Engines of Adaptation: Experimental Analyses of Emergent Thermodynamic Machines
Abstract
The aim of this DURIP proposal is to assemble custom instrumentation for the purpose of measuring emergent thermodynamic machines. While the overarching effort is a collaboration between three professors Ð including James Crutchfield (theory; UC Davis) and Erik Winfree (DNA nanotech; Caltech) Ð support is sought here for requisite measurement instrumentation for the lab of the third, Professor Michael Roukes (experimental physics; Caltech), who is pursuing experiments on solid-state, nanosystems-based instantiations of such machines. Remarkably robust and intelligent natural systems operate across the tremendous time and length scales of the natural world. At one extreme, nanoscale motor proteins shuttle nutrients along microtubule highways, adapting their loads to their host cellÕs needs. At the other, an albatross on a 3,000-mile trek efficiently tracks and adaptively leverages wind fluctuations to radically reduce energy consumption as it circumnavigates an entire ocean without touching down. What is common in the behaviors spanning these immense scales is what one can call adaptive emergent intrinsic computation. Intrinsic computation here means information processing that is reliably and robustly supported by a physical substrate maintained away from equilibrium by internal and environmental energy and entropy fluxes. Emergent refers to how a system leverages a rich palette of patterns inherent in nonlinear systems to greatly simplify a taskÕs minimal required implementation and energy costs. After decades of active research, we now appreciate how such intricate behaviors arise from locally specified yet very general distributed processing. Indeed, the albatross needs no precisely-detailed flight plan. Adaptive means that the systemÕs emergent information processing mechanisms respond to complex, often unpredictable variations in the environment, while maintaining the macroscopic functionality required for task execution, future learning, and survival. In this sense, these systemsÕ functioning relies on a kind of selfprogrammingÑ spontaneously-generated extended patterns of control and self-monitoring. This effort aims to tackle the challenge of discovering the fundamental principles of adaptive emergent intrinsic computation and to experimentally demonstrate how thermodynamic forces can drive a system to become naturally programmable. The topic is particularly timely given the scale and sophistication of the adaptive systems that are now being predicted and designed by researchers in science and engineering. Here, in this collaboration, a particularly novel approach will be pursued that harnesses the most recent advances in nonlinear physics, nanoscale thermodynamics, genetic engineering, and high-performance computing. Professor Roukes groupÕs role is to fabricate and carry out precision measurements upon nano-engineered solid-state thermodynamic machines. With the remarkable recent progress in these respective fields, combined with this teamÕs deep expertise in them, a unique and coherent effort with high probability of success is proposed to understand adaptive emergent intrinsic computation.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 25, 2021
- Source ID
- W911NF2110208
Entities
People
- Michael Roukes
Organizations
- Army Contracting Command
- California Institute of Technology
- United States Army