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We study the problem of learning the Hamiltonian of a many-body quantum system from experimental data.
Quantum approximate bayesian computation for nmr model inference
Dries Sels, Hesam Dashti, Samia Mora, Olga Demler, and Eugene Demler · 1910
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A molecular beam resonance method with separated oscillating fields
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Exponential operators and parameter differentiation in quantum physics
Ralph M Wilcox · 1967
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Computationally efficient bounds for the catalan numbers
Ronald D Dutton and Robert C Brigham · 1986
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Statistical distance and the geometry of quantum states
Samuel L. Braunstein and Carlton M. Caves · 1994
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Mark Srednicki · 1994
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Alexander Altland and Ben D Simons · 2010
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Characterization of a qubit Hamiltonian using adaptive measurements in a fixed basis
Alexandr Sergeevich, Anushya Chandran, Joshua Combes, Stephen D Bartlett, and Howard M Wiseman · 2011
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Practical characterization of quantum devices without tomography
Marcus P da Silva, Olivier Landon-Cardinal, and David Poulin · 2011
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Estimation of many-body quantum hamiltonians via compressive sensing
Alireza Shabani, Masoud Mohseni, Seth Lloyd, Robert L Kosut, and Herschel Rabitz · 2011
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Indirect quantum tomography of quadratic hamiltonians
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Christopher Ferrie, Christopher E Granade, and David G Cory · 2013
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Shengshi Pang and Todd A. Brun · 2014
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Nathan Wiebe, Christopher Granade, Christopher Ferrie, and David G Cory · 2014
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Quantum Hamiltonian identification from measurement time traces
Jun Zhang and Mohan Sarovar · 2014
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Markku PV Stenberg, Yuval R Sanders, and Frank K Wilhelm · 2014
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Locality of temperature
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Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation
Haidong Yuan and Chi-Hang Fred Fung · 2015
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Quantum bootstrapping via compressed quantum Hamiltonian learning
Nathan Wiebe, Christopher Granade, and David G Cory · 2015
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Hamiltonian tomography for quantum many-body systems with arbitrary couplings
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Scalable reconstruction of unitary processes and hamiltonians
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Solving strongly correlated electron models on a quantum computer
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From quantum chaos and eigenstate thermalization to statistical mechanics and thermodynamics
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Spectral decoupling in many-body quantum chaos
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Active learning of quantum system hamiltonians yields query advantage
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Precise Hamiltonian identification of a superconducting quantum processor
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Quantum variational learning of the entanglement Hamiltonian
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Optimal short-time measurements for Hamiltonian learning
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A quantum Hamiltonian identification algorithm: Computational complexity and error analysis
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Remote parameter estimation in a quantum spin chain enhanced by local control
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Optimal adaptive control for quantum metrology with time-dependent hamiltonians
Shengshi Pang and Andrew N Jordan · 2017
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Sample-efficient learning of interacting quantum systems
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Bounds on adaptive quantum metrology under markovian noise
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Heisenberg-limited quantum phase estimation of multiple eigenvalues with few control qubits
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Heisenberg-limited ground-state energy estimation for early fault-tolerant quantum computers
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Exponential decay of mutual information for gibbs states of local hamiltonians
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Efficient and robust estimation of many-qubit hamiltonians
Daniel Stilck Franca, Liubov A Markovich, VV Dobrovitski, Albert H Werner, and Johannes Borregaard · 2022
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Bound on eigenstate thermalization from transport
Anatoly Dymarsky · 2022
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Eigenstate thermalization hypothesis and its deviations from random-matrix theory beyond the thermalization time
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Matrix models for eigenstate thermalization
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Fluctuations of subsystem entropies at late times
Jordan Cotler, Nicholas Hunter-Jones, and Daniel Ranard · 2022
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Non-abelian eigenstate thermalization hypothesis
Chaitanya Murthy, Arman Babakhani, Fernando Iniguez, Mark Srednicki, and Nicole Yunger Halpern · 2022
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High-accuracy Hamiltonian learning via delocalized quantum state evolutions
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Query-optimal estimation of unitary channels in diamond distance
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Stochastic estimation of dynamical variables
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