120 citations · 184 across the 7 of their papers we have counts for
7 papers
Simulating groundstate and dynamical quantum phase transitions on a superconducting quantum computer
James Dborin, Vinul Wimalaweera, Fergus Barratt +3
We optimise a translationally invariant, sequential quantum circuit on a superconducting quantum device to simulate the groundstate of the quantum Ising model through its quantum c…
Deterministic Tensor Network Classifiers
L. Wright, F. Barratt, J. Dborin +3
We present tensor networks for feature extraction and refinement of classifier performance. These networks can be initialised deterministically and have the potential for implement…
Improvements to Gradient Descent Methods for Quantum Tensor Network Machine Learning
Fergus Barratt, James Dborin, Lewis Wright
Tensor networks have demonstrated significant value for machine learning in a myriad of different applications. However, optimizing tensor networks using standard gradient descent…
Matrix Product State Pre-Training for Quantum Machine Learning
James Dborin, Fergus Barratt, Vinul Wimalaweera +2
Hybrid Quantum-Classical algorithms are a promising candidate for developing uses for NISQ devices. In particular, Parametrised Quantum Circuits (PQCs) paired with classical optimi…
Automatic Post-selection by Ancillae Thermalisation
Lewis Wright, Fergus Barratt, James Dborin +2
Tasks such as classification of data and determining the groundstate of a Hamiltonian cannot be carried out through purely unitary quantum evolution. Instead, the inherent non-unit…
Parallel Quantum Simulation of Large Systems on Small Quantum Computers
Fergus Barratt, James Dborin, Matthias Bal +3
Tensor networks permit computational and entanglement resources to be concentrated in interesting regions of Hilbert space. Implemented on NISQ machines they allow simulation of qu…
Optimal local unitary encoding circuits for the surface code
Oscar Higgott, Matthew Wilson, James Hefford +4
The surface code is a leading candidate quantum error correcting code, owing to its high threshold, and compatibility with existing experimental architectures. Bravyi et al. (2006)…