activity
20202025
most citedMinimum Hardware Requirements for Hybrid Quantum-Classical DMFT

43 citations · 91 across the 7 of their papers we have counts for

collaborators

7 papers

quant-ph2025★ 2 cited

Computing band gaps of periodic materials via sample-based quantum diagonalization

Alan Duriez, Pamela C. Carvalho, Marco Antonio Barroca +7

A key objective of computational solid state physics is to predict electronic properties of periodic materials. However, electronic structure simulations based on density functiona…

quant-ph2025★ 1 cited

Variational preparation of normal matrix product states on quantum computers

Ben Jaderberg, George Pennington, Kate V. Marshall +6

Preparing matrix product states (MPSs) on quantum computers is an essential routine in the simulation of many-body physics. However, widely-used schemes based on staircase circuits…

quant-ph2024★ 1 cited

Potential of quantum scientific machine learning applied to weather modelling

Ben Jaderberg, Antonio A. Gentile, Atiyo Ghosh +5

In this work we explore how quantum scientific machine learning can be used to tackle the challenge of weather modelling. Using parameterised quantum circuits as machine learning m…

quant-ph2023★ 23 cited

Let Quantum Neural Networks Choose Their Own Frequencies

Ben Jaderberg, Antonio A. Gentile, Youssef Achari Berrada +2

Parameterized quantum circuits as machine learning models are typically well described by their representation as a partial Fourier series of the input features, with frequencies u…

quant-ph2022★ 19 cited

Recompilation-enhanced simulation of electron-phonon dynamics on IBM Quantum computers

Ben Jaderberg, Alexander Eisfeld, Dieter Jaksch +1

Simulating quantum systems is believed to be one of the first applications for which quantum computers may demonstrate a useful advantage. For many problems in physics, we are inte…

quant-ph2021★ 2 cited

Quantum Self-Supervised Learning

Ben Jaderberg, Lewis W. Anderson, Weidi Xie +3

The resurgence of self-supervised learning, whereby a deep learning model generates its own supervisory signal from the data, promises a scalable way to tackle the dramatically inc…

quant-ph2020★ 43 cited

Minimum Hardware Requirements for Hybrid Quantum-Classical DMFT

Ben Jaderberg, Abhishek Agarwal, Karsten Leonhardt +2

We numerically emulate noisy intermediate-scale quantum (NISQ) devices and determine the minimal hardware requirements for two-site hybrid quantum-classical dynamical mean-field th…