We present a unified theoretical, numerical, and experimental investigation into autonomous information heatengines (Maxwell’s demons), bridging microscopic open quantum thermodynamics, stochastic continuous moni-toring, deep reinforcement learning, and practical energy harvesting engineering. First, addressing widespreadnumerical pitfalls in quantum thermodynamics simulations, we identify an operator sign inversion in detailed-balance jump rates that previously simulated an unphysical “perpetual motion machine” yielding −19.29 kB T .Once corrected via adaptive Runge-Kutta integration, we prove that single-step work extraction from maximallyentangled Bell states is strictly bounded by kB T ln 2, and that the cyclic entropy accounting of entanglement re-generation imposes a net non-negative work cost (Wnet ≥ 0), establishing quantum entanglement as a consumedthermodynamic fuel rather than a violation of the Second Law. Second, using positive-preserving Rouchon-Ralphstochastic master equation mappings across 48 trajectory ensembles, we evaluate an Information Conveyor Beltin a 10-dot chain under continuous homodyne detection. We demonstrate that while an isolated cryogenic demonreservoir (TM = 4.2 K) enables positive extracted power, incorporating the mandatory Carnot refrigeration over-head required to maintain the cryostat exactly cancels all efficiency advantages, yielding an overall system deficitmatching the isothermal baseline. Third, we address autonomous control in partially observable Markov deci-sion processes (POMDPs) by deploying Recurrent Proximal Policy Optimization (Recurrent PPO with LSTM),enabling the demon to autonomously overcome measurement backaction and discover synchronized conveyor trans-port policies superior to classical heuristics. Finally, we design and verify Configuration D, a body-heat-poweredthermoelectric energy harvester operating an ESP32-C3 microcontroller demon. By eliminating idle wake-timedelays and overlapping 9-bit digital sensor conversion with sub-millisecond USB polling, firmware v2 slashes ac-tive controller consumption in our calibrated design model by a factor of 8.7 (from ≈ 208.5 mJ to ≈ 24.1 mJ),establishing a net-positive self-powered operational cycle (+65.8 mJ/cycle). We quantify the fundamental gap of≈ 8.4 × 1018 (≈ 19 orders of magnitude) between the Landauer erasure limit (2.87 × 10−21 J) and real-worldmicrocontrollers, delineating the rigorous boundary between physical information thermodynamics and real-worldenergy harvesting.
We present a unified theoretical, numerical, and experimental investigation into autonomous information heatengines (Maxwell’s demons), bridging microscopic open quantum thermodynamics, stochastic continuous moni-toring, deep reinforcement learning, and practical energy harvesting engineering. First, addressing widespreadnumerical pitfalls in quantum thermodynamics simulations, we identify an operator sign inversion in detailed-balance jump rates that previously simulated an unphysical “perpetual motion machine” yielding −19.29 kB T .Once corrected via adaptive Runge-Kutta integration, we prove that single-step work extraction from maximallyentangled Bell states is strictly bounded by kB T ln 2, and that the cyclic entropy accounting of entanglement re-generation imposes a net non-negative work cost (Wnet ≥ 0), establishing quantum entanglement as a consumedthermodynamic fuel rather than a violation of the Second Law. Second, using positive-preserving Rouchon-Ralphstochastic master equation mappings across 48 trajectory ensembles, we evaluate an Information Conveyor Beltin a 10-dot chain under continuous homodyne detection. We demonstrate that while an isolated cryogenic demonreservoir (TM = 4.2 K) enables positive extracted power, incorporating the mandatory Carnot refrigeration over-head required to maintain the cryostat exactly cancels all efficiency advantages, yielding an overall system deficitmatching the isothermal baseline. Third, we address autonomous control in partially observable Markov deci-sion processes (POMDPs) by deploying Recurrent Proximal Policy Optimization (Recurrent PPO with LSTM),enabling the demon to autonomously overcome measurement backaction and discover synchronized conveyor trans-port policies superior to classical heuristics. Finally, we design and verify Configuration D, a body-heat-poweredthermoelectric energy harvester operating an ESP32-C3 microcontroller demon. By eliminating idle wake-timedelays and overlapping 9-bit digital sensor conversion with sub-millisecond USB polling, firmware v2 slashes ac-tive controller consumption in our calibrated design model by a factor of 8.7 (from ≈ 208.5 mJ to ≈ 24.1 mJ),establishing a net-positive self-powered operational cycle (+65.8 mJ/cycle). We quantify the fundamental gap of≈ 8.4 × 1018 (≈ 19 orders of magnitude) between the Landauer erasure limit (2.87 × 10−21 J) and real-worldmicrocontrollers, delineating the rigorous boundary between physical information thermodynamics and real-worldenergy harvesting.
We conducted a comprehensive numerical simulation study on the practical limitations of information engines (energy harvesters) based on Maxwell's Demon, as well as on the quantum information thermodynamic breakthroughs that overcome these limitations. First, using a rigorous master equation simulation (Partial-Secular Semilocal Lindblad approach) of an autonomous engine employing quantum dots, we identified its fatal vulnerabilities (breakdown thresholds) to heat leakage and measurement errors. Furthermore, as a scalable architecture to overcome these limitations, we proposed an "Information Conveyor Belt based on continuous measurement and Bayesian inference" using superconducting circuits, and demonstrated powerful work extraction against a massive reverse bias in a 10-dot chain. Finally, challenging the prohibition of perpetual motion machines dictated by the classical Landauer's principle (information erasure cost), we proved the phenomenon of "negative erasure cost (Quantum Landauer Loophole)" using maximum quantum entanglement via simulations, thereby demonstrating the physical feasibility of true second-kind perpetual motion operation (pure power generation by spontaneous thermal excitation) at room temperature.
Standard stochastic heat engines operate blindly, enforcing work extraction protocols indiscriminately on microstates, and consequently suppressing work output, stability, efficiency. To overcome this, we propose an Otto information engine (OIE) that employs a Maxwell's demon to filter out detrimental stochastic trajectories, and demonstrate that the OIE can provide enhanced work output and stability compared to the corresponding standard Otto engine. Remarkably, even after accounting for the energetic costs of the demon, the OIE efficiency surpasses both the standard Otto limit and Carnot bound. Furthermore, by applying the fluctuation theorem of information dissipation, we derive upper and lower bounds on efficiency, confirming that our results adhere to the second law of thermodynamics. Finally, and counterintuitively, measurement errors and quantum inner friction, traditionally considered deleterious, can be harnessed as resources, which improves robustness and enables us to ignore the adiabatic strokes time.
Abstract Whether quantum computational speedups translate to fundamental thermodynamic energy savings remains unresolved. We establish the first rigorous connection between computational complexity and thermodynamic costs through DEMON(I,E) complexity classes that classify information-processing protocols by information complexity I(n) and erasure energy E(n). Four theorems prove: (1) any g-bit erasure dissipates >= g X k_B T ln 2, generalizing Landauer's principle; (2) measurement disturbance D reduces extractable work to (I-D)k_B T ln 2; (3) Grover-based quantum demons achieve provably optimal Theta(sqrt{N}) thermodynamic advantage over classical search, tight by the BBBV lower bound; and (4) quantum walks on d-dimensional lattices exhibit a dense hierarchy with continuous scaling exponent (d-1)/(2d). Computational validation across six orders of magnitude confirms predictions with <1% error. Experimental predictions include 20.5X energy reduction for trapped-ion Grover search (N=1024, T=1 mK) and 11X effective cooling for superconducting circuit QED heat-bath protocols. This work unifies 158 years of Maxwell demon research, connects algorithmic complexity to physical energy costs, and enables experimental verification of quantum thermodynamic advantages beyond computational speedup.
Information is usually treated as something we use to describe the physical world. In modern physics, however, there is growing evidence that information itself behaves like a physical resource, subject to the same laws that govern energy, heat, and matter. This paper develops that perspective through a concrete experimental proposal we call Quantum Maxwell Demon Arrays (QMDA)—systems that use measurement and feedback at the quantum scale to convert information about a system into controlled physical work. Building on established results such as the Landauer bound and the Szilard engine, we show that information acquired through measurement can be converted into usable free energy, provided that its physical costs and constraints are properly accounted for. In QMDA, measurements are not passive observations but active physical interactions whose outcomes can be stored, processed, and exploited thermodynamically. Organized into arrays, these measurement–feedback units act collectively, allowing information flow itself to shape energy extraction, entropy production, and system control. We demonstrate how QMDA can serve as experimental probes of information thermodynamics, enabling direct tests of how information constrains and enables physical processes in quantum regimes. This framework clarifies the status of measurement as a physical operation rather than a subjective act of interpretation, and it suggests new pathways toward ultra-efficient computation, precision sensing, and energy management within known thermodynamic limits. More broadly, this work supports the view that information is not merely a bookkeeping device for observers, but a fundamental ingredient of physical dynamics—one that can be quantified, manipulated, and transformed into free energy under well-defined physical rules.
Generally, the work output of stochastic heat engines is governed by the stochastic trajectory distribution and the energy spectrum. Because the trajectory distribution depends on the thermal reservoir temperatures, the work output is not only constrained by temperature but is also susceptible to thermal fluctuations. To address these limitations, we introduce two continuous Maxwell's demons into a quantum Otto cycle, forming an Otto information engine (OIE). We demonstrate that the work output of the OIE depends solely on the energy level gap, enabling arbitrary work extraction while eliminating work fluctuations, thereby ensuring cycle-to-cycle identical work output. Furthermore, we show that the engine's efficiency can surpass the standard Carnot efficiency even after accounting for the energy cost of demon's memory erasure. Finally, we show that the OIE can deliver superior output power even when the demon's measurement time is taken into account, and the corresponding Monte Carlo simulation has been executed.
Maxwell's demon explores the role of information in physical processes.Employing information about microscopic degrees of freedom, this "intelligent observer" is capable of compensating entropy production (or extracting work), apparently challenging the second law of thermodynamics.In a modern standpoint, it is regarded as a feedback control mechanism and the limits of thermodynamics are recast incorporating information-to-energy conversion.We derive a trade-off relation between information-theoretic quantities empowering the design of an efficient Maxwell's demon in a quantum system.The demon is experimentally implemented as a spin-1=2 quantum memory that acquires information, and employs it to control the dynamics of another spin-1=2 system, through a natural interaction.Noise and imperfections in this protocol are investigated by the assessment of its effectiveness.This realization provides experimental evidence that the irreversibility in a nonequilibrium dynamics can be mitigated by assessing microscopic information and applying a feed-forward strategy at the quantum scale.