arXiv subjects

Devansh Sharma

Publications and source records attributed to Devansh Sharma.

7 recordsLinked to original sources

arXiv2025

Routes of Transport in the Path Integral Lindblad Dynamics through State-to-State Analysis

Analyzing routes of transport for open quantum systems with non-equilibrium initial conditions is extremely challenging. The state-to-state approach [A. Bose, and P.L. Walters, J. Chem. Theory Comput. 2023, 19, 15, 4828-4836] has proven to be a useful method for understanding transport mechanisms in quantum systems interacting with dissipative thermal baths, and has been recently extended to non-Hermitian systems to account for empirical loss. These non-Hermitian descriptions are, however, not capable of describing empirical processes of more general nature, including but not limited to a variety of pumping processes. We extend the state-to-state analysis to account for Lindbladian descriptions of generic dissipative, pumping and decohering processes acting on a system which is exchanging energy with a thermal bath. This Lindblad state-to-state method can elucidate routes of transport in systems coupled to a bath and additionally acted upon by Lindblad jump operators. The method is demonstrated using examples of excitonic aggregates subject to incoherent pumping and draining processes. Using this new state-to-state formalism, we demonstrate the establishment of steady-state excitonic currents across molecular aggregates, yielding a different first-principles approach to quantifying the same.

quant-ph↗

arXiv2025

Walking Through Complex Spatial Patterns of Climate and Conflict-Induced Displacements

Extreme weather events are projected to intensify global migration, increase resource competition, and amplify socio-spatial phenomena, including intergroup conflicts, socioeconomic inequalities, and unplanned displacements, among others. Addressing these challenges requires consolidating heterogeneous data to identify, estimate, and predict the dynamical process behind climate-induced movements. We propose a novel hybrid approach to reconstruct hazard-induced displacements by analysing the statistical properties of a diffusion process (walks) that explores the spatial network constructed from real displacements. The likely trajectories produced by the walks inform the typical journey of individuals, identifying potential hazards that may be encountered when fleeing high-risk areas. As a proof of concept, we apply this method to Somalia's detailed displacement tracking matrix, containing 20,220 movements dating from February 8 to June 18, 2025. We reconstruct the likely routes that displaced persons could have taken when fleeing areas affected by conflict or climate hazards. We find that individuals using the most likely paths based on current flows would experience mainly droughts and conflicts, while the latter becomes less prominent at every subsequent step. We also find that the probability of conflict and drought across all trajectories is widely dispersed, meaning that there is no typical exposure. This work provides an understanding of the mechanisms underlying displacement patterns and a framework for estimating future movements in areas expected to face increasing hazards.

physics.soc-ph↗

arXiv2025

A Non-Hermitian State-to-State Analysis of Transport in Aggregates with Multiple Endpoints

Efficiency of quantum transport through aggregates with multiple end-points or traps proves to be an emergent and a highly non-equilibrium phenomenon. We present a numerically exact approach for computing the emergent time scale and amount of extraction specific to particular traps leveraging a non-Hermitian generalization of the recently introduced state-to-state transport analysis [Bose and Walters, J. Chem. Theory Comput. 2023, 19, 15, 4828-4836]. This method is able to simultaneously account for the coupling between various sites, the many-body effects brought in by the vibrations and environment held at a non-zero temperature, and the local extraction processes described by non-Hermitian terms in the Hamiltonian. In fact, our non-Hermitian state-to-state analysis goes beyond merely providing an emergent loss time-scale. It can parse the entire dynamics into the constituent internal transport pathways and loss to environment. We demonstrate this method using examples of an exciton transport in a lossy polaritonic cavity. The loss at the cavity and the extraction of the exciton from a terminal molecule provide competing mechanisms that our method helps to unravel, revealing extremely interesting non-intuitive physics. This non-Hermitian state-to-state analysis technique contributes an important link in understanding and elucidating the routes of transport in open quantum systems.

quant-ph↗

arXiv2025

Weed Detection using Convolutional Neural Network

In this paper we use convolutional neural networks (CNNs) for weed detection in agricultural land. We specifically investigate the application of two CNN layer types, Conv2d and dilated Conv2d, for weed detection in crop fields. The suggested method extracts features from the input photos using pre-trained models, which are subsequently adjusted for weed detection. The findings of the experiment, which used a sizable collection of dataset consisting of 15336 segments, being 3249 of soil, 7376 of soybean, 3520 grass and 1191 of broadleaf weeds. show that the suggested approach can accurately and successfully detect weeds at an accuracy of 94%. This study has significant ramifications for lowering the usage of toxic herbicides and increasing the effectiveness of weed management in agriculture.

cs.CV↗

arXiv2024

Impact of Loss Mechanisms on Linear Spectra of Excitonic and Polaritonic Aggregates

The presence of loss mechanisms governed by empirical time-scales affect the dynamics and spectra of systems in profound ways. However, incorporation of these effects and their interaction with the thermal dissipative environments interacting with the system prove to be challenging. We have recently developed the path integral Lindblad dynamics (PILD) method to combine numerically rigorous path integral simulations with Lindblad dynamics to account for such empirical loss mechanisms. In this work, we utilize the PILD method to study the absorption and circular dichroism spectra of chiral molecular aggregates and excitonic polaritons. We demonstrate that the effect of loss on particular states in both systems can differ not just on the basis of the symmetries of the state but also on the basis of complicated "interactions" of the system and the loss mechanism with the dissipative environments. We present probably the first numerical exploration of the CD spectrum of chiral molecular aggregates confined in a cavity. While the CD spectrum of just the excitonic aggregates itself is not amenable to simplistic understanding like the exciton chirality (EC) rule, the CD spectrum of polaritonic molecules is even more complex. Additionally, the impact of empirical loss on the polaritonic CD spectrum seems to be highly site-dependent. The impact of a lossy cavity is qualitatively different from the impact of a molecule that leaks the excitation. We explore some of those effects in depth leveraging the framework of path integral Lindblad dynamics.

physics.chem-ph↗

arXiv2022

Comparison Of Deep Object Detectors On A New Vulnerable Pedestrian Dataset

Pedestrian safety is one primary concern in autonomous driving. The under-representation of vulnerable groups in today's pedestrian datasets points to an urgent need for a dataset of vulnerable road users. In order to help train comprehensive models and subsequently drive research to improve the accuracy of vulnerable pedestrian identification, we first introduce a new dataset for vulnerable pedestrian detection in this paper: the BG Vulnerable Pedestrian (BGVP) dataset. The dataset includes four classes, i.e., Children Without Disability, Elderly without Disability, With Disability, and Non-Vulnerable. This dataset consists of images collected from the public domain and manually-annotated bounding boxes. In addition, on the proposed dataset, we have trained and tested five classic or state-of-the-art object detection models, i.e., YOLOv4, YOLOv5, YOLOX, Faster R-CNN, and EfficientDet. Our results indicate that YOLOX and YOLOv4 perform the best on our dataset, YOLOv4 scoring 0.7999 and YOLOX scoring 0.7779 on the mAP 0.5 metric, while YOLOX outperforms YOLOv4 by 3.8 percent on the mAP 0.5:0.95 metric. Generally speaking, all five detectors do well predicting the With Disability class and perform poorly in the Elderly Without Disability class. YOLOX consistently outperforms all other detectors on the mAP (0.5:0.95) per class metric, obtaining 0.5644, 0.5242, 0.4781, and 0.6796 for Children Without Disability, Elderly Without Disability, Non-vulnerable, and With Disability, respectively. Our dataset and codes are available at https://github.com/devvansh1997/BGVP.

cs.CV↗

arXiv2017

Combining Keystroke Dynamics and Face Recognition for User Verification

The massive explosion and ubiquity of computing devices and the outreach of the web have been the most defining events of the century so far. As more and more people gain access to the internet, traditional know-something and have-something authentication methods such as PINs and passwords are proving to be insufficient for prohibiting unauthorized access to increasingly personal data on the web. Therefore, the need of the hour is a user-verification system that is not only more reliable and secure, but also unobtrusive and minimalistic. Keystroke Dynamics is a novel Biometric Technique; it is not only unobtrusive, but also transparent and inexpensive. The fusion of keystroke dynamics and Face Recognition engenders the most desirable characteristics of a verification system. Our implementation uses Hidden Markov Models (HMM) for modelling the Keystroke Dynamics, with the help of two widely used Feature Vectors: Keypress Latency and Keypress Duration. On the other hand, Face Recognition makes use of the traditional Eigenfaces approach.The results show that the system has a high precision, with a False Acceptance Rate of 5.4% and a False Rejection Rate of 9.2%. Moreover, it is also future-proof, as the hardware requirements, i.e. camera and keyboard (physical or on-screen), have become an indispensable part of modern computing.

cs.HC↗