collaborators

7 papers

quant-ph2026

Performance Model for Hybrid Quantum-Classical Workflows

Pooja Rao, Dimitar Trenev, Jerome Gonthier +13

Hybrid quantum-classical workflows are expected to underpin practical quantum computing applications, yet the quantum and HPC communities lack a shared framework for reasoning abou…

cs.LG2026

MōLe-Λ: Learning the Coupled-Cluster Response State for Energies, Gradients, and Properties

Andreas Burger, Luca Thiede, Abdulrahman Aldossary +4

Coupled-cluster (CC) theory is often considered the gold standard of quantum chemistry, but its high computational cost limits routine access to accurate energies, forces and respo…

quant-ph2026

Optimizing ground state preparation protocols with autoresearch

Luis Mantilla Calderón, Jérôme F. Gonthier, Ignacio Gustin +2

Artificial intelligent language-model based coding agents have significantly changed the way we interact with computers in our day-to-day, as it is common to use them to create, im…

quant-ph2026

El Agente Cuantico: Automating quantum simulations

Ignacio Gustin, Luis Mantilla Calderón, Juan B. Pérez-Sánchez +8

Quantum simulation is central to understanding and designing quantum systems across physics and chemistry. Yet it has barriers to access from both computational complexity and comp…

cs.LG2026

Coupled Cluster con MōLe: Molecular Orbital Learning for Neural Wavefunctions

Luca Thiede, Abdulrahman Aldossary, Andreas Burger +9

Density functional theory (DFT) is the most widely used method for calculating molecular properties; however, its accuracy is often insufficient for quantitative predictions. Coupl…

quant-ph2025

Quantum simulation of carbon capture in periodic metal-organic frameworks

Dario Rocca, Jerome F. Gonthier, Joshua Levin +4

Carbon capture is vital for decarbonizing heavy industries such as steel and chemicals. Metal-organic frameworks (MOFs), with their high surface area and structural tunability, are…