arXiv subjects

Biswajit Maji

Publications and source records attributed to Biswajit Maji.

5 recordsLinked to original sources

arXiv2026

How well can Diffusion Models learn Lagrangian-Tracer Statistics in Non-reciprocal Turbulence?

Recent advances in generative artificial intelligence have led to significant potential applications in conventional fluid flows, including those that are turbulent. Can these methods be carried over to studies of novel types of turbulence, such as turbulence induced by non-reciprocity in binary-fluid systems? To answer this question, we analyze the statistics of Lagrangian-tracer particles in non-reciprocal binary-fluid turbulence, which has been studied recently in the non-reciprocal Cahn-Hilliard-Navier-Stokes (NRCHNS). We obtain our ground-truth data via extensive pseudospectral direct numerical simulations (DNSs) of the two-dimensionsl (2D) NRCHNS model. Our study yields a variety of intriguing results for probability distribution functions (PDFs) for particle accelerations and velocity-component PDFs; the latter turn out to be bimodal, completely unlike their 2D-fluid-turbulence counterparts. We relate this bimodality to lane-type structures in Eulerian-velocity components. Furthermore, we characterize Lagrangian multiscaling via Lagrangian velocity increments, their structure functions and flatnesses, and multiscaling exponent ratios, for the first time in non-reciprocal hydrodynamics. Finally, we use generative diffusion models to obtain synthetic Lagrangian trajectories for the NRCHNS system, assess how effectively they can emulate the Lagrangian statistics that we obtain from our DNSs, and highlight open challenges in the application of generative artificial intelligence in non-reciprocal systems.

physics.flu-dyn↗

arXiv2026

First observation of turbulence-like state in dense algal suspensions

Active turbulence arises typically in systems ranging from microorganisms and biopolymers to synthetic colloids, where chaotic flows are closely associated with motile topological defects in collectively swarming suspensions. Here, we report the first experimental observation of turbulence-like dynamics in a fundamentally different class of systems: dense monolayers of motile unicellular alga Chlamydomonas reinhardtii that exhibit neither orientational order nor topological defects. Nevertheless, the system displays rich spatiotemporal flow patterns with pronounced small-scale intermittency. We uncover strongly non-Gaussian velocity distribution, a feature distinct from both bacterial and classical fluid turbulence. Furthermore, we observe power-law regimes in the kinetic energy spectra, characterized by unique scaling exponents. Not only do our results provide compelling evidence for active spatiotemporal chaos in systems devoid of nematic or polar structures, but they also challenge current theoretical models. Our work opens new avenues for understanding emergent dynamics in active-matter systems and suggests intriguing biological implications, including enhanced mixing and transport in dense cell suspensions.

cond-mat.soft↗

arXiv2026

Non-reciprocal Binary-fluid Turbulence

Although effective non-reciprocal interactions have been investigated in a variety of fields, their consequences have not been explored in hydrodynamical turbulence. We initiate such an exploration by introducing non-reciprocal binary-fluid tubulence and uncover its properties by developing a two-dimensional (2D) Non-Reciprocal Cahn-Hilliard-Navier-Stokes (NRCHNS) model. We show that, as we increase the strength of the non-reciprocal terms, this model displays a hitherto unanticipated type of turbulence, with an inverse cascade of energy and an energy spectrum $E(k)\sim k^{-5/3}$, reminiscent of the well-known inverse cascade in forced, 2D fluid turbulence, but distinct from it, in so far as it develops a non-reciprocal flux $\mathbf J$. We demonstrate how NRCHNS turbulence suppresses $J(t) = |\mathbf J|$, as the Reynolds number increases. We compare and contrast 2D NRCHNS turbulence with its fluid-turbulence counterpart by examining spectra, fluxes, spectral balances, flow topologies, and signatures of multifractality.

physics.flu-dyn↗

arXiv2025

Vortex triplets, symmetry breaking, and emergent nonequilibrium plastic crystals in an active-spinner fluid

The formation of patterns and exotic nonequilibrium steady states in active-fluid systems continues to pose challenging problems -- theoretical, numerical, and experimental -- for statistical physicists and fluid dynamicists. We combine theoretical ideas from statistical mechanics and fluid mechanics to uncover a new type of self-assembled crystal of vortex triplets in an active-spinner fluid. We begin with the two-dimensional Cahn-Hilliard-Navier-Stokes (CHNS) model for a binary-fluid system of active rotors that has two important ingredients: a scalar order parameter field phi that distinguishes regions with clockwise (CW) and counter-clockwise (CCW) spinners; and an incompressible velocity field u. In addition to the conventional CHNS coupling between phi and u, this model has a torque-induced activity term, with coefficient tau, whose consequences we explore. We demonstrate that, if we increase the activity tau, it overcomes dissipation and this system displays a hitherto unanticipated emergent triangular crystal, with spinning vortex triplets at its vertices. We show that this is a nonequilibrium counterpart of an equilibrium plastic crystal. We characterise the statistical properties of this novel crystal and suggest possible experimental realisations of this new state of active matter.

cond-mat.soft↗

arXiv2025

Emergent turbulence and coarsening arrest in active-spinner fluids

We uncover activity-driven crossover from phase separation to a new turbulent state in a two-dimensional system of counter-rotating spinners. We study the statistical properties of this active-rotor turbulence using the active-rotor Cahn-Hilliard-Navier-Stokes model, and show that the vorticity $ω\propto ϕ$, the scalar field that distinguishes regions with different rotating states. We explain this intriguing proportionality theoretically, and we characterize power-law energy and concentration spectra, intermittency, and flow-topology statistics. We suggest biological implications of such turbulence.

physics.flu-dyn↗