24 citations · 27 across the 7 of their papers we have counts for
9 papers
Efficient Block Encodings for Ensembles of Molecular Hamiltonians
Cristian L. Cortes, Andrew J. Jenkins, William Pol +8
Accurately characterizing molecular properties and reactivity often requires electronic-structure calculations across an ensemble of molecular geometries. Quantum algorithms that p…
Agentic AI for Density-Functional Development: Revisiting r2SCAN
Santosh Adhikari, Kelsey A. Parker, Etinosa Osaro +2
We demonstrate physics-constrained agentic development of a meta-generalized gradient approximation (meta-GGA) functional using a large language model (LLM) to assist the search an…
RLEASE: Reinforcement Learning Efficient Active Space Engine
Etinosa Osaro, Abhishek Mitra, Andrew J. Jenkins +6
Selecting the active space for multireference electronic-structure calculations is a long-standing bottleneck that often requires expert chemical intuition and costly trial-and-err…
MLIPilot: LLM-Driven Auto-Research for Machine-Learned Interatomic Potentials
Etinosa Osaro, Santosh Adhikari, Stamatia Zavitsanou +2
Constructing production-quality machine-learned interatomic potentials (MLIPs) requires balancing accuracy, dynamical stability, and computational throughput under constraints that…
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…