A new quantum circuit method computes spectral functions A(k,ω) by simulating ARPES-like system-environment coupling, cutting sampling overhead by O(N) and demonstrated on a 54-qubit ion-trap processor for a 27-site chain.
The quantum adiabatic algorithm suppresses the prolif- eration of errors
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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.
Trotterized near-thermal dynamics are substantially more robust to gate and Trotter errors than assumed, enabled by linear gate-error scaling with entanglement and a random product state ensemble approximating thermal states.
citing papers explorer
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Spectral functions on a quantum computer through system-environment interaction
A new quantum circuit method computes spectral functions A(k,ω) by simulating ARPES-like system-environment coupling, cutting sampling overhead by O(N) and demonstrated on a 54-qubit ion-trap processor for a 27-site chain.
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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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Robustness of near-thermal dynamics on digital quantum computers
Trotterized near-thermal dynamics are substantially more robust to gate and Trotter errors than assumed, enabled by linear gate-error scaling with entanglement and a random product state ensemble approximating thermal states.