Our Research

In a field prone to hype, we peer-review our claims, we validate every algorithm on real quantum hardware across multiple platforms, and we ground every application we pursue in reproducible science.

Peer-Reviewed

Peer-Reviewed

Our work is published in top-tier journals and rigorously reviewed by the scientific community.

Our work is published in top-tier journals and rigorously reviewed by the scientific community.

Hardware Validated

Hardware Validated

Algorithms tested on real quantum hardware across Google, IBM, Quantinuum, Rigetti, and QuEra.

Algorithms tested on real quantum hardware across Google, IBM, Quantinuum, Rigetti, and QuEra.

Reproducible

Reproducible

Open methodology and transparent reporting enable independent verification of our results.

Open methodology and transparent reporting enable independent verification of our results.

Record-Breaking Achievements

Record-Breaking
Achievements

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M x

Algorithmic efficiency improvement over previous quantum methods

Nature Communications

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K x

Complexity improvement for quantum dynamics simulation

Nature Communications

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x

More operations than previous experiments

Nature Communications

Research Areas

Quantum Algorithm Design

Developing novel algorithms that bridge the gap between classical and quantum computing for practical applications.

Materials Science

Optimization Problems

Error Mitigation

a blue background with lines and dots

Research Areas

Quantum Algorithm Design

Developing novel algorithms that bridge the gap between classical and quantum computing for practical applications.

Materials Science

Optimization Problems

Error Mitigation

a blue background with lines and dots

Research Areas

Quantum Algorithm Design

Developing novel algorithms that bridge the gap between classical and quantum computing for practical applications.

Materials Science

Optimization Problems

Error Mitigation

a blue background with lines and dots

Publications

View all our collected research below.

Research paper: Strategies for solving the Fermi-Hubbard model on near-term quantum computers

QUANTUM COMPUTER

2019

Cade, C., et al.

Research paper: Mitigating Errors in Local Fermionic Encodings

QUANTUM COMPUTER

2020

Bausch, J., et al.

Research paper: Compressed variational quantum eigensolver for the Fermi-Hubbard model

QUANTUM COMPUTER

2020

Ashley Montanaro, Stasja Stanisic

Research paper: Low Weight Fermionic Encodings for Lattice Models

QUANTUM COMPUTER

2020

Charles Derby, Joel Klassen

Research paper: Error mitigation by training with fermionic linear optics

QUANTUM COMPUTER

2021

Ashley Montanaro, Stasja Stanisic

Research paper: Hamiltonian Simulation Algorithms for Near-Term Quantum Hardware

QUANTUM COMPUTER

2020

Laura Clinton, Johannes Bausch, Toby Cubitt

Research paper: Probing ground state properties of the kagome antiferromagnetic Heisenberg model using the Variational Quantum Eigensolver

QUANTUM COMPUTER

2021

Jan Lukas Bosse, Ashley Montanaro

Peptide conformational sampling using the Quantum Approximate Optimization Algorithm

QUANTUM COMPUTER

2022

Adaszewski, S., et al.

Research paper: Predicting parameters for the Quantum Approximate Optimization Algorithm for MAX-CUT from the infinite-size limit

QUANTUM COMPUTER

2021

Sami Boulebnane, Ashley Montanaro

Back to research Solving boolean satisfiability problems with the quantum approximate optimization algorithm

QUANTUM COMPUTER

2022

Sami Boulebnane, Ashley Montanaro

Accelerating the variational quantum eigensolver using parallelism

QUANTUM COMPUTER

2022

Lana Mineh, Ashley Montanaro

Optimizing fermionic encodings for both Hamiltonian and hardware

QUANTUM COMPUTER

2022

Riley W. Chien, Joel Klassen

Towards near-term quantum simulation of materials

QUANTUM COMPUTER

2022

Clinton, L., et al.

Sketching phase diagrams using low-depth variational quantum algorithms

QUANTUM COMPUTER

2023

Jan Lukas Bosse, Raul Santos, Ashley Montanaro

Dissipative ground state preparation and the dissipative quantum eigensolver

QUANTUM COMPUTER

2023

Toby S. Cubitt

Accelerating variational quantum Monte Carlo using the variational quantum eigensolver

QUANTUM COMPUTER

2023

Quantum Error Transmutation

QUANTUM COMPUTER

2023

Cubitt, T., & Zhang, D.

Enhancing density functional theory using the variational quantum eigensolver

QUANTUM COMPUTER

2024

Cubitt, T., et al.

Efficient and practical Hamiltonian simulation from time-dependent product formulas

QUANTUM COMPUTER

2024

Bosse, J. L., et al.

Unveiling quantum phase transitions from traps in variational quantum algorithms

QUANTUM COMPUTER

2024

Cao, C., et al.

Approximating dynamical correlation functions with constant depth quantum circuits

QUANTUM COMPUTER

2024

Irmejs, R., & Santos, R. A.

Quantum Phase Estimation without Controlled Unitaries

QUANTUM COMPUTER

2024

Clinton, L., et al.

Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver

QUANTUM COMPUTER

2024

Jones, B. D. M., et al.

Quantum speedups in solving near-symmetric optimization problems by low-depth QAOA

QUANTUM COMPUTER

2024

Montanaro, A., & Zhou, L.

Applying the quantum approximate optimization algorithm to general constraint satisfaction problems

QUANTUM COMPUTER

2024

Boulebnanea, S., et al.

Quantum-enhanced belief propagation for LDPC decoding

QUANTUM COMPUTER

2024

Montanaro, A., & Perez-Garcia, S. M.

Extracting the spin excitation spectrum of a fermionic system using a quantum processor

QUANTUM COMPUTER

2025

Gambetta, F. M., et al.

Fermionic Averaged Circuit Eigenvalue Sampling

QUANTUM COMPUTER

2025

Chapman, A., & Flammia, S. T.

Challenges and Advances in the Simulation of Targeted Covalent Inhibitors Using Quantum Computing

QUANTUM COMPUTER

2025

Amory, R., et al.

Robust Lindbladian Estimation for Quantum Dynamics

QUANTUM COMPUTER

2025

Cubitt, T. S., et al.

Fermionic dynamics on a trapped-ion quantum computer beyond exact classical simulation

QUANTUM COMPUTER

2025

Cubitt, T., et al.

Quantum-Enhanced Optimization by Warm Starts

QUANTUM COMPUTER

2025

Čepaitė, I., et al.

Improving time dynamics simulation by sampling the error unitary

SIMULATION

2025

Chapman, A., et al.

Programmable digital quantum simulation of 2D Fermi-Hubbard dynamics using 72 superconducting qubits

SIMULATION

2025

Montanaro, A., et al.

Interested in collaborating?

We partner with leading academic institutions and industrial research labs to advance the state of quantum computing.