arXiv:2307.16757 · Physical Review Research

Thermodynamically optimal information gain in finite-time measurement

Rihito Nagase, Takahiro Sagawa

Published Sep 3, 2024• 10 citations

Abstract

The tradeoff relation between speed and cost is a central issue in designing fast and efficient information processing devices. We derive an achievable bound on thermodynamic cost for obtaining information through finite-time (non-quasi-static) measurements. Our proof is based on optimal transport theory, which enables us to identify the explicit protocol to achieve the obtained bound. Moreover, we demonstrate that the optimal protocol can be approximately implemented by an experimentally feasible setup with quantum dots. Our results would lead to design principles of high-speed and low-energy-cost information processing. Published by the American Physical Society 2024

DOI: 10.1103/physrevresearch.6.033239

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arXiv:2307.16757 · Physical Review Research

Thermodynamically optimal information gain in finite-time measurement

Rihito Nagase, Takahiro Sagawa

Published Sep 3, 2024• 10 citations

arXiv HTML PDF

Abstract

DOI: 10.1103/physrevresearch.6.033239

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We derive an operationally defined lower bound on the physical time

\Delta t

required to execute any information-processing task, based on the total entropy produced

\Delta\Sigma

. The central result,

\Delta t \geq \tau_{\Sigma} \Delta\Sigma

, introduces the Process-Dependent Dissipation Timescale

\tau_{\Sigma} \equiv 1/\langle \dot{\Sigma} \rangle_{\text{max}}

, which quantifies the maximum achievable entropy production rate for a given physical platform. We derive

\tau_{\Sigma}

from microscopic system-bath models and validate our framework against experimental data from superconducting qubit platforms. Crucially, we obtain a Measurement Entropic Time Bound:

\Delta t_{\text{meas}} \geq \tau_{\Sigma} k_{\text{B}}[H(P) - S(\rho)]

, relating measurement time to information gained. Comparison with IBM and Google quantum processors shows agreement within experimental uncertainties. This framework provides a thermodynamic interpretation of quantum advantage as reduced entropy production per logical inference and suggests concrete optimization strategies for quantum hardware design.