24 citations · 30 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
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…
Improving the runtime of quantum phase estimation for chemistry through basis set optimization
Pauline J. Ollitrault, Jerome F. Gonthier, Dario Rocca +5
Quantum phase estimation (QPE) is a promising quantum algorithm for obtaining molecular ground-state energies with chemical accuracy. However, its computational cost, dominated by…
Enhancing initial state overlap through orbital optimization for faster molecular electronic ground-state energy estimation
Pauline J. Ollitrault, Cristian L. Cortes, Jerome F. Gonthier +7
The quantum phase estimation algorithm stands as the primary method for determining the ground state energy of a molecular electronic Hamiltonian on a quantum computer. In this con…
Reducing the runtime of fault-tolerant quantum simulations in chemistry through symmetry-compressed double factorization
Dario Rocca, Cristian L. Cortes, Jerome Gonthier +7
Quantum phase estimation based on qubitization is the state-of-the-art fault-tolerant quantum algorithm for computing ground-state energies in chemical applications. In this contex…
Assessing the query complexity limits of quantum phase estimation using symmetry aware spectral bounds
Cristian L. Cortes, Dario Rocca, Jerome Gonthier +7
The computational cost of quantum algorithms for physics and chemistry is closely linked to the spectrum of the Hamiltonian, a property that manifests in the necessary rescaling of…