canonical setting

Log-smooth + PI or LSI

V\nabla V is β\beta-Lipschitz; CPIC_{\rm PI} or CLSI1/αC_{\rm LSI}\le1/\alpha; κ=β/α\kappa=\beta/\alpha.

Upper and lower bounds

Comparison table

5 scoped results. Tildes suppress logarithmic factors.

Edit table
Best-known and comparison results for Log-smooth + PI or LSI
ResultAlgorithm or modelComplexityGuaranteeOracle / startAssumptions and notesReviewSources
best upperImplemented proximal samplerO~(κdpolylog(KL0/ε2))\widetilde O(\kappa\sqrt d\,\operatorname{polylog}(\sqrt{\operatorname{KL}_0}/\varepsilon^2))μNπTVε\lVert\mu_N-\pi\rVert_{\rm TV}\le\varepsilon under LSIV,VV,\nabla V plus proximal subroutineFinite initial KL; implementation warm startLog-Sobolev inequality.Checked high-accuracy headline for the LSI normalization.Checkedmonograph
lower unknownMatching PI/LSI oracle lower boundUnknownSame functional-inequality classV,VV,\nabla VMust be normalizedNo matching result located in the reference corpus.Open literature-check item.Unverifiedno primary source
upperLMCO~(κ2d/ε2)\widetilde O(\kappa^2d/\varepsilon^2)KLε\sqrt{\operatorname{KL}}\le\varepsilon under LSIV\nabla VFinite initial KLLog-Sobolev inequality.Classical direct-discretization baseline.Checkedmonograph
upperLMC Rényi interpolationO~(κ2dqε2logR2(μ0π))\widetilde O(\kappa^2dq\,\varepsilon^{-2}\log\mathcal R_2(\mu_0\Vert\pi))Rqε\sqrt{\mathcal R_q}\le\varepsilon under LSIV\nabla VFinite initial Rényi divergenceq2q\ge2 and theorem step-size condition.Rényi order appears explicitly in the cost.Checkedmonograph
upperULMC warm-start constructionO~(κ3/2d/ε)\widetilde O(\kappa^{3/2}\sqrt d/\varepsilon)μNπTVε\lVert\mu_N-\pi\rVert_{\rm TV}\le\varepsilon under LSIV\nabla VR2(μ0π)=O~(d)\mathcal R_2(\mu_0\Vert\pi)=\widetilde O(d)ULMC parameter choices from the corollary.Useful warm-start row; worse accuracy dependence than Metropolized methods.Checkedmonograph

Scope

Convexity is not required. The functional inequality supplies the mixing scale. PI and LSI are not interchangeable, so the guarantee column states which divergence is controlled.

Lower bounds

No matching general oracle lower bound for the PI/LSI-only class is recorded in the current monograph. Strongly-convex lower bounds are not automatically copied into this larger normalization.