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Author |
LISA Cosmology Working Group (Bartolo, N. et al); Figueroa, D.G. |
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Title |
Probing anisotropies of the Stochastic Gravitational Wave Background with LISA |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal  |
J. Cosmol. Astropart. Phys. |
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Volume |
11 |
Issue |
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Pages |
009 - 65pp |
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Keywords |
gravitational wave detectors; gravitational waves / sources; gravitational waves / theory; physics of the early universe |
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Abstract |
We investigate the sensitivity of the Laser Interferometer Space Antenna (LISA) to the anisotropies of the Stochastic Gravitational Wave Background (SGWB). We first discuss the main astrophysical and cosmological sources of SGWB which are characterized by anisotropies in the GW energy density, and we build a Signal-to-Noise estimator to quantify the sensitivity of LISA to different multipoles. We then perform a Fisher matrix analysis of the prospects of detectability of anisotropic features with LISA for individual multipoles, focusing on a SGWB with a power-law frequency profile. We compute the noise angular spectrum taking into account the specific scan strategy of the LISA detector. We analyze the case of the kinematic dipole and quadrupole generated by Doppler boosting an isotropic SGWB. We find that beta Omega(GW) similar to 2 x 10(-11) is required to observe a dipolar signal with LISA. The detector response to the quadrupole has a factor similar to 10(3) beta relative to that of the dipole. The characterization of the anisotropies, both from a theoretical perspective and from a map-making point of view, allows us to extract information that can be used to understand the origin of the SGWB, and to discriminate among distinct superimposed SGWB sources. |
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Address |
[Bartolo, Nicola; Bertacca, Daniele; Peloso, Marco; Ricciardone, Angelo] Univ Padua, Dipartimento Fis & Astron G Galilei, Via Marzolo 8, I-35131 Padua, Italy, Email: angelo.ricciardone@pd.infn.it |
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IOP Publishing Ltd |
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English |
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ISSN |
1475-7516 |
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WOS:000899443700009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5437 |
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Author |
Martinelli, M.; Scarcella, F.; Hogg, N.B.; Kavanagh, B.J.; Gaggero, D.; Fleury, P. |
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Title |
Dancing in the dark: detecting a population of distant primordial black holes |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
08 |
Issue |
8 |
Pages |
006 - 47pp |
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Keywords |
dark matter theory; gravitational waves / experiments; gravitational waves / sources; primordial black holes |
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Abstract |
Primordial black holes (PBHs) are compact objects proposed to have formed in the early Universe from the collapse of small-scale over-densities. Their existence may be detected from the observation of gravitational waves (GWs) emitted by PBH mergers, if the signals can be distinguished from those produced by the merging of astrophysical black holes. In this work, we forecast the capability of the Einstein Telescope, a proposed third-generation GW observatory, to identify and measure the abundance of a subdominant population of distant PBHs, using the difference in the redshift evolution of the merger rate of the two populations as our discriminant. We carefully model the merger rates and generate realistic mock catalogues of the luminosity distances and errors that would be obtained from GW signals observed by the Einstein Telescope. We use two independent statistical methods to analyse the mock data, finding that, with our more powerful, likelihood-based method, PBH abundances as small as fPBH approximate to 7 x 10(-6) ( fPBH approximate to 2 x 10(-6)) would be distinguishable from f(PBH) = 0 at the level of 3 sigma with a one year (ten year) observing run of the Einstein Telescope. Our mock data generation code, darksirens, is fast, easily extendable and publicly available on GitLab. |
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Address |
[Martinelli, Matteo] INAF Osservatorio Astron Roma, Via Frascati 33, I-00040 Rome, Italy, Email: matteo.martinelli@inaf.it; |
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IOP Publishing Ltd |
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1475-7516 |
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WOS:000911612900001 |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5461 |
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Author |
Gariazzo, S.; Gerbino, M.; Brinckmann, T.; Lattanzi, M.; Mena, O.; Schwetz, T.; Choudhury, S.R.; Freese, K.; Hannestad, S.; Ternes, C.A.; Tortola, M. |
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Title |
Neutrino mass and mass ordering: no conclusive evidence for normal ordering |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
10 |
Issue |
10 |
Pages |
010 - 18pp |
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Keywords |
Bayesian reasoning; neutrino properties; neutrino masses from cosmology; cosmological parameters from CMBR |
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Abstract |
The extraction of the neutrino mass ordering is one of the major challenges in particle physics and cosmology, not only for its implications for a fundamental theory of mass generation in nature, but also for its decisive role in the scale of future neutrinoless double beta decay experimental searches. It has been recently claimed that current oscillation, beta decay and cosmological limits on the different observables describing the neutrino mass parameter space provide robust decisive Bayesian evidence in favor of the normal ordering of the neutrino mass spectrum [1]. We further investigate these strong claims using a rich and wide phenomenology, with different sampling techniques of the neutrino parameter space. Contrary to the findings of Jimenez et al. [1], no decisive evidence for the normal mass ordering is found. Neutrino mass ordering analyses must rely on priors and parameterizations that are ordering-agnostic: robust results should be regarded as those in which the preference for the normal neutrino mass ordering is driven exclusively by the data, while we find a difference of up to a factor of 33 in the Bayes factors among the different priors and parameterizations exploited here. An ordering-agnostic prior would be represented by the case of parameterizations sampling over the two mass splittings and a mass scale, or those sampling over the individual neutrino masses via normal prior distributions only. In this regard, we show that the current significance in favor of the normal mass ordering should be taken as 2.7 sigma (i.e. moderate evidence), mostly driven by neutrino oscillation data. Let us stress that, while current data favor NO only mildly, we do not exclude the possibility that this may change in the future. Eventually, upcoming oscillation and cosmological data may (or may not) lead to a more significant exclusion of IO. |
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Address |
[Gariazzo, Stefano; Ternes, Christoph A.] Ist Nazl Fis Nucl INFN, Sez Torino, Via P Giuria 1, I-10125 Turin, Italy, Email: gariazzo@to.infn.it; |
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IOP Publishing Ltd |
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English |
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1475-7516 |
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Notes |
WOS:000928487200002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5477 |
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Author |
Aja, B. et al; Gimeno, B. |
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Title |
The Canfranc Axion Detection Experiment (CADEx): search for axions at 90 GHz with Kinetic Inductance Detectors |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Cosmology And Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
11 |
Issue |
11 |
Pages |
044 - 29pp |
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Keywords |
dark matter experiments; axions; dark matter detectors |
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Abstract |
We propose a novel experiment, the Canfranc Axion Detection Experiment (CADEx), to probe dark matter axions with masses in the range 330-460 μeV, within the W-band (80-110 GHz), an unexplored parameter space in the well-motivated dark matter window of Quantum ChromoDynamics (QCD) axions. The experimental design consists of a microwave resonant cavity haloscope in a high static magnetic field coupled to a highly sensitive detecting system based on Kinetic Inductance Detectors via optimized quasi-optics (horns and mirrors). The experiment is in preparation and will be installed in the dilution refrigerator of the Canfranc Underground Laboratory. Sensitivity forecasts for axion detection with CADEx, together with the potential of the experiment to search for dark photons, are presented. |
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Address |
[Aja, Beatriz; Artal, Eduardo; de la Fuente, Luisa; Pablo Pascual, Juan] Univ Cantabria, Dept Ingn Comunicac, Plaza Ciencia, Santander 39005, Spain, Email: ajab@unican.es; |
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IOP Publishing Ltd |
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English |
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1475-7516 |
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Notes |
WOS:000934034600003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5478 |
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Author |
Herrero-Garcia, J.; Patrick, R.; Scaffidi, A. |
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Title |
A semi-supervised approach to dark matter searches in direct detection data with machine learning |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
02 |
Issue |
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Pages |
039 - 19pp |
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Abstract |
The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods. |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5495 |
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Author |
Folgado, M.G.; Sanz, V. |
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Title |
Exploring the political pulse of a country using data science tools |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Computational Social Science |
Abbreviated Journal |
J. Comput. Soc. Sci. |
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Volume |
5 |
Issue |
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Pages |
987-1000 |
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Keywords |
Politics; Spain; Sentiment analysis; Artificial Intelligence; Machine learning; Neural networks; Natural Language Processing (NLP) |
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Abstract |
In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train a Fully-Connected Neural Network (FCNN) to recognise the political affiliation of a tweet. The FCNN is able to predict the origin of the tweet with a precision in the range of 71-75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as an example of how to use Twitter data and different types of Data Science tools for a political analysis. |
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Address |
[Folgado, Miguel G.; Sanz, Veronica] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Valencia 46980, Spain, Email: migarfol@upvnet.upv.es; |
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Springernature |
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English |
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ISSN |
2432-2717 |
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Notes |
WOS:000742263500002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5077 |
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Author |
Olmo, G.J.; Rubiera-Garcia, D. |
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Title |
Some recent results on Ricci-based gravity theories |
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Journal Article |
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Year |
2022 |
Publication |
International Journal of Modern Physics D |
Abbreviated Journal |
Int. J. Mod. Phys. D |
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Volume |
31 |
Issue |
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Pages |
2240012 - 15pp |
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Keywords |
Metric-affine gravity; scalar fields; stellar models; junction conditions; compact objects |
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Abstract |
In this paper, metric-afline theories in which the gravity Lagrangian is built using (projectively invariant) contractions of the Ricci tensor with itself and with the metric (Ricci-based gravity theories, or RBGs for short) are reviewed. The goal is to provide a contextualized and coherent presentation of some recent results. In particular, we focus on the correspondence that exists between the field equations of these theories and those of general relativity, and comment on how this can be used to build new solutions of physical interest. We also discuss the formalism of junction conditions in the f (R) case, and provide a brief summary on current experimental and observational bounds on model parameters. |
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Address |
[Olmo, Gonzalo J.] Univ Valencia, CSIC, Ctr Mixto, Dept Fis Teor, Valencia 46100, Spain, Email: gonzalo.olmo@uv.es; |
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World Scientific Publ Co Pte Ltd |
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English |
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ISSN |
0218-2718 |
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Notes |
WOS:000848888900001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5350 |
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Author |
Gola, S.; Mandal, S.; Sinha, N. |
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Title |
ALP-portal majorana dark matter |
Type |
Journal Article |
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Year |
2022 |
Publication |
International Journal of Modern Physics A |
Abbreviated Journal |
Int. J. Mod. Phys. A |
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Volume |
37 |
Issue |
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Pages |
2250131 - 14pp |
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Keywords |
Axion like particle; heavy neutrinos; dark matter |
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Abstract |
Axion like particles (ALPs) and right-handed neutrinos (RHNs) are two well-motivated dark matter (DM) candidates. However, these two particles have a completely different origin. Axion was proposed to solve the strong CP problem, whereas RHNs were introduced to explain light neutrino masses through seesaw mechanisms. We study the case of ALP portal RHN DM (Majorana DM) taking into account existing constraints on ALPs. We consider the leading effective operators mediating interactions between the ALP and Standard Model (SM) particles and three RHNs to generate light neutrino masses through type-I seesaw. Further, ALP-RHN neutrino coupling is introduced to generalize the model which is restricted by the relic density and indirect detection constraint. |
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Address |
[Gola, Shivam; Sinha, Nita] Inst Math Sci, CIT Campus, Chennai 600113, Tamil Nadu, India, Email: shivamg@imsc.res.in; |
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World Scientific Publ Co Pte Ltd |
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English |
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ISSN |
0217-751x |
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Notes |
WOS:000854297000001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5359 |
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Author |
Bordes, J.; Hong-Mo, C.; Tsun, T.S. |
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Title |
Resolving an ambiguity of Higgs couplings in the FSM, greatly improving thereby the model's predictive range and prospects |
Type |
Journal Article |
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Year |
2022 |
Publication |
International Journal of Modern Physics A |
Abbreviated Journal |
Int. J. Mod. Phys. A |
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Volume |
37 |
Issue |
27 |
Pages |
2250167 - 10pp |
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Keywords |
Framed standard model; Higgs decays; Yukawa couplings |
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Abstract |
We show that, after resolving what was thought to be an ambiguity in the Higgs coupling, the FSM gives, apart from two extra terms (i) and (ii) to be specified below, an effective action in the standard sector which has the same form as the SM action, the two differing only in the values of the mass and mixing parameters of quarks and leptons which the SM takes as Finputs from experiment while the FSM obtains as a result of a fit with a few parameters. Hence, to the accuracy that these two sets of parameters agree in value, and they do to a good extent as shown in earlier work,' the FSM should give the same result as the SM in all the circumstances where the latter has been successfully applied, except for the noted modifications due to (i) and (ii). If so, it would be a big step forward for the FSM. The correction terms are: (i) a mixing between the SM's gamma – Z with a new vector boson in the hidden sector, (ii) a mixing between the standard Higgs with a new scalar boson also in the hidden sector. And these have been shown a few years back to lead to (i') an enhancement of the W mass over the SM value,(2) – and (ii') effects consistent with the g – 2 and some other anomalies,(3) precisely the two deviations from the SM reported by experiments(4,5) recently much in the news. |
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Address |
[Bordes, Jose] Univ Valencia, CSIC, Dept Fis Teor, Ctr Mixto, Calle Dr Moliner 50, E-46100 Burjassot, Valencia, Spain, Email: jose.m.bordes@uv.es; |
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World Scientific Publ Co Pte Ltd |
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English |
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0217-751x |
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Notes |
WOS:000884996800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5414 |
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Author |
Albiol, A.; Albiol, F.; Paredes, R.; Plasencia-Martinez, J.M.; Blanco Barrio, A.; Garcia Santos, J.M.; Tortajada, S.; Gonzalez Montano, V.M.; Rodriguez Godoy, C.E.; Fernandez Gomez, S.; Oliver-Garcia, E.; de la Iglesia Vaya, M.; Marquez Perez, F.L.; Rayo Madrid, J.I. |
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Title |
A comparison of Covid-19 early detection between convolutional neural networks and radiologists |
Type |
Journal Article |
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Year |
2022 |
Publication |
Insights into Imaging |
Abbreviated Journal |
Insights Imaging |
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Volume |
13 |
Issue |
1 |
Pages |
122 - 12pp |
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Keywords |
Deep learning; Covid-19; Radiology |
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Abstract |
Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19. |
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Address |
[Albiol, Alberto] Univ Politecn Valencia, iTeam Inst, ETSI Telecomunicac, Camino Vera S-N, Valencia 46022, Spain, Email: alalbiol@iteam.upv.es |
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Springer |
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English |
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ISSN |
1869-4101 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
WOS:000832727200003 |
Approved |
no |
|
| |
Is ISI |
yes |
International Collaboration |
no |
|
| |
Call Number |
IFIC @ pastor @ |
Serial |
5302 |
|
| Permanent link to this record |
