11 citations · 17 across the 9 of their papers we have counts for
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Quantum Wavefunction Augmentation via Variational Autoencoders
Sonaldeep Halder, Chayan Patra, Rahul Maitra
Sample-based quantum diagonalization (SQD) has emerged as a promising route for quantum-centric supercomputing, relying on classical diagonalization of the molecular Hamiltonian wi…
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…
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…
Projective Quantum Eigensolver with Generalized Operators
Dibyendu Mondal, Chayan Patra, Dipanjali Halder +1
Determination of molecular energetics and properties is one of the core challenges in the near-term quantum computing. To this end, hybrid quantum-classical algorithms are preferre…
Towards a Resource-Optimized Dynamic Quantum Algorithm via Non-iterative Auxiliary Subspace Corrections
Chayan Patra, Debaarjun Mukherjee, Sonaldeep Halder +2
Recent quantum algorithms pertaining to electronic structure theory primarily focus on threshold-based dynamic construction of ansatz by selectively including important many-body o…
Projective Quantum Eigensolver via Adiabatically Decoupled Subsystem Evolution: a Resource Efficient Approach to Molecular Energetics in Noisy Quantum Computers
Chayan Patra, Sonaldeep Halder, Rahul Maitra
Quantum computers hold immense potential in the field of chemistry, ushering new frontiers to solve complex many body problems that are beyond the reach of classical computers. How…
Machine Learning Aided Dimensionality Reduction towards a Resource Efficient Projective Quantum Eigensolver
Sonaldeep Halder, Chayan Patra, Dibyendu Mondal +1
The recently developed Projective Quantum Eigensolver (PQE) has been demonstrated as an elegant methodology to compute the ground state energy of molecular systems in Noisy Intermd…