Machine Learning and Closed-Loop Quantum Control
FOCUS · MAR-J36 · ID: 3108563
Presentations
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Machine Learning aiding the Discovery of better Strategies for Quantum Computing
ORAL · Invited
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Publication: Puviani et al, arXiv 2312.07391 (accepted for publication in Physical Review Letters)<br>Porotti et al, PRX Quantum 4(3) 030305 (2023)<br>Zen et al, arXiv 2402.17761 (under review in Physical Review X)<br>Olle et al, npj Quantum Information vol. 10, 126 (2024)<br>Reuer et al, Nature Communications 14, 7138 (2023)
Presenters
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Florian Marquardt
Friedrich-Alexander University Erlangen-Nuremberg
Authors
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Florian Marquardt
Friedrich-Alexander University Erlangen-Nuremberg
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Most likely path approach to optimal control theory
ORAL
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Presenters
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Andrew N Jordan
Chapman University
Authors
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Andrew N Jordan
Chapman University
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Automated calibration of optimal control pulses on a superconducting quantum RAM (QRAM) device
ORAL
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Presenters
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Aaron Trowbridge
Carnegie Mellon University
Authors
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Aaron Trowbridge
Carnegie Mellon University
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Sebastien Leger
Stanford University
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Connie Miao
Stanford University
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Andy J Goldschmidt
University of Chicago
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Aditya Bhardwaj
University of Chicago
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David I Schuster
Stanford University
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Abstract Withdrawn
ORAL Withdrawn
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Abstract Withdrawn
ORAL Withdrawn
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AI-Enabled Molecular State Control using Quantum-Logic Spectroscopy
ORAL
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Publication: A. Pipi, X. Tao, P. Narang, and D.R. Leibrandt (2024). Molecular Quantum Control Algorithm Design by Reinforcement Learning. arXiv preprint arXiv:2410.11839.
Presenters
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Anastasia Pipi
University of California, Los Angeles
Authors
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Anastasia Pipi
University of California, Los Angeles
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Xuecheng Tao
University of California, Los Angeles
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David Leibrandt
University of California, Los Angeles
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Prineha Narang
University of California, Los Angeles
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Reinforcement Learning Meets Quantum Control - Artificially Intelligent Maxwell's Demon
ORAL
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Publication: arXiv:2408.15328v1 [quant-ph]
Presenters
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Robert Czupryniak
University of Rochester
Authors
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Robert Czupryniak
University of Rochester
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Paolo A Erdman
Freie Universität Berlin
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Bibek Bhandari
Chapman University
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Andrew N Jordan
Chapman University
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Jens Eisert
Freie Universität Berlin, FU Berlin
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Frank Noe
Microsoft Corporation
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GIACOMO GUARNIERI
Freie University Berlin, University of Pavia
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Quantum feedback control with a transformer neural network architecture
ORAL
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Presenters
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Pranav Vaidhyanathan
University of Oxford
Authors
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Pranav Vaidhyanathan
University of Oxford
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Mark T Mitchison
Trinity College Dublin
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Natalia Ares
University of Oxford
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Characterization of Model-Based Reinforcement Learning for Dynamical Decoupling
ORAL
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Presenters
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George Witt
University of Maryland College Park
Authors
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George Witt
University of Maryland College Park
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Jner Tzern Oon
University of Maryland College Park
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Connor A Hart
University of Maryland College Park
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Ronald L Walsworth
University of Maryland College Park
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Quantum optimal control using physics-informed neural networks with sinusoidal representations.
ORAL
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Presenters
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Sofiia Lauten
University of Wisconsin - Madison
Authors
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Sofiia Lauten
University of Wisconsin - Madison
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Matthew Otten
University of Wisconsin - Madison
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Gradient-based Quantum Control and Engineering with Adjoint Sensitivity
ORAL
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Presenters
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Kien Le
Stanford University
Authors
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Kien Le
Stanford University
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Jean-Michel Borit
Stanford University
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Rahul Trivedi
Max-Planck Institute for Quantum Optics
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Joonhee Choi
Stanford University
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Jelena Vuckovic
Stanford University
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Gradient evaluation of analytic control for quantum systems with large Hilbert space
ORAL
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Presenters
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Ashutosh Mishra
Forschungszentrum Jülich
Authors
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Ashutosh Mishra
Forschungszentrum Jülich
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Frank K Wilhelm
Forschungszentrum Juelich GmbH, Forschungszentrum Jülich
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Alessandro Ciani
Forschungszentrum Juelich GmbH
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