Wednesday, 23 April 2025
I will summarize some recent results on systems of dipole-conserving point particles, 'fractons'. These exhibit non-equilibrium dynamics characterized by attractors, that cannot be characterized by Gibbsean statistical mechanics. Fracton dynamics generically possess a 'Janus pont' of low complexity around which a bidirectional arrow of time naturally obtains. Its Boltzmann entropy is unbounded and thus the dynamics evades 'heat death' at late times, suggesting a surprisingly clean resolution of the arrow-of-time paradox in non-equilibrium dynamics.
In this talk, I present numerical results from a comprehensive Monte Carlo study in two dimensions of coarsening kinetics in the Coulomb glass (CG) model on a square lattice. The CG model is characterized by spin-spin interactions which are long-range Coulombic and antiferromagnetic. For the nonequilibrium properties we have studied spatial correlation functions and domain growth laws. At half filling and small disorders, we find that domain growth in the CG is analogous to that in the nearest-neighbor random-field Ising model. The domain length scale L(t ) shows a crossover from a regime of “power-law growth with a disorder-dependent exponent” [L(t ) ∼ t 1/z̄ ] to a regime of “logarithmic growth with a universal exponent” [L(t ) ∼ (ln t ) 1/ψ ]. We next look at the results for the asymmetric CG (slightly away from half filling) at zero disorder, where the ground state is checkerboard-like with excess holes distributed uniformly. We find that the evolution morphology is in the same dynamical universality class as the ordering ferromagnet. Further, the domain growth law is slightly slower than the Lifshitz-Cahn-Allen law, L(t ) ∼ t 1/2 , i.e., the growth exponent is underestimated. We speculate that this could be a signature of logarithmic growth in the asymptotic regime.
We consider a set of hardcore run and tumble particles on a 1d periodic lattice. The effect of external potential has been modeled as a special site where the tumbling probability is much larger than the rest of the system. We call it a ‘defect’ site and move its location along the ring lattice with speed u. When bulk tumbling rate is zero, in absence of any defect the system goes to a jammed state with no long range order. But introduction of the moving defect creates a strongly phase separated state where almost all active particles are present in a single large cluster, for small and moderate u. This striking effect is caused by the long-ranged velocity correlation of the active particles, induced by the moving defect. For large u, a single large cluster is no longer stable and breaks into multiple smaller clusters. When bulk tumbling rate is non-zero, a competition develops between the time-scales associated with tumbling and defect motion. While the moving defect attempts to create long ranged velocity order, bulk tumbling tends to randomize the velocity alignment. If the bulk tumbling rate is small enough such that relatively small number of tumbles take place during the time the moving defect travels through the entire system, the defect has enough time to restore the order in the system and our simulations show that the long range order in velocity and density survive. For larger tumbling rate, long range order is destroyed and the system develops multiple regions of high density and low density regions. We also propose possible experimental setup where our results can be verified.
When do mucus films plug lung airways? Using reduced-order simulations of a large ensemble of randomly perturbed films, we show that the answer is not determined by just the film’s volume. While very thin films always stay open and very thick films always plug, we find a range of intermediate films for which plugging is uncertain. The fastest-growing linear mode of the Rayleigh-Plateau instability ensures that the film’s volume is divided among multiple humps. However, the nonlinear growth of these humps can occur unevenly, due to spontaneous axial sliding—a lucky hump can sweep up a disproportionate share of the film’s volume and so form a plug. This sliding-induced plugging is robust and prevails with or without gravitational and ciliary transport.
In this talk, I will present findings from our recent work (Phys. Rev. B 108, 024203 (2023)), where we propose a Monte Carlo simulation to understand electron transport in a non-equilibrium steady state (NESS) for the lattice Coulomb Glass model, created by continuous excitation of single electrons to high energies followed by relaxation of the system. Around the Fermi level, the NESS state roughly obeys the Fermi-Dirac statistics, with an effective temperature (Teff) greater than the bath temperature of the system (T). Teff is a function of T and the rate of photon absorption by the system. Furthermore, we find that the change in conductivity is only a function of relaxation times and is almost independent of the bath temperature. Our results indicate that the conductivity of the NESS state can still be characterized by the Efros-Shklovskii law with an effective temperature of Teff > T. Additionally, the dominance of phononless hopping over phonon-assisted hopping is used to explain the hot electron model's relevance to the conductivity of the NESS state.
Glassy systems are ubiquitous in nature, appearing in materials ranging from window glass to biological matter. These systems are non-crystalline solids that structurally resemble liquids but exhibit extremely slow dynamics. In this talk, I will focus on a particular class of glassy materials known as topological glass formers—systems composed of ring polymers. We investigate how aging influences the dynamics of these systems and explore how their behavior changes across the temperature–stiffness phase space. Interestingly, we find a nonlinear relationship between the glass transition temperature and the stiffness of the rings. A central role is played by threading interactions—entanglement-like constraints unique to ring polymers, which become increasingly long-lived as the system ages. Together, these features give rise to a distinct form of glassy dynamics that emerges purely from the system’s topology.
Despite numerous works on the many-body localization (MBL) transition in quasiperiodic chains, the mid-spectrum behavior of correlation functions remains unexplored. Starting with the spin-spin correlation functions in a quasiperiodic XX model, we will discuss their behavior in the XXZ counterpart. Notably, we will identify various features in the disorder-interaction plane through standard observables as well as the correlation functions, and show the longitudinal correlation to be the key player which exhibits some non-trivial features across the whole phase diagram.
Statistical physics deals with the large amount of heterogeneous population, nonequilibrium systems and have facilitated the studies of complex systems dynamics. Now with the help of volumes of data available it is possible to understand the dynamical processes ongoing on complex systems through nonlinearity, feedback loops, emergence and in some instances critical transitions via data driven approaches, computational modeling and complex networks. In addition to this there are wicked problems, characterized by their complexity and interconnectedness. These are referred to as social, economical, environmental or cultural issues that defy simple solutions due to their inherent ambiguity, multiple variable interactions and lack of a clear convergent solution. The complex systems approach provides a framework for understanding and addressing such problems by emphasizing interconnectedness and feedback loops, which can help to identify and mitigate unintended consequences of policy interventions. Wicked problems involve multiple, interconnected factors, making it difficult to pinpoint through single cause or effect. Complex systems thinking involves interconnectedness of various factors and actors, helping to understand how different elements influence each other & drives the feedback loops and recognizing how actions and interventions can lead to unintended consequences through feedback loops and path dependencies which is crucial for detailed understanding and effective policy design. In this talk I will discuss some wicked problems and their complexity inspired solutions.
Keywords: Interaction, Interconnectedness, Complex networks, Random Matrices, Ecological Flourishing
In this work, I explore the topological features of aggregation patterns in the Vicsek Model, a widely used framework for describing the collective dynamics of active matter. By varying the three key parameters—population size N, interaction radius R, and noise η, different point sets of self- organising agents are generated. To analyse the emergent structures, I employ topological tools, namely the Euler characteristic and Betti numbers, in both spatial and temporal domains. The Euler characteristic, a fundamental topological invariant, provides insights into system connectivity, while Betti numbers characterise features such as connected components, loops, and voids. Three-dimensional Euler Characteristic Surfaces (ECS) are constructed that carry the summary of the spatio-temporal evolution of the Euler Characteristic. Further, a metric distance, which we name the Euler Metric (EM), is estimated between these surfaces to investigate how system parameters influence aggregation dynamics. Additionally, I analyse order parameters to distinguish between ordered and chaotic regimes, further contextualising the topological findings.
We present results of construction of the ground states of a paradigmatic strongly interacting quantum system namely the square lattice quantum dimer model as a group equivariant convolutional neural network variational state. The network is trained by minimizing, using stochastic gradient descent, the Monte Carlo estimated energy expectation value. We show comparison with exact diagonalization for small systems (size = 8x8) and with quantum Monte Carlo for larger systems up to 48x48.
Integral geometry uses four geometric invariants—the Minkowski functionals—to characterize certain subsets of three-dimensional (3D) space. The question was, how is the fluid flow in a 3D porous system related to these invariants? In this work, we systematically study the dependency of permeability on the geometrical characteristics of two categories of 3D porous systems generated: (i) stochastic and (ii) deterministic. For the stochastic systems, we investigated both normal and lognormal size distribution of grains. For the deterministic porous systems, we checked for a cubic arrangement and a hexagonal arrangement of grains of equal size. Our studies reveal that for any three-dimensional porous system, ordered or disordered, permeability k follows a unique scaling relation with the Minkowski functionals: (a) volume of the pore space, (b) integral mean curvature, (c) Euler characteristic, and (d) critical cross-sectional area of the pore space. The cubic and the hexagonal symmetrical systems formed the upper and lower bounds of the scaling relations, respectively. The disordered systems lay between these bounds. Moreover, we propose a combinatoric F that weaves together the four Minkowski functionals and follows a power-law scaling with permeability. The scaling exponent is independent of particle size and distribution and has a universal value of 0.43 for 3D porous systems built of spherical grains.
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 vor- ticity ω ∝ ϕ, the scalar field that distinguishes regions with different rotating states. We explain this intriguing proportionality theoretically, and we characterize power-law energy and concentra- tion spectra, intermittency, and flow-topology statistics. We suggest biological implications of such turbulence. This work has been done with Biswajit Maji and Nadia Bihari Padhan. https://arxiv.org/abs/2503.03843
Hard-core lattice-gas models serve as minimal yet powerful models to explore entropy-driven phase transitions. In these models, particles are restricted from occupying neighboring sites up to a specified kth next-nearest neighbor, effectively bridging the behavior from simple nearest-neighbor exclusion to the continuum hard-sphere gas. While most prior studies have examined cases up to k = 3, this talk presents a detailed investigation of the lattice-gas model on a triangular lattice up to k = 7, using a rejection free flat histogram algorithm enhanced with cluster moves. Our findings reveal that for k = 3 to k = 7, the system exhibits a single, discontinuous phase transition from a low-density disordered fluid to a high-density sublattice-ordered phase. This conclusion is supported by the analysis of partition function zeros and the nonconvexity of entropy.
We study the dynamics of an athermal inertial active particle moving in a shear-thinning medium in $d=1$. The viscosity of the medium is modeled using a Coulomb-tanh function, while the activity is represented by an asymmetric dichotomous noise with strengths $-\Delta$ and $\mu\Delta$, transitioning between these states at a rate $\lambda$. Starting from the Fokker-Planck~(FP) equation for the time-dependent probability distributions $P(v,-\Delta,t)$ and $P(v,\mu\Delta,t)$ of the particle's velocity $v$ at time $t$, moving under the influence of active forces $-\Delta$ and $\mu\Delta$ respectively, we analytically derive the steady-state velocity distribution function $P_s(v)$, explicitly dependent on $\mu$. Also, we obtain a quadrature expression for the effective diffusion coefficient $D_e$ for the symmetric active force case~($\mu=1$). For a given $\Delta$ and $\mu$, we show that $P_s(v)$ exhibits multiple transitions as $\lambda$ is varied. Subsequently, we numerically compute $P_s(v)$, the mean-squared velocity $\langle v^2\rangle(t)$, and the diffusion coefficient $D_e$ by solving the particle's equation of motion, all of which show excellent agreement with the analytical results in the steady-state. Finally, we examine the universal nature of the transitions in $P_s(v)$ by considering an alternative functional form of medium's viscosity that also capture the shear-thinning behavior.
Small systems consisting of a few particles are increasingly technologically relevant. In such systems, an intense debate in microcanonical statistical mechanics has been about the correctness of Boltzmann’s surface entropy versus Gibbs’ volume entropy. While the former considers states within a fixed energy window centered around the energy of the system, the latter considers all states with energy lesser than or equal to the energy of the system. Both entropies have shortcomings─while Boltzmann entropy predicts unphysical negative/infinite absolute temperatures for small systems with an unbounded energy spectrum, Gibbs entropy entirely disallows negative absolute temperatures, in disagreement with experiments. We consider a relative energy window, motivated by the Heisenberg energy-time uncertainty principle and an eigenstate thermalization time inversely proportional to the system energy. The resulting entropy ensures positive, finite temperatures for systems without a maximum limit on their energy and allows negative absolute temperatures in bounded energy spectrum systems, e.g., with population inversion. It also closely matches canonical ensemble predictions for prototypical systems, for instance, correctly describing the zero-point energy of an isolated quantum harmonic oscillator. Overall, we enable accurate thermodynamic models for isolated systems with few degrees of freedom.
We introduce a rejection-free, flat histogram, cluster algorithm to determine the density of states of hardcore lattice gases. We show that the algorithm is able to efficiently sample low entropy states that are usually difficult to access, even when the excluded volume per particle is large. The algorithm is based on simultaneously evaporating all the particles in a strip and reoccupying these sites with a new appropriately chosen configuration. We implement the algorithm for the particular case of the hard-core lattice gas in which the first k next-nearest neighbors of a particle are excluded from being occupied. It is shown that the algorithm is able to reproduce the known results for k = 1, 2, 3 both on the square and cubic lattices. We also show that, in comparison, the corresponding flat histogram algorithms with either local moves or unbiased cluster moves are less accurate and do not converge as the system size increases.
Exact solutions for excited states in non-integrable quantum Hamiltonians have revealed novel dynamical phenomena that can occur in quantum many-body systems. This work proposes a method to analytically construct a specific set of volume-law-entangled exact excited eigenstates in a large class of spin Hamiltonians. In particular, we show that all spin chains that satisfy a simple set of conditions host exact volume-law eigenstates in the middle of their spectra. Examples of physically relevant spin chains of this type include the transverse-field Ising model, PXP model, spin-S XY model, and spin-S Kitaev chain. Although these eigenstates are highly atypical in their structure, they are thermal with respect to local observables. Our framework also unifies many recent constructions of volume-law entangled eigenstates in the literature. Finally, we show that a similar construction also generalizes to spin models on graphs in arbitrary dimensions.
Thursday, 24 April 2025
Legendre transform between thermodynamic quantities such as the Helmholtz free energy and entropy plays a key role in the formulation of the canonical ensemble. In the standard treatment, the transform exchanges the independent variable from the system’s internal energy to its conjugate variable—the inverse temperature of the heat reservoir. In this article, we formulate a microscopic version of the trans- form between the free energy and Shannon entropy of the system, where the conju- gate variables are the microstate probabilities and the energies (scaled by the inverse temperature). The present approach gives a non-conventional perspective on the connection between information-theoretic measure of entropy and thermodynamic entropy. We focus on the exact differential property of Shannon entropy, utilizing it to derive central relations within the canonical ensemble. Thermodynamics of a system in contact with the heat reservoir is discussed in this framework. Other approaches, in particular, Jaynes’ maximum entropy principle is compared with the present approach. Ref: R.S. Johal, Microscopic Legendre Transform, Canonical Ensemble and Jaynes’ Maximum Entropy Principle, Foundations of Physics, 55:12 (2025). https://doi.org/10.1007/s10701-025-00824-7
Emergence of different interesting phenomena in different scale is the heart of different physical system in mother nature. In this presentation, we show explicitly how the strong correlation appears in double frequency sine-Gordon field theory. Our study is the detail quantum field theoretical derivation of strongly correlated quantum Ising model.
TBA
We study the nonequilibrium stationary state (NESS) induced by quantum resetting of a system of N noninteracting bosons in a harmonic trap. Under repeated resetting, the system reaches a NESS where the positions of bosons get strongly correlated due to simultaneous resetting induced by the trap. We fully characterize the steady state by analytically computing several physical observables such as the average density, extreme value statistics, order and gap statistics, and also the distribution of the number of particles in a region [−L,L], known as the full counting statistics (FCS). This is a rare example of a strongly correlated quantum many-body NESS where various observables can be exactly computed.
We present PIC-VIC, a novel computational framework for simulating collective behavior of self-propelled particles on curved surfaces. Building upon the Particle-in-Cell (PIC) method, widely used in plasma physics, we track individual particles (Lagrangian description) while employing a static Eulerian mesh for interaction calculations. Using mesh with arbitrary geometries we extend the Vicsek model to study flocking dynamics on curved manifolds. Crucially, we incorporate Laplace-Beltrami based vector diffusion to ensure geometrically consistent averaging of particle velocities, effectively implementing parallel transport on the curved surface. This particle-based PIC-VIC method complements continuum active-hydrodynamics approaches and allows for the investigation of curvature-induced fluctuations. We demonstrate the capabilities of PIC-VIC and discuss its potential for uncovering novel collective phenomena, emergent patterns, and geometry-driven interactions in biological, physical, and artificial systems constrained to non-Euclidean spaces.
In this work we develop a mean-field theory to understand how driven torque monopoles of chiral particles behave in the Stokesian regime.
Two dimensional elastic tethered membranes (ball-and-spring model) with finite bending rigidity and no self-avoidance are known to exist in a flat/crumpled phase for small/large temperatures. The change in phase is mediated by a second order phase transition. Once self-avoidance is introduced, the tethered membranes do not exhibit a crumpled phase and remain flat for all temperatures. By considering the nodes of the membrane as active Brownian particles, we observe that membranes without self-avoidance retain the crumpling transition with activity as the tuning parameter. We find evidence of a crumpled phase with Flory dimensions of 2.4 in spherical self-avoiding active membranes.
Concentrated electrolytes have the potential to improve the mechanical stability of rechargeable batteries. Using molecular dynamics simulations, we calculated the ionic conductivity of highly concentrated EC-LiTFSI electrolytes at varying salt concentrations ranging between 0.005 M and 2.5 M and examined the ion transport mechanisms. Ionic conductivity is found to increase at low salt concentrations before declining at higher salt concentrations beyond 0.6 M. Our extensive simulations and analyses suggest a universal relationship between the ionic conductivity and c as σ(c)~c^α e^(-c/c_0 ) The proposed relationship convincingly explains the ionic conductivity over a wide range of c, where the term c^α accounts for the uncorrelated motion of ions and e^(-c/c_0 ) captures the salt-induced changes in shear viscosity. Our simulations suggest vehicular mechanism to be dominant at low c regimes, which transition into a Grotthuss mechanism at high c regime, where structural relaxation is the dominant form of ion transport mechanism.
The Josephson diode effect (JDE), characterized by asymmetric critical currents in a Josephson junction, has drawn considerable attention in the field of condensed matter physics. We investigate the conditions under which JDE can manifest in a one-dimensional Josephson junction composed of a spin-orbit-coupled quantum wire with an applied Zeeman field, connected between two superconductors. Our study reveals that while spin-orbit coupling (SOC) and a Zeeman field in the quantum wire are not sufficient to induce JDE when the superconductors are purely singlet, the introduction of triplet pairing in the superconductors leads to the emergence of JDE. This finding highlights the potential of JDE as a probe for triplet superconductivity. We further demonstrate that even in absence of SOC in the quantum wire, JDE can arise when the directions of the triplet pairing and the Zeeman field are non-collinear, provided the superconductors exhibit mixed singlet-triplet pairing. Additionally, we identify specific conditions under which JDE is absent, namely, when the pairing is purely triplet and the directions of the SOC and the triplet pairing are perpendicular. Our results suggest that quantum wires in Josephson junctions could serve as effective platforms for probing triplet superconductivity through the observation of JDE.
In this talk, I will describe a method that rigorously transforms the toric code model into independent emergent qubits, which enables us to construct the toric code eigenstates exactly and devise precise quantum circuits for their implementation on quantum processors.
In this work, through a simple yet insightful thought experiment, we have numerically explored Dynamical Feminization(DF) and Bethe Rapidities (BR) in 1D Bose gases. Our thought experiment involves a box-to-box expansion of a Bose gas, providing a unique opportunity for direct numerical observation of BR and the phenomenon of DF from the evaluation of the spatial density. This investigation aims to contribute insights into the behavior of strongly correlated quantum systems during non-equilibrium processes, closely examining Bethe Rapidities and the dynamical evolution of Fermionization throughout the expansion.
We introduce a new class of first passage time optimization mediated by a threshold resetting (TR) mechanism. Inspired by many natural processes that operate under “safety covenant” or are governed by “threshold triggered events” wherein a system, structure, or process exceeds a predefined limit (threshold), causing failure, degradation, or a transition to a different state; we consider an arbitrary first passage process that is intermittently renewed when the search agents, looking for targets, are simultaneously reset upon reaching a certain threshold. Unlike the classical paradigm where the resetting events are externally modulated, here they are event driven and thus, strongly coupled to the system variables. Furthermore, the simultaneous resetting induces long-range interactions between the searchers. A unified theoretical framework is presented for computing the search time associated with this class of correlated stochastic processes, further showcasing a rich and diverse optimization phenomena.
Introducing a single hole in a strongly repulsive Hubbard model at half filling switches the ground state from an antiferromagnet to a ferromagnet on bipartite lattices. However, there is no general understanding of how the magnetic order is affected by odd loops which cause kinetic frustration. We find that local frustration strongly affects global magnetization by binding singlets in general networks.
We study extreme events of avalanche activities in finite-size two-dimensional self- organized critical (SOC) models, specifically the stochastic Manna model (SMM) and Bak-Tang-Weisenfeld (BTW) sandpile model. Employing the approach of block maxima, the study numerically reveals that the distributions for extreme avalanche size and area follow the generalized extreme value (GEV) distribution. The extreme avalanche size follows the Gumbel distribution with shape parameter $\xi=0$ while in case of the extreme avalanche area, we report $\xi>0$. We propose scaling functions for extreme avalanche activities that connect the activities on different length scales. With the help of data collapse, we estimate the precise values of these critical exponents. The scaling functions provide an understanding of the intricate dynamics for different variants of the sandpile model, shedding light on the relationship between system size and extreme event characteristics. Our findings give insight into the extreme behavior of SOC models and offer a framework to understand the statistical properties of extreme events.
Motility-induced phase separation (MIPS) describes how self-propelling particles phase-separate due to their motility, a phenomenon observed in many natural systems. Many motile organisms thrive in fluid environments, and chaotic background flows often act as mixing agents. This raises the question: how does background flow affect the phase separation of motile organisms? To explore this, we study active Brownian particles (ABPs) in a periodic four-roll-mill flow using numerical simulations. Without flow, the system undergoes MIPS. We maintain a packing fraction of 0.7 and investigate the effect of flow on phase separation, referred to as flow-induced phase separation (FIPS). To probe the FIPS regime, we define an order parameter that provides clear insights into this type of phase separation. Additionally, we explore the FIPS region by varying the Peclet number (Pe) and packing fraction (ϕ), which enhances our understanding of how these factors influence the phase separation dynamics.
Effect on arrangement of motors on cargo surface and collective transport by a team of motor proteins
Earth’s daily cycle of rotation influences the daily rhythms of all organisms. For humans, it involves sleep, metabolism, and hormone production. These circadian rhythms are remarkably precise yet adaptable, primarily entrained by natural and artificial light. In this talk, I will explore how a specialized cluster of neurons in the brain—the Suprachiasmatic Nucleus (SCN)—orchestrates these rhythms. While the SCN is thought to function as a highly connected network, its exact structure remains unknown. Understanding this structure is crucial for explaining circadian disruptions, such as jet lag, shift work misalignment, and the timescales of re-entrainment. I will present quantitative analyses of different network models that seek to capture the essential (or believed to be) properties of SCN.
Friday, 25 April 2025
The diversity of diffusive systems exhibiting long-range correlations characterized by a stochastically varying Hurst exponent calls for a generic multifractional model. In this talk I will present a simple, analytically tractable model which fills the gap between mathematical formulations of multifractional Brownian motion and empirical studies. In the model, called telegraphic multifractional Brownian motion (TeMBM), the Hurst exponent is modelled by a smoothed telegraph process which results in a stationary beta distribution of exponents as observed in biological experiments. I will also discuss a methodology to identify TeMBM in experimental data and present concrete examples from biology, climate and finance to demonstrate the efficacy of the presented approach.
Cilia and flagella are micron-sized slender filaments that actively beat in a viscous medium with remarkable accuracy despite thermal fluctuations and other uncertainties. Such precise beating is essential for swift locomotion for microorganisms and for generating an efficient flow in a carpet of cilia in fluid media. To understand the role of the interplay between dissipation and cilia activity in achieving such a precise oscillation, we study a minimal model of cilia known as the rower model. Here, the complex beating of a filament is simplified by a one-dimensional periodic motion of a micron-sized bead between two positions (the amplitude) immersed in a viscous fluid. The bead performs Brownian motion in one of the two harmonic potentials and switches to the other once it reaches two specific positions with a pump of energy which is a measure of cilia activity. We quantify the precision using the quality factor and find a scaling law for the precision with activity and dissipation. Interestingly, for an optimal amplitude where the precision becomes maximum. The scaling and optimal behavior in the quality factor can be explained by studying the noise in the first passage time. Finally, we discuss the energy budget in achieving precision.
We explore the phenomena of prethermalization in a many-body classical system of rotors under aperiodic drives characterised by waiting time distribution (WTD), where the waiting time is defined as the time between two consecutive kicks. We consider here two types of aperiodic drives: random and quasi-periodic. We observe a short-lived pseudo-thermal regime with algebraic suppression of heating for the random drive where WTD has an infinite tail, as observed for Poisson and binomial kick sequences. On the other hand, quasi-periodic drive characterised by a WTD with a sharp cut-off, as observed for Thue-Morse sequence of kick, leads to prethermal region where heating is exponentially suppressed. The kinetic energy growth is analyzed using an average surprise associated with WTD quantifying the randomness of drive. In all of the aperiodic drives we obtain the chaotic heating regime for late time, however, the diffusion constant gets renormalized by the average surprise of WTD in comparison to the periodic case.
We investigate the dynamics of subsystem particle number fluctuations in a long-range system with power-law decaying hopping strength and subjected to a local dephasing at every site. We introduce an efficient bond length representation for the four-point correlator, enabling the large-scale simulation of the dynamics of particle number fluctuations from translationally invariant initial states. Our results show that the particle number fluctuation dynamics exhibit one-parameter Family-Vicsek scaling, with superdiffusive scaling exponents for long-range hopping exponent values less than 3/2 and diffusive scaling exponents for values greater or equal to 3/2. Finally, exploiting the bond-length representation, we provide an exact analytical expression for the particle number fluctuations and their scaling exponents in the short-range limit.
Active-fluid turbulence has been found in bacterial suspensions, but not so far in their algal counterparts. We present the first experimental evidence for turbulence in dense algal suspensions of Chlamydomonas reinhardtii. We carry out a detailed analysis of the statistical properties of the flow present in these cell suspensions and show that they are quantitatively distinct from their counterparts in two-dimensional fluid and bacterial turbulence.
Refrigerators are inseparable from everyday life, industrial manufacturing, and research labs. In this talk, I will present our recent investigation on the refrigerator working between a finite-sized cold heat sink (which means that the heat capacity of the cold bath is finite) and an infinite-sized hot reservoir (environment). We assume that initially the finite-sized cold heat sink at temperature Ti ≤ Th, where Th is the hot reservoir temperature. By consuming the input work/power, the refrigerator transfers the heat from a finite-sized cold sink to the hot heat reservoir. Hence, the temperature of the finite-sized cold heat sink starts to decrease until it reaches the desired low-temperature Tf. By minimizing the input work in this heat transport process, we find the optimal path for temperature rate. We also calculate the coefficient of performance of the refrigerator.
Fundamental laws of physics are symmetric under time reversal (T) symmetry, hence we are tempted to deduce that the evolution of the world may be T-symmetric. On the other end, there is an important conjecture that a conservative system with many particles becomes randomized. The latter process, called thermalization, is related to the second law of thermodynamics that makes the macroscopic world asymmetric. In addition to these two divergent topics, I will cover additional T-breaking frameworks: multiscale energy transfer, open systems, and asymmetric objects. In driven dissipative nonequilibrium systems, including turbulence, the multiscale energy flux from large scales to small scales helps determine the arrow of time. In addition, open systems are often irreversible due to particle and energy exchanges between the system and the environment.
Phase ordering driven by nonequilibrium fluctuations is a hallmark of both living and synthetic active matter. Unlike equilibrium systems, where ordered states arise from the minimisation of free energy, active systems are fueled by the constant injection of energy at the microscopic scale. The emergence of ordered phases in such driven systems challenges our conventional views of domain growth and interfacial structure. In this talk, I will present results on the investigation of coarsening of colloidal clusters in active liquids containing E. coli, highlighting the nature of ordering in systems dominated by strong fluctuations. Our experiments reveal that uniform dispersions of colloids and swimmers are inherently unstable, resulting in spontaneous phase separation characterised by fractal interfaces and unconventional domain growth kinetics.
As natural environments are not static, the model parameters in biologically realistic problems are not constant in time, and such situations in population biology are often described in terms of effective parameters that subsume some of the details of the problem; however, it is not always possible to define an effective parameter. I will describe a simple solvable model to address when and why an effective parameter can not be defined, and the implications thereof.
In this work, we studied the three-dimensional random field Potts model (RFPM), focusing on its phase transition, which is governed by a random fixed point located at zero temperature. As finding ground states in RFPM is NP-hard, we employed our recently developed quasi-exact scheme based on graph cuts to determine approximate ground states and analyze critical behavior. We evaluated various key observables, such as magnetization, Binder and energy cumulants, specific heat, and susceptibilities, which we extrapolated to the quasi-exact ground state limit. Their finite-size scaling analyses revealed strong evidence for a continuous transition induced by disorder, in contrast to the first-order transition seen in the pure case. Our results suggest a new universality class for q-state RFPM, distinct from the RFIM.
We study some of the properties of non-equilibrium phase transitions of an interacting system that is in a state with large deviation from equilibrium. We consider a field theoretical model of scalar particles interacting with vector gauge fields with local U (1) gauge symmetry. We show that the evolution of this system towards an equilbrium state can be described using the principle of emergence of global gauge invariance. As a toy model we consider a scalar-vector model with local U (1) gauge invariance. Invoking the assumption of local U (1) gauge invariance breaking we evaluate time evolution of some of the observables of this system. To make our calculations explicit we calculate the time evolution of order parameter of this sytem and evaluate its scaling behaviour near transition region. In the mean-field approximation we show that, for the unperturbed case, that correspond to no external driving the order parameter has a universal algebriac decay m(t) ∼ t −1/2 . However for time-dependent diffusion coefficient, it is found that order parametr has a universal algabriac decay m(t) ∼ t −1/3 . The results are in total agreement with the recent findings using stochastic models of non-equilibrium system
Run-and-tumble (RT) motion is commonly observed in flagellated microswimmers, arising from synchronous and asynchronous flagellar beating. In addition to hydrodynamic interactions, mechanical coupling has recently been recognized to play a key role in flagellar synchronization. To explore this, we design a macroscopic model system that comprises dry, self-propelled robots linked by a rigid rod to model a biflagellated microorganism. To mimic a low Reynolds number environment, we program each robot to undergo overdamped active Brownian (AB) motion. We find that such a system exhibits RT-like behavior, characterized by sharp tumbles and exponentially distributed run times, consistent with real microswimmers. We quantify tumbling frequency and demonstrate its tunability across experimental parameters. Additionally, we provide a theoretical model that reproduces our results, elucidating physical mechanisms governing RT dynamics.
Proteins are biopolymers, composed of repeating sequence of amino acids (AA). In a typical sequence, the constituting AAs have different charges, hydrophobicity, and capacities to form directional and non-directional interactions. Such heterogeneity can results in sequences lacking a stable three dimensional structure. This class of proteins are intrinsically disordered protein (IDPs). A deeper understanding of IDPs require appropriate characterization of the conformations. To this end, scattering and single molecular spectroscopic measurements often assign a single Flory exponent (equivalently fractal dimension) to the IDPs. In this talk, I highlight limitation of this method by enhanced sampling of atomistic resolution conformations of disordered \beta-casein. I will show that the underlying energy landscape of the IDP contains a global minimum along with two shallow funnels. Employing static polymeric scaling laws separately for individual funnels, we find that they cannot be described by the same polymeric scaling exponent. Around the global minimum, the conformations are globular, whereas in the vicinity of local minima, we recover coil-like scaling. To elucidate the implications of structural diversity on equilibrium dynamics, we initiated standard MD simulations in the NVT ensemble with representative conformations from each funnel. Global and internal motions for different classes of trajectories show heterogeneous dynamics with globule to coil-like signatures. Thus, IDPs can behave as entirely different polymers in different regions of the conformational space.