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Stochastic simulation has been a powerful tool for studying the dynamics of gene regulatory networks, particularly in terms of understanding how cell-phenotype stability and fate-transitions are impacted by noisy gene expression. However,…

Molecular Networks · Quantitative Biology 2018-09-05 Margaret J. Tse , Brian K. Chu , Elizabeth L. Read

Lumping a Markov process introduces a coarser level of description that is useful in many contexts and applications. The dynamics on the coarse grained states is often approximated by its Markovian component. In this letter we derive…

Statistical Mechanics · Physics 2012-07-31 David Andrieux

The notion of the integral over the anticommuting Grassmann variables is applied to analyze the fermionic structure of the 2D Ising model with quenched site dilution. In the $N$-replica scheme, the model is explicitly reformulated as a…

High Energy Physics - Theory · Physics 2007-05-23 V. N. Plechko

We study the quantum version of a simplified model of optimization problems, where quantum fluctuations are introduced by a transverse field acting on the qubits. We find a complex low-energy spectrum of the quantum Hamiltonian,…

Statistical Mechanics · Physics 2010-10-13 Laura Foini , Guilhem Semerjian , Francesco Zamponi

In our previous work, we introduced the rule-based Bayesian Regression, a methodology that leverages two concepts: (i) Bayesian inference, for the general framework and uncertainty quantification and (ii) rule-based systems for the…

Machine Learning · Statistics 2022-03-01 Themistoklis Botsas , Lachlan R. Mason , Omar K. Matar , Indranil Pan

Randomized higher-order computation can be seen as being captured by a lambda calculus endowed with a single algebraic operation, namely a construct for binary probabilistic choice. What matters about such computations is the probability of…

Logic in Computer Science · Computer Science 2020-12-24 Ugo Dal Lago , Claudia Faggian , Simona Ronchi Della Rocca

Cells receive a wide variety of cellular and environmental signals, which must be processed combinatorially to generate specific and timely genetic responses. We present here a theoretical study on the combinatorial control and integration…

Soft Condensed Matter · Physics 2007-05-23 Nicolas E. Buchler , Ulrich Gerland , Terence Hwa

Biological multimodal large language models (MLLMs) have emerged as powerful foundation models for scientific discovery. However, existing models are specialized to a single modality, limiting their ability to solve inherently cross-modal…

Machine Learning · Computer Science 2026-03-17 Wonbin Lee , Dongki Kim , Sung Ju Hwang

The goal of demonstrating a quantum advantage with currently available experimental systems is of utmost importance in quantum information science. While this remains elusive for quantum computation, the field of communication complexity…

Quantum Physics · Physics 2019-09-16 Niraj Kumar , Iordanis Kerenidis , Eleni Diamanti

The problem of studying rare events is central to many areas of computer simulations. In a recent paper [Kang, P., et al., Nat. Comput. Sci. 4, 451-460, 2024], we have shown that a powerful way of solving this problem passes through the…

Computational Physics · Physics 2026-03-03 Enrico Trizio , Peilin Kang , Michele Parrinello

We introduce LAM, a subsystem of IMALL2 with restricted additive rules able to manage duplication linearly, called linear additive rules. LAM is presented as the type assignment system for a calculus endowed with copy constructors, which…

Logic in Computer Science · Computer Science 2022-01-03 Gianluca Curzi

We derive a class of multi-species aggregation-diffusion systems from stochastic interacting particle systems via relative entropy method with quantitative bounds. We show an algebraic $L^1$-convergence result using moderately interacting…

Probability · Mathematics 2025-01-07 José Antonio Carrillo , Shuchen Guo , Alexandra Holzinger

We develop a theoretical approach to the protein folding problem based on out-of-equilibrium stochastic dynamics. Within this framework, the computational difficulties related to the existence of large time scale gaps in the protein folding…

Quantitative Methods · Quantitative Biology 2009-11-13 M. Sega , P. Faccioli , F. Pederiva , G. Garberoglio , H. Orland

We establish a novel convergent iteration framework for a weak approximation of general switching diffusion. The key theoretical basis of the proposed approach is a restriction of the maximum number of switching so as to untangle and…

Numerical Analysis · Mathematics 2023-07-06 Qinjing Qiu , Reiichiro Kawai

We establish the existence of a full spectrum of Lyapunov exponents for memoryless random dynamical systems with absorption. To this end, we crucially embed the process conditioned to never being absorbed, the $Q$-process, into the…

Dynamical Systems · Mathematics 2025-08-21 Matheus M. Castro , Dennis Chemnitz , Hugo Chu , Maximilian Engel , Jeroen S. W. Lamb , Martin Rasmussen

Molecular transitions -- such as protein folding, allostery, and membrane transport -- are central to biology yet remain notoriously difficult to simulate. Their intrinsic rarity pushes them beyond reach of standard molecular dynamics,…

The identification of parameters in the Hamiltonian that describes complex many-body quantum systems is generally a very hard task. Recent attention has focused on such problems of Hamiltonian tomography for networks constructed with…

Quantum Physics · Physics 2012-07-13 Koji Maruyama , Daniel Burgarth , Akihito Ishizaki , K. Birgitta Whaley , Takeji Takui

The quantum-classical Liouville equation provides a description of the dynamics of a quantum subsystem coupled to a classical environment. Representing this equation in the mapping basis leads to a continuous description of discrete quantum…

Chemical Physics · Physics 2010-11-17 Ali Nassimi , Sara Bonella , Raymond Kapral

We consider entailment problems involving powerful constraint languages such as guarded existential rules, in which additional semantic restrictions are put on a set of distinguished relations. We consider restricting a relation to be…

Databases · Computer Science 2019-03-21 Antoine Amarilli , Michael Benedikt , Pierre Bourhis , Michael Vanden Boom

We propose a framework for the joint inference of network topology, multi-type interaction kernels, and latent type assignments in heterogeneous interacting particle systems from multi-trajectory data. This learning task is a challenging…

Machine Learning · Statistics 2026-02-05 Quanjun Lang , Xiong Wang , Fei Lu , Mauro Maggioni