arXiv subjects

Amit Dutta

Publications and source records attributed to Amit Dutta.

At least 19 recordsLinked to original sources

arXiv2026

Adaptive Training for Nautical Rules of the Road

Knowledge of the nautical rules of the road is essential for safe ship navigation and collision avoidance. We evaluated adaptive and non-adaptive versions of a ship-driving simulation trainer designed to assess and improve students' knowledge and application of these rules. We randomly assigned 30 university students to an adaptive or non-adaptive training condition and measured learning using pretest and post-test scores. Students who received adaptive training achieved significantly higher post-test scores than those who received non-adaptive training (p < 0.0001). After the post-test, all students experienced both versions of the trainer and compared them in a survey. Of the 30 students, 73% judged the adaptive trainer more effective, and 22 rated it "very engaging," compared with 9 who gave the non-adaptive trainer the same rating. These findings provide evidence that adapting scenario difficulty and providing immediate, context-sensitive feedback can improve both learning outcomes and student engagement in simulation-based training.

cs.HC↗

arXiv2026

Persistent Mean Tracking in Client--Server Open Networks

We study persistent-agent identification and mean tracking in an open client-server network where agents participate intermittently. The network consists of a core of highly regular persistent agents and a subset of transient/non-persistent agents that appear only sporadically. Since the server observes only binary activity indicators and scalar updates from active agents, naive averaging cannot recover the active persistent mean because transient-agent updates contaminate the aggregate, and heterogeneous participation introduces bias. To address this, we propose a two-phase estimation framework. In Phase I, we develop a two-layer window-based identification procedure: the first layer forms single-window activity decisions, while the second aggregates these decisions across windows to create a high-probability separation between persistent and transient agents. Under heterogeneous Bernoulli participation, we derive explicit finite-window bounds that specify how many windows the server must wait for this separation to occur with high probability. In Phase II, we use the resulting structural estimate to track the active persistent mean via a smoothing filter, and show that the tracking error contracts geometrically to a neighborhood determined by the target drift and the filter gain. We provide numerical simulations to illustrate the effectiveness of our theoretical results.

math.OC↗

arXiv2026

Source Reliability Weighted Observer Design for Open Client Server Networks

State estimation in open client server networks is challenging because the set of active observation sources changes over time, and active sources need not be valid sensors of the latent state. We study a client-server estimation problem in which a fixed but unknown state-consistent sensing class measures the latent state when active, while nuisance sources may arrive in the active set and generate observations from a different signal class. The server observes active sources, but it does not know which agents observe valid state measurements. We propose a source-reliability-weighted observer. The state estimate is a standard fixed-prior weighted least-squares update, but the information assigned to each active observation is determined by a source-level reliability score learned from repeated innovation consistency. Numerical results show that the observer, when all active sources are considered, has a finite bias, while the proposed observer initially learns source reliability and then tracks the desired latent state after a finite learning period.

math.OC↗

arXiv2024

Resilient Two-Time-Scale Local Stochastic Gradient Descent for Byzantine Federated Learning

We study local stochastic gradient descent methods for solving federated optimization over a network of agents communicating indirectly through a centralized coordinator. We are interested in the Byzantine setting where there is a subset of $f$ malicious agents that could observe the entire network and send arbitrary values to the coordinator to disrupt the performance of other non-faulty agents. The objective of the non-faulty agents is to collaboratively compute the optimizer of their respective local functions under the presence of Byzantine agents. In this setting, prior works show that the local stochastic gradient descent method can only return an approximate of the desired solutions due to the impacts of Byzantine agents. Whether this method can find an exact solution remains an open question. In this paper, we will address this open question by proposing a new variant of the local stochastic gradient descent method. Under similar conditions that are considered in the existing works, we will show that the proposed method converges exactly to the desired solutions. We will provide theoretical results to characterize the convergence properties of our method, in particular, the proposed method convergences at an optimal rate $\mathcal{O}(1/k)$ in both strongly convex and non-convex settings, where $k$ is the number of iterations. Finally, we will present a number of simulations to illustrate our theoretical results.

math.OC↗

arXiv2023

Resilient Federated Learning under Byzantine Attack in Distributed Nonconvex Optimization with 2-f Redundancy

We study the problem of Byzantine fault tolerance in a distributed optimization setting, where there is a group of $N$ agents communicating with a trusted centralized coordinator. Among these agents, there is a subset of $f$ agents that may not follow a prescribed algorithm and may share arbitrarily incorrect information with the coordinator. The goal is to find the optimizer of the aggregate cost functions of the honest agents. We will be interested in studying the local gradient descent method, also known as federated learning, to solve this problem. However, this method often returns an approximate value of the underlying optimal solution in the Byzantine setting. Recent work showed that by incorporating the so-called comparative elimination (CE) filter at the coordinator, one can provably mitigate the detrimental impact of Byzantine agents and precisely compute the true optimizer in the convex setting. The focus of the present work is to provide theoretical results to show the convergence of local gradient methods with the CE filter in a nonconvex setting. We will also provide a number of numerical simulations to support our theoretical results.

math.OC↗

arXiv2023

Quantum Annealing: An Overview

In this review, after providing the basic physical concept behind quantum annealing (or adiabatic quantum computation), we present an overview of some recent theoretical as well as experimental developments pointing to the issues which are still debated. With a brief discussion on the fundamental ideas of continuous and discontinuous quantum phase transitions, we discuss the Kibble-Zurek scaling of defect generation following a ramping of a quantum many body system across a quantum critical point. In the process, we discuss associated models, both pure and disordered, and shed light on implementations and some recent applications of the quantum annealing protocols. Furthermore, we discuss the effect of environmental coupling on quantum annealing. Some possible ways to speed up the annealing protocol in closed systems are elaborated upon: We especially focus on the recipes to avoid discontinuous quantum phase transitions occurring in some models where energy gaps vanish exponentially with the system size.

cond-mat.stat-mech↗

arXiv2022

Convergence Rates of Distributed Consensus over Cluster Networks: A Two-Time-Scale Approach

We study the popular distributed consensus method over networks composed of a number of densely connected clusters with a sparse connection between them. In these cluster networks, the method often constitutes two-time-scale dynamics, where the internal nodes within each cluster reach consensus quickly relative to the aggregate nodes across clusters. Our main contribution is to provide the rate of the distributed consensus method, which characterize explicitly the impacts of the internal and external graphs on the performance of this method. Our main result shows that this rate converges exponentially and only scales with a few number of nodes, which is relatively small to the size of the network. The key technique in our analysis is to consider a Lyapunov function which captures the impacts of different time-scale dynamics on the convergence of the method. Our approach avoids using model reduction, which is the typical way according to singular perturbation theory and relies on relatively simple definitions of the slow and fast variables. In addition, Lyapunov analysis allows us to derive the rate of distributed consensus methods over cluster networks, which is missing from the existing works using singular perturbation theory. We illustrate our theoretical results by a number of numerical simulations over different cluster networks.

math.OC↗

arXiv2022

Quasi-localization dynamics in a Fibonacci quantum rotor

We analyze the dynamics of a quantum kicked rotor (QKR) driven with a binary Fibonacci sequence of two distinct drive amplitudes. While the dynamics at low drive frequencies is found to be diffusive, a long-lived pre-ergodic regime emerges in the other limit. Further, the dynamics in this pre-ergodic regime can be associated with the onset of a dynamical quasi-localization, similar to the dynamical localization observed in a regular QKR. We establish that this peculiar behavior arises due to the presence of localized eigenstates of an approximately conserved effective Hamiltonian, which drives the evolution at Fibonacci instants. However, the effective Hamiltonian picture does not persist indefinitely and the dynamics eventually becomes ergodic after asymptotically long times.

quant-ph↗

arXiv2022

Late-time critical behavior of local string-like observables under quantum quenches

In recent times it has been observed that signatures of equilibrium quantum criticality surprisingly show up in many-body systems which are manifestly far from equilibrium. We explore such scenarios in interacting spin systems subject to a quench and develop a robust method to systematically probe ground state critical physics through nonequilibrium post-quench dynamics. Analyzing late-time behavior of finite string-like observables, we find emerging sharp signatures of equilibrium criticality. Specifically, these observables accurately detect equilibrium critical points and universal scaling exponents after long times following a quench. This happens despite the fact that the analyzed systems are strongly chaotic/ergodic and is interestingly due to a strong memory of the initial conditions retained by these observables after quench. We find that our results can also be used to explain critical signatures in post-quench domain formation, seen in a recent experiment with trapped ion quantum simulators.

cond-mat.stat-mech↗

arXiv2022

Disconnected entanglement entropy as a marker of edge modes in a periodically driven Kitaev chain

We study the disconnected entanglement entropy (DEE) of a Kitaev chain in which the chemical potential is periodically modulated with $\delta$-function pulses within the framework of Floquet theory. For this driving protocol, the DEE of a sufficiently large system with open boundary conditions turns out to be integer-quantized, with the integer being equal to the number of Majorana edge modes localized at each edge of the chain generated by the periodic driving, thereby establishing the DEE as a marker for detecting Floquet Majorana edge modes. Analysing the DEE, we further show that these Majorana edge modes are robust against weak spatial disorder and temporal noise. Interestingly, we find that the DEE may, in some cases, also detect the anomalous edge modes which can be generated by periodic driving of the nearest-neighbor hopping, even though such modes have no topological significance and not robust against spatial disorder. We also probe the behaviour of the DEE for a kicked Ising chain in the presence of an integrability breaking interaction which has been experimentally realized.

cond-mat.stat-mech↗

arXiv2022

Detecting topological phase transitions through entanglement between disconnected partitions in a Kitaev chain with long-range interactions

We explore the behaviour of the disconnected entanglement entropy (DEE) across the topological phases of a long range interacting Kitaev chain where the long range interactions decay as a power law with an exponent $α$. We show that while the DEE may not remain invariant deep within the topologically non-trivial phase when $α<1$, it nevertheless shows a quantized discontinuous jump at the quantum critical point and can act as a strong marker for the detection of topological phase transition. We also study the time evolution of the DEE after a sudden quench of the chemical potential within the same phase. In the short range limit of a finite chain, the DEE is expected to remain constant upto a critical time after the quench, which diverges in the thermodynamic limit. However, no such critical time is found to exist when the long range interactions dominate (i.e., $α<1$).

cond-mat.stat-mech↗

arXiv2022

Dynamical crossover behavior in the relaxation of quenched quantum many-body systems

A crossover between different power-law relaxation behaviors of many-body periodically driven integrable systems has come to light in recent years. We demonstrate using integrable quantum systems, that similar kinds of dynamical transitions may also occur in the relaxation of such systems following a sudden quench. Particularly, we observe two distinct power-law relaxation behaviors following a sudden quench in the integrable XY model, depending upon whether the quenched Hamiltonian lies in the commensurate or the incommensurate phase. The relaxation behavior for quenches at and near the boundary line, called the disorder line (DL), separating these phases is also characterized. The relaxation at the DL shows a new scaling exponent previously unexplored. The transitions occur through a crossover from the commensurate/incommensurate scaling behavior to the DL scaling behavior. The crossover time diverges like a power law as the parameters of the final quenched Hamiltonian approach the DL. The transitions are also observed to be robust under weak integrability breaking perturbations but disappear following strongly chaotic quenches.

cond-mat.stat-mech↗

arXiv2021

Quantum thermal machines and batteries

The seminal work by Sadi Carnot in the early nineteenth century provided the blueprint of a reversible heat engine and the celebrated second law of thermodynamics eventually followed. Almost two centuries later, the quest to formulate a quantum theory of the thermodynamic laws has thus unsurprisingly motivated physicists to visualise what are known as `quantum thermal machines' (QTMs). In this article, we review the prominent developments achieved in the theoretical construction as well as understanding of QTMs, beginning from the formulation of their earliest prototypes to recent models. We also present a detailed introduction and highlight recent progress in the rapidly developing field of `quantum batteries'.

quant-ph↗

arXiv2021

Convergence Rates of Decentralized Gradient Methods over Cluster Networks

We present an analysis for the performance of decentralized consensus-based gradient (DCG) methods for solving optimization problems over a cluster network of nodes. This type of network is composed of a number of densely connected clusters with a sparse connection between them. Decentralized algorithms over cluster networks have been observed to constitute two-time-scale dynamics, where information within any cluster is mixed much faster than the one across clusters. Based on this observation, we present a novel analysis to study the convergence of the DCG methods over cluster networks. In particular, we show that these methods converge at a rate $\ln(T)/T$ and only scale with the number of clusters, which is relatively small to the size of the network. Our result improves the existing analysis, where these methods are shown to scale with the size of the network. The key technique in our analysis is to consider a novel Lyapunov function that captures the impact of multiple time-scale dynamics on the convergence of this method. We also illustrate our theoretical results by a number of numerical simulations using DCG methods over different cluster networks.

math.OC↗

arXiv2021

Bilayer Haldane system: Topological characterization and adiabatic passages connecting Chern phases

We present a complete topological characterization of a bilayer composite of two Chern insulators (specifically, Haldane models) and explicitly establish the bulk-boundary correspondences. We show that an appropriately defined Chern number accurately maps out all the possible phases of the system and remains well-defined even in the presence of degeneracies in the occupied bands. Importantly, our result paves the way for realizing adiabatic preparation of monolayer Chern insulators. This has been a major challenge till date, given the impossibility of unitarily connecting inequivalent topological phases. We show that this difficulty can be circumvented by adiabatically varying the interlayer coupling in such a way that the system remains gapped at all times. In particular, a complete knowledge of the phase diagram of the bilayer composite immediately allows one to identify all such adiabatic passages which may connect the different Chern inequivalent phases of the individual monolayers.

cond-mat.stat-mech↗

arXiv2021

Observing Dynamical Quantum Phase Transitions through Quasilocal String Operators

We analyze signatures of the dynamical quantum phase transitions in physical observables. In particular, we show that both the expectation value and various out of time order correlation functions of the finite length product or string operators develop cusp singularities following quench protocols, which become sharper and sharper as the string length increases. We illustrated our ideas analyzing both integrable and nonintegrable one-dimensional Ising models showing that these transitions are robust both to the details of the model and to the choice of the initial state.

cond-mat.stat-mech↗

arXiv2020

Dynamical generation of Majorana edge correlations in a ramped Kitaev chain coupled to nonthermal dissipative channels

We quantitatively study the out-of-equilibrium edge-Majorana correlation in a linearly ramped one-dimensional Kitaev chain of finite length in a dissipative environment. The chemical potential is dynamically ramped to drive the chain from its topologically trivial to nontrivial phase in the presence of couplings to nonthermal Markovian baths. We consider two distinctive situations: In the first situation, the bath is quasilocal in the site basis (local in quasiparticle basis) while in the other it is local. Following a Lindbladian approach, we compute the early time dynamics as well as the asymptotic behavior of the edge-Majorana correlation to probe the interplay between two competing timescales - one due to the coherent ramping while the other to the dissipative coupling. For the quasilocal bath, we establish that there is a steady generation of Majorana correlations in asymptotic time and the presence of an optimal ramping time which facilitates a quicker approach to the topological steady state. In the second scenario, we analyze the action of a local particle-loss type of bath in which we have established the existence of an optimal ramping time which results from the competing dynamics between the unitary ramp and the dissipative coupling. While the defect generated by the former decays exponentially with increasing ramp duration, the later scales linearly with the same. This linear scaling is further established through a perturbation theory formulated using the nondimensionalized coupling to the bath as a small parameter.

cond-mat.stat-mech↗

arXiv2020

Exploring the role of asymmetric-pulse modulation in quantum thermal machines and quantum thermometry

We explore the consequences of periodically modulating a quantum two-level system (TLS) with an asymmetric pulse when the system is in contact with thermal baths. By adopting the Floquet-Lindblad formalism for our analysis, we find that the unequal "up" and "down" time duration of the pulse has two main ramifications. First, the energy gap of the multiple sidebands or photon sectors created as a result of the periodic modulation are renormalized by a term which is dependent on both the modulation strength as well as the fraction of up (or down) time duration. Second, the weights of the different sidebands are no longer symmetrically distributed about the central band or zero photon sector. We illustrate the advantages of these findings in the context of applications in quantum thermal machines and thermometry. For a thermal machine constructed by coupling the TLS to two thermal baths, we demonstrate that the asymmetric pulse provides an extra degree of control over the mode of operation of the thermal machine. Further, by appropriately tuning the weight of the subbands, we also show that an asymmetric pulse may provide superior optimality in a recently proposed protocol for quantum thermometry, where dynamical control has been shown to enhance the precision of measurement.

quant-ph↗