Colloquium: Akram Touil | LANL
In-Person PHYS 401
Location
Physics : 401
Date & Time
December 17, 2025, 11:00 am – 12:00 pm
Description
TITLE: "The Physics of Information: From Fundamentals to Cutting Edge Applications”
ABSTRACT: Establishing the thermodynamic cost of information manipulation led to Landauer's dictum, "information is physical," suggesting a deeper principle: the physics of quantum information. This talk traces that principle from fundamentals to cutting edge applications by examining information dynamics. We establish quantitative links between information-theoretic measures and operational indicators of both information spread and quantum-to-classical transitions, clarifying when and how objective classical states emerge and persist through widespread information amplification. Leveraging these insights, we outline application pathways such as diagnostics for noise and decoherence in quantum devices, resource-aware protocols for error mitigation and control, environment-assisted sensing strategies, and thermodynamically grounded principles for efficient information processing. We also highlight opportunities to apply machine learning and deep learning, for example, to infer dynamical structure from sparse observations, to learn surrogate models for open-system evolution, and to design adaptive control and error-mitigation policies. In summary, these findings illuminate a unified framework where open-system dynamics are understood as flows of information, deepening our grasp of fundamental physics while guiding the design of robust and scalable technologies.
ABSTRACT: Establishing the thermodynamic cost of information manipulation led to Landauer's dictum, "information is physical," suggesting a deeper principle: the physics of quantum information. This talk traces that principle from fundamentals to cutting edge applications by examining information dynamics. We establish quantitative links between information-theoretic measures and operational indicators of both information spread and quantum-to-classical transitions, clarifying when and how objective classical states emerge and persist through widespread information amplification. Leveraging these insights, we outline application pathways such as diagnostics for noise and decoherence in quantum devices, resource-aware protocols for error mitigation and control, environment-assisted sensing strategies, and thermodynamically grounded principles for efficient information processing. We also highlight opportunities to apply machine learning and deep learning, for example, to infer dynamical structure from sparse observations, to learn surrogate models for open-system evolution, and to design adaptive control and error-mitigation policies. In summary, these findings illuminate a unified framework where open-system dynamics are understood as flows of information, deepening our grasp of fundamental physics while guiding the design of robust and scalable technologies.
