2 citations · 5 across the 5 of their papers we have counts for
5 papers
Graph-Theoretic Neural Network Fragmentation with Covariant Direct Molecular Force Learning: Enabling Coupled-Cluster Accuracy AIMD for Fluxional Systems
Xiao Zhu, Srinivasan S. Iyengar
Accurate ab initio molecular dynamics (AIMD) simulations of complex, fluxional chemical systems are severely limited by the high computational scaling of correlated electronic stru…
Half the Interference, Most of the Answer: Approximate Quantum Simulation via Path-Sum Pruning
Sinan Pehlivanoglu, Srinivasan Iyengar, Amr Sabry
Classical simulation of quantum circuits is expensive for two distinct reasons. The obvious one is state-space size: an n-qubit system requires exponentially many amplitudes. The l…
Quantum Computing with dartboards
Ishaan Ganti, Srinivasan S. Iyengar
We present a physically appealing and elegant picture for quantum computing using rules constructed for a game of darts. A dartboard is used to represent the state space in quantum…
Analogy between Boltzmann machines and Feynman path integrals
Srinivasan S. Iyengar, Sabre Kais
We provide a detailed exposition of the connections between Boltzmann machines commonly utilized in machine learning problems and the ideas already well known in quantum statistica…
A Synthesis of Hidden Subgroup Quantum Algorithms and Quantum Chemical Dynamics
Srinivasan S. Iyengar, Anup Kumar, Debadrita Saha +1
We describe a general formalism for quantum dynamics and show how this formalism subsumes several quantum algorithms including the Deutsch, Deutsch-Jozsa, Bernstein-Vazirani, Simon…