| |
Records |
Links |
|
Author |
Barenboim, G.; Hirn, J.; Sanz, V. |
|
| |
Title |
Symmetry meets AI |
Type |
Journal Article |
| |
Year |
2021 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
|
| |
Volume |
11 |
Issue  |
1 |
Pages |
014 - 11pp |
|
| |
Keywords |
|
|
| |
Abstract |
We explore whether Neural Networks (NNs) can discover the presence of symmetries as they learn to perform a task. For this, we train hundreds of NNs on a decoy task based on well-controlled Physics templates, where no information on symmetry is provided. We use the output from the last hidden layer of all these NNs, projected to fewer dimensions, as the input for a symmetry classification task, and show that information on symmetry had indeed been identified by the original NN without guidance. As an interdisciplinary application of this procedure, we identify the presence and level of symmetry in artistic paintings from different styles such as those of Picasso, Pollock and Van Gogh. |
|
| |
Address |
[Barenboim, Gabriela; Hirn, Johannes; Sanz, Veronica] Univ Valencia, CSIC, Dept Fis Teor, E-46100 Burjassot, Spain |
|
| |
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:000680039500002 |
Approved |
no |
|
| |
Is ISI |
yes |
International Collaboration |
yes |
|
| |
Call Number |
IFIC @ pastor @ |
Serial |
4920 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Cranmer, K. et al; Sanz, V. |
|
| |
Title |
Publishing statistical models: Getting the most out of particle physics experiments |
Type |
Journal Article |
| |
Year |
2022 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
|
| |
Volume |
12 |
Issue |
1 |
Pages |
037 - 55pp |
|
| |
Keywords |
|
|
| |
Abstract |
The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases – including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits – we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results. |
|
| |
Address |
[Cranmer, Kyle; Held, Alexander] NYU, New York, NY 10003 USA, Email: kyle.cranmer@nyu.edu; |
|
| |
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:000807448000032 |
Approved |
no |
|
| |
Is ISI |
yes |
International Collaboration |
yes |
|
| |
Call Number |
IFIC @ pastor @ |
Serial |
5255 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Aarrestad, T. et al; Mamuzic, J.; Ruiz de Austri, R. |
|
| |
Title |
Benchmark data and model independent event classification for the large hadron collider |
Type |
Journal Article |
| |
Year |
2022 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
|
| |
Volume |
12 |
Issue |
1 |
Pages |
043 - 57pp |
|
| |
Keywords |
|
|
| |
Abstract |
We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (LHC) using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of > 1 billion simulated LHC events corresponding to 10 fb(-1) of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge. |
|
| |
Address |
[Aarrestad, Thea; Heinrich, Lukas A.; Jawahar, Pratik; Pierini, Maurizio; Touranakou, Mary; Wozniak, Kinga A.] European Org Nucl Res CERN, CH-1211 Geneva 23, Switzerland |
|
| |
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:000807448000038 |
Approved |
no |
|
| |
Is ISI |
yes |
International Collaboration |
yes |
|
| |
Call Number |
IFIC @ pastor @ |
Serial |
5256 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
van Beekveld, M.; Beenakker, W.; Caron, S.; Kip, J.; Ruiz de Austri, R.; Zhang, Z.Y. |
|
| |
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 |
|
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 |
Banerjee, P.; Coutinho, A.; Engel, T.; Gurgone, A.; Signer, A.; Ulrich, Y. |
|
| |
Title |
High-precision muon decay predictions for ALP searches |
Type |
Journal Article |
| |
Year |
2023 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
|
| |
Volume |
15 |
Issue |
1 |
Pages |
021 - 38pp |
|
| |
Keywords |
|
|
| |
Abstract |
We present an improved theoretical prediction of the positron energy spectrum for the polarised Michel decay & mu;+ & RARR; e+ & nu;e & nu; over bar & mu;. In addition to the full next-to-next-to-leading order correction of order & alpha;2 in the electromagnetic coupling, we include logarithmically enhanced terms at even higher orders. Logarithms due to collinear emission are included at next-to-leading accuracy up to order & alpha;4. At the endpoint of the Michel spectrum, soft photon emission results in large logarithms that are resummed up to next-to-next-to leading logarithmic accuracy. We apply our results in the context of the MEG II and Mu3e experiments to estimate the impact of the theory error on the branching ratio sensitivity for the lepton-flavour-violating decay & mu;+ & RARR; e+X of a muon into an axion-like particle X. |
|
| |
Address |
[Banerjee, Pulak] Zhejiang Univ, Zhejiang Inst Modern Phys, Dept Phys, Hangzhou 310027, Peoples R China |
|
| |
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:001038392400002 |
Approved |
no |
|
| |
Is ISI |
yes |
International Collaboration |
yes |
|
| |
Call Number |
IFIC @ pastor @ |
Serial |
5595 |
|
| Permanent link to this record |
