Author

Avinash Singh

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#machine learning Jul 2025

Meta-learning of Gibbs states for many-body Hamiltonians with applications to Quantum Boltzmann Machines

Two meta-learning algorithms are introduced: Meta-Variational Quantum Thermalizer (Meta-VQT) and Neural Network Meta-VQT (NN-Meta VQT) for efficient thermal state preparation of parametrized Hamiltonians on Noisy Intermediate-Scale Quantum (NISQ) devices and a Quantum Boltzmann Machine (QBM) on a 2-qubit Heisenberg mod...

R. V. Bhat, Rahul Bhowmick, Avinash Singh et al. · arXiv.org · 3 citations

#machine learning Preprint Mar 2025

Reducing QPU Calls in Variational Quantum Algorithms via Classical Offloading of Gradient Computation

This work evaluates ground-state estimation of 6- to 18-qubit Hamiltonians using the Variational Quantum Eigensolver (VQE) and quantum phase classification for Hamiltonians up to 12 qubits and uses these methods as a warm-start pretraining strategy for Hamiltonians with exponential-dimensional dynamical Lie algebras.

Rahul Bhowmick, Harsh Wadhwa, Avinash Singh et al. · 4 citations