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Author Navarro-Salas, J.; Pla, S. url  doi
openurl 
  Title Particle Creation and the Schwinger Model Type Journal Article
  Year 2022 Publication Symmetry-Basel Abbreviated Journal Symmetry-Basel  
  Volume 14 Issue 11 Pages 2435 - 9pp  
  Keywords Schwinger model; semiclassical theory; particle creation  
  Abstract We study the particle creation process in the Schwinger model coupled with an external classical source. One can approach the problem by taking advantage of the fact that the full quantized model is solvable and equivalent to a (massive) gauge field with a non-local effective action. Alternatively, one can also face the problem by following the standard semiclassical route. This means quantizing the massless Dirac field and considering the electromagnetic field as a classical background. We evaluate the energy created by a generic, homogeneous, and time-dependent source. The results match exactly in both approaches. This proves in a very direct and economical way the validity of the semiclassical approach for the (massless) Schwinger model, in agreement with a previous analysis based on the linear response equation. Our discussion suggests that a similar analysis for the massive Schwinger model could be used as a non-trivial laboratory to confront a fully quantized solvable model with its semiclassical approximation, therefore mimicking the long-standing confrontation of quantum gravity with quantum field theory in curved spacetime.  
  Address [Navarro-Salas, Jose] Univ Valencia, Ctr Mixto Univ Valencia CSIC, Fac Fis, Dept Fis Teor & IFIC, Burjassot 46100, Valencia, Spain, Email: jnavarro@ific.uv.es  
  Corporate Author Thesis  
  Publisher Mdpi Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000895122100001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5432  
Permanent link to this record
 

 
Author Ramirez-Uribe, S.; Hernandez-Pinto, R.J.; Rodrigo, G.; Sborlini, G.F.R. url  doi
openurl 
  Title From Five-Loop Scattering Amplitudes to Open Trees with the Loop-Tree Duality Type Journal Article
  Year 2022 Publication Symmetry-Basel Abbreviated Journal Symmetry-Basel  
  Volume 14 Issue 12 Pages 2571 - 14pp  
  Keywords perturbative QFT; higher-order calculations; multiloop Feynman integrals  
  Abstract Characterizing multiloop topologies is an important step towards developing novel methods at high perturbative orders in quantum field theory. In this article, we exploit the Loop-Tree Duality (LTD) formalism to analyse multiloop topologies that appear for the first time at five loops. Explicitly, we open the loops into connected trees and group them according to their topological properties. Then, we identify a kernel generator, the so-called N7MLT universal topology, that allows us to describe any scattering amplitude of up to five loops. Furthermore, we provide factorization and recursion relations that enable us to write these multiloop topologies in terms of simpler subtopologies, including several subsets of Feynman diagrams with an arbitrary number of loops. Our approach takes advantage of many symmetries present in the graphical description of the original fundamental five-loop topologies. The results obtained in this article might shed light into a more efficient determination of higher-order corrections to the running couplings, which are crucial in the current and future precision physics program.  
  Address [Ramirez-Uribe, Selomit; Rodrigo, German] Univ Valencia, Inst Fis Corpuscular, Consejo Super Invest Cient, Parc Cient, E-46980 Paterna, Spain, Email: roger@uas.edu.mx  
  Corporate Author Thesis  
  Publisher Mdpi Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000904374000001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5450  
Permanent link to this record
 

 
Author Khosa, C.K.; Sanz, V.; Soughton, M. url  doi
openurl 
  Title A simple guide from machine learning outputs to statistical criteria in particle physics Type Journal Article
  Year 2022 Publication Scipost Physics Core Abbreviated Journal SciPost Phys. Core  
  Volume 5 Issue 4 Pages 050 - 31pp  
  Keywords  
  Abstract In this paper we propose ways to incorporate Machine Learning training outputs into a study of statistical significance. We describe these methods in supervised classification tasks using a CNN and a DNN output, and unsupervised learning based on a VAE. As use cases, we consider two physical situations where Machine Learning are often used: high-pT hadronic activity, and boosted Higgs in association with a massive vector boson.  
  Address [Khosa, Charanjit Kaur] Univ Bristol, HH Wills Phys Lab, Tyndall Ave, Bristol BS8 1TL, Avon, England, Email: Charanjit.Kaur@bristol.ac.uk;  
  Corporate Author Thesis  
  Publisher Scipost Foundation Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000929724800002 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5475  
Permanent link to this record
 

 
Author van Beekveld, M.; Beenakker, W.; Caron, S.; Kip, J.; Ruiz de Austri, R.; Zhang, Z.Y. url  doi
openurl 
  Title Non-standard neutrino spectra from annihilating neutralino dark matter Type Journal Article
  Year 2023 Publication Scipost Physics Core Abbreviated Journal SciPost Phys. Core  
  Volume 6 Issue 1 Pages 006 - 23pp  
  Keywords  
  Abstract Neutrino telescope experiments are rapidly becoming more competitive in indirect de-tection searches for dark matter. Neutrino signals arising from dark matter annihilations are typically assumed to originate from the hadronisation and decay of Standard Model particles. Here we showcase a supersymmetric model, the BLSSMIS, that can simulta-neously obey current experimental limits while still providing a potentially observable non-standard neutrino spectrum from dark matter annihilation.  
  Address [van Beekveld, Melissa] Univ Oxford, Rudolf Peierls Ctr Theoret Phys, Clarendon Lab, Parks Rd, Oxford OX1 3PU, England, Email: melissa.vanbeekveld@physics.ox.ac.uk;  
  Corporate Author Thesis  
  Publisher Scipost Foundation Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000928492200001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5480  
Permanent link to this record
 

 
Author Herrero-Garcia, J.; Patrick, R.; Scaffidi, A. url  doi
openurl 
  Title A semi-supervised approach to dark matter searches in direct detection data with machine learning Type Journal Article
  Year 2022 Publication Journal of Cosmology and Astroparticle Physics Abbreviated Journal J. Cosmol. Astropart. Phys.  
  Volume 02 Issue Pages 039 - 19pp  
  Keywords  
  Abstract The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5495  
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ific federMinisterio de Ciencia e InnovaciĆ³nAgencia Estatal de Investigaciongva