Article
Physics, Multidisciplinary
Salambo Dago, Ludovic Bellon
Summary: This study investigates the energy exchanges during erasure processes and the cost of fast operations. It reveals that fast operations require an overhead to Landauer's bound, mainly due to dissipation in the overdamped regime and heating of the memory in the underdamped regime.
PHYSICAL REVIEW LETTERS
(2022)
Article
Mathematics, Interdisciplinary Applications
Zaitang Huang, Qi Li, Junfei Cao
Summary: This paper examines the dynamics of a stochastic diffusive plant-herbivore system, establishing the global existence and uniqueness of solutions through the fixed point theorem. The extinction and invariant measure for the system are investigated using comparison theorem and Krylov-Bogoliubov theorem, while a large deviation result is proven through martingale inequality and special energy estimates.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Mathematics, Applied
Wenpo Yao, Jun Wang, Matjaz Perc, Wenli Yao, Jiafei Dai, Daqing Guo, Dezhong Yao
Summary: Through theoretical and experimental analyses, this paper emphasizes the strong similarities and close associations between time irreversibility and amplitude irreversibility measures. We clarify the connections of and the differences between the two types of permutation-based parameters for quantitative nonequilibrium, thereby bridging the concepts of amplitude irreversibility and time irreversibility, and expanding the selection of quantitative tools for studying nonequilibrium processes in complex systems.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Engineering, Industrial
Lauren N. Steimle, Vinayak S. Ahluwalia, Charmee Kamdar, Brian T. Denton
Summary: The article explores the issue of decision-making in MDPs with uncertain parameters and introduces new solution methods. Numerical experiments show that the customized implementation significantly outperforms traditional methods, and that the variance among model parameters can be a crucial factor in problem-solving value.
Article
Engineering, Industrial
Zhizhong Tan, Bei Wu, Ada Che
Summary: This article proposes a comprehensive resilience modeling and quantifying framework for a multi-state system, using time-homogeneous Markov process to describe the evolution of performance over time. Four types of resilience metrics are introduced to characterize different dimensions of system resilience. Explicit formulas for these metrics are derived using the theory of aggregated stochastic processes, and simulation-based algorithms are proposed to validate these formulas.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Mathematics, Applied
Lichao Feng, Lei Liu, Zhihui Wu, Qiumei Liu
Summary: This paper investigates delay-dependent exponential stability and asymptotic boundedness for highly nonlinear Markov jump neutral SFDSs by weakening the global Lipschitz condition for the delay parts of the drift coefficients. The research also explores the method of multiple degenerate functionals in this context to address challenging factors in stability criteria.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Mathematics, Applied
Yanjie Zhang, Xiao Wang, Zibo Wang, Jinqiao Duan
Summary: This paper firstly analyzes the strong convergence of the projective integration method for multiscale stochastic dynamical systems. Then, the pth moment error bounds between the solution of the slow component and the solution of the effective system are obtained. Finally, the analytical results are verified through a specific numerical example.
APPLIED MATHEMATICS LETTERS
(2023)
Article
Chemistry, Multidisciplinary
Ilia A. Solov'yov, Gennady Sushko, Ida Friis, Andrey V. Solov'yov
Summary: This paper discusses the application of stochastic dynamics in complex systems and its implementation in MBN Explorer. It introduces the basic concepts and theories of stochastic dynamics and provides several examples to demonstrate its applicability in different systems.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2022)
Article
Engineering, Manufacturing
Jie Ning
Summary: This study introduces reducible Markov decision processes and stochastic games, whose exact solutions can be obtained by solving simpler coordinate MDPs and coordinate games, respectively. The value function and optimal policy of a reducible model are linear functions of those of the associated coordinate model, providing substantial simplification in analysis and computation. Reducible models offer modeling flexibility and applicability in various contexts, including capacity and inventory management and duopoly competition.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Engineering, Electrical & Electronic
Chenhao Li, Simon Godsill
Summary: The non-homogeneous Poisson process allows the intensity of point generation to vary across time or space domains, with applications in signal processing and machine learning but limited by intractable likelihood function and computationally efficient inference schemes. This paper proposes a framework that combines non-homogeneous Poisson model with continuous-time state-space models for efficient online inference. The proposed approach shows improved performance and computational efficiency compared to batch-based competitor algorithm and a simple baseline kernel estimation scheme.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Wenjie Huang, William B. Haskell
Summary: A stochastic approximation algorithm was developed to solve risk-aware Markov decision processes, covering various risk measures and establishing almost sure convergence and convergence rate of the algorithm. The overall convergence rate of the algorithm was proven to be Omega((ln(1/delta epsilon)/epsilon(2))(1/k) + (ln(1/epsilon))(1/(1-k))) with probability at least 1-delta for a given error tolerance epsilon > 0 and learning rate k in the range (1/2, 1].
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Mathematics
Martha Carpinteyro, Francisco Venegas-Martinez, Ali Aali-Bujari
Summary: This paper develops a stochastic volatility model to explain the dynamics of gold, silver, and platinum returns from 1994 to 2019. The study reveals differences in volatility and jump characteristics among the three precious metals, providing substantial recommendations for investors.
Article
Physics, Fluids & Plasmas
Stephen Teitsworth, John C. Neu
Summary: Stochastic line integrals are proposed as a useful metric for quantitatively characterizing irreversibility and detailed balance violation in noise-driven dynamical systems. By studying two-dimensional systems, it is found that stochastic line integrals can be expressed in terms of a stream function, allowing for analytical understanding of the scaling dependence on key parameters.
Article
Statistics & Probability
Xavier Erny, Eva Locherbach, Dasha Loukianova
Summary: This paper considers a system of Hawkes processes with mean field interactions in a diffusive regime. Each process has a stochastic intensity that is a solution of a stochastic differential equation driven by N independent Poisson random measures. The paper proves that as the number of interacting components N goes to infinity, the intensity converges in distribution in the Skorokhod space to a CIR-type diffusion. Furthermore, the paper also demonstrates the convergence in distribution of the Hawkes processes to a limit point process with the limit diffusion as intensity. To prove these convergence results, analytical techniques based on the convergence of the associated infinitesimal generators and Markovian semigroups are used.
Article
Engineering, Chemical
Chunbing Huang, Federica Cattani, Patrick M. Piccione, Federico Galvanin
Summary: The paper introduces a compartment-based stochastic model to study the collision-exchange process between system members, showing that the system equilibrium is independent of its initial distribution. The derived differential equations reveal the deterministic time evolution of material amount on system members. The example of seed coating process demonstrates the feasibility of the stochastic modelling approach and its agreement with experimental results.
CHEMICAL ENGINEERING SCIENCE
(2022)
Article
Biology
Andrea Mazzolini, Antonio Celani
JOURNAL OF THEORETICAL BIOLOGY
(2020)
Article
Multidisciplinary Sciences
Jonas Neipel, Jonathan Bauermann, Stefano Bo, Tyler Harmon, Frank Juelicher
Article
Mechanics
Lennart Dabelow, Stefano Bo, Ralf Eichhorn
Summary: The defining feature of active particles is their constant self-propulsion through the conversion of chemical energy into directed motion, keeping them permanently out of equilibrium. Despite potentially sharing certain equilibrium features, active particles may break the time-reversal symmetry in anharmonic potentials while fulfilling it in harmonic potentials in steady-state trajectories.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2021)
Article
Physics, Multidisciplinary
Aykut Argun, Giovanni Volpe, Stefano Bo
Summary: This study introduces a data-driven method called RANDI, which utilizes recurrent neural networks to analyze single anomalous diffusion trajectories, successfully inferring the anomalous exponent and identifying the mechanisms responsible for anomalous diffusion. Our method has proven to be the most versatile, consistently ranking in the top 3 for all tasks in the Anomalous Diffusion challenge.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2021)
Article
Mechanics
Francesco Borra, Massimo Cencini, Antonio Celani
Summary: The effectiveness of collective navigation of biological or artificial agents must address the conflicting requirements of staying in a group while avoiding close encounters and limiting energy expenditure. Research shows that optimized multiple objectives can explain observed group behaviors and provide a theoretical basis for biomimetic algorithms used by artificial agents.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2021)
Article
Multidisciplinary Sciences
Gorka Munoz-Gil, Giovanni Volpe, Miguel Angel Garcia-March, Erez Aghion, Aykut Argun, Chang Beom Hong, Tom Bland, Stefano Bo, J. Alberto Conejero, Nicolas Firbas, Oscar Orts, Alessia Gentili, Zihan Huang, Jae-Hyung Jeon, Helene Kabbech, Yeongjin Kim, Patrycja Kowalek, Diego Krapf, Hanna Loch-Olszewska, Michael A. Lomholt, Jean-Baptiste Masson, Philipp G. Meyer, Seongyu Park, Borja Requena, Ihor Smal, Taegeun Song, Janusz Szwabinski, Samudrajit Thapa, Hippolyte Verdier, Giorgio Volpe, Artur Widera, Maciej Lewenstein, Ralf Metzler, Carlo Manzo
Summary: Deviations from Brownian motion leading to anomalous diffusion are commonly found in transport dynamics, but challenging to characterize. An open competition comparing different approaches for single trajectory analysis showed that machine learning methods outperform classical approaches.
NATURE COMMUNICATIONS
(2021)
Article
Biology
Lars Hubatsch, Louise M. Jawerth, Celina Love, Jonathan Bauermann, Ty Dora Tang, Stefano Bo, Anthony A. Hyman, Christoph A. Weber
Summary: This study establishes a physics-based dynamic equation framework that accurately determines diffusion coefficients within liquid condensates and validates the framework's performance through experiments. The research demonstrates that this method can be applied to protein condensates and polyelectrolyte-coacervate systems, showing very accurate and precise results.
Article
Physics, Fluids & Plasmas
Francesco Borra, Luca Biferale, Massimo Cencini, Antonio Celani
Summary: This study focuses on a model of two competing microswimming agents engaged in a pursue-evasion task within a low-Reynolds-number environment. The agents, with limited maneuverability and partial information about the opponent's position and motion, are trained using adversarial reinforcement learning to overcome partial observability and discover increasingly complex sequences of moves.
PHYSICAL REVIEW FLUIDS
(2022)
Article
Physics, Multidisciplinary
Antonio Celani, Gautam Reddy, Massimo Vergassola
Summary: This study investigates the role of partial stickiness on turbulent transport among particles or with a surface. The results show that enforcing the constraints of orthogonality and normalization leads to previously obtained results in a more intuitive way. Additionally, a general model of transport within the atmospheric boundary layer is introduced, and the study demonstrates the existence of acceptable boundary conditions within certain parameter ranges.
ANNALES HENRI POINCARE
(2022)
Article
Chemistry, Physical
N. Orzan, C. Leone, A. Mazzolini, J. Oyero, A. Celani
Summary: Airborne wind energy is a lightweight technology that utilizes airborne devices like kites and gliders to extract power from the wind. Conventional methods are unable to optimize the control of these devices due to the dynamical complexity of turbulent aerodynamics. In this study, we propose to use reinforcement learning to solve this problem, which allows the system to learn an optimal strategy through trial-and-error interactions with the environment. Our simulation results demonstrate that reinforcement learning can effectively control a kite to tow a vehicle for long distances, and the algorithm's physically transparent interpretation allows for a simple list of maneuvering instructions to describe the approximately optimal strategy.
EUROPEAN PHYSICAL JOURNAL E
(2023)
Article
Chemistry, Physical
Chiara Calascibetta, Luca Biferale, Francesco Borra, Antonio Celani, Massimo Cencini
Summary: This study tackles the problem of optimizing both the dispersion rate and control activation cost for two active particles in 2D complex flows using multi-objective reinforcement learning (MORL) with variable swimming velocity. The combination of scalarization techniques and Q-learning algorithm enables MORL to find an optimal Pareto frontier and outperform heuristic strategies as benchmarks. Moreover, the authors investigate the impact of decision time on the performance of the reinforcement learning strategies, highlighting the need for enhanced knowledge of the flow for longer decision times.
EUROPEAN PHYSICAL JOURNAL E
(2023)
Article
Biochemistry & Molecular Biology
Emanuele Panizon, Antonio Celani
Summary: Searching for a target is a fundamental task for many living organisms, and long-distance search guided by olfactory cues is a typical example. Research shows that sharing information among individuals can significantly decrease search times, even without explicit coordination.
Article
Physics, Fluids & Plasmas
R. A. Heinonen, L. Biferale, A. Celani, M. Vergassola
Summary: In many practical scenarios, flying insects face the challenge of searching for emitted cues in turbulent environments. In this study, a partially observable Markov decision process is used to model this search problem, and the Perseus algorithm is employed to compute near-optimal strategies for minimizing arrival time. The computed strategies outperform several heuristic strategies and provide insights into the search difficulty and robustness in different environmental conditions.
Article
Physics, Fluids & Plasmas
Ruben Lier, Jay Armas, Stefano Bo, Charlie Duclut, Frank Juelicher, Piotr Surowka
Summary: This study demonstrates the existence of odd elasticity in viscoelastic materials, which is present not only in active systems but also in passive chiral viscoelastic fluids. Linear viscoelastic chiral solids require activity to exhibit odd elastic responses.
Article
Physics, Multidisciplinary
Stefano Bo, Lars Hubatsch, Jonathan Bauermann, Christoph A. Weber, Frank Juelicher
Summary: This study discusses the stochastic trajectories of single molecules in a phase-separated liquid with coexisting dense and dilute phases. The research shows that molecular trajectories can be described as diffusion with drift in an effective potential. Furthermore, it explores how the physics of phase coexistence affects the statistics of molecular trajectories, particularly in relation to displacements of molecules crossing phase boundaries.
PHYSICAL REVIEW RESEARCH
(2021)
Review
Physics, Multidisciplinary
Sebastian Mizera
Summary: This article discusses the mathematical properties and physical implications of scattering amplitudes, and traces these properties back to physics through simple scattering problems.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2024)