Autonomous information thermal machine was modelled allowing access to fluctuations in energetic and informational currents. This device performs both heat-driven information erasure and refrigeration powered by information; efficiencies were also defined to measure these processes. A computational model of an autonomous device converting between heat and information developed. The machine erases data using heat or cools down by utilising information; efficiencies were defined to measure these processes at small scales.

Extending this work with quantum effects in its “information storage” allows researchers to better understand how such devices function when random fluctuations are key. A computational model of a self-operating device, akin to a miniature engine running on both heat and information instead of just fuel, created. Researchers focused on how random fluctuations impact performance and efficiency in this system, similar to measuring average car speeds on a busy highway where individual vehicles travel at slightly different rates.

To better understand its behaviour when randomness is significant, the model extended with an advanced memory bank which uses quantum mechanics allowing multiple states simultaneously; think of it as more than simple 0s and 1s. These developments provide insights into designing efficient devices that convert between energy and information at microscopic levels, but what role does coherence play in optimising such machines.

Coherence drives dissipative region growth enabling novel thermodynamic exploration

Computational modelling revealed a sharp expansion of the dissipative region within autonomous information thermal machine. Increasing coherence, measured by absolute values of ‘c’, enlarged this area up to threefold compared to zero coherence levels. Previously, maintaining distinct operating modes such as efficient refrigeration or erasure was impossible due to overwhelming dissipation; now, this advancement allows examination of how quantum effects impact energy and information conversion at microscopic scales.

This goes beyond classical models that treat data storage simply as strings of zeros and ones. A ‘counting formalism tracked fluctuations in energetic and informational exchanges, revealing subtle changes in precision alongside average current measurements. Detailed analysis using ‘full counting statistics’ showed increasing coherence also led to decreases in cold heat current, causing refrigeration failure when currents became negative.

While higher coherence did increase quantum bias on the tape, it primarily induced mixing within the machine instead of enhancing useful thermodynamic action, complete informational contribution rose to 1.9 for maximum observed coherence. Above all, signal-to-noise ratio calculations revealed no improvement over classical limits at any level of coherence tested.

Coherent Data Storage Reveals Tradeoffs Between Performance and Energy Reset Costs

Designing devices that convert information into useful work at minuscule scales promises breakthroughs in fields from computing to refrigeration; however, practical efficiency remains elusive. The team at Instituto de Física Interdisciplinar y Sistemas Complecos IFISC (CSIC-UIB) modelled an autonomous machine converting between heat and information alongside thermal reservoirs and a data store called a ‘tape’. This computational framework allows examination of both energy transfer and informational currents, essential for understanding nanoscale devices, alongside the random fluctuations inherent in their operation. It can perform two key functions: erasing data using heat or cooling via information processing, with defined efficiencies measuring each process. Incorporating ‘coherent information storage alters machine performance; data exists as multiple states simultaneously rather than simple on/off signals. However, a key question lingers regarding precision, how much does performance dip when accounting for energy lost during data ‘resetting’. The research clarifies how this coherent approach impacts tiny machines converting information into work, a concept important to future technologies. By holding multiple possibilities instead of simple on/off states, scientists clarify new avenues for optimising these devices at minuscule scales and unlocking more efficient designs for nanoscale devices across diverse fields like computing and cooling.

This research modelled an autonomous machine interacting with heat and information reservoirs, a “tape”, to understand the conversion between thermal and informational resources. The study demonstrated that the machine could perform both information erasure using heat and information-powered refrigeration, allowing researchers to define efficiencies for each process. This work provides insights useful for designing and optimizing information-to-work conversion devices at small scales by clarifying how fluctuations impact operation.

👉 More information
🗞 Stochastic and quantum autonomous information machine: efficiency fluctuations, precision and optimization
✍️ Lucas Trigal and Gonzalo Manzano (Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB))
🧠 ArXiv: https://arxiv.org/abs/2610.32683

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