Searcharxiv⌕ Search

arXiv subjects

Satya N. Majumdar

Publications and source records attributed to Satya N. Majumdar.

At least 19 recordsLinked to original sources

Weakly interacting Bose-Einstein condensate with stochastic resetting

Stochastic resetting can generate strong correlations in many-body systems through a shared fluctuating environment. Here, we investigate how such dynamically emergent correlations (DEC) coexist with intrinsic (direct) interactions in a weakly repulsive Bose-Einstein condensate described within the Gross-Pitaevskii framework. The condensate undergoes free expansion from an initial Thomas-Fermi state and is stochastically reset to this initial state at a constant rate. We show that the resetting protocol drives the system into a unique nonequilibrium steady state and obtain its density profile, edge statistics, and full counting statistics analytically. The steady-state density retains an inverted-parabolic form within the core, while developing exponentially decaying tails outside it. We further show that resetting induces nontrivial fluctuations of the condensate edge and particle number, yielding exact scaling forms for the edge distribution and the full counting statistics. Our results provide a tractable setting for exploring the interplay between intrinsic repulsive interactions and attractive DEC generated by a common stochastic environment in quantum many-body systems.

cond-mat.stat-mech↗

Tuning the strength of emergent correlations in a Brownian gas via batch resetting

We study a gas of $N$ diffusing particles on the line subject to batch resetting: at rate $r$, a uniformly random subset of $m$ particles is reset to the origin. Despite the absence of interactions, the dynamics generates a nonequilibrium stationary state (NESS) with long-range correlations. Since standard renewal methods fail for $m<N$, we introduce a new general Fokker--Planck framework with an exact recursive closure of marginal densities. We obtain exact results, both for the NESS and for the time dependence of the correlations, which are valid for arbitrary $m$ and $N$. By varying $m$, the system interpolates between an uncorrelated regime ($m=1$) and the fully synchronous resetting case ($m=N$). For all $1<m<N$, correlations exhibit a non-monotonic time dependence due to the emergence of an intrinsic decorrelation mechanism. In the stationary state, the correlation strength can be tuned by varying $m$, and it displays a transition at a critical value $N_c=6$. Our predictions extend to any spatial dimension $d$, where the critical value $N_c=6$ remains unchanged, and they are experimentally testable in existing optical-trap setups.

cond-mat.stat-mech↗

The distribution of the moment of inertia for harmonically trapped noninteracting Bosons at finite temperature: large deviations

We compute the full probability distribution of the moment of inertia $I \propto \sum_{i=1}^N \vec{r}_i^2$ of a gas of $N$ noninteracting bosons trapped in a harmonic potential $V(r) = (1/2) m ω^2 r^2$, in all dimensions and at all temperatures. The appropriate thermodynamic limit in a trapped Bose gas consists in taking $N\to\infty$ and $ω\to 0$ with their product $ρ= Nω^d$ fixed, where $ρ$ plays a role analogous to density in a translationally invariant system. In this thermodynamic limit and in dimensions $d>1$, the harmonically trapped Bose gas undergoes a Bose--Einstein condensation (BEC) transition as $ρ$ crosses a critical value $ρ_c(β)$, where $β$ denotes the inverse temperature. We show that the nature of the condensation is different for $1 2$. Near the condensation transition, for simplicity, we provide the analysis only for $d>2$. We show that the probability distribution $P_β(I,N)$ of $I$ admits a large deviation form $P_β(I,N) \sim e^{-VΦ(I/V)}$, where $V = ω^{-d} \gg 1$. We compute explicitly the rate function $Φ(z)$ and show that it exhibits a singularity at a critical value $z=z_c$, where its second derivative undergoes a discontinuous jump. In addition, on the condensed side, $Φ(z)$ becomes independent of $ρ$ for $z 1$. This provides a real-space diagnostic for the BEC transition in the noninteracting Bose gas.

cond-mat.stat-mech↗

Entanglement Scaling and Full Counting Statistics in Excited States of Two-Dimensional Rotating Fermions

We investigate the entanglement entropy of a class of $N$-particle excited state of fermions confined in a two-dimensional harmonic trap rotating at an angular frequency $Ω$. The excited state is constructed by filling a particular set of $N$ single-particle energy levels. We analytically compute the Rényi entropies of order $q$ in a disc of radius $r$ around the centre of the trap, and the cumulants corresponding to number fluctuations of fermions within the disc. We found that the area law scaling of entanglement entropy holds even for a class of excited states. We also verified the well-known series expansion of entanglement entropy in terms of the particle number cumulants for non-interacting fermions. We further derive the centered cumulant generating function, demonstrating that the associated probability distribution function in the disc has identical scaling properties, up to a variable shift, to the known ground-state result. Finally, we extend our result to an annular region, showing that both the Rényi entropy and particle number cumulants of the annulus decompose into sums of the corresponding quantities of the two bounding discs. These additive relations hold as long as the width of the annulus is sufficiently large.

cond-mat.stat-mech↗

Splitting probabilities for Brownian motion with diffusing boundaries: Application to polymer translocation

We study the translocation of a polymer chain through a nanopore where the chain length fluctuates stochastically due to the polymerization-depolymerization processes at the chain ends. We map this process to an equivalent representation where the pore performs a stochastic random-walk-like process on a line in the presence of two diffusing sinks on either side of it with diffusion constants $D_1$ and $D_3$ respectively. The translocation process terminates when the pore hits either of the two outer diffusing sinks. In the case where the pore motion itself is diffusive with diffusion constant $D_2$, we compute exactly the splitting probability that the pore hits the left (right) sink before hitting the right (left) sink. We show that the splitting probability in the presence of mobile sinks is rather nontrivial compared to the classical case of immobile sinks (the latter corresponds to the case when the chain length is fixed). Furthermore, we also compute exactly the probability distribution of the translocation time and that of the chain length at the completion time of the translocation. We show that both distributions have power law tails with exponents that depend continuously on the diffusion constants $D_1$, $D_2$ and $D_3$. We validate our analytical predictions via numerical simulations. We then present numerical results for the case when the pore performs a fractional Brownian motion with Hurst exponent $0<H<1$, while the sinks are still diffusive.

cond-mat.stat-mech↗

Ergodicity Breaking in Active Run-and-Tumble Particles in a Double-Well Potential

We investigate the dynamics of a run-and-tumble particle in a double-well potential and demonstrate that, in stark contrast to Brownian particles, active dynamics can lead to strong ergodicity breaking. When the barrier height exceeds a critical threshold, the long-time position distribution depends crucially on the initial condition: if the particle starts within the basin of attraction of one well, it remains trapped there, while if it begins between the two basins, it can reach either well with a finite probability, which we compute exactly via hitting probabilities. Below the critical barrier height, ergodicity is restored and the system converges to a unique stationary distribution, which we derive analytically. Using this result, we also estimate the characteristic barrier crossing time and show that it violates Kramer's-Arrhenius law, and displays a divergence near the critical height following a Vogel-Fulcher-Tammann-like form with an anomalous exponent $1/2$.

cond-mat.stat-mech↗

Experimental evidence for strong emergent correlations between particles in a switching trap

We experimentally study a system of $N = 4$ two-dimensional Brownian particles, each confined in a harmonic trap with identical stiffness. The stiffness switches simultaneously between two values at random Poissonian times. This collective switching drives the system into a non-equilibrium stationary state (NESS) with strong long-range correlations between the positions of the particles. Remarkably, we find that, despite the presence of hydrodynamic interactions between the particles mediated by the surrounding fluid, the statistics of some observables are insensitive to hydrodynamic interactions and are well described by the noninteracting theory. Comparing with exact theoretical predictions for noninteracting particles, we observe excellent agreement between theory and experiments for three such observables, namely the correlations between particles, extreme value and order statistics (maxima, minima and ranked positions) and the full counting statistics (i.e., the distribution of the number of particles in a finite interval $[-L, L]$ around the trap center).

cond-mat.stat-mech↗

Quantum resetting with memory

We introduce a quantum stochastic resetting protocol with uniform memory, in which each resetting event returns the system to a state visited at a time chosen uniformly from its entire history. The resulting dynamics is nonunitary, non-Markovian and a direct quantum generalization of the classical preferential relocation model. Working in the energy eigenbasis, we derive the exact evolution of every density-matrix element for an arbitrary time-independent Hamiltonian and show that the Hamiltonian enters the dynamics only through the corresponding Bohr frequencies. This leads to a natural distinction between two classes of quantum systems: gapped and gapless. In \emph{gapped systems} (systems with a discrete energy spectrum), while the diagonal elements remain unchanged, the off-diagonal elements of the density matrix in the energy eigenbasis decay algebraically with a continuously varying exponent and with an amplitude that oscillates periodically in $\log t$. The system therefore approaches a stationary state that is independent of the resetting rate and retains a strong memory of the initial state. In \emph{gapless systems} (systems with a continuous energy spectrum), arbitrarily small Bohr frequencies prevent stationarity. Instead, the position distribution spreads on the universal (ultra-slow) scale $\log(rt)/r$, independently of the initial state and of the details of the Hamiltonian. We illustrate these results with a two-level system, a harmonic oscillator, and a free quantum particle, and contrast them with their classical counterparts.

cond-mat.stat-mech↗

Generating pairwise entanglement in periodically driven quantum spin chains with stochastic resetting

We show that stochastic resetting may lead to finite entanglement between individual, spatially separated spins (pairwise entanglement) in the steady state of the spin chains driven periodically with frequency $ω_D$. We find the presence of a critical resetting rate $r_c$ below which the steady state pairwise entanglement, measured via concurrence $C$, vanishes. We also identify an optimal resetting rate $r_m$ at which $C$ becomes maximum. These critical and optimal rates exhibit a non-monotonic dependence on $ω_D$. Our analysis demonstrates the existence of special drive frequencies at which $r_c$ vanishes and $r_m$ attains minima. We compute $C$ in the presence of stochastic resetting using exact diagonalization for both the integrable XY model and non-integrable Rydberg spin chains, which demonstrate these features. Our numerical results match perturbative analytical expressions for the special drive frequencies in the large drive amplitude regime.

quant-ph↗

Exact Stationary State of a $d$-dimensional Run-and-Tumble Particle in a Harmonic Potential

We derive the exact nonequilibrium steady state of a run-and-tumble particle (RTP) in $d$ dimensions confined in an isotropic harmonic trap $V(\mathbf r)=μr^{2}/2$, with $r=\|\mathbf r\|$. Rotational invariance reduces the problem to the stationary single-coordinate marginal $p_X(x)$, from which the radial distribution $p_R(r)$ and the full joint stationary density follow by explicit integral transforms. We first focus on a generalized trapped RTP in one dimension, where post-tumble velocities are drawn from an arbitrary distribution $W(v)$. Using a Kesten-type recursion, we represent its stationary position in terms of a stick-breaking (or Dirichlet) process, yielding closed-form expressions for its distribution and its moments. Specializing $W(v)$ to the projected velocity law of an isotropic RTP, we reconstruct $p_R(r)$ and the full joint distribution of all the coordinates in $d=1,2,3$. In $d=1$ and $d=2$, the radial law simplifies to a beta distribution, while in $d=3$, we derive closed-form expressions for $p_R(r)$ and the stationary joint distribution $P(x,y,z)$, which differ from a beta distribution. In all cases, we characterize a persistence-controlled shape transition at the turning surface $r=v_0/μ$, where $v_0$ is the self-propulsion speed. We further include thermal noise characterized by a diffusion coefficient $D>0$, showing that the stationary law is a Gaussian convolution of the $D=0$ result, which regularizes turning-point singularities and controls the crossover between persistence- and diffusion-dominated regimes as $D \to 0$ and $D \to \infty$ respectively. All analytical predictions are systematically validated against numerical simulations.

cond-mat.stat-mech↗

Effects of confinement in a Brownian gas with simultaneous stochastic resetting and dynamically emergent correlations

We study $N$ non-interacting Brownian particles in an external potential under simultaneous stochastic resetting to the origin. Although they do not interact directly, common resets generate strong dynamically emergent correlations (DEC). We analyze how confinement modifies these correlations and the nonequilibrium stationary state for $V(x)=κ|x|^α$, $α\geq0$, focusing mainly on two analytically tractable cases: harmonic confinement (HC), $α=2$, and box confinement (BC), $α\to\infty$. In both cases the stationary state is controlled by the competition between confinement and resetting lengths. We derive exact results for the stationary joint distribution, density, correlations, extreme value statistics (EVS), and gap statistics. While the density behaves similarly in HC and BC, the normalized correlation coefficient differs sharply. In BC it is non-monotonic and overshoots the unconfined value, as hard walls suppress decorrelating trajectories. In HC it instead increases monotonically toward the unconfined limit. For general $α$, the behavior is monotonic for $0<α<α_c=1+\sqrt{5}$ and non-monotonic for $α>α_c$. The difference between HC and BC is also visible in edge observables. In HC, the maximum scales as $M_1=O(\sqrt{\ln N})$ and has a limiting distribution with bounded support and a shape transition controlled by the ratio of the two length scales. In BC, the maximum is at distance $O(1/N)$ from the boundary, as in equilibrium, but its fluctuations have a broad power-law tail with logarithmic corrections. The first gap shows a similar contrast: BC gives a smaller typical gap but stronger anomalous fluctuations than HC. Finally, we extend the EVS analysis to general $α$ and identify, via simulations and scaling arguments, three universality classes: $0\leqα\leq1$, $1<α<\infty$, and the singular limit $α\to\infty$.

cond-mat.stat-mech↗

Ultra slow sub-logarithmic diffusion of a sluggish random walker subject to resetting with memory

We solve a model of sluggish stochastic motion in which a Brownian particle diffuses with a diffusion coefficient that decays algebraically with the distance to the origin, as $|x|^{-α}$. Additionally, the particle resets with a constant rate $r$ to positions previously visited in the past, so that frequently visited regions are more likely to be revisited. An exact expression is obtained at all times for the position distribution in arbitrary spatial dimensions. At late times, the typical displacement of the walker from the origin grows extremely slowly, as $[\ln(rt)]^{1/(α+2)}$, and the position distribution tends to a scaling law. For any $α>0$, the scaling function has a bimodal shape with a minimum at $x=0$ and non-Gaussian tails. Although the mean square displacement is hard to compute, some generalized moments of this process can be calculated exactly at all times in one dimension, and are shown to be closely related to the moments of the well-studied model with a constant diffusion coefficient.

cond-mat.stat-mech↗

A tridiagonal matrix-valued process with stochastic resetting for arbitrary Dyson index $β>0$

We introduce a symmetric tridiagonal matrix-valued process ($β$-TMP) $H(t)$ whose diagonal entries $H_{k,k}(t)$ evolve independently via an Ornstein-Uhlenbeck process starting at the origin and the off-diagonal entries $H_{k,k+1}(t)$ evolve independently via the Cox-Ingersoll-Ross process, starting at the origin and with parameters that depend on the row index $k$. We show that the joint distribution of the entries of the matrix can be computed exactly at all times and moreover, the joint distribution of its $N$ real eigenvalues can be computed exactly at all times too. We then subject this time-evolving matrix-valued process to stochastic resetting with rate $r$ in two different settings: (i) simultaneous resetting of the matrix entries to the origin with rate $r$ ($β$-SRTMP process) and (ii) independent resetting of the matrix entries to the origin with rate $r$ ($β$-IRTMP process). We show that the joint distribution of the eigenvalues of the $β$-SRTMP process at long times can be computed analytically and it coincides with the joint distribution of the positions of the resetting Dyson Brownian motion in its stationary state for arbitrary $β>0$. For the $β$-IRTMP stationary ensemble, computing analytically the joint distribution of eigenvalues or even the average density of eigenvalues is difficult. However, generating the stationary $β$-IRTMP ensemble numerically is relatively straightforward and we compare its numerical average eigenvalue density to the corresponding analytical results for the $β$-SRTMP stationary ensemble with same parameter values, showing that they are quite different from each other. Finally, we provide a simple and concrete application of this tridiagonal matrix-valued process in computing the annealed partition function of a disordered quantum tight-binding Hamiltonian on a one-dimensional lattice.

cond-mat.stat-mech↗

Diffusion with stochastic resetting on a lattice

We provide an exact formula for the mean first-passage time (MFPT) to a target at the origin for a single particle diffusing on a $d$-dimensional hypercubic {\em lattice} starting from a fixed initial position $\vec R_0$ and resetting to $\vec R_0$ with a rate $r$. Previously known results in the continuous space are recovered in the scaling limit $r\to 0$, $R_0=|\vec R_0|\to \infty$ with the product $\sqrt{r}\, R_0$ fixed. However, our formula is valid for any $r$ and any $\vec R_0$ that enables us to explore a much wider region of the parameter space that is inaccessible in the continuum limit. For example, we have shown that the MFPT, as a function of $r$ for fixed $\vec R_0$, diverges in the two opposite limits $r\to 0$ and $r\to \infty$ with a unique minimum in between, provided the starting point is not a nearest neighbour of the target. In this case, the MFPT diverges as a power law $\sim r^ϕ$ as $r\to \infty$, but very interestingly with an exponent $ϕ= (|m_1|+|m_2|+\ldots +|m_d|)-1$ that depends on the starting point $\vec R_0= a\, (m_1,m_2,\ldots, m_d)$ where $a$ is the lattice spacing and $m_i$'s are integers. If, on the other hand, the starting point happens to be a nearest neighbour of the target, then the MFPT decreases monotonically with increasing $r$, approaching a universal limiting value $1$ as $r\to \infty$, indicating that the optimal resetting rate in this case is infinity. We provide a simple physical reason and a simple Markov-chain explanation behind this somewhat unexpected universal result. Our analytical predictions are verified in numerical simulations on lattices up to $50$ dimensions. Finally, in the absence of a target, we also compute exactly the position distribution of the walker in the nonequlibrium stationary state that also displays interesting lattice effects not captured by the continuum theory.

cond-mat.stat-mech↗

Sluggish quantum mechanics of noninteracting fermions with spatially varying effective mass

We analyze a class of one-dimensional quantum systems characterized by a position-dependent kinetic term arising as the continuum limit of an inhomogeneous tight-binding model with spatially varying hopping amplitudes. In this limit, the Schrodinger equation takes the so-called BenDaniel-Duke form with an effective mass, scaling as $m_{eff}(x) = m_{eff}|x|^α$ with $α> 0$, leading to a framework we term sluggish quantum mechanics, where particle motion is progressively suppressed at larger distances. Both without any external potential and with $V_{ext}(x)=\frac{1}{2}m_{eff}ω^2 |x|^{α+2}$, we obtain the eigenfunctions and the quantum propagators exactly. We then investigate the problem of $N$ noninteracting spinless fermions in the trap, determining the many-body ground-state wavefunction and the joint probability density function of the positions of the $N$ fermions. We show that the many-body quantum probability density in the ground state forms a determinantal point process whose correlation kernel can be computed for any $N$, giving access to the average density as well as higher order correlation functions for any finite $N$. Moreover, we analyze the scaling form of this kernel in the large $N$ limit in the bulk, near the edge, and close to the origin. Our results show that the scaled average density profile for large $N$ has a finite support symmetric with respect to the origin, but has a non-monotonic shape with a vanishing minimum at the origin for any $α>0$. One of the key findings of our work is that the scaled kernel near the origin $x=0$ for $α>0$ is neither the Bessel nor the Airy kernel (that are standard for trapped fermions), but is new, and is given by a sum of two Bessel kernels with different indices. Our results thus provide a framework relevant to engineered optical lattices with position-dependent tunneling.

cond-mat.stat-mech↗

Proxitaxis: an adaptive search strategy based on proximity and stochastic resetting

We introduce \emph{proxitaxis}, a simple search strategy where the searcher has only information about the distance from the target but not the direction. The strategy consists of three crucial components: (i) local adaptive moves with distance-dependent hopping rate, (ii) intermittent long range returns via stochastic resetting to a certain location $\vec{R}_0$, and (iii) an inspection move where the searcher dynamically updates the resetting position $\vec{R}_0$. We compute analytically the capture probability of the target within this strategy and show that it can be maximized by an optimal choice of the control parameters of this strategy. Moreover, the optimal strategy undergoes multiple phase transitions as a function of the control parameters. These phase transitions are generic and occur in all dimensions.

cond-mat.stat-mech↗

A first passage problem for a Poisson counting process with a linear moving boundary

The time to first crossing for the Poisson counting process with respect to a linear moving barrier with offset is a classic problem, although key results remain scattered across the literature and their equivalence is often unclear. Here we present a unified and pedagogical treatment of two approaches: the direct time-domain approach based on path-decomposition techniques and the Laplace-domain approach based on the Pollaczek-Spitzer formula. Beyond streamlining existing derivations and establishing their consistency, we leverage the complementary nature of the two methods to obtain new exact analytical results. Specifically, we derive an explicit large deviation function for the first-passage time distribution in the subcritical regime and closed-form expressions for the conditional mean first-passage time for arbitrary offset. Despite its simplicity, this first crossing process exhibits non-trivial critical behavior and provides a rare example where all the main results of interest can be derived exactly.

cond-mat.stat-mech↗

Emerging correlations between diffusing particles evolving via simultaneous resetting with memory

We study the emergence of correlations between $N$ components of the position of a diffusive walker in $N$ dimensions that starts at the origin and resets to previously visited sites with certain probabilities. This is equivalent to $N$ independent one-dimensional diffusive processes starting from the origin and being subject to simultaneous resetting to positions visited in the past. Resetting follows a memory kernel that interpolates between resetting to the origin only, and the preferential relocation model, a path-dependent process which is highly non-Markov. For weak memory, the correlation coefficient between two components of the $N$-dimensional process grows monotonously with time and tends at late times to a constant bounded by $1/5$, the value corresponding to the non-equilibrium steady state of resetting to the origin. When memory is sufficiently long-ranged, the correlation is non-monotonous and reaches a maximum at a finite time before converging to its asymptotic value. These two regimes are separated by a critical memory parameter value. In the limiting case of the preferential relocation model, the components become uncorrelated at both short and long times, but the correlation vanishes logarithmically slowly at late times. The emergence of correlations through resetting can be described in a unified way in all cases by noticing that the processes are conditionally independent and identically distributed, even in the presence of memory. In the non-Markovian case, the conditioning parameter is the duration of a Brownian path composed of several parts of the full trajectory of a fixed duration $t$.

cond-mat.stat-mech↗