Records |
Author |
Villanueva-Domingo, P.; Villaescusa-Navarro, F. |
Title |
Removing Astrophysics in 21 cm Maps with Neural Networks |
Type |
Journal Article |
Year |
2021 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
Volume |
907 |
Issue |
1 |
Pages |
44 - 14pp |
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Cosmology; Cold dark matter; Dark matter; Dark matter distribution; H I line emission; Intergalactic medium; Cosmological evolution; Convolutional neural networks; Large-scale structure of the universe |
Abstract |
Measuring temperature fluctuations in the 21 cm signal from the epoch of reionization and the cosmic dawn is one of the most promising ways to study the universe at high redshifts. Unfortunately, the 21 cm signal is affected by both cosmology and astrophysics processes in a nontrivial manner. We run a suite of 1000 numerical simulations with different values of the main astrophysical parameters. From these simulations we produce tens of thousands of 21 cm maps at redshifts 10 <= z <= 20. We train a convolutional neural network to remove the effects of astrophysics from the 21 cm maps and output maps of the underlying matter field. We show that our model is able to generate 2D matter fields not only that resemble the true ones visually but whose statistical properties agree with the true ones within a few percent down to scales 2 Mpc(-1). We demonstrate that our neural network retains astrophysical information that can be used to constrain the value of the astrophysical parameters. Finally, we use saliency maps to try to understand which features of the 21 cm maps the network is using in order to determine the value of the astrophysical parameters. |
Address |
[Villanueva-Domingo, Pablo] Univ Valencia, Inst Fis Corpuscular IFIC, CSIC, Apartado Correos 22085, E-46071 Valencia, Spain, Email: Pablo.Villanueva@ific.uv.es; |
Corporate Author |
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Thesis |
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Publisher |
Iop Publishing Ltd |
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 |
0004-637x |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
|
Notes |
WOS:000612333400001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4698 |
Permanent link to this record |
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Author |
Asai, M.; Cortes-Giraldo, M.A.; Gimenez-Alventosa, V.; Gimenez, V.; Salvat, F. |
Title |
The PENELOPE Physics Models and Transport Mechanics. Implementation into Geant4 |
Type |
Journal Article |
Year |
2021 |
Publication |
Frontiers in Physics |
Abbreviated Journal |
Front. Physics |
Volume |
9 |
Issue |
|
Pages |
738735 - 20pp |
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
coupled electron-photon transport; Monte Carlo simulation; PENELOPE code system; random-hinge method; Geant4 toolkit |
Abstract |
A translation of the penelope physics subroutines to C++, designed as an extension of the Geant4 toolkit, is presented. The Fortran code system penelope performs Monte Carlo simulation of coupled electron-photon transport in arbitrary materials for a wide energy range, nominally from 50 eV up to 1 GeV. Penelope implements the most reliable interaction models that are currently available, limited only by the required generality of the code. In addition, the transport of electrons and positrons is simulated by means of an elaborate class II scheme in which hard interactions (involving deflection angles or energy transfers larger than pre-defined cutoffs) are simulated from the associated restricted differential cross sections. After a brief description of the interaction models adopted for photons and electrons/positrons, we describe the details of the class-II algorithm used for tracking electrons and positrons. The C++ classes are adapted to the specific code structure of Geant4. They provide a complete description of the interactions and transport mechanics of electrons/positrons and photons in arbitrary materials, which can be activated from the G4ProcessManager to produce simulation results equivalent to those from the original penelope programs. The combined code, named PenG4, benefits from the multi-threading capabilities and advanced geometry and statistical tools of Geant4. |
Address |
[Asai, Makoto] SLAC Natl Accelerator Lab, Menlo Pk, CA USA, Email: miancortes@us.es; |
Corporate Author |
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Thesis |
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Publisher |
Frontiers Media Sa |
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 |
2296-424x |
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:000742889400001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5080 |
Permanent link to this record |
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Author |
NEXT Collaboration (Kekic, M. et al); Benlloch-Rodriguez, J.M.; Carcel, S.; Carrion, J.V.; Diaz, J.; Felkai, R.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Martinez-Lema, G.; Martinez-Vara, M.; Muñoz Vidal, J.; Novella, P.; Palmeiro, B.; Querol, M.; Renner, J.; Romo-Luque, C.; Sorel, M.; Uson, A.; Yahlali, N. |
Title |
Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment |
Type |
Journal Article |
Year |
2021 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
Volume |
01 |
Issue |
1 |
Pages |
189 - 22pp |
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Dark Matter and Double Beta Decay (experiments) |
Abstract |
Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses. |
Address |
[Hauptman, J.; Nygren, D. R.] Iowa State Univ, Dept Phys & Astron, 12 Phys Hall, Ames, IA 50011 USA, Email: marija.kekic@usc.es |
Corporate Author |
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Thesis |
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Publisher |
Springer |
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 |
1029-8479 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
|
Notes |
WOS:000616730800001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4729 |
Permanent link to this record |
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Author |
NEXT Collaboration (Martinez-Lema, G. et al); Benlloch-Rodriguez, J.M.; Carcel, S.; Carrion, J.V.; Diaz, J.; Felkai, R.; Kekic, M.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Martinez-Vara, M.; Muñoz Vidal, J.; Novella, P.; Palmeiro, B.; Querol, M.; Renner, J.; Romo-Luque, C.; Sorel, M.; Uson, A.; Yahlali, N. |
Title |
Sensitivity of the NEXT experiment to Xe-124 double electron capture |
Type |
Journal Article |
Year |
2021 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
Volume |
02 |
Issue |
2 |
Pages |
203 - 25pp |
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Dark Matter and Double Beta Decay (experiments) |
Abstract |
Double electron capture by proton-rich nuclei is a second-order nuclear process analogous to double beta decay. Despite their similarities, the decay signature is quite different, potentially providing a new channel to measure the hypothesized neutrinoless mode of these decays. The Standard-Model-allowed two-neutrino double electron capture (2 nu EC EC) has been predicted for a number of isotopes, but only observed in Kr-78, Ba-130 and, recently, Xe-124. The sensitivity to this decay establishes a benchmark for the ultimate experimental goal, namely the potential to discover also the lepton-number-violating neutrinoless version of this process, 0 nu EC EC. Here we report on the current sensitivity of the NEXT-White detector to Xe-124 2 nu EC EC and on the extrapolation to NEXT-100. Using simulated data for the 2 nu EC EC signal and real data from NEXT-White operated with Xe-124-depleted gas as background, we define an optimal event selection that maximizes the NEXT-White sensitivity. We estimate that, for NEXT-100 operated with xenon gas isotopically enriched with 1 kg of Xe-124 and for a 5-year run, a sensitivity to the 2 nu EC EC half-life of 6 x 10(22) y (at 90% confidence level) or better can be reached. |
Address |
[Goldschmidt, A.; Hauptman, J.; Laing, A.; Martinez, A.; Para, A.] Iowa State Univ, Dept Phys & Astron, 12 Phys Hall, Ames, IA 50011 USA, Email: gonzalo.martinez.lema@weizmann.ac.il |
Corporate Author |
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Thesis |
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Publisher |
Springer |
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 |
1029-8479 |
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:000624564800002 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4749 |
Permanent link to this record |
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Author |
NEXT Collaboration (Simon, A. et al); Carcel, S.; Carrion, J.V.; Diaz, J.; Felkai, R.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Martinez-Vara, M.; Muñoz Vidal, J.; Novella, P.; Palmeiro, B.; Querol, M.; Renner, J.; Romo-Luque, C.; Sorel, M.; Uson, A.; Yahlali, N. |
Title |
Boosting background suppression in the NEXT experiment through Richardson-Lucy deconvolution |
Type |
Journal Article |
Year |
2021 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
Volume |
07 |
Issue |
7 |
Pages |
146 - 38pp |
Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Dark Matter and Double Beta Decay (experiments) |
Abstract |
Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of similar to 10(27) yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of <similar to> 5 when reconstructing electron-positron pairs in the Tl-208 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterraneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of similar to 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV e(-)e(+) pairs, it leads to a background rejection factor of 27 at 57% signal efficiency. |
Address |
[Hauptman, J.] Iowa State Univ, Dept Phys & Astron, Ames, IA USA, Email: ander@post.bgu.ac.il; |
Corporate Author |
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Thesis |
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Publisher |
Springer |
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 |
|
Edition |
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ISSN |
1029-8479 |
ISBN |
|
Medium |
|
Area |
|
Expedition |
|
Conference |
|
Notes |
WOS:000677621700001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4906 |
Permanent link to this record |