Ignorance based inference of optimality in thermodynamic processes

TL;DR

This paper introduces an ignorance-based prior to quantify incomplete information and applies it to estimate the optimal work output of a heat engine, providing a novel approach to thermodynamic inference.

Contribution

It presents a new ignorance-based prior distribution and demonstrates its application in estimating thermodynamic optimality, advancing inference methods in thermodynamics.

Findings

Derived an ignorance-based prior distribution.

Applied it to estimate heat engine work.

Provided a new inference framework for thermodynamics.

Abstract

We derive ignorance based prior distribution to quantify incomplete information and show its use to estimate the optimal work characteristics of a heat engine.