469 citations · 896 across the 27 of their papers we have counts for
32 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…
Benchmarking a randomized quantum algorithm for estimating expectation values of molecular observables
Anna Schroeder, Gian-Luca R. Anselmetti, Matthias Degroote +5
Randomized quantum algorithms for the estimation of expectation values of molecular observables offer a promising route to early fault-tolerant quantum advantage by trading circuit…
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…
Fullqubit alchemist: Quantum algorithm for alchemical free energy calculations
Po-Wei Huang, Gregory Boyd, Gian-Luca R. Anselmetti +11
Accurately computing the free energies of biological processes is a cornerstone of computer-aided drug design, but it is a daunting task. The need to sample vast conformational spa…
Dividing and Conquering the Van Vleck Catastrophe
Sophia Simon, Gian-Luca R. Anselmetti, Raffaele Santagati +4
The quantum-computational cost of determining ground state energies through quantum phase estimation depends on the overlap between an easily preparable initial state and the targe…
Faster quantum chemistry simulations on a quantum computer with improved tensor factorization and active volume compilation
Athena Caesura, Cristian L. Cortes, William Pol +8
Electronic structure calculations of molecular systems are among the most promising applications for fault-tolerant quantum computing (FTQC) in quantum chemistry and drug design. H…
Classical optimisation of reduced density matrix estimations with classical shadows using N-representability conditions under shot noise considerations
Gian-Luca R. Anselmetti, Matthias Degroote, Nikolaj Moll +2
Classical shadow tomography has become a powerful tool in learning about quantum states prepared on a quantum computer. Recent works have used classical shadows to variationally en…
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…
Amplified Amplitude Estimation: Exploiting Prior Knowledge to Improve Estimates of Expectation Values
Sophia Simon, Matthias Degroote, Nikolaj Moll +3
We provide a method for estimating the expectation value of an operator that can utilize prior knowledge to accelerate the learning process on a quantum computer. Specifically, sup…
Estimation of electrostatic interaction energies on a trapped-ion quantum computer
Pauline J. Ollitrault, Matthias Loipersberger, Robert M. Parrish +12
We present the first hardware implementation of electrostatic interaction energies using a trapped-ion quantum computer. As test system for our computation, we focus on the reducti…
Classical and quantum cost of measurement strategies for quantum-enhanced auxiliary field Quantum Monte Carlo
Matthew Kiser, Anna Schroeder, Gian-Luca R. Anselmetti +4
Quantum-enhanced auxiliary field quantum Monte Carlo (QC-AFQMC) uses output from a quantum computer to increase the accuracy of its classical counterpart. The algorithm requires th…
Improved precision scaling for simulating coupled quantum-classical dynamics
Sophia Simon, Raffaele Santagati, Matthias Degroote +3
We present a super-polynomial improvement in the precision scaling of quantum simulations for coupled classical-quantum systems in this paper. Such systems are found, for example,…
Fault-tolerant quantum algorithm for symmetry-adapted perturbation theory
Cristian L. Cortes, Matthias Loipersberger, Robert M. Parrish +9
The efficient computation of observables beyond the total energy is a key challenge and opportunity for fault-tolerant quantum computing approaches in quantum chemistry. Here we co…
Fault-tolerant quantum computation of molecular observables
Mark Steudtner, Sam Morley-Short, William Pol +8
Over the past three decades significant reductions have been made to the cost of estimating ground-state energies of molecular Hamiltonians with quantum computers. However, compara…
Quantum-enhanced quantum Monte Carlo: an industrial view
Maximilian Amsler, Peter Deglmann, Matthias Degroote +10
In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemist…
Drug design on quantum computers
Raffaele Santagati, Alan Aspuru-Guzik, Ryan Babbush +12
Quantum computers promise to impact industrial applications, for which quantum chemical calculations are required, by virtue of their high accuracy. This perspective explores the c…
Interaction Energies on Noisy Intermediate-Scale Quantum Computers
Matthias Loipersberger, Fionn D. Malone, Alicia R. Welden +7
The computation of interaction energies on noisy intermediate-scale quantum (NISQ) computers appears to be challenging with straightforward application of existing quantum algorith…
Efficient quantum computation of molecular forces and other energy gradients
Thomas E. O'Brien, Michael Streif, Nicholas C. Rubin +12
While most work on the quantum simulation of chemistry has focused on computing energy surfaces, a similarly important application requiring subtly different algorithms is the comp…
Towards the Simulation of Large Scale Protein-Ligand Interactions on NISQ-era Quantum Computers
Fionn D. Malone, Robert M. Parrish, Alicia R. Welden +6
We explore the use of symmetry-adapted perturbation theory (SAPT) as a simple and efficient means to compute interaction energies between large molecular systems with a hybrid meth…
Multi-car paint shop optimization with quantum annealing
Sheir Yarkoni, Alex Alekseyenko, Michael Streif +3
We present a generalization of the binary paint shop problem (BPSP) to tackle an automotive industry application, the multi-car paint shop (MCPS) problem. The objective of the opti…
Quantum algorithms with local particle number conservation: noise effects and error correction
Michael Streif, Martin Leib, Filip Wudarski +2
Quantum circuits with local particle number conservation (LPNC) restrict the quantum computation to a subspace of the Hilbert space of the qubit register. In a noiseless or fault-t…
Beating classical heuristics for the binary paint shop problem with the quantum approximate optimization algorithm
Michael Streif, Sheir Yarkoni, Andrea Skolik +2
The binary paint shop problem (BPSP) is an APX-hard optimization problem of the automotive industry. In this work, we show how to use the Quantum Approximate Optimization Algorithm…