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Despite fundamental interests in learning quantum circuits, the existence of a computationally efficient algorithm for learning shallow quantum circuits remains an open question.
“Proof of the strong subadditivity of quantum-mechanical entropy”
Elliott. Lieb and Mary Ruskai · 1941
Earlier work this paper cites.
“Constant depth circuits, Fourier transform, and learnability”
Nathan Linial, Yishay Mansour and Noam Nisan · 1993
Earlier work this paper cites.
“Elementary gates for quantum computation”
Adriano Barenco et al · 1995
Earlier work this paper cites.
“Strengths and weaknesses of quantum computing”
Charles Bennett, Ethan Bernstein, Gilles Brassard and Umesh Vazirani · 1997
Earlier work this paper cites.
“Grover’s quantum searching algorithm is optimal”
Christof Zalka · 1999
Earlier work this paper cites.
“Classical simulation of noninteracting-fermion quantum circuits”
Barbara Terhal and David DiVincenzo · 2002
Earlier work this paper cites.
“A simple formula for the average gate fidelity of a quantum dynamical operation”
Michael Nielsen · 2002
Earlier work this paper cites.
“Learning Juntas”
Elchanan Mossel, Ryan O’Donnell and Rocco. Servedio · 2003
Earlier work this paper cites.
“Adaptive Quantum Computation, Constant Depth Quantum Circuits and Arthur-Merlin Games”, 2004
Barbara. Terhal and David. DiVincenzo · 2004
Earlier work this paper cites.
“Improved simulation of stabilizer circuits”
Scott Aaronson and Daniel Gottesman · 2004
Earlier work this paper cites.
“Reversible quantum cellular automata”, 2004
B. Schumacher and R.. Werner · 2004
Earlier work this paper cites.
“Synthesis of quantum logic circuits”
Vivek Shende, Stephen Bullock and Igor Markov · 2005
Earlier work this paper cites.
“Perfect distinguishability of quantum operations”
Runyao Duan, Yuan Feng and Mingsheng Ying · 2009
Earlier work this paper cites.
“Efficient quantum state tomography”
Marcus Cramer et al · 2010
Earlier work this paper cites.
“Quantum state tomography via compressed sensing”
David Gross et al · 2010
Earlier work this paper cites.
“Robust online Hamiltonian learning”
Christopher Granade, Christopher Ferrie, Nathan Wiebe and David Cory · 2012
Earlier work this paper cites.
“Index Theory of One Dimensional Quantum Walks and Cellular Automata”
D. Gross, V. Nesme, H. Vogts and R.. Werner · 2012
Earlier work this paper cites.
“A survey of quantum property testing”
Ashley Montanaro and Ronald de Wolf · 2013
Earlier work this paper cites.
“Learning Algorithms from Natural Proofs”
Marco. Carmosino, Russell Impagliazzo, Valentine Kabanets and Antonina Kolokolova · 2016
Earlier work this paper cites.
“Quantum Supremacy for Simulating a Translation-Invariant Ising Spin Model”
Xun Gao, Sheng-Tao Wang and L.-M. Duan · 2017
Earlier work this paper cites.
“Efficient tomography of a quantum many-body system”
BP Lanyon et al · 2017
Earlier work this paper cites.
“Learning stabilizer states by Bell sampling”
Ashley Montanaro · 2017
Earlier work this paper cites.
“Geometry of quantum states: an introduction to quantum entanglement”
Ingemar Bengtsson and Karol Życzkowski · 2017
Earlier work this paper cites.
“Quantum advantage with shallow circuits”
Sergey Bravyi, David Gosset and Robert Koenig · 2018
Earlier work this paper cites.
“Architectures for quantum simulation showing a quantum speedup”
Juan Bermejo-Vega et al · 2018
Earlier work this paper cites.
“Classification with quantum neural networks on near term processors”
Edward Farhi and Hartmut Neven · 2018
Earlier work this paper cites.
“Barren plateaus in quantum neural network training landscapes”
Jarrod McClean et al · 2018
Earlier work this paper cites.
“Learning the quantum algorithm for state overlap”
Lukasz Cincio, Yiğit Subaşı, Andrew Sornborger and Patrick Coles · 2018
Earlier work this paper cites.
“Quantum generative adversarial learning”
Seth Lloyd and Christian Weedbrook · 2018
Earlier work this paper cites.
“Architectures for Quantum Simulation Showing a Quantum Speedup”
Juan Bermejo-Vega et al · 2018
Earlier work this paper cites.
“Shadow tomography of quantum states”
Scott Aaronson · 2018
Earlier work this paper cites.
“The theory of quantum information”
John Watrous · 2018
Earlier work this paper cites.
“Exponential separation between shallow quantum circuits and unbounded fan-in shallow classical circuits”
Adam Watts, Robin Kothari, Luke Schaeffer and Avishay Tal · 2019
Earlier work this paper cites.
“Parameterized quantum circuits as machine learning models”
Marcello Benedetti, Erika Lloyd, Stefan Sack and Mattia Fiorentini · 2019
Earlier work this paper cites.
“Quantum-assisted quantum compiling”
Sumeet Khatri et al · 2019
Earlier work this paper cites.
“A generative modeling approach for benchmarking and training shallow quantum circuits”
Marcello Benedetti et al · 2019
Earlier work this paper cites.
“Learning a local Hamiltonian from local measurements”
Eyal Bairey, Itai Arad and Netanel Lindner · 2019
Earlier work this paper cites.
“Finite Correlation Length Implies Efficient Preparation of Quantum Thermal States”
Fernando… Brandão and Michael. Kastoryano · 2019
Cited alongside, same era.
“Quantum advantage with noisy shallow circuits”
Sergey Bravyi, David Gosset, Robert Koenig and Marco Tomamichel · 2020
Cited alongside, same era.
“Closing gaps of a quantum advantage with short-time hamiltonian dynamics”
Jonas Haferkamp et al · 2020
Cited alongside, same era.
“Training deep quantum neural networks”
Kerstin Beer et al · 2020
Cited alongside, same era.
“Recurrent quantum neural networks”
Johannes Bausch · 2020
Cited alongside, same era.
“Noise resilience of variational quantum compiling”
Kunal Sharma, Sumeet Khatri, Marco Cerezo and Patrick Coles · 2020
Cited alongside, same era.
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Tyson Jones and Simon Benjamin · 2022
Later among the works it cites.
“Dynamical simulation via quantum machine learning with provable generalization”
Joe Gibbs et al · 2022
Later among the works it cites.
“Enhancing generative models via quantum correlations”
Xun Gao et al · 2022
Later among the works it cites.
“Generation of high-resolution handwritten digits with an ion-trap quantum computer”
Manuel Rudolph et al · 2022
Later among the works it cites.
“Generative quantum learning of joint probability distribution functions”
Elton Zhu et al · 2022
Later among the works it cites.
“Optimal learning of quantum Hamiltonians from high-temperature Gibbs states”
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Cristina Cirstoiu et al · 2020
Cited alongside, same era.
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Brian Coyle, Daniel Mills, Vincent Danos and Elham Kashefi · 2020
Cited alongside, same era.
“Sample-efficient learning of quantum many-body systems”
Anurag Anshu, Srinivasan Arunachalam, Tomotaka Kuwahara and Mehdi Soleimanifar · 2020
Cited alongside, same era.
“Efficient estimation of Pauli channels”
Steven Flammia and Joel Wallman · 2020
Cited alongside, same era.
“Hamiltonian tomography via quantum quench”
Zhi Li, Liujun Zou and Timothy Hsieh · 2020
Cited alongside, same era.
“Improved quantum data analysis”
Costin Bădescu and Ryan O’Donnell · 2020
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Jeongwan Haah, Robin Kothari and Ewin Tang · 2022
Later among the works it cites.
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Later among the works it cites.
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Later among the works it cites.
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Later among the works it cites.
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Senrui Chen, Sisi Zhou, Alireza Seif and Liang Jiang · 2022
Later among the works it cites.
“Practical and Efficient Hamiltonian Learning”, 2022
Wenjun Yu, Jinzhao Sun, Zeyao Han and Xiao Yuan · 2022
Later among the works it cites.
“Efficient and robust estimation of many-qubit Hamiltonians”
Daniel Franca et al · 2022
Later among the works it cites.
“Practical Black Box Hamiltonian Learning”
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Later among the works it cites.
“Scalably learning quantum many-body Hamiltonians from dynamical data”
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Later among the works it cites.
“Learning to predict arbitrary quantum processes”
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Later among the works it cites.
“The randomized measurement toolbox”
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Later among the works it cites.
“Nontrivial Quantum Cellular Automata in Higher Dimensions”
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Later among the works it cites.
“Three-Dimensional Quantum Cellular Automata from Chiral Semion Surface Topological Order and beyond”
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Later among the works it cites.
“Projected least-squares quantum process tomography”
Trystan Surawy-Stepney, Jonas Kahn, Richard Kueng and Madalin Guta · 2022
Later among the works it cites.
“Unconditional Quantum Advantage for Sampling with Shallow Circuits”
Adam Watts and Natalie Parham · 2023
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“Computational advantage of quantum random sampling”
Dominik Hangleiter and Jens Eisert · 2023
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“Out-of-distribution generalization for learning quantum dynamics”
Matthias Caro et al · 2023
Later among the works it cites.
“The power and limitations of learning quantum dynamics incoherently”
Sofiene Jerbi et al · 2023
Later among the works it cites.
“Learning quantum systems”
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Later among the works it cites.
“Improved Stabilizer Estimation via Bell Difference Sampling”
Sabee Grewal, Vishnu Iyer, William Kretschmer and Daniel Liang · 2023
Later among the works it cites.
“Efficient Tomography of Non-Interacting-Fermion States”
Scott Aaronson and Sabee Grewal · 2023
Later among the works it cites.
“Probabilistic error cancellation with sparse Pauli–Lindblad models on noisy quantum processors”
Ewout Van, Zlatko Minev, Abhinav Kandala and Kristan Temme · 2023
Later among the works it cites.
“Learning many-body Hamiltonians with Heisenberg-limited scaling”
Hsin-Yuan Huang, Yu Tong, Di Fang and Yuan Su · 2023
Later among the works it cites.
“A survey on the complexity of learning quantum states”, 2023
Anurag Anshu and Srinivasan Arunachalam · 2023
Later among the works it cites.
“Classical simulation of short-time quantum dynamics”
Dominik Wild and Álvaro Alhambra · 2023
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“Polynomial-time classical sampling of high-temperature quantum Gibbs states”
Chao Yin and Andrew Lucas · 2023
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“Shadow process tomography of quantum channels”
Jonathan Kunjummen, Minh Tran, Daniel Carney and Jacob Taylor · 2023
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Nengkun Yu and Tzu-Chieh Wei · 2023
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Jeongwan Haah, Robin Kothari, Ryan O’Donnell and Ewin Tang · 2023
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“Testing and learning quantum juntas nearly optimally”
Thomas Chen, Shivam Nadimpalli and Henry Yuen · 2023
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“Out-of-distribution generalization for learning quantum dynamics”
Matthias Caro et al · 2023
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