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Sorting cells based on their intrinsic properties is a highly desirable objective, since changes in cell deformability are often associated with various stress conditions and diseases. Deterministic lateral displacement (DLD) devices offer…

Fluid Dynamics · Physics 2024-06-03 Zunmin Zhang , Wei Chien , Ewan Henry , Dmitry A. Fedosov , Gerhard Gompper

Sorting algorithms have attracted a great deal of attention and study, as they have numerous applications to Mathematics, Computer Science and related fields. In this thesis, we first deal with the mathematical analysis of the Quicksort…

Data Structures and Algorithms · Computer Science 2015-10-05 Vasileios Iliopoulos

In this paper, we proposed a stochastic model which describes two species of particles moving in counterflow. The model generalizes the theoretical framework describing the transport in random systems since particles can work as mobile…

Soft Condensed Matter · Physics 2017-08-09 Eduardo Velasco Stock , Roberto da Silva , Henrique Almeida Fernandes

We show that directed ratchet transport of a driven overdamped Brownian particle subjected to a spatially periodic and symmetric potential can be reliably controlled by tailoring a biharmonic temporal force, in coherence with the…

Statistical Mechanics · Physics 2015-06-12 Pedro J. Martínez , Ricardo Chacón

We consider Rayleigh particles in a periodically modulated optical trap formed by two counter-propagating Gaussian beams. It is shown that for certain values of parameters the system exhibits transient chaos which manifests itself in…

Chaotic Dynamics · Physics 2025-12-04 E. N. Bulgakov , K. N. Pichugin , D. N. Maksimov

Using the framework of generalized exclusion processes we study mixtures of passive and active particles interacting by steric repulsion. The particles move in a pore with periodically modulated aperture, which is modeled by a…

Statistical Mechanics · Physics 2025-08-14 Frantisek Slanina , Miroslav Kotrla

Motility is a basic feature of living microorganisms, and how it works is often determined by environmental cues. Recent efforts have focused on develop- ing artificial systems that can mimic microorganisms, and in particular their…

This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters.…

Machine Learning · Statistics 2018-06-15 Karol Gellert , Erik Schlögl

We propose a sequential Monte Carlo algorithm for parameter learning when the studied model exhibits random discontinuous jumps in behaviour. To facilitate the learning of high dimensional parameter sets, such as those associated to neural…

Machine Learning · Statistics 2024-12-19 John-Joseph Brady , Yuhui Luo , Wenwu Wang , Víctor Elvira , Yunpeng Li

Molecules with complex internal structure in time-dependent periodic potentials are studied by using short Rubinstein-Duke model polymers as an example. We extend our earlier work on transport in stochastically varying potentials to cover…

Statistical Mechanics · Physics 2015-05-18 Janne Kauttonen , Juha Merikoski

In spite of the widespread use of optical tweezers as a quantitative tool to measure small forces, there exists no unambiguous and simple experimental method for either validating its theoretically predicted form or empirically…

Soft Condensed Matter · Physics 2013-01-25 Deepak Kumar , Shankar Ghosh , S. Bhattacharya

Eukaryotic cells maintain their inner order by a hectic process of distillation of molecular factors taking place on the surface of their lipid membranes. To understand the properties of this molecular sorting process, a physical model of…

Soft Condensed Matter · Physics 2023-08-16 A. Piras , E. Floris , L. Dall'Asta , A. Gamba

We present a mechanism to sort out particles of different masses in an asymmetric channel, where the entropic barriers arise naturally and control the diffusion of these particles. When particles are subjected to an oscillatory force, with…

Soft Condensed Matter · Physics 2021-10-18 Narender Khatri , P. S. Burada

We present local distributed, stochastic algorithms for \emph{alignment} in self-organizing particle systems (SOPS) on two-dimensional lattices, where particles occupy unique sites on the lattice, and particles can make spatial moves to…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-15 Hridesh Kedia , Shunhao Oh , Dana Randall

The transport of Brownian particles in a slit geometry in the presence of an arbitrary two-dimensional periodic energy landscape and driven by an external force or convected by a flow field is investigated by means of macrotransport theory.…

Statistical Mechanics · Physics 2012-10-16 Jorge A. Bernate , German Drazer

The main motivation of this work is the quantitative prediction and description of particle manipulation (displacement across streamlines) in microfluidic flow. Much attention has been paid recently to placing particles in fast oscillatory…

Fluid Dynamics · Physics 2026-03-24 Xuchen Liu

Combining experiments and computer simulations, we use a spatially periodic and flashing light-field to direct the motion of phototactic active colloids. Here, the colloids self-organize into a density spike pattern, which resembles a shock…

Soft Condensed Matter · Physics 2019-05-23 Celia Lozano , Benno Liebchen , Borge ten Hagen , Clemens Bechinger , Hartmut Löwen

Ratcheting surfaces are a common motif in nature and appear in plant awns and grasses. They are known to profer selective advantages for seed dispersion and burial. In two simple model experiments we show that these anisotropically toothed…

Soft Condensed Matter · Physics 2008-06-25 I. M. Kulić , M. Mani , H. Mohrbach , R. Thaokar , L. Mahadevan

We investigate the migration of particles of different geometrical shapes and sizes in a scaled-up model of a gravity-driven deterministic lateral displacement (g-DLD) device. Specifically, particles move through a square array of…

Fluid Dynamics · Physics 2016-05-04 Mingliang Jiang , Kostyantyn Budzan , German Drazer

We investigate sampling laws for particle algorithms and the influence of these laws on the efficiency of particle approximations of marginal likelihoods in hidden Markov models. Among a broad class of candidates we characterize the…

Computation · Statistics 2014-02-21 Nick Whiteley , Anthony Lee