Ignorance based inference of optimality in thermodynamic processes

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.

Latex, 10 pages, 3 figures

References in corpus (5)

• Bayes in the sky: Bayesian inference and model selection in cosmology
• Efficiency at maximum power: An analytically solvable model for stochastic heat engines
• Efficiency at maximum power of low dissipation Carnot engines
• Expected Behavior of Quantum Thermodynamic Machines with Prior Information
• Informative priors and the analogy between quantum and classical heat engines

Cited by in corpus (3)

• Efficiencies of power plants, quasi-static models and the geometric-mean temperature
• Estimating performance of Feynman's ratchet with limited information
• Optimal engine performance using inference for non-identical finite source and sink