Publications (18)
Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passes
Daniel Mills, Ifan Williams, Jacob Swain +3
Many quantum software development kits provide a suite of circuit optimisation passes. These passes have been highly optimised and tested in isolation. However, the order in which…
Laughlin states change under large geometry deformations and imaginary time Hamiltonian dynamics
Gabriel Matos, Bruno Mera, José M. Mourão +2
We study the change of the Laughlin states under large deformations of the geometry of the sphere and the plane, associated with Mabuchi geodesics on the space of metrics with Hami…
Fast stabilizer state preparation via AI-optimized graph decimation
Michael Doherty, Matteo Puviani, Jasmine Brewer +4
We propose a general method for preparing stabilizer states with reduced two-qubit gate count and depth compared to the state of the art. The method starts from a graph state repre…
Semi-supervised permutation invariant particle-level anomaly detection
Gabriel Matos, Elena Busch, Ki Ryeong Park +1
The development of analysis methods to distinguish potential beyond the Standard Model phenomena in a model-agnostic way can significantly enhance the discovery reach in collider e…
Efficiently Simulable Pauli Correlation Encoding
Daniele Lizzio Bosco, Gabriel Matos, Chen-Yu Liu +4
Pauli Correlation Encoding (PCE) is a heuristic framework for binary optimisation that encodes classical variables into many-body Pauli observables. While PCE requires fewer qubits…
Trainability of Parametrised Linear Combinations of Unitaries
Nikhil Khatri, Stefan Zohren, Gabriel Matos
A principal concern in the optimisation of parametrised quantum circuits is the presence of barren plateaus, which present fundamental challenges to the scalability of applications…