Quantum Speedups for Log-Concave Sampling from Local Structure

arXiv:2609.20253 · quant-ph, cs.DS · Submitted 2026-08-14 · Read on arXiv

quant-ph, cs.DS

Submitted: 2026-08-14

Updated: 2026-08-14

Terminology

• Query Complexity — 9× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Sparsity — 4× in this paper · explained in 4 episodes
• Spectral Gap — 4× in this paper · explained in 5 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Langevin Dynamics — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• 2-Wasserstein Distance — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptive Algorithm — 1× in this paper · explained in 1 episode
• Algorithmic Primitives — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Regret — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Wasserstein Distance — 1× in this paper · explained in 4 episodes

Sources

• Entropy contraction of the Gibbs sampler under log-concavity
• When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
• Quantum Speedups for Sampling and Non-convex Optimization with Stochastic Oracles

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