The unitary contribution from weak system-bath coupling in collision-model thermal state preparation tightens the fixed-point error bound, scaling rigorously as J² where J is the coupling strength.
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8 Pith papers cite this work, alongside 14 external citations. Polarity classification is still indexing.
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Quantum Gibbs samplers thermalize to Gibbs states in polynomial time at high temperatures for Lieb-Robinson bounded Hamiltonians and are BQP-complete at low temperatures via circuit-to-Hamiltonian reductions.
k-local quantum Hamiltonians admit system-size-independent spectral gap for Gibbs samplers at high temperature, enabling FPT quantum approximation algorithms for partition functions.
Proves KMS detailed balance on the transition part of an approximate Lindbladian suffices for the fixed point to approach the Gibbs state arbitrarily closely regardless of Lamb shift structure, giving O(ε^{-1}) thermalization complexity.
Adiabatic evolution prepares local thermal states from initial Gibbs states while conserving entropy density in the thermodynamic limit, with mirror-circuit benchmarking of hardware noise entropy demonstrated experimentally on a 5x4 Ising model.
Introduces local-circuit approximations to quasilocal dissipative processes for efficient, provably convergent quantum Gibbs sampling at high temperatures.
A quantum MCMC algorithm leveraging the MBL phase and its thermal-to-localized transition to tune acceptance rates and sample thermal distributions on programmable quantum simulators for combinatorial optimization.
Dissipative protocols on quantum hardware prepare approximate thermal states for kagome AFIM up to 79 sites and AFHM via simulation, with circuit depth independent of size and linear in inverse temperature.
citing papers explorer
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Rigorous error bounds for dissipative thermal state preparation from weak system-bath coupling
The unitary contribution from weak system-bath coupling in collision-model thermal state preparation tightens the fixed-point error bound, scaling rigorously as J² where J is the coupling strength.
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Efficient thermalization and universal quantum computing with quantum Gibbs samplers
Quantum Gibbs samplers thermalize to Gibbs states in polynomial time at high temperatures for Lieb-Robinson bounded Hamiltonians and are BQP-complete at low temperatures via circuit-to-Hamiltonian reductions.
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Fast mixing of all-to-all quantum systems at high temperatures
k-local quantum Hamiltonians admit system-size-independent spectral gap for Gibbs samplers at high temperature, enabling FPT quantum approximation algorithms for partition functions.
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Overcoming the Lamb Shift in System-Bath Interaction Models via KMS Detailed Balance: High-Accuracy Thermalization with Time-Bounded Interactions
Proves KMS detailed balance on the transition part of an approximate Lindbladian suffices for the fixed point to approach the Gibbs state arbitrarily closely regardless of Lamb shift structure, giving O(ε^{-1}) thermalization complexity.
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Adiabatic preparation of thermal states and entropy-noise relation on noisy quantum computers
Adiabatic evolution prepares local thermal states from initial Gibbs states while conserving entropy density in the thermodynamic limit, with mirror-circuit benchmarking of hardware noise entropy demonstrated experimentally on a 5x4 Ising model.
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Efficient Quantum Gibbs Sampling with Local Circuits
Introduces local-circuit approximations to quasilocal dissipative processes for efficient, provably convergent quantum Gibbs sampling at high temperatures.
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Quantum Markov chain Monte Carlo method with programmable quantum simulators
A quantum MCMC algorithm leveraging the MBL phase and its thermal-to-localized transition to tune acceptance rates and sample thermal distributions on programmable quantum simulators for combinatorial optimization.
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Preparing thermal states of frustrated quantum spin systems using 139 qubits
Dissipative protocols on quantum hardware prepare approximate thermal states for kagome AFIM up to 79 sites and AFHM via simulation, with circuit depth independent of size and linear in inverse temperature.