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Taking Bigger Metropolis Steps by Dragging Fast Variables

6 Pith papers cite this work. Polarity classification is still indexing.

6 Pith papers citing it
abstract

I show how Markov chain sampling with the Metropolis-Hastings algorithm can be modified so as to take bigger steps when the distribution being sampled from has the characteristic that its density can be quickly recomputed for a new point if this point differs from a previous point only with respect to a subset of 'fast' variables. I show empirically that when using this method, the efficiency of sampling for the remaining 'slow' variables can approach what would be possible using Metropolis updates based on the marginal distribution for the slow variables.

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  • Resolving the Planck-DESI tension by nonminimally coupled quintessence astro-ph.CO · 2025-08-03 · unverdicted · none · ref 90 · internal anchor

    Non-minimally coupled quintessence resolves the Planck-DESI Ω_m tension at >3σ while the effective equation of state stays above w=-1 and other tensions on neutrino mass and growth rate are relieved.

  • Extended Dark Energy analysis using DESI DR2 BAO measurements astro-ph.CO · 2025-03-18 · conditional · none · ref 85 · internal anchor

    Extended analysis of DESI DR2 data confirms robust evidence for dynamical dark energy with phantom crossing preference, stable under parametric and non-parametric modeling.