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David Hocker
David Hocker
Postdoctoral Researcher, Center for Neural Science, NYU
Verified email at nyu.edu
Title
Cited by
Cited by
Year
Exploring the tradeoff between fidelity and time optimal control of quantum unitary transformations
KW Moore Tibbetts, C Brif, MD Grace, A Donovan, DL Hocker, TS Ho, ...
Physical Review A—Atomic, Molecular, and Optical Physics 86 (6), 062309, 2012
912012
Characterization of control noise effects in optimal quantum unitary dynamics
D Hocker, C Brif, MD Grace, A Donovan, TS Ho, KM Tibbetts, R Wu, ...
Physical Review A 90 (6), 062309, 2014
452014
Subpopulations of neurons in lOFC encode previous and current rewards at time of choice
DL Hocker, CD Brody, C Savin, CM Constantinople
Elife 10, e70129, 2021
322021
Shannon entropy based time-dependent deterministic sampling for efficient “on-the-fly” quantum dynamics and electronic structure
D Hocker, X Li, SS Iyengar
Journal of chemical theory and computation 7 (2), 256-268, 2011
222011
Optimal nonlinear coherent mode transitions in Bose-Einstein condensates utilizing spatiotemporal controls
D Hocker, J Yan, H Rabitz
Physical Review A 93 (5), 053612, 2016
152016
Transformation of acoustic information to sensory decision variables in the parietal cortex
JD Yao, KO Zemlianova, DL Hocker, C Savin, CM Constantinople, ...
Proceedings of the National Academy of Sciences 120 (2), e2212120120, 2023
112023
Myopic control of neural dynamics
D Hocker, IM Park
PLoS computational biology 15 (3), e1006854, 2019
102019
Multistep inference for generalized linear spiking models curbs runaway excitation
D Hocker, IM Park
2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 613-616, 2017
92017
Survey of control performance in quantum information processing
D Hocker, Y Zheng, R Kosut, T Brun, H Rabitz
Quantum Information Processing 15, 4361-4390, 2016
82016
Shannon Information Entropy Based Time-Dependent Deterministic Sampling Techniques for Efficient “on-The-Fly” Quantum Dynamics and Electronic Structure
D Hocker, X Li, SS Iyengar
J. Chem. Theory Comput 7, 256, 2011
72011
Exploring the control landscape for nonlinear quantum dynamics
J Yan, D Hocker, R Long, TS Ho, H Rabitz
Physical Review A 89 (6), 063408, 2014
52014
Evaluation of Quantum Control Protocols for Physical Machine Descriptions
D Hocker, H Rabitz, YC Zheng, T Brun, A Shafaei, M Pedram
IARPA QCS Project report, 2012
52012
PEET: a Matlab tool for estimating physical gate errors in quantum information processing systems
D Hocker, R Kosut, H Rabitz
Quantum Information Processing 15, 3489-3518, 2016
32016
Protecting quantum gates from control noise.
C Brif, MD Grace, KC Young, DL Hocker, KW Moore, TS Ho, H Rabitz
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2011
32011
Multistep inference for generalized linear spiking models curbs runaway excitation. In 2017 8th International IEEE
D Hocker, IM Park
EMBS Conference on Neural Engineering (NER), 613-616, 0
2
Curriculum learning inspired by behavioral shaping trains neural networks to adopt animal-like decision making strategies
D Hocker, CM Constantinople, C Savin
bioRxiv, 2024.01. 12.575461, 2024
12024
Lessons from the quantum control landscape: Robust optimal control of quantum systems and optimal control of nonlinear Schrödinger equations
DL Hocker
Princeton University, 2016
12016
Invariance in multi-objective quantum control
D Hocker, H Rabitz
arXiv preprint arXiv:1507.05918, 2015
2015
Improving robustness of quantum gates to control noise.
C Brif, M Grace, K Young, DL Hocker, KW Moore, TS Ho, H Rabitz
Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA …, 2012
2012
Robustness of quantum information processing to the control noise.
C Brif, MD Grace, KW Moore, DL Hocker, TS Ho, H Rabitz
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2011
2011
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