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Author |
Allanach, B.C.; Bednyakov, A.; Ruiz de Austri, R. |
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Title |
Higher order corrections and unification in the minimal supersymmetric standard model: SOFTSUSY3.5 |
Type |
Journal Article |
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Year |
2015 |
Publication |
Computer Physics Communications |
Abbreviated Journal |
Comput. Phys. Commun. |
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Volume |
189 |
Issue  |
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Pages |
192-206 |
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Keywords |
Sparticle; MSSM |
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Abstract |
We explore the effects of three-loop minimal supersymmetric standard model renormalisation group equation terms and some leading two-loop threshold corrections on gauge and Yukawa unification: each being one loop higher order than current public spectrum calculators. We also explore the effect of the higher order terms (often 2-3 GeV) on the lightest CP even Higgs mass prediction. We illustrate our results in the constrained minimal supersymmetric standard model. Neglecting threshold corrections at the grand unified scale, the discrepancy between the unification scale alpha(s) and the other two unified gauge couplings changes by 0.1% due to the higher order corrections and the difference between unification scale bottom-tau Yukawa couplings neglecting unification scale threshold corrections changes by up to 1%. The difference between unification scale bottom and top Yukawa couplings changes by a few percent. Differences due to the higher order corrections also give an estimate of the size of theoretical uncertainties in the minimal supersymmetric standard model spectrum. We use these to provide estimates of theoretical uncertainties in predictions of the dark matter relic density (which can be of order one due to its strong dependence on sparticle masses) and the LHC sparticle production cross-section (often around 30%). The additional higher order corrections have been incorporated into SOFTSUSY, and we provide details on how to compile and use the program. We also provide a summary of the approximations used in the higher order corrections. Program Summary Nature of problem: Calculating supersymmetric particle spectrum and mixing parameters in the minimal supersymmetric standard model. The solution to the renormalisation group equations must be consistent with boundary conditions on supersymmetry breaking parameters, as well as the weak-scale boundary condition on gauge couplings, Yukawa couplings and the Higgs potential parameters. Program title: SOFTSUSY Catalogue identifier: ADPMv50 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ADPMv50.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 240528 No. of bytes in distributed program, including test data, etc.: 2597933 Distribution format: tar.gz Programming language: C++, Fortran. Computer: Personal computer. Operating system: Tested on Linux 3.4.6. Word size: 64 bits. Classification: 11.1, 11.6. External routines: At least GiNaC1.3.5 [1] and CLN1.3.1 (both freely obtainable from http://www.ginac.de). Does the new version supersede the previous version?: Yes Catalogue identifier of previous version: ADPMv40 Journal reference of previous version: Comput. Phys. Comm. 185 (2014) 2322 Solution method: Nested iterative algorithm. Reasons for new version: Extension to include additional two and three-loop terms. Summary of revisions: All quantities in the minimal supersymmetric standard model are extended to have three-loop renormalisation group equations (including 3-family mixing) in the limit of real parameters and some leading two-loop threshold corrections are incorporated to the third family Yukawa couplings and the strong gauge coupling. Restrictions: SOFTSUSY will provide a solution only in the perturbative regime and it assumes that all couplings of the model are real (i.e. CP-conserving). If the parameter point under investigation is non-physical for some reason (for example because the electroweak potential does not have an acceptable minimum), SOFTSUSY returns an error message. The higher order corrections included are for the real R-parity conserving minimal supersymmetric standard model (MSSM) only. Running time: A minute per parameter point. The tests provided with the package only take a few seconds to run. |
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[Allanach, B. C.] Univ Cambridge, DAMTP, CMS, Cambridge CB3 0WA, England, Email: rruiz@ific.uv.es |
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Elsevier Science Bv |
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English |
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0010-4655 |
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Notes |
WOS:000350087300021 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2142 |
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Author |
Kim, J.S.; Reuter, J.; Rolbiecki, K.; Ruiz de Austri, R. |
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Title |
A resonance without resonance: Scrutinizing the diphoton excess at 750 GeV |
Type |
Journal Article |
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Year |
2016 |
Publication |
Physics Letters B |
Abbreviated Journal |
Phys. Lett. B |
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Volume |
755 |
Issue |
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Pages |
403-408 |
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Keywords |
BSM phenomenology; LHC |
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Abstract |
Motivated by the recent diphoton excesses reported by both ATLAS and CMS collaborations, we suggest that a new heavy spinless particle is produced in gluon fusion at the LHC and decays to a couple of lighter pseudoscalars which then decay to photons. The new resonances could arise from a new strongly interacting sector and couple to Standard Model gauge bosons only via the corresponding Wess-Zumino-Witten anomaly. We present a detailed recast of the newest 13 TeV data from ATLAS and CMS together with the 8 TeV data to scan the consistency of the parameter space for those resonances. |
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Address |
[Kim, Jong Soo; Rolbiecki, Krzysztof] UAM CSIC, Inst Fis Teor, Madrid, Spain, Email: jong.kim@csic.es; |
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Elsevier Science Bv |
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English |
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0370-2693 |
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Notes |
WOS:000373568100059 |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2713 |
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Author |
Allanach, B.C.; Martin, S.P.; Robertson, D.G.; Ruiz de Austri, R. |
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Title |
The inclusion of two-loop SUSYQCD corrections to gluino and squark pole masses in the minimal and next-to-minimal supersymmetric standard model: SOFTSUSY3.7 |
Type |
Journal Article |
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Year |
2017 |
Publication |
Computer Physics Communications |
Abbreviated Journal |
Comput. Phys. Commun. |
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Volume |
219 |
Issue |
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Pages |
339-345 |
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Keywords |
Gluino; Squark; MSSM; NMSSM |
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Abstract |
We describe an extension of the SOFTSUSY spectrum calculator to include two-loop supersymmetric QCD (SUSYQCD) corrections of order O(alpha(2)(s)) to gluino and squark pole masses, either in the minimal supersymmetric standard model (MSSM) or the next-to-minimal supersymmetric standard model (NMSSM). This document provides an overview of the program and acts as a manual for the new version of SOFTSUSY, which includes the increase in accuracy in squark and gluino pole mass predictions. Program summary Program title: SOFTSUSY Program Files doi: http://dx.doLorg/10.17632/sh77x9j7hs.1 Licensing provisions: GNU GPLv3 Programming language: C++, fortran, C Nature of problem: Calculating supersymmetric particle spectrum, mixing parameters and couplings in the MSSM or the NMSSM. The solution to the renormalization group equations must be consistent with theoretical boundary conditions on supersymmetry breaking parameters, as well as a weak-scale boundary condition on gauge couplings, Yukawa couplings and the Higgs potential parameters. Solution method: Nested fixed point iteration. Restrictions: SOFTSUSY will provide a solution only in the perturbative regime and it assumes that all couplings of the model are real (i.e. CP-conserving). If the parameter point under investigation is nonphysical for some reason (for example because the electroWeak potential does not have an acceptable minimum), SOFTSUSY returns an error message. The higher order corrections included are for the MSSM (R-parity conserving or violating) or the real R-parity conserving NMSSM only. Journal reference of previous version: Comput. Phys. Comm. 189 (2015) 192. Does the new version supersede the previous version?: Yes. Reasons for the new version: It is desirable to improve the accuracy of the squark and gluinos mass predictions, since they strongly affect supersymmetric particle production cross-sections at colliders. Summary of revisions: The calculation of the squark and gluino pole masses is extended to be of next-to next-to leading order in SUSYQCD, i.e. including terms up to O(g(s)(4)/(16 pi(2))(2)). Additional comments: Program obtainable from http://softsusy.hepforge.org/ |
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Address |
[Allanach, B. C.] Univ Cambridge, DAMTP, CMS, Wilberforce Rd, Cambridge CB3 0WA, England, Email: rruiz@ific.uv.es |
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Elsevier Science Bv |
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English |
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0010-4655 |
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Notes |
WOS:000407984100030 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3258 |
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Author |
MoEDAL Collaboration (Acharya, B. et al); Bernabeu, J.; Garcia, C.; Mamuzic, J.; Mitsou, V.A.; Ruiz de Austri, R.; Santra, A.; Vento, V.; Vives, O. |
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Title |
Search for magnetic monopoles with the MoEDAL forward trapping detector in 2.11 fb(-1) of 13 TeV proton-proton collisions at the LHC |
Type |
Journal Article |
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Year |
2018 |
Publication |
Physics Letters B |
Abbreviated Journal |
Phys. Lett. B |
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Volume |
782 |
Issue |
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Pages |
510-516 |
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Keywords |
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Abstract |
We update our previous search for trapped magnetic monopoles in LHC Run 2 using nearly six times more integrated luminosity and including additional models for the interpretation of the data. The MoEDAL forward trapping detector, comprising 222 kg of aluminium samples, was exposed to 2.11 fb(-1) of 13 TeV proton-proton collisions near the LHCb interaction point and analysed by searching for induced persistent currents after passage through a superconducting magnetometer. Magnetic charges equal to the Dirac charge or above are excluded in all samples. The results are interpreted in Drell-Yan production models for monopoles with spins 0, 1/2 and 1: in addition to standard point-like couplings, we also consider couplings with momentum-dependent form factors. The search provides the best current laboratory constraints for monopoles with magnetic charges ranging from two to five times the Dirac charge. |
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Address |
[Acharya, B.; Alexandre, J.; Baines, S.; Ellis, J. R.; Fairbairn, M.; Mavromatos, N. E.; Sakellariadou, M.; Sarkar, S.] Kings Coll London, Dept Phys, Theoret Particle & Phys Cosmol Grp, London, England, Email: philippe.mermod@cern.ch |
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Elsevier Science Bv |
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English |
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0370-2693 |
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Notes |
WOS:000438486900076 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3664 |
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Author |
Gomez, M.E.; Lola, S.; Ruiz de Austri, R.; Shafi, Q. |
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Title |
Confronting SUSY GUT With Dark Matter, Sparticle Spectroscopy and Muon (g – 2) |
Type |
Journal Article |
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Year |
2018 |
Publication |
Frontiers in Physics |
Abbreviated Journal |
Front. Physics |
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Volume |
6 |
Issue |
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Pages |
127 - 9pp |
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Keywords |
grand unification; supersymmetry; dark matter; LHC; sparticle spectroscopy |
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Abstract |
We explore the implications of LHC and cold dark matter searches for supersymmetric particle mass spectra in two different grand unified models with left-right symmetry, SO(10) and SU(4)(c) x SU(2)(L) x SU(2)(R) (4-2-2). We identify characteristic differences between the two scenarios, which imply distinct correlations between experimental measurements and the particular structure of the GUT group. The gauge structure of 4-2-2 enhances significantly the allowed parameter space as compared to SO(10), giving rise to a variety of coannihilation scenarios compatible with the LHC data, LSP dark matter and the ongoing muon g-2 experiment. |
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Address |
[Gomez, Mario E.] Univ Huelva, Fac Ciencias Expt, Dept Ciencias Integradas, Huelva, Spain, Email: mario.gomez@dfa.uhu.es |
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Frontiers Media Sa |
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English |
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ISSN |
2296-424x |
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Notes |
WOS:000450940000001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3808 |
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Author |
Begone, G.; Deisenroth, M.P.; Kim, J.S.; Liem, S.; Ruiz de Austri, R.; Welling, M. |
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Title |
Accelerating the BSM interpretation of LHC data with machine learning |
Type |
Journal Article |
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Year |
2019 |
Publication |
Physics of the Dark Universe |
Abbreviated Journal |
Phys. Dark Universe |
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Volume |
24 |
Issue |
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Pages |
100293 - 5pp |
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Keywords |
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Abstract |
The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators. Performing statistically convergent scans of high-dimensional BSM theories is consequently challenging, and in practice unfeasible for very high-dimensional BSM theories. We present here a new machine learning method that accelerates the interpretation of LHC data, by learning the relationship between BSM theory parameters and data. As a proof-of-concept, we demonstrate that this technique accurately predicts natural SUSY signal events in two signal regions at the High Luminosity LHC, up to four orders of magnitude faster than standard techniques. The new approach makes it possible to rapidly and accurately reconstruct the theory parameters of complex BSM theories, should an excess in the data be discovered at the LHC. |
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Address |
[Begone, Gianfranco; Liem, Sebastian] Univ Amsterdam, GRAPPA, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands, Email: jongsoo.kim@tu-dortmund.de |
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Elsevier Science Bv |
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English |
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ISSN |
2212-6864 |
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Conference |
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Notes |
WOS:000465292500018 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3994 |
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Author |
Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
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Title |
Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge |
Type |
Journal Article |
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Year |
2021 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
656 |
Issue |
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Pages |
A62 - 18pp |
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Keywords |
catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing |
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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. |
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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 |
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English |
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0004-6361 |
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Notes |
WOS:000725877600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5053 |
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Author |
Kim, J.S.; Lopez-Fogliani, D.E.; Perez, A.D.; Ruiz de Austri, R. |
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Title |
The new (g-2)(mu) and right-handed sneutrino dark matter |
Type |
Journal Article |
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Year |
2022 |
Publication |
Nuclear Physics B |
Abbreviated Journal |
Nucl. Phys. B |
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Volume |
974 |
Issue |
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Pages |
115637 - 23pp |
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Keywords |
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Abstract |
In this paper we investigate the (g – 2)(mu) discrepancy in the context of the R-parity conserving next-to minimal supersymmetric Standard Model plus right-handed neutrinos superfields. The model has the ability to reproduce neutrino physics data and includes the interesting possibility to have the right-handed sneutrino as the lightest supersymmetric particle and a viable dark matter candidate. Since right-handed sneutrinos are singlets, no new contributions for delta a(mu) with respect to the MSSM and NMSSM are present. However, the possibility to have the right-handed sneutrino as the lightest supersymmetric particle opens new ways to escape Large Hadron Collider and direct detection constraints. In particular, we find that dark matter masses within 10 less than or similar to m((upsilon) over tildeR) less than or similar to 600 GeV are fully compatible with current experimental constraints. Remarkably, not only spectra with light sleptons are needed, but we obtain solutions with m((mu) over tilde) greater than or similar to 600 GeV in the entire dark matter mass range that could be probed by new (g – 2)(mu) data in the near future. In addition, dark matter direct detection experiments will be able to explore a sizable portion of the allowed parameter space with mvR < 300 GeV, while indirect detection experiments will be able to probe a much smaller fraction within 200 less than or similar to m((nu)over tilde>R) less than or similar to 350 GeV. |
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Address |
[Kim, Jong Soo] Univ Witwatersrand, Sch Phys, Johannesburg, South Africa, Email: jongsoo.kim@tu-dortmund.de; |
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Elsevier |
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English |
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ISSN |
0550-3213 |
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Notes |
WOS:000760320700019 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5135 |
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Author |
Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Bhattacharyya, S.; Caron, S.; Johannesson, G.; Ruiz de Austri, R.; van den Oetelaar, C.; Zaharijas, G.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian |
Type |
Journal Article |
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Year |
2022 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
662 |
Issue |
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Pages |
A109 - 8pp |
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Keywords |
astronomical databases; miscellaneous; methods; data analysis; stars; imaging; techniques; image processing |
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Abstract |
Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available. |
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Address |
[Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys, IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl |
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Edp Sciences S A |
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English |
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0004-6361 |
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Notes |
WOS:000818665600009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5291 |
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Author |
Stoppa, F.; Ruiz de Austri, R.; Vreeswijk, P.; Bhattacharyya, S.; Caron, S.; Bloemen, S.; Zaharijas, G.; Principe, G.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation |
Type |
Journal Article |
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Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
680 |
Issue |
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Pages |
A108 - 14pp |
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Keywords |
astronomical databases: miscellaneous; methods: data analysis; stars: imaging; techniques: image processing |
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Abstract |
Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities. |
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Address |
[Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys, IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl |
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Corporate Author |
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Thesis |
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Publisher |
Edp Sciences S A |
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 |
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:001131898100003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5887 |
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| Permanent link to this record |
