7 papers
Predicting Entanglement Entropy from Particle Tunneling of Interacting Fermions Using Kolmogorov-Arnold Networks
Elvira Bilokon, Valeriia Bilokon, Abhijit Sen +3
Entanglement entropy is a fundamental measure of quantum correlations and a key resource underpinning advances in quantum information and many-body physics. We uncover a universal…
K-U-KAN: Koopman-Enhanced U-KAN for 3D Dental Reconstruction from a Single Panoramic X-ray Radiograph
Bikram Keshari Parida, Abhijit Sen, Wonsang You
A panoramic X-ray compresses a 3D jaw into a 2D strip; we aim to recover the missing depth cleanly and fast. Existing implicit neural representations render realistic volumes but a…
Feature Engineering is Not Dead: Reviving Classical Machine Learning with Entropy, HOG, and LBP Feature Fusion for Image Classification
Abhijit Sen, Giridas Maiti, Bikram K. Parida +3
Feature engineering continues to play a critical role in image classification, particularly when interpretability and computational efficiency are prioritized over deep learning mo…
From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial
Abhijit Sen, Sonali Panda, Mahima Arya +3
This tutorial is designed to make reinforcement learning (RL) more accessible to undergraduate students by offering clear, example-driven explanations. It focuses on bridging the g…
Physics-informed time series analysis with Kolmogorov-Arnold Networks under Ehrenfest constraints
Abhijit Sen, Illya V. Lukin, Kurt Jacobs +3
The prediction of quantum dynamical responses lies at the heart of modern physics. Yet, modeling these time-dependent behaviors remains a formidable challenge because quantum syste…
Input-Output Optics as a Causal Time Series Mapping: A Generative Machine Learning Solution
Abhijit Sen, Bikram Keshari Parida, Kurt Jacobs +1
The response of many-body quantum systems to an optical pulse can be extremely challenging to model. Here we explore the use of neural networks, both traditional and generative, to…