Computing with Physical Systems

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There has been an explosion of interest in unconventional approaches to computing with physical systems (some recent reviews/works: [MMB2022], [SM2023], [WOG+2020], [HAK+23]). This has been driven by multiple factors, including (1) the realization that there is the potential to build vastly more energy-efficient or faster computers if we rethink how we harness physical processes for computing – giving up some of the abstractions computers have relied on for 50+ years in exchange for being able to operate closer to the fundamental limits that physics allows, and (2) the growth of machine learning – which provides both a strong motivator for more efficient machines to be built, as well as a wealth of methods that can be used to reimagine how computers work. This Aspen Winter Conference will bring together both theorists and experimentalists across a broad range of disciplines – including soft condensed matter, biological physics, neuroscience, machine learning, hard condensed matter, optics, fluid dynamics, and quantum information science – who typically do not have the opportunity to interact but who are all exploring various aspects of computing in different physical systems. Topics will include:

  • Information processing and dynamics in classical and quantum systems, including (but not limited to) electronic, spintronic, optical, mechanical, fluidic, biological, and chemical systems.
  • Devices, architectures, and algorithms for constructing physical machines that can learn without electronic processors.
  • Fundamental limits to computing: time, energy, precision.
  • Integrated sensing, computation, and actuation.

The conference will feature invited talks and discussion sessions. All participants will be invited to present posters. A welcome reception will be held on Sunday 7 January 2024, and the scientific program will take place from Monday 8 January 2024 until lunchtime on Friday 12 January 2024.


January 7
January 12
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