toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. url  doi
openurl 
  Title A deep Generative Artificial Intelligence system to predict species coexistence patterns Type Journal Article
  Year 2022 Publication (up) Methods in Ecology and Evolution Abbreviated Journal Methods Ecol. Evol.  
  Volume 13 Issue Pages 1052-1061  
  Keywords artificial intelligence; direct interactions; generative adversarial networks; indirect interactions; species coexistence; variational AutoEncoders  
  Abstract Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge.  
  Address [Hirn, Johannes; Enrique Garcia, Jose; Sanz, Veronica] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: miguel.verdu@ext.uv.es  
  Corporate Author Thesis  
  Publisher Wiley Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2041-210x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000765239700001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5155  
Permanent link to this record
 

 
Author Huang, F.; Sanz, V.; Shu, J.; Xue, X. url  doi
openurl 
  Title LIGO as a probe of dark sectors Type Journal Article
  Year 2021 Publication (up) Physical Review D Abbreviated Journal Phys. Rev. D  
  Volume 104 Issue 10 Pages 095001 - 9pp  
  Keywords  
  Abstract We show how current LIGO data is able to probe interesting theories beyond the Standard Model, particularly dark sectors where a dark Higgs boson triggers symmetry breaking via a first-order phase transition. We use publicly available LIGO O2 data to illustrate how these sectors, even if disconnected from the Standard Model, can be probed by gravitational wave detectors. We link the LIGO measurements with the model content and mass scale of the dark sector, finding that current O2 data are testing a broad set of scenarios that can be mapped into many different types of dark-sector models where the breaking of SU(N) theories with Nf fermions is triggered by a dark Higgs boson at scales ? similar or equal to 108-109 GeV with reasonable parameters for the scalar potential.  
  Address [Huang, Fei; Shu, Jing; Xue, Xiao] Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China, Email: huangf4@uci.edu;  
  Corporate Author Thesis  
  Publisher Amer Physical Soc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2470-0010 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000716446500001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5021  
Permanent link to this record
 

 
Author Sanchis-Lozano, M.A.; Sanz, V. url  doi
openurl 
  Title Observable imprints of primordial gravitational waves on the temperature anisotropies of the cosmic microwave background Type Journal Article
  Year 2024 Publication (up) Physical Review D Abbreviated Journal Phys. Rev. D  
  Volume 109 Issue 6 Pages 063529 - 11pp  
  Keywords  
  Abstract We examine the contribution of tensor modes, in addition to the dominant scalar ones, on the temperature anisotropies of the cosmic microwave background (CMB). To this end, we analyze in detail the temperature two -point angular correlation function C(Theta) from the Planck 2018 dataset, focusing on large angles (Theta greater than or similar to 120 degrees) corresponding to small l multipoles. A hierarchical set of infrared cutoffs are naturally introduced to the scalar and tensor power spectra of the CMB by invoking an extra Kaluza-Klein spatial dimension compactifying at about the grand unified theory scale between the Planck epoch and the start of inflation. We associate this set of lower scalar and tensor cutoffs with the parity of the multipole expansion of the C(Theta) function. By fitting the Planck 2018 data we compute the multipole coefficients, thereby reproducing the well-known odd -parity preference in angular correlations seen by all three satellite missions: Cosmic Background Explorer, WMAP, and Planck. Our fits improve significantly once tensor modes are included in the analysis, hence providing a hint of the imprints of primordial gravitational waves on the temperature correlations observed in the CMB today. To conclude, we suggest a relationship between, on the one hand, the lack of (positive) large -angle correlations and the odd -parity dominance in the CMB and, on the other hand, the effect of primordial gravitational waves on the CMB temperature anisotropies.  
  Address [Sanchis-Lozano, Miguel -Angel; Sanz, Veronica] Univ Valencia, Dept Fis Teor, CSIC, Valencia 46100, Spain, Email: miguel.angel.sanchis@ific.uv.es;  
  Corporate Author Thesis  
  Publisher Amer Physical Soc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2470-0010 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001195716600006 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 6038  
Permanent link to this record
 

 
Author Kasieczka, G. et al; Sanz, V. url  doi
openurl 
  Title The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics Type Journal Article
  Year 2021 Publication (up) Reports on Progress in Physics Abbreviated Journal Rep. Prog. Phys.  
  Volume 84 Issue 12 Pages 124201 - 64pp  
  Keywords anomaly detection; machine learning; unsupervised learning; weakly supervised learning; semisupervised learning; beyond the standard model; model-agnostic methods  
  Abstract A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.  
  Address [Kasieczka, Gregor] Univ Hamburg, Inst Expt Phys, Hamburg, Germany, Email: gregor.kasieczka@uni-hamburg.de;  
  Corporate Author Thesis  
  Publisher IOP Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0034-4885 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000727698500001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5039  
Permanent link to this record
 

 
Author LHC BSM Reinterpretation Forum (Abdallah, W. et al); Mitsou, V.A.; Sanz, V. url  doi
openurl 
  Title Reinterpretation of LHC results for new physics: status and recommendations after run 2 Type Journal Article
  Year 2020 Publication (up) Scipost Physics Abbreviated Journal SciPost Phys.  
  Volume 9 Issue 2 Pages 022 - 45pp  
  Keywords  
  Abstract We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpretation Forum. We detail current experimental offerings in direct searches for new particles, measurements, technical implementations and Open Data, and provide a set of recommendations for further improving the presentation of LHC results in order to better enable reinterpretation in the future. We also provide a brief description of existing software reinterpretation frameworks and recent global analyses of new physics that make use of the current data.  
  Address [Abdallah, Waleed; Dutta, Juhi] Harish Chandra Res Inst HBNI, Allahabad 211019, Uttar Pradesh, India, Email: Andy.Buckley@glasgow.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 2542-4653 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000573102600007 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4547  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records:
ific federMinisterio de Ciencia e InnovaciĆ³nAgencia Estatal de Investigaciongva