A new rigorous Gibbs sampling method is given for bosonic models by proving that their dissipative generators have positive spectral gaps, enabling efficient quantum preparation of thermal states for Bose-Hubbard Hamiltonians.
(Sub)exponential quantum speedup for opti- mization
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Multivariate DQI uses N-variable polynomials for weighted Max-LINSAT, derives closed-form asymptotics for expectation and concentration, provides a single-decoder preparation circuit, and shows outperformance over weighted Prange for some OPI cases while extending to Hamiltonian DQI.
The paper identifies four key hurdles in the transition from NISQ to FASQ quantum computers and argues that targeting them will accelerate progress toward useful quantum advantage.
citing papers explorer
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Simulating Thermal Properties of Bose-Hubbard Models on a Quantum Computer
A new rigorous Gibbs sampling method is given for bosonic models by proving that their dissipative generators have positive spectral gaps, enabling efficient quantum preparation of thermal states for Bose-Hubbard Hamiltonians.
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Multivariate Decoded Quantum Interferometry for Weighted Optimization
Multivariate DQI uses N-variable polynomials for weighted Max-LINSAT, derives closed-form asymptotics for expectation and concentration, provides a single-decoder preparation circuit, and shows outperformance over weighted Prange for some OPI cases while extending to Hamiltonian DQI.
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Mind the gaps: The fraught road to quantum advantage
The paper identifies four key hurdles in the transition from NISQ to FASQ quantum computers and argues that targeting them will accelerate progress toward useful quantum advantage.