Non-Ideal Measurement Heat Engines

TL;DR

This paper compares measurement engines with different types of correlations, showing that thermally correlated engines can outperform entanglement-based ones when considering reset and cooling costs, and identifies optimal conditions for efficiency.

Contribution

It introduces a comparison of non-ideal measurement engines based on entanglement and thermal correlations, highlighting the advantages of thermal correlations in practical scenarios.

Findings

Thermally correlated engines can outperform entanglement engines at the same work output.

Optimal efficiency in thermally correlated engines is achieved with a higher temperature pointer.

Accounting for reset and cooling costs alters the comparative performance of measurement engines.

Abstract

We discuss the role of non-ideal measurements within the context of measurement engines by contrasting examples of measurement engines which have the same work output but with varying amounts of entanglement. Accounting for the cost of resetting, correlating the engine to a pointer state and also the cost of cooling the pointer state, we show that for a given work output, thermally correlated engines can outperform corresponding entanglement engines. We also show that the optimal efficiency of the thermally correlated measurement engine is achieved with a higher temperature pointer than the pointer temperature of the optimal entanglement engine.