| Records |
| Author |
Middeldorf-Wygas, M.M.; Oldengott, I.M.; Bödeker, D.; Schwarz, D.J. |
| Title |
Cosmic QCD transition for large lepton flavor asymmetries |
Type |
Journal Article |
| Year |
2022 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
Volume  |
105 |
Issue |
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Pages |
123533 - 10pp |
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| Abstract |
We study the impact of large lepton flavor asymmetries on the cosmic QCD transition. Scenarios of unequal lepton flavor asymmetries are observationally almost unconstrained and therefore open up a whole new parameter space for the cosmic QCD transition. We find that for large asymmetries, the formation of a Bose-Einstein condensate of pions can occur and identify the corresponding parameter space. In the vicinity of the QCD transition scale, we express the pressure in terms of a Taylor expansion with respect to the complete set of chemical potentials. The Taylor coefficients rely on input from lattice QCD calculations from the literature. The domain of applicability of this method is discussed. |
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Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5497 |
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| Author |
Garcia Navarro, J.E.; Fernandez-Prieto, L.M.; Villaseñor, A.; Sanz, V.; Ammirati, J.B.; Diaz Suarez, E.A.; Garcia, C. |
| Title |
Performance of Deep Learning Pickers in Routine Network Processing Applications |
Type |
Journal Article |
| Year |
2022 |
Publication |
Seismological Research Letters |
Abbreviated Journal |
Seismol. Res. Lett. |
| Volume |
93 |
Issue |
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Pages |
2529-2542 |
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| Abstract |
Picking arrival times of P and S phases is a fundamental and time‐consuming task for the routine processing of seismic data acquired by permanent and temporary networks. A large number of automatic pickers have been developed, but to perform well they often require the tuning of multiple parameters to adapt them to each dataset. Despite the great advance in techniques, some problems remain, such as the difficulty to accurately pick S waves and earthquake recordings with a low signal‐to‐noise ratio. Recently, phase pickers based on deep learning (DL) have shown great potential for event identification and arrival‐time picking. However, the general adoption of these methods for the routine processing of monitoring networks has been held back by factors such as the availability of well‐documented software, computational resources, and a gap in knowledge of these methods. In this study, we evaluate recent available DL pickers for earthquake data, comparing the performance of several neural network architectures. We test the selected pickers using three datasets with different characteristics. We found that the analyzed DL pickers (generalized phase detection, PhaseNet, and EQTransformer) perform well in the three tested cases. They are very efficient at ignoring large‐amplitude transient noise and at picking S waves, a task that is often difficult even for experienced analysts. Nevertheless, the performance of the analyzed DL pickers varies widely in terms of sensitivity and false discovery rate, with some pickers missing a significant percentage of true picks and others producing a large number of false positives. There are also variations in run time between DL pickers, with some of them requiring significant resources to process large datasets. In spite of these drawbacks, we show that DL pickers can be used efficiently to process large seismic datasets and obtain results comparable or better than current standard procedures. |
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no |
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yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5500 |
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| Author |
Fanchiotti, H.; Garcia Canal, C.A.; Mayosky, M.; Veiga, A.; Vento, V. |
| Title |
Measuring the Hannay geometric phase |
Type |
Journal Article |
| Year |
2022 |
Publication |
American Journal of Physics |
Abbreviated Journal |
Am. J. Phys. |
| Volume |
90 |
Issue |
6 |
Pages |
430-435 |
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| Abstract |
The Hannay geometric phase is the classical analog of the well-known Berry phase. Its most familiar example is the effect of the latitude lambda on the motion of a Foucault pendulum. We describe an electronic network whose behavior is exactly equivalent to that of the pendulum. The circuit can be constructed from off-the-shelf components using two matched transconductance amplifiers that comprise a gyrator to introduce the non-reciprocal behavior needed to mimic the pendulum. One may precisely measure the dependence of the Hannay phase on lambda by circuit simulation and by laboratory measurements on a constructed circuit. |
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[Fanchiotti, H.; Canal, C. A. Garcia] Univ Nacl La Plata, IFLP, CONICET, CC67, RA-1900 La Plata, Argentina |
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AIP Publishing |
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English |
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0002-9505 |
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| Notes |
WOS:000804547100009 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5276 |
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| Author |
Borsato, M. et al; Zurita, J.; Henry, L.; Jashal, B.K.; Oyanguren, A. |
| Title |
Unleashing the full power of LHCb to probe stealth new physics |
Type |
Journal Article |
| Year |
2022 |
Publication |
Reports on Progress in Physics |
Abbreviated Journal |
Rep. Prog. Phys. |
| Volume |
85 |
Issue |
2 |
Pages |
024201 - 45pp |
| Keywords |
LHCb; stealth physics; BSM physics; hidden sectors; long-lived particles; dark matter |
| Abstract |
In this paper, we describe the potential of the LHCb experiment to detect stealth physics. This refers to dynamics beyond the standard model that would elude searches that focus on energetic objects or precision measurements of known processes. Stealth signatures include long-lived particles and light resonances that are produced very rarely or together with overwhelming backgrounds. We will discuss why LHCb is equipped to discover this kind of physics at the Large Hadron Collider and provide examples of well-motivated theoretical models that can be probed with great detail at the experiment. |
| Address |
[Borsato, M.] Heidelberg Univ, Phys Inst, Heidelberg, Germany, Email: xabier.cid.vidal@cern.ch |
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IOP Publishing Ltd |
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English |
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0034-4885 |
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WOS:000762056700001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5151 |
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AbdusSalam, S.S. et al; Eberhardt, O. |
| Title |
Simple and statistically sound recommendations for analysing physical theories |
Type |
Journal Article |
| Year |
2022 |
Publication |
Reports on Progress in Physics |
Abbreviated Journal |
Rep. Prog. Phys. |
| Volume |
85 |
Issue |
5 |
Pages |
052201 - 11pp |
| Keywords |
particle physics; statistics; methodology |
| Abstract |
Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Our examples can be reproduced with the code publicly available at Zenodo. |
| Address |
[AbdusSalam, Shehu S.; Fowlie, Andrew] Shahid Beheshti Univ, Dept Phys, Tehran, Iran, Email: andrew.j.fowlie@njnu.edu.cn |
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IOP Publishing Ltd |
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English |
Summary Language |
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Series Issue |
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Edition |
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| ISSN |
0034-4885 |
ISBN |
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Expedition |
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Conference |
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| Notes |
WOS:000791574900001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5221 |
| Permanent link to this record |
