arXiv subjects

Johan du Buisson

Publications and source records attributed to Johan du Buisson.

8 recordsLinked to original sources

arXiv2026

From Classical Stochastic to Monitored Quantum Dynamics: Dynamical Phase Coexistence in East Circuit Models

Kinetically constrained models have been widely studied in the context of glass formers and non-equilibrium statistical mechanics. Although their simple local rules often result in structureless static properties, their dynamics exhibit intricate emergent phenomena. In this work, we investigate monitored quantum circuit models that interpolate between classical stochastic and unitary quantum dynamics. For any finite measurement strength, the measurement records provide an experimentally accessible probe of the emergence of dynamical phases. By interpreting space-time resolved records as microstates of a fictitious 1+1D spin system, we employ thermodynamic concepts that allow us to investigate the dynamical coexistence between an active and inactive phase. We combine insights from classical stochastic dynamics and numerical simulations of monitored quantum dynamics to investigate different signatures of this dynamical phase coexistence as the measurement strength is varied. Our results shed light on the persistence of dynamical phase coexistence in the quantum regime, offering insights into future experimental studies of complex many-body dynamics in quantum simulators.

quant-ph↗

arXiv2025

Hunting for Maxwell's Demon in the Wild

The paradox of Maxwell's demon motivated the development of information thermodynamics and the creation of nanoscale information engines. We now understand that machines such as the molecular motors within cells can in principle harvest fluctuations and thereby operate as a Maxwell demon -- but do they? Answering this question would seemingly require simultaneous measurement of all system degrees of freedom, which is generally intractable in single-molecule experiments. Here, we derive a simple statistical estimator to infer both the direction and magnitude of subsystem heat flows, and thus determine whether -- and how strongly -- a motor operates as a Maxwell demon. The estimator uses only trajectory measurements for a single degree of freedom. Simulating both colloidal information engines and kinesin molecular motors, we show that our estimator can precisely and accurately detect Maxwell-demon behavior with experimentally accessible resolution and quantities of data. Moreover, we find that kinesin transitions to a Maxwell-demon mechanism in the presence of nonequilibrium noise, with a corresponding increase in velocity consistent with experiments. These findings suggest that molecular motors may have evolved to leverage active fluctuations within cells.

cond-mat.stat-mech↗

arXiv2024

Performance limits of information engines

We review recent studies of a colloidal information engine that consists of a bead in water and held by an optical trap. The bead is ratcheted upward without any apparent external work, by taking advantage of favorable thermal fluctuations. Much of the previous work on such engines aimed to show that accounting for information-processing costs can reconcile the observed motion with the second law of thermodynamics. By contrast, we focus on the factors that limit the performance of such engines by optimizing variously the upward velocity, rate of gravitational free-energy extraction, or ability to track a trajectory. We then consider measurement noise, which degrades engine performance. A naive use of noisy measurements in the feedback algorithm leads to a phase transition at finite signal-to-noise ratio: below the transition, the engine no longer functions. A more sophisticated, `Bayesian' algorithm eliminates the phase transition and improves performance. Finally, operating the information engine in a nonequilibrium environment with extra force fluctuations can enhance the performance by orders of magnitude, even to the point where the energy extracted exceeds that needed to run the information processing. Autonomous implementations of an information engine in such environments could be powered entirely by the additional energy of the bath.

cond-mat.stat-mech↗

arXiv2023

Large deviations of the stochastic area for linear diffusions

The area enclosed by the two-dimensional Brownian motion in the plane was studied by Lévy, who found the characteristic function and probability density of this random variable. For other planar processes, in particular ergodic diffusions described by linear stochastic differential equations (SDEs), only the expected value of the stochastic area is known. Here, we calculate the generating function of the stochastic area for linear SDEs, which can be related to the integral of the angular momentum, and extract from the result the large deviation functions characterising the dominant part of its probability density in the long-time limit, as well as the effective SDE describing how large deviations arise in that limit. In addition, we obtain the asymptotic mean of the stochastic area, which is known to be related to the probability current, and the asymptotic variance, which is important for determining from observed trajectories whether or not a diffusion is reversible. Examples of reversible and irreversible linear SDEs are studied to illustrate our results.

cond-mat.stat-mech↗

arXiv2023

Dynamical large deviations of linear diffusions

Linear diffusions are used to model a large number of stochastic processes in physics, including small mechanical and electrical systems perturbed by thermal noise, as well as Brownian particles controlled by electrical and optical forces. Here, we use techniques from large deviation theory to study the statistics of time-integrated functionals of linear diffusions, considering three classes of functionals or observables relevant for nonequilibrium systems which involve linear or quadratic integrals of the state in time. For these, we derive exact results for the scaled cumulant generating function and the rate function, characterizing the fluctuations of observables in the long-time limit, and study in an exact way the set of paths or effective process that underlies these fluctuations. The results gives a complete description of how fluctuations arise in linear diffusions in terms of effective forces that remain linear in the state or, alternatively, in terms of fluctuating densities and currents that solve Riccati-type equations. We illustrate these results using two common nonequilibrium models, namely, transverse diffusions in two dimensions involving a non-conservative rotating force, and two interacting particles in contact with heat baths at different temperatures.

cond-mat.stat-mech↗

arXiv2023

Dynamical large deviations of diffusions

We solve two problems related to the fluctuations of time-integrated functionals of Markov diffusions, used in physics to model nonequilibrium systems. In the first we derive and illustrate the appropriate boundary conditions on the spectral problem used to obtain the large deviations of current-type observables for reflected diffusions. For the second problem we study linear diffusions and obtain exact results for the generating function associated with linear additive, quadratic additive and linear current-type observables by using the Feynman-Kac formula. We investigate the long-time behavior of the generating function for each of these observables to determine both the so-called rate function and the form of the effective process responsible for manifesting the fluctuations of the associated observable. It is found that for each of these observables, the effective process is again a linear diffusion. We apply our general results for a variety of linear diffusions in $\mathbb{R}^2$, with particular emphasis on investigating the manner in which the density and current of the original process are modified in order to create fluctuations.

cond-mat.stat-mech↗

arXiv2021

Large deviations of currents in diffusions with reflective boundaries

We study the large deviations of current-type observables defined for Markov diffusion processes evolving in smooth bounded regions of $\mathbb{R}^d$ with reflections at the boundaries. We derive for these the correct boundary conditions that must be imposed on the spectral problem associated with the scaled cumulant generating function, which gives, by Legendre transform, the rate function characterizing the likelihood of current fluctuations. Two methods for obtaining the boundary conditions are presented, based on the diffusive limit of random walks and on the Feynman--Kac equation underlying the evolution of generating functions. Our results generalize recent works on density-type observables, and are illustrated for an $N$-particle single-file diffusion on a ring, which can be mapped to a reflected $N$-dimensional diffusion.

cond-mat.stat-mech↗

arXiv2020

Dynamical large deviations of reflected diffusions

We study the large deviations of time-integrated observables of Markov diffusions that have perfectly reflecting boundaries. We discuss how the standard spectral approach to dynamical large deviations must be modified to account for such boundaries by imposing zero-current conditions, leading to Neumann or Robin boundary conditions, and how these conditions affect the driven process, which describes how large deviations arise in the long-time limit. The results are illustrated with the drifted Brownian motion and the Ornstein-Uhlenbeck process reflected at the origin. Other types of boundaries and applications are discussed.

cond-mat.stat-mech↗