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We demonstrate a data-driven method to solve for the invariant probability density function of a randomly perturbed dynamical system. The key idea is to replace the boundary condition of numerical schemes by a least squares problem…

Numerical Analysis · Mathematics 2019-03-27 Yao Li

Density-dependent diffusion is a widespread phenomenon in nature. We have examined the density-dependent diffusion behavior of some biological processes such as tumor growth and invasion [23]. Here, we extend our previous work by developing…

Statistical Mechanics · Physics 2022-02-14 Ahmed M. Fouad , Marwa M. Fouad

An individual's opinion concerning political bias in the media is shaped by exogenous factors (independent analysis of media outputs) and endogenous factors (social activity, e.g. peer pressure by political allies and opponents in a…

Physics and Society · Physics 2026-03-11 Jarra Horstman , Andrew Melatos , Farhad Farokhi

We study the problem of robust estimation under heterogeneous corruption rates, where each sample may be independently corrupted with a known but non-identical probability. This setting arises naturally in distributed and federated…

Machine Learning · Computer Science 2025-10-02 Syomantak Chaudhuri , Jerry Li , Thomas A. Courtade

We compare the relation between dispersion and dissipation for two random variables that can be used to characterize the precision of a Brownian clock. The first random variable is the current between states. In this case, a certain…

Statistical Mechanics · Physics 2017-08-03 Somrita Ray , Andre C. Barato

A cell dynamical system model for deterministic chaos enables precise quantification of the round-off error growth,i.e., deterministic chaos in digital computer realizations of mathematical models of continuum dynamical systems. The model…

General Physics · Physics 2007-05-23 A. Mary Selvam

We study the transport behavior induced by a small bias voltage through a quantum dot connected to one-channel disordered wires by means of a quantum Monte Carlo method. We model the quantum dot by the Hubbard-Anderson impurity and the…

Strongly Correlated Electrons · Physics 2013-01-01 Alberto Camjayi , Liliana Arrachea

This paper describes a compound Poisson-based random effects structure for modeling zero-inflated data. Data with large proportion of zeros are found in many fields of applied statistics, for example in ecology when trying to model and…

Applications · Statistics 2009-07-29 Marie-Pierre Etienne , Eric Parent , Benoit Hugues , Bernier Jacques

The dynamical behavior for a quantum Brownian particle is investigated under a random potential of the fractional iterative map on a one-dimensional lattice. For our case, the quantum expectation values can be obtained numerically from the…

Statistical Mechanics · Physics 2007-05-23 Kyungsik Kim , Y. S. Kong , M. K. Yum , J. T. Kim

We explore the changes in static structure of a two-dimensional system of active Brownian particles (ABP) with hard-disk interactions, using event-driven Brownian dynamics simulations. In particular, the effect of the self-propulsion…

Statistical Mechanics · Physics 2017-12-27 Nadine de Macedo Biniossek , Hartmut Löwen , Thomas Voigtmann , Frank Smallenburg

We describe a two-dimensional model for active particles whose self-propulsion speed is not fixed, but varies in time, and whose motion is subject to both translational and rotational diffusion. In the conventional treatment of active…

Soft Condensed Matter · Physics 2025-10-01 Tayeb Jamali

A binary string of length $2^k$ induces the Boolean function of $k$ variables whose Shannon expansion is the given binary string. This Boolean function then is representable via a unique reduced ordered binary decision diagram (ROBDD). The…

Information Theory · Computer Science 2011-11-08 J. Kieffer , P. Flajolet , E. -h. Yang

Offline reinforcement learning (RL) enables policy optimization from fixed datasets, making it suitable for safety-critical applications where online exploration is infeasible. However, these datasets are often contaminated by adversarial…

Machine Learning · Computer Science 2026-05-19 Shriram Karpoora Sundara Pandian , Ali Baheri

We study high-dimensional mean estimation in a collaborative setting where data is contributed by $N$ users in batches of size $n$. In this environment, a learner seeks to recover the mean $\mu$ of a true distribution $P$ from a collection…

Machine Learning · Computer Science 2026-02-25 Maryam Aliakbarpour , Vladimir Braverman , Yuhan Liu , Junze Yin

Sticky Brownian motion is the simplest example of a diffusion process that can spend finite time both in the interior of a domain and on its boundary. It arises in various applications such as in biology, materials science, and finance.…

Numerical Analysis · Mathematics 2020-07-21 Nawaf Bou-Rabee , Miranda Holmes-Cerfon

We propose a new algorithm to generate a fractional Brownian motion, with a given Hurst parameter, 1/2<H<1 using the correlated Bernoulli random variables with parameter p; having a certain density. This density is constructed using the…

Computation · Statistics 2019-05-15 Buket Coskun , Ceren Vardar-Acar , Hakan Demirtas

The movement of a particle described by Brownian motion is quantified by a single parameter, $D$, the diffusion constant. The estimation of $D$ from a discrete sequence of noisy observations is a fundamental problem in biological single…

Subcellular Processes · Quantitative Biology 2016-04-13 Peter K. Relich , Mark J. Olah , Patrick J. Cutler , Keith A. Lidke

We model the dynamics of asset prices and associated derivatives by consideration of the dynamics of the conditional probability density process for the value of an asset at some specified time in the future. In the case where the price…

Pricing of Securities · Quantitative Finance 2011-11-14 Damir Filipović , Lane P. Hughston , Andrea Macrina

We propose a cosmological scenario based on the assumption that the Standard Model possesses a large number of copies. It is demonstrated that baryons in the hidden copies of the standard model can naturally account for the dark matter. The…

High Energy Physics - Theory · Physics 2009-08-11 Gia Dvali , Ignacy Sawicki , Alexander Vikman

In the pooled data problem we are given $n$ agents with hidden state bits, either $0$ or $1$. The hidden states are unknown and can be seen as the underlying ground truth $\sigma$. To uncover that ground truth, we are given a querying…

Machine Learning · Computer Science 2023-03-02 Max Hahn-Klimroth , Dominik Kaaser , Malin Rau