A5101562471- Particle physics theoretical and experimental studies
- Quantum Computing Algorithms and Architecture
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
- Quantum-Dot Cellular Automata
- Advanced Data Storage Technologies
- Dark Matter and Cosmic Phenomena
- Quantum Information and Cryptography
University College London
2022
Imperial College London
2014-2021
Rockefeller University
2014
This paper presents a novel quantum walk approach to simulating parton showers on computer. We demonstrate that the paradigm offers natural and more efficient devices, with emission probabilities implemented as coin flip for walker, particle emissions either gluons or quark pairs corresponding movement of walker in two dimensions. A algorithm is proposed simplified, toy model 31-step, collinear shower, hence significantly increasing number steps shower can be simulated compared previous...
The interpretation of measurements high-energy particle collisions relies heavily on the performance full event generators, which include calculation hard process and subsequent parton shower step. With continuous improvement quantum devices, dedicated algorithms are needed to exploit potential that computers can provide. We propose general extendable for gate facilitate calculations helicity amplitudes process. amplitude exploits equivalence between spinors qubits unique features a computer...
We motivate a measurement of various ratios W and Z cross sections at the Large Hadron Collider (LHC) large values boson transverse momentum (p T ≳ M W,Z ). study dependence predictions for these cross-section on multiplicity associated jets, p LHC centre-of-mass energy. present flavour decomposition initial-state partons an evaluation theoretical uncertainties. show that + /W − ratio is sensitive to up-quark down-quark parton distribution functions (PDFs), while other uncertainties are...
Galaxy morphology, a key tracer of the evolution galaxy's physical structure, has motivated extensive research on machine learning techniques for efficient and accurate galaxy classification. The emergence quantum computers generated optimism about potential significantly improving accuracy such classifications by leveraging large dimensionality Hilbert space. This paper presents quantum-enhanced support vector algorithm classifying galaxies based their morphology. requires computation...