2 citations · 3 across the 10 of their papers we have counts for
12 papers
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…
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…
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…
Protein folding with an all-to-all trapped-ion quantum computer
Sebastián V. Romero, Alejandro Gomez Cadavid, Pavle Nikačević +8
We experimentally demonstrate that the bias-field digitized counterdiabatic quantum optimization (BF-DCQO) algorithm, implemented on IonQ's fully connected trapped-ion quantum proc…
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 New Hybrid Quantum-Classical Algorithm for Solving the Unit Commitment Problem
Willie Aboumrad, Phani R V Marthi, Suman Debnath +2
Solving problems related to planning and operations of large-scale power systems is challenging on classical computers due to their inherent nature as mixed-integer and nonlinear p…
Algorithmic Advances Towards a Realizable Quantum Lattice Boltzmann Method
Apurva Tiwari, Jason Iaconis, Jezer Jojo +4
The Quantum Lattice Boltzmann Method (QLBM) is one of the most promising approaches for realizing the potential of quantum computing in simulating computational fluid dynamics. Man…
Accelerating large-scale linear algebra using variational quantum imaginary time evolution
Willie Aboumrad, Daiwei Zhu, Claudio Girotto +6
The solution of large sparse linear systems via factorization methods such as LU or Cholesky decomposition, can be computationally expensive due to the introduction of non-zero ele…
Quantum Large Language Model Fine-Tuning
Sang Hyub Kim, Jonathan Mei, Claudio Girotto +2
We introduce a hybrid quantum-classical deep learning architecture for large language model fine-tuning. The classical portion of the architecture is a sentence transformer that is…
End-to-End Demonstration of Quantum Generative Adversarial Networks for Steel Microstructure Image Augmentation on a Trapped-Ion Quantum Computer
Samwel Sekwao, Jason Iaconis, Claudio Girotto +6
Generative adversarial networks (GANs) are a machine learning technique capable of producing high-quality synthetic images. In the field of materials science, when a crystallograph…
Quantum Computing for Optimizing Aircraft Loading
Ananth Kaushik, Sang Hyub Kim, Willie Aboumrad +3
The aircraft loading optimization problem is a computationally hard problem with the best known classical algorithm scaling exponentially with the number of objects. We propose a q…