Bulletin of the American Physical Society
2024 APS March Meeting
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session A28: Stochastic Thermodynamics of Biological and Artificial Information Processing
8:00 AM–10:36 AM,
Monday, March 4, 2024
Room: 101I
Sponsoring
Units:
GSNP DBIO
Chair: Xiaofei Guo, University of Amsterdam
Abstract: A28.00006 : Thermodynamically Optimal Information Gain in Finite Time Measurement*
9:24 AM–9:36 AM
Presenter:
Rihito Nagase
(Univ of Tokyo)
Authors:
Rihito Nagase
(Univ of Tokyo)
Takahiro Sagawa
(Univ of Tokyo)
In this talk, I will show the finite-time enegy cost for measurement process by incorporating optimal transport theory, which has attracted attention as a theory that provides tight bounds on the energy cost required for finite-time processes. First, we derive the upper bound on the mutual information that can be obtained under a given optimal transport distance. This is the most mathematically nontrivial part of this presentation. I will then explain that, by considering the dual problem, this upper bound gives the fundamental bound on the thermodynamic cost required to obtain information in finite-time measurement. This bound is tight, and we can also identify the optimal protocol to achieve it. Moreover, I will explain that, in an experimentally feasible setting with quantum dots, the optimal protocol can be approximately implemented. This result is expected to lead to design principles for high-speed and low-energy-cost information processes.
*R.N. is supported by the World-leading Innovative Graduate Study Program for Materials Research, Industry, and Technology (MERIT-WINGS) of the University of Tokyo. T.S. is supported by Japan Society for the Promotion of Science (JSPS) KAKENHI Grants No. JP19H05796. T.S. is also supported by the Institute of AI and Beyond of the University of Tokyo. This work is also supported by JST ERATO Grant Number JPMJER2302, Japan.
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