Thermodynamics of quantum information

pJ Berakdarp

Sina Hamedani Raja

Austin K. Daniel, Yuri V. Rostovtsev

Jincheng Zhang

This paper explores the emerging intersection of quantum thermodynamics and quantum information processing. The core argument presented is that quantum information processing fundamentally relies on the thermodynamic properties of quantum systems and can be significantly advanced by leveraging the principles of quantum thermodynamics. This work establishes a framework for analyzing and designing quantum information protocols through the lens of thermodynamic constraints and efficiencies. We introduce a novel perspective where quantum information tasks are viewed as thermodynamic processes, allowing for a more rigorous understanding of their limitations and potential optimizations. The methodology presented aims to bridge the gap between information theory and thermodynamics, ultimately leading to the development of more robust and efficient quantum information systems. Key concepts explored include quantum work, heat dissipation, entropy production, and their implications for quantum data storage, quantum computation, and quantum communication. This research contributes to a fundamental shift in how we approach quantum information processing, moving beyond purely computational considerations to incorporate the underlying thermodynamic realities of quantum systems.

Koji Maruyama, Časlav Brukner, Vlatko Vedral

Thermodynamics is a macroscopic physical theory whose two very general laws are independent of any underlying dynamical laws and structures. Nevertheless, its generality enables us to understand a broad spectrum of phenomena in physics, information science and biology. Does thermodynamics then imply any results in quantum information theory? Taking accessible information in a system as an example, we show that thermodynamics implies a weaker bound on it than the quantum mechanical one (the Holevo bound). In other words, if any post-quantum physics should allow more information storage it could still be under the umbrella of thermodynamics.

Jincheng Zhang

Quantum Information Thermodynamics (QIT) offers a novel perspective on algorithm design, leveraging the principles of thermodynamics to understand and optimize the process of evaluation and improvement. This paper proposes a framework that connects algorithm performance to the fundamental thermodynamic laws governing information flow, resource utilization, and stability. We argue that traditional algorithmic approaches often fail to fully capture the complexities of information processing, and QIT provides a pathway to develop algorithms with enhanced robustness, efficiency, and adaptability. The core mechanism involves identifying and manipulating key thermodynamic parameters within the algorithm's evaluation cycle, ultimately leading to improved performance metrics. This work aims to contribute to a more comprehensive understanding of algorithm optimization and provides a foundation for future research in this rapidly evolving field.