Records |
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 |
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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 |
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Scipost Foundation |
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English |
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Series Volume |
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ISSN |
2542-4653 |
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Expedition |
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Conference |
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Notes |
WOS:000807448000038 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5256 |
Permanent link to this record |
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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 |
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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 |
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Scipost Foundation |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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ISSN |
2542-4653 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000680039500002 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4920 |
Permanent link to this record |
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Author |
Khosa, C.K.; Sanz, V. |
Title |
Anomaly Awareness |
Type |
Journal Article |
Year |
2023 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
Volume |
15 |
Issue |
2 |
Pages |
053 - 24pp |
Keywords |
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Abstract |
We present a new algorithm for anomaly detection called Anomaly Awareness. The algorithm learns about normal events while being made aware of the anomalies through a modification of the cost function. We show how this method works in different Particle Physics situations and in standard Computer Vision tasks. For example, we apply the method to images from a Fat Jet topology generated by Standard Model Top and QCD events, and test it against an array of new physics scenarios, including Higgs production with EFT effects and resonances decaying into two, three or four subjets. We find that the algorithm is effective identifying anomalies not seen before, and becomes robust as we make it aware of a varied-enough set of anomalies. |
Address |
[Khosa, Charanjit K.] Univ Manchester, Dept Phys & Astron, Manchester M13 9PL, England |
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Scipost Foundation |
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English |
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ISSN |
2542-4653 |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:001048488200002 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5610 |
Permanent link to this record |
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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 |
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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 |
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Scipost Foundation |
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English |
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Series Editor |
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ISSN |
2542-4653 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:001038392400002 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5595 |
Permanent link to this record |
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Author |
LHC BSM Reinterpretation Forum (Abdallah, W. et al); Mitsou, V.A.; Sanz, V. |
Title |
Reinterpretation of LHC results for new physics: status and recommendations after run 2 |
Type |
Journal Article |
Year |
2020 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
Volume |
9 |
Issue |
2 |
Pages |
022 - 45pp |
Keywords |
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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 |
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Thesis |
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Scipost Foundation |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2542-4653 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000573102600007 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4547 |
Permanent link to this record |