A groundbreaking development in the field of stochastic thermodynamics offers promising insights into the interplay between computation and energy efficiency, potentially aiding in the fight against climate change. Published in the Proceedings of the National Academy of Sciences, this research unveils mathematical tools that explore the inner workings of computational systems operating far from thermal equilibrium.
Traditionally, thermal equilibrium occurs when there is no heat exchange between two systems. However, computers, which consume energy and emit heat during information processing, function in a state that is far removed from equilibrium. The critical question posed by researchers is how the energy required for physical systems to perform computations relates to the specifics of those computations.
For over a century, physicists and computer scientists have sought to bridge the gap between thermodynamics and computation, but until recently, they lacked a rigorous framework to study such systems. Stochastic thermodynamics has changed this landscape, providing the necessary mathematical instruments to quantitatively analyze the behavior of non-equilibrium systems across various scales.
David Wolpert, a professor at the Santa Fe Institute, describes this shift as a major revolution in non-equilibrium physics. He states, “It gives us tools to explore and quantify everything that happens with systems, even those arbitrarily far from equilibrium.” These tools include mathematical theorems, uncertainty relations, and thermodynamic speed limits, which can help researchers investigate the connections between energy, computation, and climate impact.
As energy demands for computations continue to rise, understanding these losses becomes imperative. Jan Korbel, a postdoctoral researcher at the Complexity Science Hub in Vienna, emphasizes, “Every calculation in every computer requires energy, part of which is lost as heat, warming not only the system but the planet.”
The implications of stochastic thermodynamics extend beyond computing. Biological systems, such as cells and neurons, also perform computations outside equilibrium. Wolpert notes that the insights gained could lead to more energy-efficient designs for real-world devices, acting as a “unifying glue” that connects various scientific domains.
“These considerations were absent in the work of 20th-century physicists. Now they allow us to think about the real energy dynamics of these systems,” he adds, signifying a transformative moment in our understanding of energy and computation.