English

An intuition for physicists: information gain from experiments

Statistical Mechanics 2022-08-29 v3 Instrumentation and Methods for Astrophysics Data Analysis, Statistics and Probability

Abstract

How much one has learned from an experiment is quantifiable by the information gain, also known as the Kullback-Leibler divergence. The narrowing of the posterior parameter distribution P(θD)P(\theta|D) compared with the prior parameter distribution π(θ)\pi(\theta), is quantified in units of bits, as: DKL(Pπ)=log2(P(θD)π(θ))P(θD)dθ D_{\mathrm{KL}}(P|\pi)=\int\log_{2}\left(\frac{P(\theta|D)}{\pi(\theta)}\right)\,P(\theta|D)\,d\theta . This research note gives an intuition what one bit of information gain means. It corresponds to a Gaussian shrinking its standard deviation by a factor of three.

Keywords

Cite

@article{arxiv.2205.00009,
  title  = {An intuition for physicists: information gain from experiments},
  author = {Johannes Buchner},
  journal= {arXiv preprint arXiv:2205.00009},
  year   = {2022}
}

Comments

Accepted to RNAAS; Corrected typos (Thanks to Tariq Yasin and Torsten En{\ss}lin)

R2 v1 2026-06-24T11:02:59.293Z