2,236 research outputs found

    Symmetry in Full Counting Statistics, Fluctuation Theorem, and Relations among Nonlinear Transport Coefficients in the Presence of a Magnetic Field

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    We study full counting statistics of coherent electron transport through multi-terminal interacting quantum-dots under a finite magnetic field. Microscopic reversibility leads to the symmetry of the cumulant generating function, which generalizes the fluctuation theorem in the context of quantum transport. Using this symmetry, we derive the Onsager-Casimir relation in the linear transport regime and universal relations among nonlinear transport coefficients.Comment: 4.1pages, 1 figur

    Fluctuation theorem for currents in open quantum systems

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    A quantum-mechanical framework is set up to describe the full counting statistics of particles flowing between reservoirs in an open system under time-dependent driving. A symmetry relation is obtained which is the consequence of microreversibility for the probability of the nonequilibrium work and the transfer of particles and energy between the reservoirs. In some appropriate long-time limit, the symmetry relation leads to a steady-state quantum fluctuation theorem for the currents between the reservoirs. On this basis, relationships are deduced which extend the Onsager-Casimir reciprocity relations to the nonlinear response coefficients.Comment: 19 page

    Thermodynamic time asymmetry in nonequilibrium fluctuations

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    We here present the complete analysis of experiments on driven Brownian motion and electric noise in a RCRC circuit, showing that thermodynamic entropy production can be related to the breaking of time-reversal symmetry in the statistical description of these nonequilibrium systems. The symmetry breaking can be expressed in terms of dynamical entropies per unit time, one for the forward process and the other for the time-reversed process. These entropies per unit time characterize dynamical randomness, i.e., temporal disorder, in time series of the nonequilibrium fluctuations. Their difference gives the well-known thermodynamic entropy production, which thus finds its origin in the time asymmetry of dynamical randomness, alias temporal disorder, in systems driven out of equilibrium.Comment: to be published in : Journal of Statistical Mechanics: theory and experimen

    Thermodynamic large fluctuations from uniformized dynamics

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    Large fluctuations have received considerable attention as they encode information on the fine-scale dynamics. Large deviation relations known as fluctuation theorems also capture crucial nonequilibrium thermodynamical properties. Here we report that, using the technique of uniformization, the thermodynamic large deviation functions of continuous-time Markov processes can be obtained from Markov chains evolving in discrete time. This formulation offers new theoretical and numerical approaches to explore large deviation properties. In particular, the time evolution of autonomous and non-autonomous processes can be expressed in terms of a single Poisson rate. In this way the uniformization procedure leads to a simple and efficient way to simulate stochastic trajectories that reproduce the exact fluxes statistics. We illustrate the formalism for the current fluctuations in a stochastic pump model

    To adapt or not to adapt? Technical debt and learning driven self-adaptation for managing runtime performance

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    Self-adaptive system (SAS) can adapt itself to optimize various key performance indicators in response to the dynamics and uncertainty in environment. In this paper, we present Debt Learning Driven Adaptation (DLDA), an framework that dynamically determines when and whether to adapt the SAS at runtime. DLDA leverages the temporal adaptation debt, a notion derived from the technical debt metaphor, to quantify the time-varying money that the SAS carries in relation to its performance and Service Level Agreements. We designed a temporal net debt driven labeling to label whether it is economically healthier to adapt the SAS (or not) in a circumstance, based on which an online machine learning classifier learns the correlation, and then predicts whether to adapt under the future circumstances. We conducted comprehensive experiments to evaluate DLDA with two different planners, using 5 online machine learning classifiers, and in comparison to 4 state-of-the-art debt- oblivious triggering approaches. The results reveal the effectiveness and superiority of DLDA according to different metrics

    Fluctuation theorem for the effusion of an ideal gas

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    The probability distribution of the entropy production for the effusion of an ideal gas between two compartments is calculated explicitly. The fluctuation theorem is verified. The analytic results are in good agreement with numerical data from hard disk molecular dynamics simulations.Comment: 11 pages, 10 figures, 2 table

    Dynamical fluctuations for semi-Markov processes

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    We develop an Onsager-Machlup-type theory for nonequilibrium semi-Markov processes. Our main result is an exact large time asymptotics for the joint probability of the occupation times and the currents in the system, establishing some generic large deviation structures. We discuss in detail how the nonequilibrium driving and the non-exponential waiting time distribution influence the occupation-current statistics. The violation of the Markov condition is reflected in the emergence of a new type of nonlocality in the fluctuations. Explicit solutions are obtained for some examples of driven random walks on the ring.Comment: Minor changes, accepted for publication in Journal of Physics

    Vortices in the two-dimensional Simple Exclusion Process

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    We show that the fluctuations of the partial current in two dimensional diffusive systems are dominated by vortices leading to a different scaling from the one predicted by the hydrodynamic large deviation theory. This is supported by exact computations of the variance of partial current fluctuations for the symmetric simple exclusion process on general graphs. On a two-dimensional torus, our exact expressions are compared to the results of numerical simulations. They confirm the logarithmic dependence on the system size of the fluctuations of the partialflux. The impact of the vortices on the validity of the fluctuation relation for partial currents is also discussed.Comment: Revised version to appear in Journal of Statistical Physics. Minor correction

    Gab2 deficiency prevents Flt3-ITD driven acute myeloid leukemia in vivo

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    Internal tandem duplications (ITD) of the FMS-like tyrosine kinase 3 (FLT3) predict poor prognosis in acute myeloid leukemia (AML) and often co-exist with inactivating DNMT3A mutations. In vitro studies implicated Grb2-associated binder 2 (GAB2) as FLT3-ITD effector. Utilizing a Flt3-ITD knock-in, Dnmt3a haploinsufficient mouse model, we demonstrate that Gab2 is essential for the development of Flt3-ITD driven AML in vivo, as Gab2 deficient mice displayed prolonged survival, presented with attenuated liver and spleen pathology and reduced blast counts. Furthermore, leukemic bone marrow from Gab2 deficient mice exhibited reduced colony-forming unit capacity and increased FLT3 inhibitor sensitivity. Using transcriptomics, we identify the genes encoding for Axl and the Ret co-receptor Gfra2 as targets of the Flt3-ITD/Gab2/Stat5 axis. We propose a pathomechanism in which Gab2 increases signaling of these receptors by inducing their expression and by serving as downstream effector. Thereby, Gab2 promotes AML aggressiveness and drug resistance as it incorporates these receptor tyrosine kinases into the Flt3-ITD signaling network. Consequently, our data identify GAB2 as a promising biomarker and therapeutic target in human AML
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