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20202026
most citedPotential Applications of Quantum Computing at Los Alamos National Laboratory

3 citations · 3 across the 12 of their papers we have counts for

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5 papers · 1 filter

quant-ph2026

Conditions for Quantum Advantage in AC Power Flow

Parikshit Pareek, Abhijith Jayakumar, Carleton Coffrin +1

This paper aims to contextualize the requirements for Quantum Computing (QC) algorithms to achieve a quantum advantage in solving the alternating current power flow (ACPF) problem,…

cs.LG2026

Finite Sample Bounds for Learning with Score Matching

Devin Smedira, Abhijith Jayakumar, Sidhant Misra +2

Learning of continuous exponential family distributions with unbounded support remains an important area of research for both theory and applications in high-dimensional statistics…

quant-ph2026

The Quantum Hamiltonian Analysis Toolkit: Lowering the Barrier to Quantum Computing with Hamiltonians

Brendan K. Krueger, Stephan Eidenbenz, Shamminuj Aktar +8

We present the Quantum Hamiltonian Analysis Toolkit (QHAT), a newly developed application that provides a user-friendly interface for studying Hamiltonians and performing Hamiltoni…

cs.LG2026

Computationally sufficient statistics for Ising models

Abhijith Jayakumar, Shreya Shukla, Marc Vuffray +2

Learning Gibbs distributions using only sufficient statistics has long been recognized as a computationally hard problem. On the other hand, computationally efficient algorithms fo…

cs.LG2026

Discrete Diffusion with Sample-Efficient Estimators for Conditionals

Karthik Elamvazhuthi, Abhijith Jayakumar, Andrey Y. Lokhov

We study a discrete denoising diffusion framework that integrates a sample-efficient estimator of single-site conditionals with round-robin noising and denoising dynamics for gener…