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Author |
Capozzi, F.; Ferreira, R.Z.; Lopez-Honorez, L.; Mena, O. |
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Title |
CMB and Lyman-alpha constraints on dark matter decays to photons |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
06 |
Issue |
6 |
Pages |
060 - 23pp |
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Keywords |
reionization; axions; cosmological parameters from CMBR; dark matter theory |
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Abstract |
Dark matter energy injection in the early universe modifies both the ionization history and the temperature of the intergalactic medium. In this work, we improve the CMB bounds on sub-keV dark matter and extend previous bounds from Lyman-& alpha; observations to the same mass range, resulting in new and competitive constraints on axion-like particles (ALPs) decaying into two photons. The limits depend on the underlying reionization history, here accounted self-consistently by our modified version of the publicly available DarkHistory and CLASS codes. Future measurements such as the ones from the CMB-S4 experiment may play a crucial, leading role in the search for this type of light dark matter candidates. |
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Address  |
[Capozzi, Francesco] Univ Aquila, Dipartimento Sci Fis & Chim, I-67100 Laquila, Italy, Email: francesco.capozzi@univaq.it; |
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Publisher |
IOP Publishing Ltd |
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Language |
English |
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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 |
1475-7516 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:001025410500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5584 |
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Author |
CMS and CALICE Collaborations (Acar, B. et al); Irles, A. |
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Title |
Performance of the CMS High Granularity Calorimeter prototype to charged pion beams of 20-300 GeV/c |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
18 |
Issue |
8 |
Pages |
P08014 - 32pp |
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Keywords |
Calorimeters; Large detector systems for particle and astroparticle physics; Radiation-hard detectors; Si microstrip and pad detectors |
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Abstract |
The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimeter (HGCAL). The electromagnetic section of the HGCAL is based on silicon sensors interspersed between lead and copper (or copper tungsten) absorbers. The hadronic section uses layers of stainless steel as an absorbing medium and silicon sensors as an active medium in the regions of high radiation exposure, and scintillator tiles directly read out by silicon photomultipliers in the remaining regions. As part of the development of the detector and its readout electronic components, a section of a silicon-based HGCAL prototype detector along with a section of the CALICE AHCAL prototype was exposed to muons, electrons and charged pions in beam test experiments at the H2 beamline at the CERN SPS in October 2018. The AHCAL uses the same technology as foreseen for the HGCAL but with much finer longitudinal segmentation. The performance of the calorimeters in terms of energy response and resolution, longitudinal and transverse shower profiles is studied using negatively charged pions, and is compared to GEANT4 predictions. This is the first report summarizing results of hadronic showers measured by the HGCAL prototype using beam test data. |
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Address |
[Caraway, B.; Dittmann, J.; Hatakeyama, K.; Kanuganti, A. R.; Wilson, J. S.] Baylor Univ, Waco, TX 76706 USA, Email: Seema.Sharma@cern.ch |
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Publisher |
IOP Publishing Ltd |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
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Expedition |
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Conference |
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Notes |
WOS:001085057700002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5784 |
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Author |
Caron, S.; Eckner, C.; Hendriks, L.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
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Title |
Mind the gap: the discrepancy between simulation and reality drives interpretations of the Galactic Center Excess |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
06 |
Issue |
6 |
Pages |
013 - 56pp |
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Keywords |
dark matter simulations; gamma ray experiments; Machine learning; millisecond pulsars |
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Abstract |
The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model (-yEM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of-yEMs with increasing parametric freedom. We calculate the fractional contribution (fsrc) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the ryEM. For the simplest ryEM, we obtain fsrc = 0.10 f 0.07, while the most complex model yields fsrc = 0.79 f 0.24. In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed ryEM. The quoted results for fsrc do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated ryEM iterations. We quantify the reality gap between our ryEMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed ryEMs have gaps to reality. Our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked “out of domain” uncertainties in future interpretations. |
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Address |
[Caron, Sascha; Hendriks, Luc] Radboud Univ Nijmegen, Theoret High Energy Phys, Heyendaalseweg 135, NL-6525 AJ Nijmegen, Netherlands, Email: scaron@nikhef.nl; |
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Corporate Author |
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Publisher |
IOP Publishing Ltd |
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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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 |
1475-7516 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:001025516000009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5576 |
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Author |
Caron, S.; Ruiz de Austri, R.; Zhang, Z.Y. |
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Title |
Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories? |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
03 |
Issue |
3 |
Pages |
004 - 37pp |
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Keywords |
Specific BSM Phenomenology; Supersymmetry |
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Abstract |
Model-independent search strategies have been increasingly proposed in recent years because on the one hand there has been no clear signal for new physics and on the other hand there is a lack of a highly probable and parameter-free extension of the standard model. For these reasons, there is no simple search target so far. In this work, we try to take a new direction and ask the question: bearing in mind that we have a large number of new physics theories that go beyond the Standard Model and may contain a grain of truth, can we improve our search strategy for unknown signals by using them “in combination”? In particular, we show that a signal hypothesis based on a large, intermingled set of many different theoretical signal models can be a superior approach to find an unknown BSM signal. Applied to a recent data challenge, we show that “mixture-of-theories training” outperforms strategies that optimize signal regions with a single BSM model as well as most unsupervised strategies. Applications of this work include anomaly detection and the definition of signal regions in the search for signals of new physics. |
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Address |
[Caron, Sascha; Zhang, Zhongyi] Radboud Univ Nijmegen, High Energy Phys, Heyendaalseweg 135, NL-6525 AJ Nijmegen, Netherlands, Email: scaron@nikhef.nl; |
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Corporate Author |
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Thesis |
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Publisher |
Springer |
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 |
1029-8479 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000943095100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5494 |
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Author |
Fernandez Casani, A.; Garcia Montoro, C.; Gonzalez de la Hoz, S.; Salt, J.; Sanchez, J.; Villaplana Perez, M. |
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Title |
Big Data Analytics for the ATLAS EventIndex Project with Apache Spark |
Type |
Journal Article |
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Year |
2023 |
Publication |
Computational and Mathematical Methods |
Abbreviated Journal |
Comput. Math. Methods |
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Volume |
2023 |
Issue |
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Pages |
6900908 - 19pp |
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Keywords |
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Abstract |
The ATLAS EventIndex was designed to provide a global event catalogue and limited event-level metadata for ATLAS experiment of the Large Hadron Collider (LHC) and their analysis groups and users during Run 2 (2015-2018) and has been running in production since. The LHC Run 3, started in 2022, has seen increased data-taking and simulation production rates, with which the current infrastructure would still cope but may be stretched to its limits by the end of Run 3. A new core storage service is being developed in HBase/Phoenix, and there is work in progress to provide at least the same functionality as the current one for increased data ingestion and search rates and with increasing volumes of stored data. In addition, new tools are being developed for solving the needed access cases within the new storage. This paper describes a new tool using Spark and implemented in Scala for accessing the big data quantities of the EventIndex project stored in HBase/Phoenix. With this tool, we can offer data discovery capabilities at different granularities, providing Spark Dataframes that can be used or refined within the same framework. Data analytic cases of the EventIndex project are implemented, like the search for duplicates of events from the same or different datasets. An algorithm and implementation for the calculation of overlap matrices of events across different datasets are presented. Our approach can be used by other higher-level tools and users, to ease access to the data in a performant and standard way using Spark abstractions. The provided tools decouple data access from the actual data schema, which makes it convenient to hide complexity and possible changes on the backed storage. |
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Address |
[Casani, Alvaro Fernandez; Montoro, Carlos Garcia; de la Hoz, Santiago Gonzalez; Salt, Jose; Sanchez, Javier; Perez, Miguel Villaplana] CSIC UV, Inst Corpuscular Phys IFIC, E-46980 Paterna, Spain, Email: alvaro.fernandez@ific.uv.es; |
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Corporate Author |
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Thesis |
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Publisher |
Wiley-Hindawi |
Place of Publication |
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Language |
English |
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Notes |
WOS:001079548500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5706 |
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