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)
Porotti et al, PRX Quantum 4(3) 030305 (2023)
Zen et al, arXiv 2402.17761 (under review in Physical Review X)
Olle et al, npj Quantum Information vol. 10, 126 (2024)
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Abstract Withdrawn
ORAL · Withdrawn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Abstract Withdrawn
ORAL · Withdrawn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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