We present an experimental realization of an autonomous Maxwell's demon, which extracts microscopic information from a system and reduces its entropy by applying feedback. It is based on two capacitively coupled single-electron devices, both integrated on the same electronic circuit. This setup allows a detailed analysis of the thermodynamics of both the demon and the system as well as their mutual information exchange. The operation of the demon is directly observed as a temperature drop in the system. We also observe a simultaneous temperature rise in the demon arising from the thermodynamic cost of generating the mutual information.
Recently, the fundamental laws of thermodynamics have been reconsidered for small systems. The discovery of the fluctuation relations [1][2][3][4][5] has spurred theoretical [1,6,7,[9][10][11][12][13] and experimental [14-23] studies on thermodynamics of systems with few degrees of freedom. The concept of entropy production has been extended to the microscopic level by considering stochastic trajectories of a system coupled to a heat bath. However, the experimental observation of the microscopic entropy production remains elusive. We measure distributions of the microscopic entropy production in a single-electron box consisting of two islands with a tunnel junction. The islands are coupled to separate heat baths at different temperatures, maintaining a steady thermal nonequilibrium. As Jarzynski equality between work and free energy is not applicable in this case, the entropy production becomes the relevant parameter. We verify experimentally that the integral and detailed fluctuation relations are satisfied. Furthermore, the coarse-grained entropy production [10-12, 23, 24] from trajectories of electronic transitions is related to the bare entropy production by a universal formula. Our results reveal the fundamental roles of irreversible entropy production in non-equilibrium small systems.Entropy production is a hallmark of irreversible thermodynamic processes. The concept of a stochastic microscopic trajectory allows one to define entropy for small systems [1]. However, such trajectories depend on the scale of observation. If one only accesses mesoscopic degrees of freedom, one observes coarse-grained trajectories of mesoscopic states. The corresponding entropy production then differs from the bare entropy production without coarse-graining. In fact, it has been recently shown that coarse-graining of the slow background degrees of freedom for stochastic dynamics may actually lead to a modification of the fluctuation relations for entropy [23]. To clarify the concept of microscopic entropy production in non-equilibrium, accurate measurements are needed for systems, where the concepts of stochastic dynamics and time scale separation between the system and the heat bath are well-defined.A single-electron box (SEB) device at low temperatures is an excellent test bench for thermodynamics in small systems [22,25,26].The SEB employed here is shown in Fig. 1(a). The electrons in the normal-metal copper island (N) can tunnel to the superconducting Al island (S) through the aluminum oxide insulator (I). The sample fabrication [27] methods are similar to those in Ref. [22], but the design is different in that the S side of the junction does not overlap with the normal conductor in order to intentionally weaken the relaxation of energy in S [28]. Moreover, the main results in Ref. [22] were extracted from measurements at the temperature of 220 mK, whereas these measurements are conducted at 140 mK. Lower temperature further weakens the relaxation significantly [28], leading to and elevated temperature in S. We denote by n ...
Measuring the thermodynamic properties of open quantum systems poses a major challenge. A calorimetric detection has been proposed as a feasible experimental scheme to measure work and fluctuation relations in open quantum systems. However, the detection requires a finite size for the environment, which influences the system dynamics. This process cannot be modeled with the standard stochastic approaches. We develop a quantum jump model suitable for systems coupled to a finite-size environment. With the method we study the common fluctuation relations and prove that they are satisfied.
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Quantum computing and neural networks show great promise for the future of information processing. In this paper we study a quantum reservoir computer (QRC), a framework harnessing quantum dynamics and designed for fast and efficient solving of temporal machine learning tasks such as speech recognition, time series prediction and natural language processing. Specifically, we study memory capacity and accuracy of a quantum reservoir computer based on the fully connected transverse field Ising model by investigating different forms of inter-spin interactions and computing timescales. We show that variation in inter-spin interactions leads to a better memory capacity in general, by engineering the type of interactions the capacity can be greatly enhanced and there exists an optimal timescale at which the capacity is maximized. To connect computational capabilities to physical properties of the underlaying system, we also study the out-of-time-ordered correlator and find that its faster decay implies a more accurate memory. Furthermore, as an example application on real world data, we use QRC to predict stock values.
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