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In this work, we initiate the study of learning quantum processes from quantum statistical queries.
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“Efficient noise-tolerant learning from statistical queries”
Michael Kearns · 1998
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Srinivasan Arunachalam, Alex B. Grilo, and Henry Yuen · 2002
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“Physical one-way functions”
Ravikanth Pappu, Ben Recht, Jason Taylor, and Neil Gershenfeld · 2002
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Blaise Gassend, Dwaine Clarke, Marten Van Dijk, and Srinivas Devadas · 2002
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Alp Atici and Rocco A Servedio · 2005
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“Fpga intrinsic pufs and their use for ip protection”
Jorge Guajardo, Sandeep S Kumar, Geert-Jan Schrijen, and Pim Tuyls · 2007
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“Physical unclonable functions for device authentication and secret key generation”
G Edward Suh and Srinivas Devadas · 2007
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“Quantum-process tomography: Resource analysis of different strategies”
Masoud Mohseni, Ali T Rezakhani, and Daniel A Lidar · 2008
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“Optimizing quantum process tomography with unitary 2-designs”
Andrew James Scott · 2008
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“Quantum boolean functions” (2008)
Ashley Montanaro and Tobias J Osborne · 2008
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Richard A Low · 2009
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“Quantum computation and quantum information”
Michael A Nielsen and Isaac L Chuang · 2010
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Bernhard Baumgartner · 2011
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“Quantum-secure message authentication codes”
Dan Boneh and Mark Zhandry · 2013
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Elizabeth Meckes and Mark Meckes · 2013
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“Hamiltonian learning and certification using quantum resources”
Nathan Wiebe, Christopher Granade, Christopher Ferrie, and David G Cory · 2014
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“Pufs at a glance”
Ulrich Rührmair and Daniel E Holcomb · 2014
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“An introduction to quantum machine learning”
Maria Schuld, Ilya Sinayskiy, and Francesco Petruccione · 2015
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“The clifford group forms a unitary 3-design” (2015)
Zak Webb · 2015
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“Efficient quantum tomography”
Ryan O’Donnell and John Wright · 2016
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“Breaking symmetric cryptosystems using quantum period finding”
Marc Kaplan, Gaëtan Leurent, Anthony Leverrier, and María Naya-Plasencia · 2016
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“Strong machine learning attack against PUFs with no mathematical model”
Fatemeh Ganji, Shahin Tajik, Fabian Fäßler, and Jean-Pierre Seifert · 2016
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“Learning stabilizer states by bell sampling” (2017)
Ashley Montanaro · 2017
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“Guest column: A survey of quantum learning theory”
Srinivasan Arunachalam and Ronald de Wolf · 2017
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“Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography”
Robin Blume-Kohout, John King Gamble, Erik Nielsen, Kenneth Rudinger, Jonathan Mizrahi, Kevin Fortier, and Peter Maunz · 2017
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“Using simon’s algorithm to attack symmetric-key cryptographic primitives”
Thomas Santoli and Christian Schaffner · 2017
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“A general characterization of the statistical query complexity”
Vitaly Feldman · 2017
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“Multiqubit clifford groups are unitary 3-designs”
Huangjun Zhu · 2017
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“A retrospective and a look forward: Fifteen years of physical unclonable function advancement”
Chip-Hong Chang, Yue Zheng, and Le Zhang · 2017
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“Puf-based solutions for secure communications in advanced metering infrastructure (ami)”
“A unified framework for quantum unforgeability” (2021)
Mina Doosti, Mahshid Delavar, Elham Kashefi, and Myrto Arapinis · 2021
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“Efficient quantum measurement of pauli operators in the presence of finite sampling error”
Ophelia Crawford, Barnaby van Straaten, Daochen Wang, Thomas Parks, Earl Campbell, and Stephen Brierley · 2021
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“Quantum algorithms for sampling log-concave distributions and estimating normalizing constants”
Andrew M Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, and Ruizhe Zhang · 2022
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“Foundations for learning from noisy quantum experiments” (2022)
Hsin-Yuan Huang, Steven T Flammia, and John Preskill · 2022
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“On security notions for encryption in a quantum world”
Céline Chevalier, Ehsan Ebrahimi, and Quoc-Huy Vu · 2022
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Mahshid Delavar, Sattar Mirzakuchaki, Mohammad Hassan Ameri, and Javad Mohajeri · 2017
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“Optimal quantum sample complexity of learning algorithms”
Srinivasan Arunachalam and Ronald De Wolf · 2018
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“Neural network state estimation for full quantum state tomography” (2018)
Qian Xu and Shuqi Xu · 2018
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“Shadow tomography of quantum states”
Scott Aaronson · 2018
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“Unforgeable quantum encryption”
Gorjan Alagic, Tommaso Gagliardoni, and Christian Majenz · 2018
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“Learning-with-errors problem is easy with quantum samples”
Alex B. Grilo, Iordanis Kerenidis, and Timo Zijlstra · 2019
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“An adaptive variational algorithm for exact molecular simulations on a quantum computer”
Harper R Grimsley, Sophia E Economou, Edwin Barnes, and Nicholas J Mayhall · 2019
Cited alongside, same era.
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“Learning classical readout quantum PUFs based on single-qubit gates”
Niklas Pirnay, Anna Pappa, and Jean-Pierre Seifert · 2022
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“Exponential separations between learning with and without quantum memory”
Sitan Chen, Jordan Cotler, Hsin-Yuan Huang, and Jerry Li · 2022
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“The randomized measurement toolbox”
Andreas Elben, Steven T. Flammia, Hsin-Yuan Huang, Richard Kueng, John Preskill, Benoît Vermersch, and Peter Zoller · 2022
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“Provably efficient machine learning for quantum many-body problems”
Hsin-Yuan Huang, Richard Kueng, Giacomo Torlai, Victor V Albert, and John Preskill · 2022
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“On the hardness of pac-learning stabilizer states with noise”
Aravind Gollakota and Daniel Liang · 2022
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“Measurements of quantum hamiltonians with locally-biased classical shadows”
Charles Hadfield, Sergey Bravyi, Rudy Raymond, and Antonio Mezzacapo · 2022
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“Learning quantum circuits of some t gates”
Ching-Yi Lai and Hao-Chung Cheng · 2022
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“One t gate makes distribution learning hard”
M Hinsche, M Ioannou, A Nietner, J Haferkamp, Y Quek, D Hangleiter, J-P Seifert, J Eisert, and R Sweke · 2023
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Alexander Nietner · 2023
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“Query-optimal estimation of unitary channels in diamond distance”
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“Learning to predict arbitrary quantum processes”
Hsin-Yuan Huang, Sitan Chen, and John Preskill · 2023
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“Learning unitaries with quantum statistical queries” (2023)
Armando Angrisani · 2023
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“Shadow process tomography of quantum channels”
Jonathan Kunjummen, Minh C Tran, Daniel Carney, and Jacob M Taylor · 2023
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“Overlapped grouping measurement: A unified framework for measuring quantum states”
Bujiao Wu, Jinzhao Sun, Qi Huang, and Xiao Yuan · 2023
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“On the role of entanglement and statistics in learning”
Srinivasan Arunachalam, Vojtech Havlicek, and Louis Schatzki · 2024
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“Classical shadows for quantum process tomography on near-term quantum computers”
Ryan Levy, Di Luo, and Bryan K Clark · 2024
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Yihui Quek, Daniel Stilck França, Sumeet Khatri, Johannes Jakob Meyer, and Jens Eisert · 2024
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“Learning quantum processes without input control”
Marco Fanizza, Yihui Quek, and Matteo Rosati · 2024
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“Classical verification of quantum learning”
Matthias C Caro, Marcel Hinsche, Marios Ioannou, Alexander Nietner, and Ryan Sweke · 2024
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“Learning quantum processes and hamiltonians via the pauli transfer matrix”
Matthias C Caro · 2024
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“Introduction to haar measure tools in quantum information: A beginner’s tutorial”
Antonio Anna Mele · 2024
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