18 papers
DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems
Seongmin Kim, Abhinav Rijal, Yuri Alexeev +5
While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to exponentially large search spaces.…
Pathfinding Quantum Simulations of Neutrinoless Double-Beta Decay
Ivan A. Chernyshev, Roland C. Farrell, Marc Illa +10
We present results from co-designed quantum simulations of the neutrinoless double-beta decay of a simple nucleus in 1+1D quantum chromodynamics using IonQ's Forte-generation trapp…
A Non-Variational Quantum Approach to the Job Shop Scheduling Problem
Miguel Angel Lopez-Ruiz, Emily L. Tucker, Emma M. Arnold +3
Quantum heuristics offer a potential advantage for combinatorial optimization but are constrained by near-term hardware limitations. We introduce Iterative-QAOA, a variant of QAOA…
TorchQuantumDistributed
Oliver Knitter, Jonathan Mei, Masako Yamada +1
TorchQuantumDistributed (tqd) is a PyTorch-based [Paszke et al., 2019] library for accelerator-agnostic differentiable quantum state vector simulation at scale. This enables studyi…
Guided sampling ansätzes for variational quantum computing
Daniel Gunlycke, John P. T. Stenger, Andrii Maksymov +3
Quantum computing is a promising technology because of the ability of quantum computers to process vector spaces with dimensions that increase exponentially with the simulated syst…
Molecular Properties in Quantum-Classical Auxiliary-Field Quantum Monte Carlo: Correlated Sampling with Application to Accurate Nuclear Forces
Joshua J. Goings, Kyujin Shin, Seunghyo Noh +6
We extend correlated sampling from classical auxiliary-field quantum Monte Carlo to the quantum-classical (QC-AFQMC) framework, enabling accurate nuclear force computations crucial…