activity
20242026
collaborators

9 papers

quant-ph2026

Advancing Practical Quantum Embedding Simulations via Operator Commutativity Based State Preparation for Complex Chemical Systems

Dibyendu Mondal, Ashish Kumar Patra, Rahul Maitra

Determining the exponentially scaled ground state wavefunction and the associated molecular properties remains one of the central challenges in quantum chemistry. Hybrid quantum-cl…

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

Operator Commutativity Screening and Progressive Operator Block Reordering toward Many-body Inspired Quantum State Preparation

Dibyendu Mondal, Debaarjun Mukherjee, Rahul Maitra

In the field of quantum chemistry, the variational quantum eigensolver (VQE) has emerged as a highly promising approach to determine molecular energies and properties within the no…

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…

quant-ph2025

Efficient quantum state preparation through seniority driven operator selection

Dipanjali Halder, Dibyendu Mondal, Rahul Maitra

Quantum algorithms require accurate representations of electronic states on a quantum device, yet the approximation of electronic wave functions for strongly correlated systems rem…

quant-ph2025

Energy Landscape Plummeting in Variational Quantum Eigensolver: Subspace Optimization, Non-iterative Corrections and Generator-informed Initialization for Improved Quantum Efficiency

Chayan Patra, Rahul Maitra

Variational Quantum Eigensolver (VQE) faces significant challenges due to hardware noise and the presence of barren plateaus and local traps in the optimization landscape. To mitig…