activity
19922023
most citedParton distributions for the LHC Run II

2.6k citations · 12.9k across the 86 of their papers we have counts for

collaborators

88 papers

quant-ph2023★ 16 cited

Efficient option pricing with unary-based photonic computing chip and generative adversarial learning

Hui Zhang, Lingxiao Wan, Sergi Ramos-Calderer +9

In the modern financial industry system, the structure of products has become more and more complex, and the bottleneck constraint of classical computing power has already restrict…

quant-ph2021★ 6 cited

An Optimized Quantum Implementation of ISD on Scalable Quantum Resources

Andre Esser, Sergi Ramos-Calderer, Emanuele Bellini +2

The security of code based constructions is usually assessed by Information Set Decoding (ISD) algorithms. In the quantum setting, amplitude amplification yields an asymptotic squa…

quant-ph2021★ 9 cited

Solving systems of Boolean multivariate equations with quantum annealing

Sergi Ramos-Calderer, Carlos Bravo-Prieto, Ruge Lin +4

Polynomial systems over the binary field have important applications, especially in symmetric and asymmetric cryptanalysis, multivariate-based post-quantum cryptography, coding the…

hep-ph2021

An open-source machine learning framework for global analyses of parton distributions

Richard D. Ball, Stefano Carrazza, Juan Cruz-Martinez +14

We present the software framework underlying the NNPDF4.0 global determination of parton distribution functions (PDFs). The code is released under an open source licence and is acc…

hep-ph2021★ 429 cited

The Path to Proton Structure at One-Percent Accuracy

Richard D. Ball, Stefano Carrazza, Juan Cruz-Martinez +14

We present a new set of parton distribution functions (PDFs) based on a fully global dataset and machine learning techniques: NNPDF4.0. We expand the NNPDF3.1 determination with 44…

quant-ph2021★ 17 cited

Variational Quantum Eigensolver for SU() Fermions

Mirko Consiglio, Wayne J. Chetcuti, Carlos Bravo-Prieto +5

Variational quantum algorithms aim at harnessing the power of noisy intermediate-scale quantum computers, by using a classical optimizer to train a parameterized quantum circuit to…