arXiv subjects

Pragna Das

Publications and source records attributed to Pragna Das.

10 recordsLinked to original sources

arXiv2025

Emergence of Unruh prethermalization for uniformly accelerating many-atom system

A uniformly accelerated atom in an inertial vacuum generally thermalizes and reaches a Gibbs state. This phenomenon is commonly known as the Unruh effect. Here, we show that the situation is entirely different for the many-atoms problem. In the case of non-interacting accelerating atoms, we show that a regime exists where the entire system reaches a prethermal generalized Gibbs state before it thermalizes. The prethermal state is protected by emergent conserved quantities; hence, the system behaves like a nearly-integrable one, which shows a sharp distinction from the Unruh effect. We coin the term ``Unruh prethermalization" to characterize this phenomenon. The measure of entanglement is a good estimation of the lifetime of the prethermal state and is consistent with previous studies. Finally, we show that in such a regime, the dynamics show a Dicke superradiance-type radiation burst before reaching the prethermal state. In contrast, only a mono-exponential decay is observed for Unruh thermalization. In addition, to highlight the significance of our results, we compare them with existing experimental observations.

quant-ph↗

arXiv2025

A detailed study on various phases in dissipative anisotropic Dicke model

We present a comprehensive study of different phases in the Dicke model incorporating both anisotropy and dissipation. We begin with a concise review of the quantum phase transition in this setting, highlighting how these two parameters shift the critical point. We then perform a detailed investigation of the transition from ergodic to nonergodic phases by analyzing the eigenvalue and eigenvector properties of the Liouvillian with the aid of scaling of the Liouvillian gap and the average participation ratio. Our results show that the eigenvector properties of the Liouvillian are consistent with its spectral characteristics, leading to a phase diagram that has similarities with the closed counterpart. Furthermore, we demonstrate that the Liouvillian gap exhibits distinct scaling behaviors in these two phases. Finally, we extend our study to the driven case by applying a Thue-Morse quasiperiodic drive. In this case, we find that bosonic dissipation plays a crucial role in stabilizing the prethermal plateau, offering an effective mechanism to halt the heating effect arising from the quasi-periodic drive.

quant-ph↗

arXiv2023

The disordered Dicke model

We introduce and study the disordered Dicke model in which the spin-boson couplings are drawn from a random distribution with some finite width. Regarding the quantum phase transition we show that when the standard deviation $σ$ of the coupling strength gradually increases, the critical value of the mean coupling strength $μ$ gradually decreases and after a certain $σ$ there is no quantum phase transition at all; the system always lies in the super-radiant phase. We derive an approximate expression for the quantum phase transition in the presence of disorder in terms of $μ$ and $σ$, which we numerically verify. Studying the thermal phase transition in the disordered Dicke model, we obtain an analytical expression for the critical temperature in terms of the mean and standard deviation of the coupling strength. We observe that even when the mean of the coupling strength is zero, there is a finite temperature transition if the standard deviation of the coupling is sufficiently high. Disordered couplings in the Dicke model will exist in quantum dot superlattices, and we also sketch how they can be engineered and controlled with ultracold atoms or molecules in a cavity.

cond-mat.stat-mech↗

arXiv2023

Periodically and quasiperiodically driven-anisotropic Dicke model

We analyze the anisotropic Dicke model in the presence of a periodic drive and under a quasiperiodic drive. The study of drive-induced phenomena in this experimentally accesible model is important since although it is simpler than full-fledged many-body quantum systems, it is still rich enough to exhibit many interesting features. We show that under a quasiperiodic Fibonacci (Thue-Morse) drive, the system features a prethermal plateau that increases as an exponential (stretched exponential) with the driving frequency before heating to an infinite-temperature state. In contrast, when the model is periodically driven, the dynamics reaches a plateau that is not followed by heating. In either case, the plateau value depends on the energy of the initial state and on the parameters of the undriven Hamiltonian. Surprisingly, this value does not always approach the infinite-temperature state monotonically as the frequency of the periodic drive decreases. We also show how the drive modifies the quantum critical point and discuss open questions associated with the analysis of level statistics at intermediate frequencies.

quant-ph↗

arXiv2023

Phase transitions of the anisotropic Dicke model

We systematically analyze the various phase transitions of the anisotropic Dicke model that is endowed with both rotating and counter-rotating light-matter couplings. In addition to the ground state quantum phase transition (QPT) from the normal to the super-radiant phase, the anisotropic Dicke model also exhibits other transitions namely the excited state quantum phase transition (ES- QPT), ergodic to non-ergodic transition (ENET) and the temperature dependent phase transition. We show that these phase transitions are profitably studied not only with the standard consecutive level spacing ratio, but also with the aid of various eigenvector quantities such as von Neumann entanglement entropy, the participation ratio, multifractal dimension and mutual information. For ENET, both the statics and dynamics of the participation ratio offer a consistent and useful picture. An exciting finding from our work is that the ESQPT and the ENET are closely related to each other. We show this with the aid of two characteristic energies in the spectrum corresponding to jumps in von Neumann entropy.

quant-ph↗

arXiv2021

Phase transitions of the Dicke model: a unified perspective

The Dicke model exhibits a variety of phase transitions. The quantum phase transition from the normal phase to the super-radiant phase is marked by a dramatic change in the scaling of the participation ratio. We find that the ground state in the super-radiant phase exhibits multifractality manifest in the participation ratio scaling as the square root of the full Hilbert space dimension. The thermal phase transition temperature, for which we obtain an exact analytical expression, is strikingly captured by the mutual information between two spins. In the excited state quantum phase transition within the super-radiant phase, we discover a new upper cut-off energy; the central energy band between the lower and upper cut-off energies shows distinctly different behaviour. This finding is corroborated with the aid of several eigenvector properties: von Neumann entanglement entropy between spins and bosons, the mean photon number, concurrence between two spins, and participation ratio. Thus we obtain a unified picture for the three different kinds of phase transitions.

cond-mat.stat-mech↗

arXiv2018

A Study of Time-varying Cost Parameter Estimation Methods in Automated Transportation Systems based on Mobile Robots

Control of systems of automated guided vehicles involves action planning at many levels. For efficient control of these systems, accurate estimation of cost parameters (speed, energy, task completion performance, \textit{et~cetera} is required. These parameters change along time, particularly in battery-operated robots, which are very sensitive to battery level variations. This work addresses the problem of on-line cost parameter identification and estimation for proper control decisions of the individual mobile robots and for the system as a whole. Several filtering and estimation methods have been investigated with respect to travelling times, which are dramatically affected by battery charges and condition of facility's floors, among other factors. Results show that these parameters depend on the robot, the route and the moment, so they are linked to a particular robot, a region of the floor and a time period (or to a battery level). Moreover, differences with static, pre-runtime travelling time computations, either heuristically or by characterization of real robots, are large enough to affect to system's performance and overall productivity and efficiency.

cs.RO↗

arXiv2018

Parameter estimation for optimal path planning in internal transportation

The costs incurred in a mobile robot (MR) change due to change in physical and environmental factors. Usually, there are two approaches to consider these costs, either explicitly modelling these different factors to calculate the cost or consider heuristics costs. First approach is lengthy and cumbersome and requires a new model for every new factor. Heuristics cost cannot account for the change in cost due to change in state. This work proposes a new method to compute these costs, without the need of explicitly modelling the factors. The identified cost is modelled in a bi-linear state-space form where the change of costs is formed due to the change of these states. This eliminates the need to model all factors to derive the cost for every robot. In context of transportation, the travel time is identified as the key parameter to understand costs of traversing paths to carry material. The necessity to identify and estimate these travel times is proved by using them in route planning. The paths are computed constantly and average of total path costs of these paths are compared with that of paths obtained by heuristics costs. The results show that average total path costs of paths obtained through on-line estimated travel times are 15\% less that of paths obtained by heuristics costs.

eess.SY↗

arXiv2018

An Ontology to Support Collective Intelligence in Decentralised Multi-Robot Systems

In most multi-robot systems, conditions of the floor, battery and mechanical parts are important and impact cost-efficiency. The costs are generally interpreted through performance times. The relation between performance times andthese factors are not directly derivable, though, performance time has a direct correlation with discharge of batteries. Inroute planning, travel time of an edge is the performance time and may be required to be estimated for multiple times.These estimated travel times are different than heuristics costs as they depict the real states which are impossible toknow from heuristics. This facilitates path planning algorithms to choose the edges with least real travel times or coststo form the path. Nevertheless, a good estimation is dependent on historical data which are close in time. But, there aresituations when all the travel times for one or more edge(s) are not available for the entire duration of operation of theMRS to an individual robot. Then, it is imperative for that robot to gather the necessary travel times from others inthe system as a reference observation. The mechanism of information sharing between one robot to others in the systemhas been devised in a form of a common ontology-based knowledge. This ontology helps to fetch and share informationforming a collective knowledge base facilitating a comprehensive control and planning for the system. This greatly helpsthe MR to estimate travel times more accurately and precisely. Also, accurate estimation affects route planning to bemore precise with reduced cost. The total cost of paths generated through the travel times estimated through sharingis 40% less on average than that of paths generated through travel times without sharing.

cs.MA↗

arXiv2017

Adaptive Cost Coefficient Identification for Planning Optimal Operation in Mobile Robot based Internal Transportation

Decisions in automated logistic systems can be improved based on knowledge of real-time state of individual parts and also environmental factors. These knowledge can be obtained through travel time of edges by individual robots which represents the utility based costs in the system. Our work focuses on identifying \textbf{cost coefficients} in an autonomous multi-robot system used for internal transportation. With suitable predictions of these travel times the current status of cost involved in traversing from one node to another can be known. Thus suitable state-space model is formulated and Kalman filtering is used to estimate these travel time to use as weights for cost efficient route planning. Experiments show that paths obtained using online \textbf{travel times} as weights have total traversing cost reduces by 15\% on average.

eess.SY↗