arXiv subjects

Aritra K. Mukhopadhyay

Publications and source records attributed to Aritra K. Mukhopadhyay.

16 recordsLinked to original sources

arXiv2026

Learning Effective Hydro-Phoretic Interactions in Active Matter

In the quest to understand large-scale collective behavior in active matter, the complexity of hydrodynamic and phoretic interactions remains a fundamental challenge. To date, most works either focus on minimal models that do not (fully) account for these interactions, or explore relatively small systems. The present work develops a generic method that combines high-fidelity simulations with symmetry-preserving descriptors and neural networks to predict hydro-phoretic interactions directly from particle coordinates (effective interactions). This method enables, for the first time, self-contained particle-only simulations and theories with full hydro-phoretic two-body interactions.

cond-mat.soft↗

arXiv2026

Quantum-enabled active matter at the atomic scale

Active matter comprises particles that extract energy from their local environment and convert it into motion. Although active particles have been miniaturized down to the nanoscale, realizing activity at the fundamentally smaller scale of individual atoms remains an open challenge, where quantum effects become increasingly relevant. Here, we experimentally demonstrate that individual Cs-133 atoms confined in an optical dipole trap extract energy from an ultracold bath of Rb-87 atoms via quantum-mechanical spin interactions and convert it into active motion. We quantitatively reproduce the resulting dynamics using a parameter-free active Langevin model derived from kinetic theory and support it with event-driven Monte Carlo collision simulations. The microscopic origin of activity is identified as quantum spin exchange, which transfers discrete internal spin energy into kinetic motion. Our work establishes a quantum-enabled route to active matter at the fundamental size limit of single atoms and opens perspectives for exploring the interplay of activity, quantum physics, and mesoscopic non-equilibrium thermodynamics.

quant-ph↗

arXiv2026

Learning microstructure in active matter

Understanding microstructure in terms of closed-form expressions is an open challenge in nonequilibrium statistical physics. We propose a simple and generic method that combines particle-resolved simulations, deep neural networks and symbolic regression to predict the pair-correlation function of passive and active particles. Our analytical closed-form results closely agree with Brownian dynamics simulations, even at relatively large packing fractions and for strong activity. The proposed method is broadly applicable, computationally efficient, and can be used to enhance the predictive power of nonequilibrium continuum theories and for designing pattern formation.

cond-mat.soft↗

arXiv2026

Automated decision-making by chemical echolocation in active droplets

Motile microorganisms, like bacteria and algae, unify abilities like self-propulsion, autonomous navigation, and decision-making on the micron scale. While recent breakthroughs have led to the creation of synthetic microswimmers and nanoagents that can also self-propel, they still lack the functionality and sophistication of their biological counterparts. This study pioneers a mechanism enabling synthetic agents to autonomously navigate and make decisions, allowing them to solve mazes and transport cargo through complex environments without requiring external cues or guidance. The mechanism exploits chemo-hydrodynamic signals, produced by agents like active droplets or colloids, to remotely sense and respond to their environment - similar to echolocation. Our research paves the way for endowing autonomous, motile synthetic agents with functionalities that have been so far exclusive to biological organisms.

cond-mat.soft↗

arXiv2024

AMEP: The Active Matter Evaluation Package for Python

The Active Matter Evaluation Package (AMEP) is a Python library for analyzing simulation data of particle-based and continuum simulations. It provides a powerful and simple interface for handling large data sets and for calculating and visualizing a broad variety of observables that are relevant to active matter systems. Examples range from the mean-square displacement and the structure factor to cluster-size distributions, binder cumulants, and growth exponents. AMEP is written in pure Python and is based on powerful libraries such as NumPy, SciPy, Matplotlib, and scikit-image. Computationally expensive methods are parallelized and optimized to run efficiently on workstations, laptops, and high-performance computing architectures, and an HDF5-based data format is used in the backend to store and handle simulation data as well as analysis results. AMEP provides the first comprehensive framework for analyzing simulation results of both particle-based and continuum simulations (as well as experimental data) of active matter systems. In particular, AMEP also allows it to analyze simulations that combine particle-based and continuum techniques such as used to study the motion of bacteria in chemical fields or for modeling particle motion in a flow field. AMEP is available at https://amepproject.de and can be installed via conda and pip.

cond-mat.soft↗

arXiv2024

Active adaptolates: motility-induced percolating structures with an adaptive packing geometry

It is well known that periodic potentials can be used to induce freezing and melting in colloids. Here, we transfer this concept to active systems and find the emergence of a so-far unknown active matter phase in between the frozen solid-like phase and the molten phase. This phase of "active adaptolates" adopts the geometry of the underlying lattice like the frozen phase, maintains ballistic dynamics like the molten phase, and percolates. In particular, this finding creates a route to use external fields for designing the intrinsic structure of active systems without qualitatively affecting their dynamics.

cond-mat.soft↗

arXiv2023

Self-solidifying active droplets showing memory-induced chirality

Most synthetic microswimmers do not reach the autonomy of their biological counterparts in terms of energy supply and diversity of motion. Here we report the first all-aqueous droplet swimmer powered by self-generated polyelectrolyte gradients, which shows memory-induced chirality while self-solidifying. An aqueous solution of surface tension-lowering polyelectrolytes self-solidifies on the surface of acidic water, during which polyelectrolytes are gradually emitted into the surrounding water and induce linear self-propulsion via spontaneous symmetry breaking. The low diffusion coefficient of the polyelectrolytes leads to long-lived chemical trails which cause memory effects that drive a transition from linear to chiral motion without requiring any imposed symmetry breaking. The droplet swimmer is capable of highly efficient removal (up to 85%) of uranium from aqueous solutions within 90 min, benefiting from self-propulsion and flow-induced mixing. Our results provide a route to fueling self-propelled agents which can autonomously perform chiral motion and collect toxins.

cond-mat.soft↗

arXiv2021

Interactions in Active Colloids

The past two decades have seen a remarkable progress in the development of synthetic colloidal agents which are capable of creating directed motion in an unbiased environment at the microscale. These self-propelling particles are often praised for their enormous potential to self-organize into dynamic nonequilibrium structures such as living clusters, synchronized super-rotor structures or self-propelling molecules featuring a complexity which is rarely found outside of the living world. However, the precise mechanisms underlying the formation and dynamics of many of these structures are still barely understood, which is likely to hinge on the gaps in our understanding of how active colloids interact. In particular, besides showing comparatively short-ranged interactions which are well known from passive colloids (Van der Waals, electrostatic etc.), active colloids show novel hydrodynamic interactions as well as phoretic and substrate-mediated "osmotic" cross-interactions which hinge on the action of the phoretic field gradients which are induced by the colloids on other colloids in the system. The present article discusses the complexity and the intriguing properties of these interactions which in general are long-ranged, non-instantaneous, non-pairwise and non-reciprocal and which may serve as key ingredients for the design of future nonequilibrium colloidal materials. Besides providing a brief overview on the state of the art of our understanding of these interactions a key aim of this review is to emphasize open key questions and corresponding open challenges.

cond-mat.soft↗

arXiv2020

Asymptotic population imbalance of an ultracold bosonic ensemble in a driven double-well

We demonstrate that an ultracold many-body bosonic ensemble confined in an one-dimensional (1D) double well potential exhibits a population imbalance between the two wells at large timescales, when the depth of the wells are modulated by a time-dependent driving force. The specific form of the driving force is shown to break spatial parity and time-reversal symmetries, which leads to such an asymptotic population imbalance (API). The value of the API can be flexibly controlled by changing the phase of the driving force and the total number of particles. While the API is highly sensitive to the initial state in the few-particle regime, this dependence on the initial state is lost as we approach the classical limit of large particle numbers. We perform a Floquet analysis in the few-particle regime and an analysis based on a driven classical non-rigid pendulum in the many-particle regime. Although the obtained API values in the many-particle regime agree very well with that obtained in the classical limit, we show that there exists a significant disagreement in the corresponding real-time population imbalance due to quantum correlations.

quant-ph↗

arXiv2020

Controlling vortical motion of particles in two-dimensional driven superlattices

We demonstrate the control of vortical motion of neutral classical particles in driven superlattices. Our superlattice consists of a superposition of individual lattices whose potential depths are modulated periodically in time but with different phases. This driving scheme breaks the spatial reflection symmetries and allows an ensemble of particles to rotate with an average angular velocity. An analysis of the underlying dynamical attractors provides an efficient method to control the angular velocities of the particles by changing the driving amplitude. As a result, spatially periodic patterns of particles showing different vortical motion can be created. Possible experimental realizations include holographic optical lattice based setups for colloids or cold atoms.

nlin.CD↗

arXiv2020

Multiple current reversals using superimposed driven lattices

We demonstrate that directed transport of particles in a two dimensional driven lattice can be dynamically reversed multiple times by superimposing additional spatially localized lattices on top of a background lattice. The timescales of such current reversals can be flexibly controlled by adjusting the spatial locations of the superimposed lattices. The key principle behind the current reversals is the conversion of the particle dynamics from chaotic to ballistic, which allow the particles to explore regions of the underlying phase space which are inaccessible otherwise. Our results can be experimentally realized using cold atoms in driven optical lattices and allow for the control of transport of atomic ensembles in such setups.

cond-mat.stat-mech↗

arXiv2019

Controlling transport of underdamped particles in two-dimensional driven Bravais lattices

We demonstrate the directed transport of underdamped particles in two dimensional lattices of arbitrary geometry driven by an unbiased ac-driving force. The direction of transport can be controlled via the lattice geometry as well as the strength and orientation of the oscillating drive. The breaking of the spatial inversion symmetry, which is necessary for the emergence of directed transport, is achieved solely due to the structure and geometry of the lattice. The most important criterion determining the transport direction is shown to be the ballistic attractors underlying the phase space of our weakly dissipative non-linear dynamical system. This allows the prediction of transport direction even for setups like driven oblique lattices where the standard symmetry arguments of transport control fail. Our results can be experimentally realized using holographic optical lattice based setups with colloids or cold atoms.

cond-mat.stat-mech↗

arXiv2018

Dimensional coupling induced current reversal in two-dimensional driven lattices

We show that the direction of directed particle transport in a two dimensional ac-driven lattice can be dynamically reversed by changing the structure of the lattice in the direction perpendicular to the applied driving force. These structural changes introduce dimensional coupling effects, the strength of which governs the timescale of the current reversals. The underlying mechanism is based on the fact that dimensional coupling allows the particles to explore regions of phase space which are inaccessible otherwise. The experimental realization for cold atoms in ac-driven optical lattices is discussed.

cond-mat.quant-gas↗

arXiv2017

Simultaneous control of multi-species particle transport and segregation in driven lattices

We provide a generic scheme to separate the particles of a mixture by their physical properties like mass, friction or size. The scheme employs a periodically shaken two dimensional dissipative lattice and hinges on a simultaneous transport of particles in species-specific directions. This selective transport is achieved by controlling the late-time nonlinear particle dynamics, via the attractors embedded in the phase space and their bifurcations. To illustrate the spectrum of possible applications of the scheme, we exemplarily demonstrate the separation of polydisperse colloids and mixtures of cold thermal alkali atoms in optical lattices.

nlin.CD↗

arXiv2016

Freezing, accelerating and slowing directed currents in real time with superimposed driven lattices

We provide a generic scheme offering real time control of directed particle transport in superimposed driven lattices. This scheme allows to accelerate, slow and freeze the transport on demand, by switching one of the lattices subsequently on and off. The underlying physical mechanism hinges on a systematic opening and closing of channels between transporting and non-transporting phase space structures upon switching, and exploits cantori structures which generate memory effects in the population of these structures. Our results should allow for real time control of cold thermal atomic ensembles in optical lattices, but might also be useful as a design principle for targeted delivery of molecules or colloids in optical devices.

nlin.CD↗

arXiv2014

Rogue solitons in Heisenberg spin chain

Following the connection of the non-linear Schrödinger equation with the continuum Heisenberg spin chain, we find the rogue soliton equivalent in the spin system. The breathers are also mapped to the corresponding space or time localized oscillatory modes, through the moving curve analogy. The spatio-temporal evolution of the curvature and torsion of the curve, underlying these dynamical systems, are explicated to illustrate the localization property of the rogue waves.

nlin.PS↗