7 citations · 15 across the 16 of their papers we have counts for
18 papers
Geometric Kolmogorov--Arnold Network (GeoKAN)
Abhijit Sen, Bikram Keshari Parida, Giridas Maiti +2
We introduce Geometric Kolmogorov--Arnold Networks (GeoKANs), a family of geometry-aware KAN-type models in which approximation is carried out in learned, geometry-adapted coordina…
Symplectic split-operator method for the time-dependent unitary Tavis-Cummings model
Roman Ovsiannikov, Kurt Jacobs, Andrii G. Sotnikov +1
We present a fast, memory-efficient, unitarity-preserving numerical method beyond the rotating-wave approximation for the closed Tavis-Cummings model in which a multilevel spin sys…
The Birth of Quantum Mechanics and the Dirac Equation
Volodimir Simulik, Denys I. Bondar
The year 2025 marked the centennial of quantum mechanics, inaugurated by Heisenberg's matrix formulation and the foundational contributions of Pauli, Schrodinger, and Dirac. Concur…
NV-ensemble enabled microwave/NV parametric amplifier with optimal driving
Roman Ovsiannikov, Kurt Jacobs, Andrii G. Sotnikov +2
In our recent study [arXiv:2601.03407] we showed that a hybrid non-degenerate parametric amplifier could be realized for a microwave mode and an ensemble of NV-centers (or other sp…
Symplectic Split-Operator Propagators from Tridiagonalized Multi-Mode Bosonic Hilbert Spaces for Bose-Hubbard Hamiltonians
Denys I. Bondar, Ole Steuernagel
In this methods paper, we show how to tridia\-go\-nalize two families of bosonic multimode systems: optomechanical and Bose-Hubbard hamiltonians. Using tools from number theory, we…
Hilbert Space Black Hole Analog: Unidirectional Transport without Driving
Elvira Bilokon, Valeriia Bilokon, Frank Großmann +2
Black holes permit matter to cross their event horizon in only one direction. We show that interacting bosons in optical lattices with asymmetric barrier exhibit an analogous pheno…
Hybrid non-degenerate parametric amplifier for a microwave cavity mode and an NV ensemble
Roman Ovsiannikov, Kurt Jacobs, Andrii G. Sotnikov +2
We introduce an implementation of a non-degenerate parametric amplifier in which the signal and idler modes, respectively, a microwave mode and an ensemble of spins (e.g., nitrogen…
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…
Generalized Boundary Conditions for the qBounce Experiment
Eric J. Sung, Benjamin Koch, Tobias Jenke +2
Discrepancies between theory and recent qBounce data have prompted renewed scrutiny of how boundary conditions are implemented for ultracold neutrons bouncing above a mirror in Ear…
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…
The Mass and Velocity of Light from Energy and Momentum Conservation
Volodimir Simulik, Denys I. Bondar
While the numerical value of the speed of light is known with extraordinary precision, its theoretical definition remains a subject of fundamental interest. We show that the defini…
Unitary Gate Synthesis via Polynomial Optimization
Llorenç Balada Gaggioli, Denys I. Bondar, Jiri Vala +2
Quantum optimal control plays a crucial role in the development of quantum technologies, particularly in the design and implementation of fast and accurate gates for quantum comput…
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…
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…
Enhancement of superconducting pairing via quantum Lyapunov control
Oleksandr Povitchan, Denys I. Bondar, Andrii G. Sotnikov
We demonstrate that quantum Lyapunov control provides an effective strategy for enhancing superconducting correlations in the Fermi-Hubbard model without requiring careful paramete…
Few-fermion resonant tunneling and underbarrier trapping in asymmetric potentials
Elvira Bilokon, Valeriia Bilokon, Dusty R. Lindberg +3
Understanding quantum tunneling in many-body systems is crucial for advancing quantum technologies and nanoscale device design. Despite extensive studies of quantum tunneling, the…
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…
Physics Informed Kolmogorov-Arnold Neural Networks for Dynamical Analysis via Efficent-KAN and WAV-KAN
Subhajit Patra, Sonali Panda, Bikram Keshari Parida +4
Physics-informed neural networks have proven to be a powerful tool for solving differential equations, leveraging the principles of physics to inform the learning process. However,…