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Thermodynamic Computers Go With the (Energy) Flow
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information theory
Thermodynamic Computers Go With the (Energy) Flow
By
Philip Ball
July 15, 2026
Today’s computers need safeguards against random energy fluctuations. Thermodynamic computers would put those fluctuations to use.
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Ada Zejun Shen/Quanta Magazine
Introduction
By Philip Ball
Contributing Writer
July 15, 2026
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computer science
computers
information theory
physics
thermodynamics
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In the quest to make computers accurate and reliable, noise is the enemy. The thermal jiggling of atoms is a constant threat to the precision needed for detailed calculations. Whether we’re dealing with familiar classical devices like the laptops or supercomputers that we use today, or fancy quantum devices that promise us faster computation tomorrow, we don’t want some haphazard heat fluctuation to flip a binary digit from a 1 to a 0, sending a calculation off course. So computer engineers work hard to make computers immune to noise, by switching bits at energies far above the random ripples of the environment.
But what if noise could be made into the computer engineer’s friend? What if, instead of trying to make devices that work despite the hubbub of thermal fluctuations that ruffle everything in the universe, we could harness that noise to actually do the computing?
That’s the goal of a nascent field called thermodynamic computing. Since the Computing Community Consortium hosted its first conference on thermodynamic computing in 2019, a small community of researchers has been laboring to put it into practice. Recently, some of them have simulated thermodynamic computation in standard silicon-based logic circuits, showing that the basic concepts seem to work in principle.
The approach could produce computers that consume little power and dissipate little heat — a huge advantage, given the power-hungry operation of today’s devices and the increasing struggle to prevent ultra-dense miniaturized circuits from melting down.
Thermodynamic computing would make use of thermodynamic processes, which distribute and dissipate energy and inevitably increase randomness at the microscopic scale. “The field is about designing computers that exploit thermodynamics as a computational resource,” said Patrick Coles, a physicist at the startup Normal Computing in New York. If it works, it could transform not only the computing industry but the very way we think about computation itself.
A Path Through the Energy Landscape
The second law of thermodynamics tells us that the entropy of a closed system should increase over time; things should become less organized overall. This means that energy gets dissipated as random thermal fluctuations, which are generally of no use to anyone. Some processes in nature, however, use those fluctuations to find their way to a more organized state.
“I think thermodynamic computing was developed with the thought that it was piggybacking on the computation that ‘already happens out there’ in the rest of the world but [is] not explicitly labeled as such,” said David Sivak, a statistical physicist at Simon Fraser University in Burnaby, Canada.
In thermodynamics, the way a physical system changes over time (its dynamics) can be described as a trajectory through an “energy landscape,” a kind of map of the total energies of different configurations of a system’s components. In this landscape, valleys are where the system settles into comfortable, low-energy configurations, while peaks are high-energy configurations that are relatively unstable. A system like this reaches equilibrium when it settles in the lowest valley and stays there.
If this all seems a bit abstract, think about milk. What allows many people to digest dairy products is a chainlike enzyme called lactase, which is produced in the small intestine and fits together like a puzzle piece with the complex sugar in milk called lactose. The compatibility between their shapes allows lactase to break lactose apart into its simple sugar components, which are more easily managed by the digestive system.
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