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View article: Entropy Production and Irreversibility in the Linearized Stochastic Amari Neural Model
Entropy Production and Irreversibility in the Linearized Stochastic Amari Neural Model Open
One among the most intriguing results coming from the application of statistical mechanics to the study of the brain is the understanding that it, as a dynamical system, is inherently out of equilibrium. In the realm of non-equilibrium sta…
View article: Thermalization is typical in large classical and quantum harmonic systems
Thermalization is typical in large classical and quantum harmonic systems Open
We establish an analytical criterion for dynamical thermalization within harmonic systems, applicable to both classical and quantum models. Specifically, we prove that thermalization of various observables—such as particle energies in phys…
View article: Langevin dynamics with generalized time-reversal symmetry
Langevin dynamics with generalized time-reversal symmetry Open
When analyzing the equilibrium properties of a stochastic process, identifying the parity of the variables under time-reversal is imperative. This initial step is required to assess the presence of detailed balance, and to compute the entr…
View article: Conceptual and practical approaches for investigating irreversible processes
Conceptual and practical approaches for investigating irreversible processes Open
Current research in statistical mechanics mostly concerns the investigation of out-of-equilibrium, irreversible processes, which are ubiquitous in nature and still far from being theoretically understood. Even the precise characterization …
View article: Optimal Control of an Electromechanical Energy Harvester
Optimal Control of an Electromechanical Energy Harvester Open
Many techniques originally developed in the context of deterministic control theory have recently been applied to the quest for optimal protocols in stochastic processes. Given a system subject to environmental fluctuations, one may ask wh…
View article: Optimal Control of an Electromechanical Energy Harvester
Optimal Control of an Electromechanical Energy Harvester Open
Many techniques originally developed in the context of deterministic control theory have been recently applied to the quest for optimal protocols in stochastic processes. Given a system subject to environmental fluctuations, one may ask wh…
View article: Active-like dynamics of worm-like chains driven by an external traveling-wave force
Active-like dynamics of worm-like chains driven by an external traveling-wave force Open
We present a simplified theory for semiflexible flagella under the action of a traveling-wave perturbation that emulates the organized active forces generated by molecular motors, capable of inducing beating patterns to the filament.
View article: H-theorem at negative temperature: the random exchange model with bounds
H-theorem at negative temperature: the random exchange model with bounds Open
Random exchange kinetic models are widely employed to describe the conservative dynamics of large interacting systems. Due to their simplicity and generality, they are quite popular in several fields, from statistical mechanics to biophysi…
View article: Detecting time-irreversibility in multiscale systems: correlation and response functions in the Lorenz96 model
Detecting time-irreversibility in multiscale systems: correlation and response functions in the Lorenz96 model Open
Due to their relevance to geophysical systems, the investigation of multiscale systems through the lens of statistical mechanics has gained popularity in recent years. The aim of our work is the characterization of the nonequilibrium prope…
View article: Conceptual and practical approaches for investigating irreversible processes
Conceptual and practical approaches for investigating irreversible processes Open
Current research in statistical mechanics mostly concerns the investigation of out-of-equilibrium, irreversible processes, which are ubiquitous in nature and still far from being theoretically understood. Even the precise characterization …
View article: Response of Worm-like Chains to Traveling-Wave Active Forces
Response of Worm-like Chains to Traveling-Wave Active Forces Open
We present a simplified theory for semiflexible flagella under the action of a traveling-wave perturbation that emulates the organized active forces generated by molecular motors, capable of inducing beating patterns to the filament. By mo…
View article: TTV and CMV viral load dynamics: Which emerges first during immunosuppression?
TTV and CMV viral load dynamics: Which emerges first during immunosuppression? Open
Novel biomarkers reflecting the degree of immunosuppression in transplant patients are required to ensure eventual personalized equilibrium between rejection and infection risks. With the above aim, Torque Teno Virus (TTV) viremia was prec…
View article: Extreme heat wave sampling and prediction with analog Markov chain and comparisons with deep learning
Extreme heat wave sampling and prediction with analog Markov chain and comparisons with deep learning Open
We present a data-driven emulator, a stochastic weather generator (SWG), suitable for estimating probabilities of prolonged heat waves in France and Scandinavia. This emulator is based on the method of analogs of circulation to which we ad…
View article: H-theorem at negative temperature: the random exchange model with bounds
H-theorem at negative temperature: the random exchange model with bounds Open
Random exchange kinetic models are widely employed to describe the conservative dynamics of large interacting systems. Due to their simplicity and generality, they are quite popular in several fields, from statistical mechanics to biophysi…
View article: Statistical features of systems driven by non-Gaussian processes: theory & practice
Statistical features of systems driven by non-Gaussian processes: theory & practice Open
Nowadays many tools, e.g. fluctuation relations, are available to characterize the statistical properties of non-equilibrium systems. However, most of these tools rely on the assumption that the driving noise is normally distributed. Here …
View article: Revealing the Nonequilibrium Nature of a Granular Intruder: The Crucial Role of Non-Gaussian Behavior
Revealing the Nonequilibrium Nature of a Granular Intruder: The Crucial Role of Non-Gaussian Behavior Open
The characterization of the distance from equilibrium is a debated problem in particular in the treatment of experimental signals. If the signal is a one-dimensional time series, such a goal becomes challenging. A paradigmatic example is t…
View article: Statistical features of systems driven by non-Gaussian processes: theory & practice
Statistical features of systems driven by non-Gaussian processes: theory & practice Open
Nowadays many tools, e.g. fluctuation relations, are available to characterize the statistical properties of non-equilibrium systems. However, most of these tools rely on the assumption that the driving noise is normally distributed. Here …
View article: Stochastic weather generator and deep learning approach for predicting and sampling extreme European heatwaves
Stochastic weather generator and deep learning approach for predicting and sampling extreme European heatwaves Open
Sampling rare events such as extreme heatwaves whose return period is larger than the length of available observations requires developing and benchmarking new  simulation methods. There is growing interest in applying deep learn…
View article: Revealing the Nonequilibrium Nature of a Granular Intruder: The Crucial Role of Non-Gaussian Behavior
Revealing the Nonequilibrium Nature of a Granular Intruder: The Crucial Role of Non-Gaussian Behavior Open
The characterization of the distance from equilibrium is a debated problem in particular in the treatment of experimental signals. If the signal is a 1-dimensional time-series, such a goal becomes challenging. A paradigmatic example is the…
View article: Inference of time irreversibility from incomplete information: Linear systems and its pitfalls
Inference of time irreversibility from incomplete information: Linear systems and its pitfalls Open
Data from experiments and theoretical arguments are the two pillars sustaining the job of modeling physical systems through inference. In order to solve the inference problem, the data should satisfy certain conditions that depend also upo…
View article: Coupling rare event algorithms with data-based learned committor functions using the analogue Markov chain
Coupling rare event algorithms with data-based learned committor functions using the analogue Markov chain Open
Rare events play a crucial role in many physics, chemistry, and biology phenomena, when they change the structure of the system, for instance in the case of multistability, or when they have a huge impact. Rare event algorithms have been d…
View article: Committor Functions for Climate Phenomena at the Predictability Margin: The Example of El Niño–Southern Oscillation in the Jin and Timmermann Model
Committor Functions for Climate Phenomena at the Predictability Margin: The Example of El Niño–Southern Oscillation in the Jin and Timmermann Model Open
Many atmosphere and climate phenomena lie in the gray zone between weather and climate: they are not amenable to deterministic forecast, but they still depend on the initial condition. A natural example is medium-range forecasting, which i…
View article: Inference in non-equilibrium systems from incomplete information: the case of linear systems and its pitfalls
Inference in non-equilibrium systems from incomplete information: the case of linear systems and its pitfalls Open
Data from experiments and theoretical arguments are the two pillars sustaining the job of modelling physical systems through inference. In order to solve the inference problem, the data should satisfy certain conditions that depend also up…
View article: Advances in rare event simulations using data-based estimation of committor functions
Advances in rare event simulations using data-based estimation of committor functions Open
<p>Rare events, such as heat waves, floods, or hurricanes, play a crucial role in climate dynamics mainly due to the large impact they have. Predicting the occurrence of such events is thus a major challenge.<span>&#160;<…
View article: Committor Functions for Climate Phenomena at the Predictability Margin: The example of El Niño Southern Oscillation in the Jin and Timmerman model
Committor Functions for Climate Phenomena at the Predictability Margin: The example of El Niño Southern Oscillation in the Jin and Timmerman model Open
Many phenomena in the climate system lie in the gray zone between weather and climate: they are not amenable to deterministic forecast, but they still depend on the initial condition. A natural example is medium-range forecasting, which is…
View article: Predicting extreme events using dynamics based machine learning.&#160;
Predicting extreme events using dynamics based machine learning.  Open
<p>Many phenomena in the climate system lie in the gray zone between weather and climate: they are not amenable to deterministic forecast, but they still depend on the initial condition. A natural example is medium-range forecasting,…
View article: Drivers of midlatitude extreme heat waves revealed by analogues and machine learning
Drivers of midlatitude extreme heat waves revealed by analogues and machine learning Open
<p>One of the big challenges today is to appropriately describe heat waves, which are relevant due to their impact on human society. Common characteristics in mid-latitudes involve meanders of the westerly flow and concomitant large …
View article: Machine Learning of committor functions for predicting high impact climate events
Machine Learning of committor functions for predicting high impact climate events Open
<p>There is a growing interest in the climate community to improve the prediction of high impact climate events, for instance ENSO (El-Ni\~no--Southern Oscillation) or extreme events, using a combination of model and observation data…