|
|
Carrio, F. (2022). The Data Acquisition System for the ATLAS Tile Calorimeter Phase-II Upgrade Demonstrator. IEEE Trans. Nucl. Sci., 69(4), 687–695.
Abstract: The tile calorimeter (TileCal) is the central hadronic calorimeter of the ATLAS experiment at the large hadron collider (LHC). In 2025, the LHC will be upgraded leading to the high luminosity LHC (HL-LHC). The HL-LHC will deliver an instantaneous luminosity up to seven times larger than the LHC nominal luminosity. The ATLAS Phase-II upgrade (2025-2027) will accommodate the subdetectors to the HL-LHC requirements. As part of this upgrade, the majority of the TileCal on-detector and off-detector electronics will be replaced using a new readout strategy, where the on-detector electronics will digitize and transmit digitized detector data to the off-detector electronics at the bunch crossing frequency (40 MHz). In the counting rooms, the off-detector electronics will compute reconstructed trigger objects for the first-level trigger and will store the digitized samples in pipelined buffers until the reception of a trigger acceptance signal. The off-detector electronics will also distribute the LHC clock to the on-detector electronics embedded within the digital data stream. The TileCal Phase-II upgrade project has undertaken an extensive research and development program that includes the development of a Demonstrator module to evaluate the performance of the new clock and readout architecture envisaged for the HL-LHC. The Demonstrator module equipped with the latest version of the on-detector electronics was built and inserted into the ATLAS experiment. The Demonstrator module is operated and read out using a Tile PreProcessor (TilePPr) Demonstrator which enables backward compatibility with the present ATLAS Trigger and Data AcQuisition (TDAQ), and the timing, trigger, and command (TTC) systems. This article describes in detail the main hardware and firmware components of the clock distribution and data acquisition systems for the Demonstrator module, focusing on the TilePPr Demonstrator.
|
|
|
|
Dai, L. R., Oset, E., & Geng, L. S. (2022). The D-s(+)->pi(+KSKS0)-K-0 reaction and the I=1 partner of the f(0)(1710) state. Eur. Phys. J. C, 82(3), 225–9pp.
Abstract: We have identified the decay modes of the D-s(+)-> pi K+*K+*(-),pi+K*(0)(K) over bar*(0) reactions producing a pion and two vector mesons. The posterior vector-vector interaction generates two resonances that we associate to the f(0)(1710) and the a(0)(1710) recently claimed, and they decay to the observed K+K- or (KSKS0)-K-0 pair, leading to the reactions D-s(+)->pi+K+K-,pi(+KSKS0)-K-0. The results depend on two parameters related to external and internal emission. We determine a narrow region of the parameters consistent with the large N-c limit within uncertainties which gives rise to decay widths in agreement with experiment. With this scenario we make predictions for the branching ratio of the a(0)(1710) contribution to the D-s(+)->pi(K+KS0)-K-0 reaction, finding values within the range of (1.3 +/- 0.4)x10(-3). Comparison of these predictions with coming experimental results on that latter reaction will be most useful to deepen our understanding on the nature of these two resonances.
|
|
|
|
Lin, J. X., Li, J. T., Jiang, S. J., Liang, W. H., & Oset, E. (2021). The D-s(+) -> a(0)(980)e(+)nu(e) reaction and the a(0)(980) – f(0)(980) mixing. Eur. Phys. J. C, 81(11), 1017–8pp.
Abstract: We perform a study of the D-s(+) -> a(0)(980) (f(0)(980))e(+)nu(e) reactions investigating the different sources of isospin violation which make the production of the a0(980) possible. We find that loops involving kaons in the production mechanism provide a source of isospin violation since they do not cancel due to the different mass of charged and neutral kaons, but we also find that the main source comes from the breaking of isospin in the meson-meson transition T matrices, which contain information on the nature of the low lying scalar mesons. The reaction is thus very sensitive to the nature of the a(0)(980) and f(0)(980) resonances. Our results are consistent with the present upper bound for a(0)(980) production and only a factor three smaller, indicating that future runs with more statistics should find actual numbers for this reaction from where we can learn more about the origin of the scalar resonances and their nature.
|
|
|
|
van Beekveld, M., Caron, S., & Ruiz de Austri, R. (2020). The current status of fine-tuning in supersymmetry. J. High Energy Phys., 01(1), 147–41pp.
Abstract: In this paper, we minimize and compare two different fine-tuning measures in four high-scale supersymmetric models that are embedded in the MSSM. In addition, we determine the impact of current and future dark matter direct detection and collider experiments on the fine-tuning. We then compare the low-scale electroweak measure with the high-scale Barbieri-Giudice measure. We find that they reduce to the same value when the higgsino parameter drives the degree of fine-tuning. We also find spectra where the high-scale measure turns out to be lower than the low-scale measure. Depending on the high-scale model and fine-tuning definition, we find a minimal fine-tuning of 3-38 (corresponding to O(10-1)%) for the low-scale measure, and 63-571 (corresponding to O(1-0.1)%) for the high-scale measure. We stress that it is too early to conclude on the fate of supersymmetry, based only on the fine-tuning paradigm.
|
|
|
|
KM3NeT Collaboration(Aiello, S. et al), Calvo, D., Coleiro, A., Colomer, M., Gozzini, S. R., Hernandez-Rey, J. J., et al. (2020). The Control Unit of the KM3NeT Data Acquisition System. Comput. Phys. Commun., 256, 107433–16pp.
Abstract: The KM3NeT Collaboration runs a multi-site neutrino observatory in the Mediterranean Sea. Water Cherenkov particle detectors, deep in the sea and far off the coasts of France and Italy, are already taking data while incremental construction progresses. Data Acquisition Control software is operating off-shore detectors as well as testing and qualification stations for their components. The software, named Control Unit, is highly modular. It can undergo upgrades and reconfiguration with the acquisition running. Interplay with the central database of the Collaboration is obtained in a way that allows for data taking even if Internet links fail. In order to simplify the management of computing resources in the long term, and to cope with possible hardware failures of one or more computers, the KM3NeT Control Unit software features a custom dynamic resource provisioning and failover technology, which is especially important for ensuring continuity in case of rare transient events in multi-messenger astronomy. The software architecture relies on ubiquitous tools and broadly adopted technologies and has been successfully tested on several operating systems.
|
|
|
|
D'Auria, G. et al, Gonzalez-Iglesias, D., Gimeno, B., & Pereira, D. E. (2024). The CompactLight Design Study. Eur. Phys. J.-Spec. Top., , 1–208.
Abstract: CompactLight is a Design Study funded by the European Union under the Horizon 2020 research and innovation funding programme, with Grant Agreement No. 777431. CompactLight was conducted by an International Collaboration of 23 international laboratories and academic institutions, three private companies, and five third parties. The project, which started in January 2018 with a duration of 48 months, aimed to design an innovative, compact, and cost-effective hard X-ray FEL facility complemented by a soft X-ray source to pave the road for future compact accelerator-based facilities. The result is an accelerator that can be operated at up to 1 kHz pulse repetition rate, beyond today's state of the art, using the latest concepts for high brightness electron photoinjectors, very high gradient accelerating structures in X-band, and novel short-period undulators. In this report, we summarize the main deliverable of the project: the CompactLight Conceptual Design Report, which overviews the current status of the design and addresses the main technological challenges.
|
|
|
|
Jiang, S. J., Sakai, S., Liang, W. H., & Oset, E. (2019). The chi c J decay to phi K*(K)over-bar, phi h(1)(1380) testing the nature of axial vector meson resonances. Phys. Lett. B, 797, 134831–5pp.
Abstract: We perform a theoretical study of the chi(cJ) -> phi K*(K) over bar -> phi K pi(K) over bar reaction taking into account the K*(K) over bar final state interaction, which in the chiral unitary approach is responsible, together with its coupled channels, for the formation of the low lying axial vector mesons, in this case the h(1)(1380) given the selection of quantum numbers. Based on this picture we can easily explain why in the chi(c0) decay the h(1)(1380) resonance is not produced, and, in the case of chi(c1) and chi(c2) decay, why a dip in the K+ pi K-0(-) mass distribution appears in the 1550-1600 MeV region, that in our picture comes from a destructive interference between the tree level mechanism and the rescattering that generates the h(1)(1380) state. Such a dip is not reproduced in pictures where the nominal h(1)(1380) signal is added incoherently to a background, which provides support to the picture where the resonance appears from rescattering of vector-pseudoscalar components.
|
|
|
|
Aja, B. et al, & Gimeno, B. (2022). The Canfranc Axion Detection Experiment (CADEx): search for axions at 90 GHz with Kinetic Inductance Detectors. J. Cosmol. Astropart. Phys., 11(11), 044–29pp.
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.
|
|
|
|
Villaescusa-Navarro, F. et al, & Villanueva-Domingo, P. (2023). The CAMELS Project: Public Data Release. Astrophys. J. Suppl. Ser., 265(2), 54–14pp.
Abstract: The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lya spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at .
|
|
|
|
Villaescusa-Navarro, F. et al, & Villanueva-Domingo, P. (2022). The CAMELS Multifield Data Set: Learning the Universe's Fundamental Parameters with Artificial Intelligence. Astrophys. J. Suppl. Ser., 259(2), 61–14pp.
Abstract: We present the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) Multifield Data set (CMD), a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from more than 2000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span similar to 100 million light-years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine-learning models, CMD is the largest data set of its kind containing more than 70 TB of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.
|
|
