arXiv subjects

Nuno Filipe Castro

Publications and source records attributed to Nuno Filipe Castro.

15 recordsLinked to original sources

arXiv2026

BSMArt 2: simpler and faster parameter space scans

We present version 2 of BSMArt, a powerful yet lightweight scanning tool designed to simplify the exploration of parameter spaces of new physics models. Aside from architectural improvements, simpler installation and expanded documentation with examples, the new version includes additional tools and new machine learning and Monte Carlo scanning algorithms: Affine MC, Contour Finding, MLScanner, DLScanner, MLS, and CMA-ES. We showcase two variants of CMA-ES scans with physics applications relevant for soft lepton excesses at the LHC. We demonstrate that it is easily possible to find diverse and interesting parameter points for future testing.

hep-ph↗

arXiv2025

Jet evolution in a quantum computer: quark and gluon dynamics

The intrinsic quantum nature of jets and the Quark-Gluon Plasma makes the study of jet quenching a promising candidate to benefit from quantum computing power. Standing as a precursor of the full study of this phenomenon, we study the propagation of SU(3) partons in Quark-Gluon Plasma using quantum simulation algorithms. The algorithms are developed in detail, and the propagation of both quarks and gluons is analysed and compared with analytical expectations. The results, obtained with quantum simulators, demonstrate that the algorithm successfully simulates parton propagation, yielding results consistent with analytical baseline calculations.

hep-ph↗

arXiv2025

Exploring Scotogenic Parameter Spaces and Mapping Uncharted Dark Matter Phenomenology with Multi-Objective Search Algorithms

We present a novel artificial intelligence approach to explore beyond Standard Model parameter spaces by leveraging a multi-objective optimisation algorithm. We apply this methodology to a non-minimal scotogenic model which is constrained by Higgs mass, anomalous magnetic moment of the muon, dark matter relic density, dark matter direct detection, neutrino masses and mixing, and lepton flavour violating processes. Our results successfully expand on the phenomenological realisations presented in previous work. We compare between multi- and single-objective algorithms and we observe more phenomenologically diverse solutions and an improved search capacity coming from the former. We use novelty detection to further explore sparsely populated regions of phenomenological interest. These results suggest a powerful search strategy that combines the global exploration of multi-objective optimisation with the exploitation of single-objective optimisation.

hep-ph↗

arXiv2025

Sensitivity to New Physics Phenomena in Anomaly Detection: A Study of Untunable Hyperparameters

The search for physics beyond the Standard Model (BSM) at collider experiments requires model-independent strategies to avoid missing possible discoveries of unexpected signals. Anomaly detection (AD) techniques offer a promising approach by identifying deviations from the Standard Model (SM) and have been extensively studied. The sensitivity of these methods to untunable hyperparameters has not been systematically compared, however. This study addresses it by investigating four semi-supervised AD methods -- Auto-Encoders, Deep Support Vector Data Description, Histogram-based Outlier Score, and Isolation Forest -- trained on simulated SM background events. In this paper, we study the sensitivity of these methods to BSM benchmark signals as a function of these untunable hyperparameters. Such a study is complemented by a proposal of a non-parametric permutation test using signal-agnostic statistics, which can provide a robust statistical assessment.

hep-ph↗

arXiv2024

Focus topics for the ECFA study on Higgs / Top / EW factories

In order to stimulate new engagement and trigger some concrete studies in areas where further work would be beneficial towards fully understanding the physics potential of an $e^+e^-$ Higgs / Top / Electroweak factory, we propose to define a set of focus topics. The general reasoning and the proposed topics are described in this document.

hep-ph↗

arXiv2023

Fitting a Collider in a Quantum Computer: Tackling the Challenges of Quantum Machine Learning for Big Datasets

Current quantum systems have significant limitations affecting the processing of large datasets with high dimensionality, typical of high energy physics. In the present paper, feature and data prototype selection techniques were studied to tackle this challenge. A grid search was performed and quantum machine learning models were trained and benchmarked against classical shallow machine learning methods, trained both in the reduced and the complete datasets. The performance of the quantum algorithms was found to be comparable to the classical ones, even when using large datasets. Sequential Backward Selection and Principal Component Analysis techniques were used for feature's selection and while the former can produce the better quantum machine learning models in specific cases, it is more unstable. Additionally, we show that such variability in the results is caused by the use of discrete variables, highlighting the suitability of Principal Component analysis transformed data for quantum machine learning applications in the high energy physics context.

hep-ph↗

arXiv2023

Berry: A code for the differentiation of Bloch wavefunctions from DFT calculations

Density functional calculations of electronic structures of materials is one of the most used techniques in theoretical solid state physics. These calculations retrieve single electron wavefunctions and their eigenenergies. The berry suite of programs amplifies the usefulness of DFT by ordering the eigenstates in analytic bands, allowing the differentiation of the wavefunctions in reciprocal space. It can then calculate Berry connections and curvatures and the second harmonic generation conductivity. The berry software is implemented for two dimensional materials and was tested in hBN and InSe. In the near future, more properties and functionalities are expected to be added.

cond-mat.mes-hall↗

arXiv2022

Exploring Parameter Spaces with Artificial Intelligence and Machine Learning Black-Box Optimisation Algorithms

Constraining Beyond the Standard Model theories usually involves scanning highly multi-dimensional parameter spaces and check observable predictions against experimental bounds and theoretical constraints. Such task is often timely and computationally expensive, especially when the model is severely constrained and thus leading to very low random sampling efficiency. In this work we tackled this challenge using Artificial Intelligence and Machine Learning search algorithms used for Black-Box optimisation problems. Using the cMSSM and the pMSSM parameter spaces, we consider both the Higgs mass and the Dark Matter Relic Density constraints to study their sampling efficiency and parameter space coverage. We find our methodology to produce orders of magnitude improvement of sampling efficiency whilst reasonably covering the parameter space.

hep-ph↗

arXiv2021

A continuous integration and web framework in support of the ATLAS Publication Process

The ATLAS collaboration defines methods, establishes procedures, and organises advisory groups to manage the publication processes of scientific papers, conference papers, and public notes. All stages are managed through web systems, computing programs, and tools that are designed and developed by the collaboration. A framework called FENCE is integrated into the CERN GitLab software repository, to automatically configure workspaces where each analysis can be documented by the analysis team and managed by the relevant coordinators. Continuous integration is used to guide the writers in applying consistent and correct formatting when preparing papers to be submitted to scientific journals. Additional software assures the correctness of other aspects of each paper, such as the lists of collaboration authors, funding agencies, and foundations. The framework and the workflow therein provide automatic and easy support to the researchers and facilitates each phase of the publication process, allowing authors to focus on the article contents. The framework and its integration with the most up to date and efficient tools has consequently provided a more professional and efficient automatized work environment to the whole collaboration.

cs.DL↗

arXiv2020

Study of interference effects in the search for flavour-changing neutral current interactions involving the top quark and a photon or a $Z$ boson at the LHC

Flavour-changing neutral-current interactions of the top quark can be searched for in top-quark pair production with one top quark decaying to an up-type quark and a neutral boson, and they can be searched for in the single production of a top quark in association with such a boson. Both processes interfere if an additional up-type quark is produced in the case of single production. The impact of these interference effects on searches for flavour-changing neutral currents at the LHC is studied for the case where the neutral boson is a photon or a $Z$ boson. Interference effects are found to be smaller than variations of the renormalisation and factorisation scales.

hep-ph↗

arXiv2019

Machine Learning in High Energy Physics Community White Paper

Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas for machine learning in particle physics. We detail a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit.

physics.comp-ph↗

arXiv2015

Interpretation of vector-like quark searches: the case of a heavy gluon in composite Higgs models and vector-like quarks

Pair production of new vector-like quarks in $pp$ collisions is considered model independent as it is usually dominated by QCD production. Nonetheless, the presence of a new massive color octet (heavy gluon) in some composite Higgs models may modify the pair production rate of vector-like quarks. This scenario is considered and the possible differences between the usual QCD production and the production mediated via heavy gluons is studied. The sensitivity to these differences in the LHC (run-1 and run-2) are studied. No sizeable differences have been found, which suggests that the published experimental results can be easily reinterpreted by a simple cross-section scaling. This reinterpretation has been also done for the run-1 results published by the collaborations.

hep-ph↗

arXiv2015

Interpretation of Vector-like Quark Searches: Heavy Gluons in Composite Higgs Models

Pair production of new vector-like quarks in pp collisions is considered model independent as it is usually dominated by QCD production. We discuss the interpretation of vector-like quark searches in the case that QCD is not the only relevant production mechanism for the new quarks. In particular we consider the effect of a new massive color octet vector boson with sizeable decay branching ratio into the new quarks. We pay special attention to the sensitivity of the Large Hadron Collider experiments, both in run-1 and early run-2, to differences in the kinematical distributions from the different production mechanisms. We have found that even though there can be significant differences in some kinematical distributions at the parton level, the differences are washed out at the reconstruction level. Thus, the published experimental results can be reinterpreted in models with heavy gluons by simply rescaling the production cross section.

hep-ph↗

arXiv2015

Production of t$γ$, tZ and tH via Flavour Changing Neutral Currents

A UFO model describing general top quark Flavour Changing Neutral Currents is presented. We use it to study t$γ$, tH and tZ production via FCNCs anomalous couplings at the Large Hadron Collider, in particular how the distributions of physical observables depend on the anomalous couplings. A sensitivity study of the Large Hadron Collider experiments to tZ production via FCNC in its second stage of operation is also performed.

hep-ph↗

arXiv2015

Dark Matter Benchmark Models for Early LHC Run-2 Searches: Report of the ATLAS/CMS Dark Matter Forum

This document is the final report of the ATLAS-CMS Dark Matter Forum, a forum organized by the ATLAS and CMS collaborations with the participation of experts on theories of Dark Matter, to select a minimal basis set of dark matter simplified models that should support the design of the early LHC Run-2 searches. A prioritized, compact set of benchmark models is proposed, accompanied by studies of the parameter space of these models and a repository of generator implementations. This report also addresses how to apply the Effective Field Theory formalism for collider searches and present the results of such interpretations.

hep-ex↗