| Records |
| Author |
Capdevilla, R.; Meloni, F.; Simoniello, R.; Zurita, J. |
Title  |
Hunting wino and higgsino dark matter at the muon collider with disappearing tracks |
Type |
Journal Article |
| Year |
2021 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
| Volume |
06 |
Issue |
6 |
Pages |
133 - 31pp |
| Keywords |
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| Abstract |
We study the capabilities of a muon collider experiment to detect disappearing tracks originating when a heavy and electrically charged long-lived particle decays via X+-> Y(+)Z(0), where X+ and Z(0) are two almost mass degenerate new states and Y+ is a charged Standard Model particle. The backgrounds induced by the in-flight decays of the muon beams (BIB) can create detector hit combinations that mimic long-lived particle signatures, making the search a daunting task. We design a simple strategy to tame the BIB, based on a detector-hit-level selection exploiting timing information and hit-to-hit correlations, followed by simple requirements on the quality of reconstructed tracks. Our strategy allows us to reduce the number of tracks from BIB to an average of 0.08 per event, hence being able to design a cut-and-count analysis that shows that it is possible to cover weak doublets and triplets with masses close to root s/2 in the 0.1-10 ns range. In particular, this implies that a 10 TeV muon collider is able to probe thermal MSSM higgsinos and thermal MSSM winos, thus rivaling the FCC-hh in that respect, and further enlarging the physics program of the muon collider into the territory of WIMP dark matter and long-lived signatures. We also provide parton-to-reconstructed level efficiency maps, allowing an estimation of the coverage of disappearing tracks at muon colliders for arbitrary models. |
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| ISSN |
1029-8479 |
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| Notes |
WOS:000665787500001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
4868 |
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| Author |
Aiola, S.; Amhis, Y.; Billoir, P.; Jashal, B.K.; Henry, L.; Oyanguren, A.; Marin Benito, C.; Polci, F.; Quagliani, R.; Schiller, M.; Wang, M. |
| Title |
Hybrid seeding: A standalone track reconstruction algorithm for scintillating fibre tracker at LHCb |
Type |
Journal Article |
| Year |
2021 |
Publication |
Computer Physics Communications |
Abbreviated Journal |
Comput. Phys. Commun. |
| Volume |
260 |
Issue |
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Pages |
107713 - 5pp |
| Keywords |
Track reconstruction; Pattern Recognition; LHCb |
| Abstract |
We describe the Hybrid seeding, a stand-alone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by exploiting the knowledge of the LHCb magnetic field and the position of energy deposits in the scintillating fibre tracker detector. Moreover, we achieve a low fake rate and a small contribution to the overall timing budget of the LHCb real-time data processing. |
| Address |
[Billoir, P.; Polci, F.; Quagliani, R.] Sorbonne Univ, Paris Diderot Sorbonne Paris Cite, LPNHE, CNRS IN2P3, Paris, France, Email: louis.henry@cern.ch; |
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| Publisher |
Elsevier |
Place of Publication |
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Editor |
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English |
Summary Language |
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Series Issue |
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Edition |
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| ISSN |
0010-4655 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
WOS:000608243400007 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
4685 |
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| Author |
Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
| Title |
Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge |
Type |
Journal Article |
| Year |
2021 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
| Volume |
656 |
Issue |
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Pages |
A62 - 18pp |
| Keywords |
catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing |
| Abstract |
Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources. |
| Address |
[Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com |
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| Publisher |
Edp Sciences S A |
Place of Publication |
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| Language |
English |
Summary Language |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
0004-6361 |
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:000725877600001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5053 |
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| Author |
Babiano-Suarez, V. et al; Lerendegui-Marco, J.; Balibrea-Correa, J.; Caballero, L.; Calvo, D.; Ladarescu, I.; Real, D.; Domingo-Pardo, C. |
| Title |
Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques |
Type |
Journal Article |
| Year |
2021 |
Publication |
European Physical Journal A |
Abbreviated Journal |
Eur. Phys. J. A |
| Volume |
57 |
Issue |
6 |
Pages |
197 - 17pp |
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| Abstract |
i-TED is an innovative detection system which exploits Compton imaging techniques to achieve a superior signal-to-background ratio in (n, gamma) cross-section measurements using time-of-flight technique. This work presents the first experimental validation of the i-TED apparatus for high-resolution time-of-flight experiments and demonstrates for the first time the concept proposed for background rejection. To this aim, the Au-197(n, gamma) and Fe-56(n, gamma) reactions were studied at CERN n_TOF using an i-TED demonstrator based on three position-sensitive detectors. Two C6D6 detectors were also used to benchmark the performance of i-TED. The i-TED prototype built for this study shows a factor of similar to 3 higher detection sensitivity than state-of-the-art C6D6 detectors in the 10 keV neutron-energy region of astrophysical interest. This paper explores also the perspectives of further enhancement in performance attainable with the final i-TED array consisting of twenty position-sensitive detectors and newanalysis methodologies based on Machine-Learning techniques. |
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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 |
1434-6001 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
WOS:000662881100001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
4875 |
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| Author |
Watanabe, H. et al; Montaner-Piza, A. |
| Title |
Impact of shell evolution on Gamow-Teller beta decay from a high-spin long-lived isomer in Ag-127 |
Type |
Journal Article |
| Year |
2021 |
Publication |
Physics Letters B |
Abbreviated Journal |
Phys. Lett. B |
| Volume |
823 |
Issue |
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Pages |
136766 - 6pp |
| Keywords |
Shell evolution; Gamow-Teller beta decay; Isomer; Ag-127; Radioactive isotope beam |
| Abstract |
The change of the shell structure in atomic nuclei, so-called “nuclear shell evolution”, occurs due to changes of major configurations through particle-hole excitations inside one nucleus, as well as due to variation of the number of constituent protons or neutrons. We have investigated how the shell evolution affects Gamow-Teller (GT) transitions that dominate the beta decay in the region below Sn-132 using the newly obtained experimental data on a long-lived isomer in Ag-127. The T-1/2 = 67.5(9) ms isomer has been identified with a spin and parity of (27/2(+)) at an excitation energy of 1942(-20)(+14) keV, and found to decay via an internal transition of an E3 character, which competes with the dominant beta-decay branches towards the high-spin states in Cd-127. The underlying mechanism of a strong GT transition from the Ag-127 isomer is discussed in terms of configuration-dependent optimization of the effective single-particle energies in the framework of a shell-model approach. |
| Address |
[Watanabe, H.] Beihang Univ, Sch Phys, Beijing 100191, Peoples R China, Email: hiroshi@ribf.riken.jp |
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| Publisher |
Elsevier |
Place of Publication |
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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 |
0370-2693 |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
WOS:000719296400003 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5041 |
| Permanent link to this record |
