Exact recording of Metropolis-Hastings-class Monte Carlo simulations using one bit per sample
Albert H. Mao, Rohit V. Pappu

TL;DR
This paper introduces a method to record Metropolis-Hastings Monte Carlo simulations exactly using only one bit per sample, enabling lossless data capture and improved analysis flexibility.
Contribution
It presents a novel one-bit recording scheme for MH simulations that preserves all information without restricting system or algorithm design.
Findings
Exact recording with one bit per sample demonstrated on charged particle system
Method preserves full sample information without data loss
Compatible with various MH algorithm variants
Abstract
The Metropolis-Hastings (MH) algorithm is the prototype for a class of Markov chain Monte Carlo methods that propose transitions between states and then accept or reject the proposal. These methods generate a correlated sequence of random samples that convey information about the desired probability distribution. Deciding how this information gets recorded is an important step in the practical design of MH-class algorithm implementations. Many implementations discard most of this information in order to reduce demands on storage capacity and disk writing throughput. Here, we describe how recording a bit string containing 1's for acceptance and 0's for rejection allows the full sample sequence to be recorded with no information loss, facilitating decoupling of simulation design from the constraints of data analysis. The recording uses only one bit per sample, which is an upper bound on…
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