| Records |
| Author |
Conde, D.; Castillo, F.L.; Escobar, C.; García, C.; Garcia Navarro, J.E.; Sanz, V.; Zaldívar, B.; Curto, J.J.; Marsal, S.; Torta, J.M. |
| Title |
Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning |
Type |
Journal Article |
| Year |
2023 |
Publication |
Space Weather |
Abbreviated Journal  |
Space Weather |
| Volume |
21 |
Issue |
11 |
Pages |
e2023SW003474 - 27pp |
| Keywords |
geomagnetic storms; deep learning; forecasting; SYM-H; uncertainties; hyper-parameter optimization |
| Abstract |
Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests. |
| Address |
[Conde, D.; Escobar, C.; Garcia, C.; Garcia, J. E.; Sanz, V.; Zaldivar, B.] Univ Valencia, CSIC, Ctr Mixto, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: Daniel.Conde@ific.uv.es |
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Thesis |
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| Publisher |
Amer Geophysical Union |
Place of Publication |
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Editor |
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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 |
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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:001104189700001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5804 |
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| 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 |
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| 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; |
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Thesis |
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| Publisher |
Scipost Foundation |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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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:000928492200001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5480 |
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| Author |
Baamara, Y.; Gessner, M.; Sinatra, A. |
| Title |
Quantum-enhanced multiparameter estimation and compressed sensing of a field |
Type |
Journal Article |
| Year |
2023 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
| Volume |
14 |
Issue |
3 |
Pages |
050 - 18pp |
| Keywords |
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| Abstract |
We show that a significant quantum gain corresponding to squeezed or over-squeezed spin states can be obtained in multiparameter estimation by measuring the Hadamard coefficients of a 1D or 2D signal. The physical platform we consider consists of twolevel atoms in an optical lattice in a squeezed-Mott configuration, or more generally by correlated spins distributed in spatially separated modes. Our protocol requires the possibility to locally flip the spins, but relies on collective measurements. We give examples of applications to scalar or vector field mapping and compressed sensing. |
| Address |
[Baamara, Youcef; Sinatra, Alice] Univ PSL, Univ Sorbonne, ENS, Lab Kastler Brossel,CNRS, 24 Rue Lhomond, F-75231 Paris, France, Email: alice.sinatra@lkb.ens.fr |
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Thesis |
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| Publisher |
Scipost Foundation |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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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:000974981200008 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5519 |
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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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Thesis |
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| Publisher |
Scipost Foundation |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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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: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 |
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 |
| Corporate Author |
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Thesis |
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| Publisher |
Scipost Foundation |
Place of Publication |
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Editor |
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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:001048488200002 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5610 |
| Permanent link to this record |
