Quantum-enhanced proposal distributions, defined by parameterized unitaries, showed potential for outperforming classical strategies in proposing effective moves in Monte Carlo Markov chains (MCMC). However, it is crucial to carefully tune the parameters defining these distributions, as they determine the resulting advantage over the classical counterpart. In the present work, we propose a general optimisation algorithm that exploits estimates of the autocorrelation function of a certain observable to optimise the parameters defining the proposal distributions. A Python simulator of the first version of the algorithm is available on my GitHub.
Supervisors: Prof. Crispin Barnes, Prof. Giuseppe Carleo, Dr. Hugo V. Lepage.
Colleagues: Chris Long
During my internship at IQM Quantum Computers, as part of the DAS Team (Design and Simulation Team), I worked on the development of software tools for automating the simulation and design of superconducting Quantum Processing Units (QPUs). A small part of my contributions can be found here (public projects only).
Supervisors: Dr. Alessandro Landra, Dr. Caspar Ockeloen-Korppi
In the present work we aim to optimize the design of a coupled resonator waveguide QED (Quantum Electrodynamics) to obtain flat transmission on a defined frequency range through apodization of the transmission peaks. Apodized coupled resonator waveguides have been used for filtering applications as they operate as band-pass filters. However, in recent years these devices have captivated more interest because of their possible use in slow light applications.
Supervisor: Prof. Pasquale Scarlino
Colleagues: Dr. Vincent Jouanny, Gabriele Libardi
This work aims to investigate which are the best rapid thermal annealing (RTA) parameters for crystallizing Germanium nanowires grown on a patterned Silicon substrate, obtaining optimal crystal quality. This is crucial for utilizing the nanowires to produce fully functioning hole spin qubits.
Supervisor: Prof. Anna Fontcuberta i Morral.
Colleagues: Dr. Santhanu Panikar Ramanandan