Albandea, D., Del Debbio, L., Hernandez, P., Kenway, R., Marsh Rossney, J., & Ramos, A. (2023). Learning trivializing flows. Eur. Phys. J. C, 83(7), 676–14pp.
Abstract: The recent introduction of machine learning techniques, especially normalizing flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling efficiency of the traditional hybrid Monte Carlo (HMC) algorithm. In this work we study a modified HMC algorithm that draws on the seminal work on trivializing flows by L & uuml;scher. Autocorrelations are reduced by sampling from a simpler action that is related to the original action by an invertible mapping realised through Normalizing Flows models with a minimal set of training parameters. We test the algorithm in a f(4) theory in 2D where we observe reduced autocorrelation times compared with HMC, and demonstrate that the training can be done at small unphysical volumes and used in physical conditions. We also study the scaling of the algorithm towards the continuum limit under various assumptions on the network architecture.
|
n_TOF Collaboration(Michalopoulou, V. et al), Babiano-Suarez, V., Caballero, L., Domingo-Pardo, C., Ladarescu, I., & Tain, J. L. (2023). Measurement of the neutron-induced fission cross section of Th-230 at the CERN n_TOF facility. Phys. Rev. C, 108(1), 014616–15pp.
Abstract: The neutron-induced fission cross section of Th-230 has been measured at the neutron time-of-flight facility n_TOF located at CERN. The experiment was performed at the experimental area EAR-1 with a neutron flight path of 185 m, using Micromegas detectors for the detection of the fission fragments. The Th-230(n, f ) cross section was determined relative to the U-235(n, f ) one, covering the energy range from the fission threshold up to 400 MeV. The results from the present work are compared with existing cross-section datasets and the observed discrepancies are discussed and analyzed. Finally, using the code EMPIRE 3.2.3 a theoretical study, based on the statistical model, was performed leading to a satisfactory reproduction of the experimental results with the proper tuning of the respective parameters, while for incident neutron energy beyond 200 MeV the fission of( 230)Th was described by Monte Carlo simulations.
|
n_TOF Collaboration(Torres-Sanchez, P. et al), Babiano-Suarez, V., Caballero, L., Domingo-Pardo, C., Ladarescu, I., & Tain, J. L. (2023). Measurement of the 14N(n, p) 14C cross section at the CERN n_TOF facility from subthermal energy to 800 keV. Phys. Rev. C, 107(6), 064617–15pp.
Abstract: Background: The 14N(n, p) 14C reaction is of interest in neutron capture therapy, where nitrogen-related dose is the main component due to low-energy neutrons, and in astrophysics, where 14N acts as a neutron poison in the s process. Several discrepancies remain between the existing data obtained in partial energy ranges: thermal energy, keV region, and resonance region. Purpose: We aim to measure the 14N(n, p) 14C cross section from thermal to the resonance region in a single measurement for the first time, including characterization of the first resonances, and provide calculations of Maxwellian averaged cross sections (MACS). Method: We apply the time-of-flight technique at Experimental Area 2 (EAR-2) of the neutron time-of-flight (n_TOF) facility at CERN. 10B(n, & alpha;) 7Li and 235U(n, f ) reactions are used as references. Two detection systems are run simultaneously, one on beam and another off beam. Resonances are described with the R-matrix code SAMMY. Results: The cross section was measured from subthermal energy to 800 keV, resolving the first two resonances (at 492.7 and 644 keV). A thermal cross section was obtained (1.809 & PLUSMN; 0.045 b) that is lower than the two most recent measurements by slightly more than one standard deviation, but in line with the ENDF/B-VIII.0 and JEFF-3.3 evaluations. A 1/v energy dependence of the cross section was confirmed up to tens of keV neutron energy. The low energy tail of the first resonance at 492.7 keV is lower than suggested by evaluated values, while the overall resonance strength agrees with evaluations. Conclusions: Our measurement has allowed determination of the 14N(n, p) cross section over a wide energy range for the first time. We have obtained cross sections with high accuracy (2.5%) from subthermal energy to 800 keV and used these data to calculate the MACS for kT = 5 to kT = 100 keV.
|
Montesinos, V., Albaladejo, M., Nieves, J., & Tolos, L. (2023). Properties of the Tcc(3875)+ and Tcbar,cbar(3875)- and their heavy-quark spin partners in nuclear matter. Phys. Rev. C, 108(3), 035205–15pp.
Abstract: We discuss the modification of the properties of the tetraquark-like Tcc(3875)+ and Tc over bar c over bar (3875)- states in dense nuclear matter. We consider the Tcc+ and Tc over bar c over bar – in vacuum as purely isoscalar D*D and D*D S-wave bound states, respectively, dynamically generated from a heavy-quark effective interaction between the charmed mesons. We compute the D, D, D*, and D* spectral functions embedded in a nuclear medium and use them to determine the corresponding Tcc+ and Tc over bar c over bar – self-energies and spectral functions. We find important modifications of the D*D and D*D scattering amplitudes and of the pole position of these exotic states already for p0/2, with p0 the normal nuclear density. We also discuss the dependence of these results on the D*D (D*D) molecular component in the Tcc+ (Tc over bar c- over bar ) wave function. Owing to the different nature of the D(*)N and D(*)N interactions, we find characteristic changes of the in-medium properties of the Tcc(3875)+ and Tc over bar c over bar (3875)-, which become increasingly visible as the density increases. The experimental confirmation of the found distinctive density pattern will give support to the existence of molecular components in these tetraquark-like states, since in the case they were mostly colorless compact quark structures (cct over bar t over bar and c over bar c over bar tt, with t = u, d), the density behaviors of the Tcc(3875)+ and Tc over bar c over bar (3875)- nuclear medium spectral functions, though different, would not likely be the same as those found in this work for molecular scenarios. Finally, we perform similar analyses for the isoscalar JP = 1+ heavy-quark spin symmetry partners of the Tcc+ (T cc *+ ) and the T c over bar c- over bar (T*- c over bar c over bar ) by considering the D*0D*+ and D*0D*- scattering T matrices.
|
Fernandez Casani, A., Garcia Montoro, C., Gonzalez de la Hoz, S., Salt, J., Sanchez, J., & Villaplana Perez, M. (2023). Big Data Analytics for the ATLAS EventIndex Project with Apache Spark. Comput. Math. Methods, 2023, 6900908–19pp.
Abstract: The ATLAS EventIndex was designed to provide a global event catalogue and limited event-level metadata for ATLAS experiment of the Large Hadron Collider (LHC) and their analysis groups and users during Run 2 (2015-2018) and has been running in production since. The LHC Run 3, started in 2022, has seen increased data-taking and simulation production rates, with which the current infrastructure would still cope but may be stretched to its limits by the end of Run 3. A new core storage service is being developed in HBase/Phoenix, and there is work in progress to provide at least the same functionality as the current one for increased data ingestion and search rates and with increasing volumes of stored data. In addition, new tools are being developed for solving the needed access cases within the new storage. This paper describes a new tool using Spark and implemented in Scala for accessing the big data quantities of the EventIndex project stored in HBase/Phoenix. With this tool, we can offer data discovery capabilities at different granularities, providing Spark Dataframes that can be used or refined within the same framework. Data analytic cases of the EventIndex project are implemented, like the search for duplicates of events from the same or different datasets. An algorithm and implementation for the calculation of overlap matrices of events across different datasets are presented. Our approach can be used by other higher-level tools and users, to ease access to the data in a performant and standard way using Spark abstractions. The provided tools decouple data access from the actual data schema, which makes it convenient to hide complexity and possible changes on the backed storage.
|
