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Rajesh Singh

Publications and source records attributed to Rajesh Singh.

At least 19 recordsLinked to original sources

Boundary- and Screening-Induced Bubbly Phases in Autophoretic Active Matter

Spatial confinement and chemical screening fundamentally reshape the non-equilibrium phase behavior of autophoretic active particles. Here, we present a systematic study mapping the collective dynamics of self-propelled particles governed by chemo-attractive translational forces ($\mu_t < 0$) and chemo-repulsive rotational torques ($\mu_r > 0$) across varying screening parameters $\kappa$, torque magnitudes $\mu_r$, and boundary condition coefficients $\Lambda^c$. Beyond standard chemotactic macro-phase separation and dynamic clustering, we report the emergence of novel boundary- and screening-induced bubbly phases, classified into boiling and bursting bubbles. Using a metric triad of steady-state cluster fraction $\langle S \rangle$, temporal fluctuation magnitude $\sigma_S$, and coordination number $\langle Q \rangle$, we draw phase diagrams to demarcate phases for no-flux boundaries ($\Lambda^c = 1$) and chemically permeable interfaces ($\Lambda^c = 0$) . Increasing chemical screening ($\kappa$) systematically suppresses long-range attraction, driving sequential phase transitions from macro-scale collapse toward bubbly states, dynamic micro-clusters, and homogeneous gas phases, while simultaneously inducing aggregate shape anisotropy. These findings provide predictive design rules for controlling active assembly and transport in microfluidic environments.

cond-mat.soft

Mechanics and statistics of a solvable model of an autophoretic colloidal chain

Equilibrium statistical mechanics owes much of its analytical tractability to symmetry: detailed balance, gradient flows, and the resulting vanishing of steady-state entropy production follow directly from the structure of the underlying dynamics, not from any smallness of the driving. Exact solutions of this kind are rare away from equilibrium. Here we identify a class of far-from-equilibrium active colloidal chains -- coupled via roto-translational, autophoretic (monopolar) interactions -- that admit an exact quasi equilibrium description: at fixed chain geometry, the orientational equations of motion for every monomer are derivable from a scalar potential, detailed balance holds exactly in the orientational sector, while the positional sector breaks the equilibrium structure. The associated steady-state entropy production rate (EPR) vanishes identically for this sector, even though the full system is manifestly driven and dissipative. We solve this reduced dynamics exactly for dimers and semi-analytically for general $N$-mers, obtain the orientational fluctuations and the full-system EPR in closed form, and show that all dissipation is carried by the translational (center-of-mass) sector. We further examine the effect of dipolar chemical emission -- expected from asymmetric micelle deposition at the monomer scale -- and find that the equilibrium structure holds exactly for dimers, whereas for longer chains no such description is possible. A purely dipolar coupling instead producesa genuinely non-equilibrium state with no static attractor, sustaining non-monotonic drift with no fixed limit, and an EPR that itself never reaches steady state. Monopolar coupling remains necessary and sufficient for the polarized state; dipolar coupling alone breaks the quasi-equilibrium structure without replacing it with a new static one.

cond-mat.soft

Collective dynamics of chemo-mechanical colloidal chains with active tips

We report a study of the emergent dynamics arising in two-dimensional suspensions of semi-flexible chains whose tip is chemically active, generating a phoretic field. By varying the chain length (number of monomers per chain $N_{pc}$), the area fraction $\phi$, and the sign of the phoretic coupling $J_0$, we map out a rich non-equilibrium phase diagram in the presence of phoretic interactions. For repulsive phoretic interactions ($J_0 > 0$) between the chains, we find that short chains ($N_{pc} = 2$) develop a transient chaotic flow state that crosses over at long times to a global polar flock with super-diffusive mean-squared displacement and long-ranged velocity correlations. Surprisingly, we find this state to have suppressed density fluctuations, indicating the emergence of hyperuniformity. At intermediate chain lengths ($N_{pc} \sim 4$-$8$), the repulsive chemical field drives chaotic mesoscale flows -- a dry route to active turbulence -- without the need for hydrodynamic interactions or steric alignment interactions. For attractive phoretic interactions ($J_0 < 0$), chains self-organise into hedgehog-like micellar aggregates with heads forming the core and flexible tails radiating outward, in structural analogy with amphiphile micellisation but driven entirely by non-equilibrium self-propulsion. A coarse-grained theory of a tip-emitting active rod predicts the onset of the flocking of dimers, though overestimates the presence of polar order for longer chains. Our results establish phoretic tip activity as a minimal, experimentally realisable mechanism for a spectrum of collective states hitherto attributed to hydrodynamic interactions or steric alignment.

cond-mat.soft

Inferring activity from fluid flow in continuum models of active matter

Active matter systems are driven out of thermodynamic equilibrium by localized, microscale energy dissipation. While hydrodynamic continuum frameworks are highly successful at simulating these non-equilibrium phenomena (the forward problem), characterizing real-world active materials is fundamentally bottlenecked by the difficulty of measuring active stresses directly. This paper addresses the inverse problem using deep learning: model inference and model selection from observable flow field data of active fluids. We formulate a generalized hydrodynamic inversion framework applied to two cornerstone paradigms of active continuum physics: Active Model H (representing scalar active matter) and Active Nematics (representing active systems with orientational order). We demonstrate that the kinetic energy spectrum obtained from the fluid flow fields preserve a high-fidelity signature of activity to infer parameters of active model H and active nematics. Our deep learning method presents a principled way to bear upon questions of model inference and selection given the flow field data in continuum models of active matter.

cond-mat.soft

Hydrodynamic Phase Separation and Morphological Evolution in Chiral Active-Passive Mixtures

The collective behavior of passive particles within chiral active matter has emerged as a significant area of soft matter research. However, most existing studies focus on systems where chirality is imposed by external torques rather than intrinsic activity. In this work, we study emergent dynamics in a suspension of active spinners and passive colloids by computing many-body hydrodynamic interactions via Ewald summation. By systematically exploring a broad range of area fractions and rotational velocities, we identify distinct phase-separation regimes sensitive to the system's kinematic parameters. Specifically, we report the emergence of unique structural morphologies, including the formation of passive particle vortices surrounding phase-separated active spinners and the development of large-scale active-passive bands. We characterize the underlying dynamics by analyzing the temporal evolution of characteristic length scales and the non-equilibrium velocity distributions of the passive particles. Our findings provide new insights into the role of long-range hydrodynamic couplings in governing the self-organization of non-equilibrium condensed matter.

cond-mat.soft

Ewald summing irreducible components of flow around active particles

We present a method to compute Ewald summation for the irreducible components of flow around active particles to study hydrodynamic interactions in active colloidal suspensions. An active particle is modeled as a colloidal sphere with a surface slip velocity. Using this model, we obtain an irreducible representation of the fluid flow produced by an active particle in periodic geometry of Stokes flow for an arbitrary surface slip. The solution of the active flow is obtained in terms of lattice sum of the Oseen tensor and their derivatives. The lattice sum is accelerated using the Ewald summation technique. We apply the method to compute explicit expression for rigid body motion of hydrodynamically interacting active particles. Our method presents a way for dynamic simulation of active particles due to arbitrary mode of active slip in periodic geometry of Stokes flow.

cond-mat.soft

Emergent flocking dynamics in chemorepulsive active colloids: interplay of disorder and noise

Recent studies of active colloidal matter have revealed that a global polar order can arise from chemorepulsive interactions among particles without any explicit alignment interaction between them. In this work, we investigate such chemically interacting active colloids in the presence of quenched disorder, where a fraction of particles are randomly pinned in space. These pinned particles are restricted to rotational motion while remaining chemically coupled to the mobile population. In addition, angular noise is incorporated into the rotational dynamics to capture stochastic effects. To elucidate the interplay of quenched disorder and noise, we construct phase diagrams based on polar order and its fluctuations, and systematically analyze the associated disorder- and noise-driven phase transitions. Surprisingly, we find that the phase transition driven by the noise is significantly dependent on the density of the particles, whereas such a density-dependence is not present when the control parameter is the pinning fraction. The finite-size effects on these transitions are also examined. An effective interaction range, governed by the coefficient related to screening of the chemorepulsive interaction, plays a crucial role in collective behavior. When the effective interaction range is much smaller than the system size, the system exhibits density band formation, a feature absent in the long-range interaction regime. Moreover, near the transition point, the order parameter distribution becomes bimodal for the case of short-range interaction.

cond-mat.soft

Principal Component Based Estimation of Finite Population Mean under Multicollinearity

Auxiliary information is frequently utilized in survey sampling to improve the efficiency of estimators of the finite population mean. However, the simultaneous use of multiple auxiliary variables often induces multicollinearity, which adversely affects the stability and performance of conventional estimators. To address this issue, the present study proposes a principal component analysis (PCA) based estimation approach for the finite population mean in the presence of multicollinearity between two auxiliary variables. The proposed methodology transforms the correlated auxiliary variables into a set of orthogonal principal components, thereby removing the effect of multicollinearity while preserving the essential information contained in the auxiliary variables. An efficient estimator is then constructed using these components under simple random sampling without replacement. The bias and mean square error (MSE) of the proposed estimator are derived up to the first order of approximation. The performance of the proposed estimator is evaluated through both empirical and simulation studies under varying correlation structures. Moreover, the presence of multicollinearity is evaluated using variance inflation factors, condition indices, and eigenvalues. The results from empirical and simulation studies demonstrate that the proposed PCA-based estimator outperforms several conventional estimators in terms of MSE and percentage relative efficiency (PRE) when multicollinearity exists, ensuring robust and efficient estimation of the population mean.

stat.ME

Optimal transport and control of an active particle near a plane wall

The control of active colloidal particles via optical traps is a cornerstone for research of matter at the micron and nanometer scale. A central challenge in this domain is the derivation of optimal transport protocols that minimize the mean work required to move a particle over a finite-time interval. Here, we present the Ritz method in which open-loop protocols are constructed from a global basis of Chebyshev polynomials. The protocols are optimized using either a genetic algorithm or a gradient-based method. We apply the method to study optimal transport of an active particle, which is modeled as a force-dipole (or a stresslet) near a no-slip wall. The methodology is validated in the limits of zero activity and infinite wall separation, where it successfully recovers the known analytical protocols and the theoretical minimum work. Crucially, we demonstrate that the presence of the activity breaks the time-reversal symmetry of the optimal protocol found. This symmetry breaking is shown to be a complex function of the transport direction and the particle's intrinsic activity. Because the presented approach requires only the capability to simulate stochastic trajectories, it offers a robust, principled framework for optimizing transport protocols in complex fluid environments that remain inaccessible to exact analytical treatment.

cond-mat.soft

Active phase separation: role of attractive interactions from stalled particles

Dry active matter systems are well-known to exhibit Motility-Induced Phase Separation (MIPS). However, in wet active systems, attractive hydrodynamic interactions mediated by active particles stalled at a boundary can introduce complementary mechanisms for aggregation. In the work of Caciagli et al. (PRL 125, 068001, 2020), it was shown that the attractive hydrodynamic interactions due to active particles stalled at a boundary can be described in terms of an effective potential. In this paper, we present a model of active Brownian particles, where a fraction of active particles are stalled, and thus, mediate inter-particle interactions through the effective potential. Our investigation of the model reveals that a small fraction of stalled particles in the system allows for the formation of dynamical clusters at significantly lower densities than predicted by standard MIPS. We provide a comprehensive phase diagram in terms of weighted average cluster sizes that is mapped in the plane of the fraction of stalled particles ($\alpha$) and the Peclet number. Our findings demonstrate that even a marginal value of $\alpha$ is sufficient to drive phase separation at low global densities, bridging the gap between theoretical models and experimental observations of dilute active systems.

cond-mat.soft

Flocking transition in phoretically interacting active particles with pinning disorder

Recent studies in the collective behavior of active colloids have shown that a global polar order may emerge due to long-ranged chemo-repulsive interactions between them. Here, we report the role of pinning disorder in the flocking transition for such a system. To this end, we study the problem of chemically interacting active colloids with some fraction of the colloids randomly pinned over space such that they can only rotate while phoretically interacting with other particles. Using this model, we investigate the sustenance of global polar order in the presence of quenched spatial disorder. We quantify the flocking transition by studying the global polarization, and the role of finite-size effects. We find that in the crystallite flocking phase, even a small fraction of pinning can destroy spatial crystalline order, although polar order in the form of a liquid phase is maintained. It is observed that polar order is sustained in a system with a higher pinning fraction if the long-ranged repulsive force is subsequently increased. However, in absence of chemo-repulsive forces between particles, polar order drastically decreases even with a smaller pinning fraction. Our work suggests that the flocking transition of active colloids can be controlled via "translationally inert" obstacles, that rotate but do not translate whilst interacting with the bulk.

cond-mat.soft

Intracellular phagosome shell is rigid enough to transfer outside torque to the inner spherical particle

Intracellular phagosomes have a lipid bilayer encapsulated fluidic shell outside the particle, on the outer side of which, molecular motors are attached. An optically trapped spherical birefringent particle phagosome provides an ideal platform to probe fluidity of the shell, as the inner particle is optically confined both in translation and in rotation. Using a recently reported method to calibrate the translation and pitch rotations - yielding a spatial resolution of about 2 nm and angular resolution of 0.1 degrees - we report novel roto-translational coupled dynamics. We also suggest a new technique where we explore the correlation between the translation and pitch rotation to study extent of activity. Given that a spherical birefringent particle phagosome is almost a sphere, the fact that it turns due to the activity of the motors is not obvious, even implying high rigidity of shell. Applying a minimal model for the roto-translational coupling, we further show that this coupling manifests itself as sustained fluxes in phase space, a signature of broken detailed balance.

physics.bio-ph

Minimal mechanism for flocking in phoretically interacting active particles

Coherent collective motion is a widely observed phenomenon in active matter systems. Here, we report a flocking transition mechanism in a system of chemically interacting active colloidal particles sustained purely by chemo-repulsive torques at low to medium densities. The basic requirements to maintain the global polar order are excluded volume repulsions and long-ranged repulsive torques. This mechanism requires that the time scale individual colloids move a unit length to be dominant with respect to the time they deterministically respond to chemical gradients, or equivalently, pair colloids sliding together a minimal unit length before deterministically rotating away from each other. Switching on the translational repulsive forces renders the flock a crystalline structure. Furthermore, liquid flocks are observed for a range of chemo-attractive inter-particle forces. Various properties of these two distinct flocking phases are contrasted and discussed. We complement these results with stability analysis of a hydrodynamic model, which admits the transition corresponding to destabilization of the flocking state observed in particle-based simulations.

cond-mat.soft

Shape-specific fluctuations of an active colloidal interface

Motivated by a recently synthesizable class of active interfaces formed by linked self--propelled colloids, we investigate the dynamics and fluctuations of a phoretically (chemically) interacting active interface with roto--translational coupling. We enumerate all steady--state shapes of the interface across parameter space and identify a regime where the interface acquires a finite curvature, leading to a characteristic ''C--shaped'' topology, along with persistent self--propulsion. In this phase, the interface height fluctuations obey Family--Vicsek scaling but with novel exponents: a dynamic exponent $z_h \approx 0.5$, a roughness exponent $\alpha_h \approx 0.9$ and a super--ballistic growth exponent $\beta_h \approx 1.7$. In contrast, the orientational fluctuations of the colloidal monomers exhibit a negative roughness exponent, reflecting a surprising smoothness law, where steady--state fluctuations diminish with increasing system size. Together, these findings point towards a unique non--equilibrium universality class associated with self--propelled interfaces of non--standard shape.

cond-mat.soft

Autophoretic skating along permeable surfaces

The dynamics of self-propelled colloidal particles are strongly influenced by their environment through hydrodynamic and, in many cases, chemical interactions. We develop a theoretical framework to describe the motion of confined active particles by combining the Lorentz reciprocal theorem with a Galerkin discretisation of surface fields, yielding an equation of motion that efficiently captures self-propulsion without requiring an explicit solution for the bulk fluid flow. Applying this framework, we identify and characterise the long-time behaviours of a Janus particle near rigid, permeable, and fluid-fluid interfaces, revealing distinct motility regimes, including surface-bound skating, stable hovering, and chemo-hydrodynamic reflection. Our results demonstrate how the solute permeability and the viscosity contrast of the surface influence a particle's dynamics, providing valuable insights into experimentally relevant guidance mechanisms for autophoretic particles. The computational efficiency of our method makes it particularly well-suited for systematic parameter sweeps, offering a powerful tool for mapping the phase space of confined active particles and informing high-fidelity numerical simulations.

physics.flu-dyn

Inferring activity from the flow field around active colloidal particles using deep learning

Active colloidal particles create flow around them due to non-equilibrium process on their surfaces. In this paper, we infer the activity of such colloidal particles from the flow field created by them via deep learning. We first explain our method for one active particle, inferring the $2s$ mode (or the stresslet) and the $3t$ mode (or the source dipole) from the flow field data, along with the position and orientation of the particle. We then apply the method to a system of many active particles. We find excellent agreements between the predictions and the true values of activity. Our method presents a principled way to predict arbitrary activity from the flow field created by active particles.

cond-mat.soft

SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training

Existing text-to-image (T2I) diffusion models face several limitations, including large model sizes, slow runtime, and low-quality generation on mobile devices. This paper aims to address all of these challenges by developing an extremely small and fast T2I model that generates high-resolution and high-quality images on mobile platforms. We propose several techniques to achieve this goal. First, we systematically examine the design choices of the network architecture to reduce model parameters and latency, while ensuring high-quality generation. Second, to further improve generation quality, we employ cross-architecture knowledge distillation from a much larger model, using a multi-level approach to guide the training of our model from scratch. Third, we enable a few-step generation by integrating adversarial guidance with knowledge distillation. For the first time, our model SnapGen, demonstrates the generation of 1024x1024 px images on a mobile device around 1.4 seconds. On ImageNet-1K, our model, with only 372M parameters, achieves an FID of 2.06 for 256x256 px generation. On T2I benchmarks (i.e., GenEval and DPG-Bench), our model with merely 379M parameters, surpasses large-scale models with billions of parameters at a significantly smaller size (e.g., 7x smaller than SDXL, 14x smaller than IF-XL).

cs.CV

Fluctuating hydrodynamics of an autophoretic particle near a permeable interface

We study the autophoretic motion of a spherical active particle interacting chemically and hydrodynamically with its fluctuating environment in the limit of rapid diffusion and slow viscous flow. Then, the chemical and hydrodynamic fields can be expressed in terms of integrals. The resulting boundary-domain integral equations provide a direct way of obtaining the traction on the particle, requiring the solution of linear integral equations. An exact solution for the chemical and hydrodynamic problems is obtained for a particle in an unbounded domain. For motion near boundaries, we provide corrections to the unbounded solutions in terms of chemical and hydrodynamic Green's functions, preserving the dissipative nature of autophoresis in a viscous fluid for all physical configurations. Using this, we give the fully stochastic update equations for the Brownian trajectory of an autophoretic particle in a complex environment. First, we analyse the Brownian dynamics of particles capable of complex motion in the bulk. We then introduce a chemically permeable planar surface of two immiscible liquids in the vicinity of the particle and provide explicit solutions to the chemo-hydrodynamics of this system. Finally, we study the case of an isotropically phoretic particle hovering above an interface as a function of interfacial solute permeability and viscosity contrast.

cond-mat.soft