3 papers
quant-ph2026
Physics-Informed Generative Machine Learning for Accelerated Quantum-centric Supercomputing
Chayan Patra, Dibyendu Mondal, Sonaldeep Halder +4
Quantum centric supercomputing (QCSC) framework, such as sample-based quantum diagonalization (SQD) holds immense promise toward achieving practical quantum utility to solve challe…
quant-ph2025
Fragment, Entangle, and Consolidate: Strong Correlation through Bi-fold Quantum Circuits
Arpan Choudhury, Sonaldeep Halder, Rahul Maitra +1
An accurate description of strong correlation is quintessential for the exploration of emerging chemical phenomena. While near-term variational quantum algorithms provide a theoret…
physics.chem-ph2025
Construction of Chemistry Inspired Dynamic Ansatz Utilizing Generative Machine Learning
Sonaldeep Halder, Kartikey Anand, Rahul Maitra
Generative machine learning models like the Restricted Boltzmann Machine (RBM) provide a practical approach for ansatz construction within the quantum computing framework. This wor…