. - Richard Y. Li; Sharvari Gujja; Sweta R. Bajaj; Omar E. Gamel; Nicholas Cilfone; Jeffrey R. Gulcher; Daniel A. Lidar; Thomas W. Chittenden (Patterns, 2021)

Charged particle tracking with quantum annealing optimization. - Alexander Zlokapa; Abhishek Anand; Jean-Roch Vlimant; Javier M. Duarte; Joshua A. Job; Daniel A. Lidar; Maria Spiropulu (Quantum Mach. Intell., 2021)

ClassiFIM: An Unsupervised Method To Detect Phase Transitions. - Victor Kasatkin; Evgeny Mozgunov; Nicholas Ezzell; Utkarsh Mishra; Itay Hen; Daniel A. Lidar (CoRR, 2024)

Beyond unital noise in variational quantum algorithms: noise-induced barren plateaus and limit sets. - Phattharaporn Singkanipa; Daniel A. Lidar (Quantum, 2025)