toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author (up) van Beekveld, M.; Caron, S.; Hendriks, L.; Jackson, P.; Leinweber, A.; Otten, S.; Patrick, R.; Ruiz de Austri, R.; Santoni, M.; White, M. url  doi
openurl 
  Title Combining outlier analysis algorithms to identify new physics at the LHC Type Journal Article
  Year 2021 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 09 Issue 9 Pages 024 - 33pp  
  Keywords Phenomenological Models; Supersymmetry Phenomenology  
  Abstract The lack of evidence for new physics at the Large Hadron Collider so far has prompted the development of model-independent search techniques. In this study, we compare the anomaly scores of a variety of anomaly detection techniques: an isolation forest, a Gaussian mixture model, a static autoencoder, and a beta-variational autoencoder (VAE), where we define the reconstruction loss of the latter as a weighted combination of regression and classification terms. We apply these algorithms to the 4-vectors of simulated LHC data, but also investigate the performance when the non-VAE algorithms are applied to the latent space variables created by the VAE. In addition, we assess the performance when the anomaly scores of these algorithms are combined in various ways. Using supersymmetric benchmark points, we find that the logical AND combination of the anomaly scores yielded from algorithms trained in the latent space of the VAE is the most effective discriminator of all methods tested.  
  Address [van Beekveld, Melissa] Clarendon Lab, Rudolf Peierls Ctr Theoret Phys, 20 Pks Rd, Oxford OX1 3PU, England, Email: mcbeekveld@gmail.com;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000695421600003 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4973  
Permanent link to this record
 

 
Author (up) van Beekveld, M.; Caron, S.; Ruiz de Austri, R. url  doi
openurl 
  Title The current status of fine-tuning in supersymmetry Type Journal Article
  Year 2020 Publication Journal of High Energy Physics Abbreviated Journal J. High Energy Phys.  
  Volume 01 Issue 1 Pages 147 - 41pp  
  Keywords Supersymmetry Phenomenology  
  Abstract In this paper, we minimize and compare two different fine-tuning measures in four high-scale supersymmetric models that are embedded in the MSSM. In addition, we determine the impact of current and future dark matter direct detection and collider experiments on the fine-tuning. We then compare the low-scale electroweak measure with the high-scale Barbieri-Giudice measure. We find that they reduce to the same value when the higgsino parameter drives the degree of fine-tuning. We also find spectra where the high-scale measure turns out to be lower than the low-scale measure. Depending on the high-scale model and fine-tuning definition, we find a minimal fine-tuning of 3-38 (corresponding to O(10-1)%) for the low-scale measure, and 63-571 (corresponding to O(1-0.1)%) for the high-scale measure. We stress that it is too early to conclude on the fate of supersymmetry, based only on the fine-tuning paradigm.  
  Address [van Beekveld, Melissa; Caron, Sascha] Radboud Univ Nijmegen, Theoret High Energy Phys, Heyendaalseweg 135, NL-6525 AJ Nijmegen, Netherlands, Email: mcbeekveld@gmail.com;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1029-8479 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000512011100001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4275  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

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