83 citations · 234 across the 18 of their papers we have counts for
9 papers · 1 filter
Robust Quantum Machine Learning for Collider Event Selection under Detector Variability
Christopher Brown, Michael Spannowsky, Simon Williams
Robust machine-learning methods are becoming increasingly important for high-energy physics data analysis as experiments enter the era of higher luminosity and future higher-energy…
Continuous-variable photonic quantum extreme learning machines for fast collider-data selection
Benedikt Maier, Michael Spannowsky, Simon Williams
We study continuous-variable photonic quantum extreme learning machines as fast, low-overhead front-ends for collider data processing. Data is encoded in photonic modes through qua…
Qumode Tensor Networks for False Vacuum Decay in Quantum Field Theory
Steven Abel, Michael Spannowsky, Simon Williams
False vacuum decay in scalar quantum field theory (QFT) is a cornerstone of early Universe cosmology and high energy physics, yet its real-time dynamics is essentially inaccessible…
Real-Time Scattering on Quantum Computers via Hamiltonian Truncation
James Ingoldby, Michael Spannowsky, Timur Sypchenko +2
We present a quantum computational framework using Hamiltonian Truncation (HT) for simulating real-time scattering processes in -dimensional scalar theory. Unlike trad…
Real-Time Scattering Processes with Continuous-Variable Quantum Computers
Steven Abel, Michael Spannowsky, Simon Williams
We propose a framework for simulating the real-time dynamics of quantum field theories (QFTs) using continuous-variable quantum computing (CVQC). Focusing on ()-dimensional $φ…
The role of data embedding in quantum autoencoders for improved anomaly detection
Jack Y. Araz, Michael Spannowsky
The performance of Quantum Autoencoders (QAEs) in anomaly detection tasks is critically dependent on the choice of data embedding and ansatz design. This study explores the effects…
Enhancing Quantum Field Theory Simulations on NISQ Devices with Hamiltonian Truncation
James Ingoldby, Michael Spannowsky, Timur Sypchenko +1
Quantum computers can efficiently simulate highly entangled quantum systems, offering a solution to challenges facing classical simulation of Quantum Field Theories (QFTs). This pa…
Simulating quantum field theories on continuous-variable quantum computers
Steven Abel, Michael Spannowsky, Simon Williams
We delve into the use of photonic quantum computing to simulate quantum mechanics and extend its application towards quantum field theory. We develop and prove a method that levera…
Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms
Jack Y. Araz, Michael Spannowsky, Matthew Wingate
This study investigates the thermal properties of the repulsive Fermi-Hubbard model with chemical potential using variational quantum algorithms, crucial in comprehending particle…