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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 .
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Jueid, A., Kip, J., Ruiz de Austri, R., & Skands, P. (2023). Impact of QCD uncertainties on antiproton spectra from dark-matter annihilation. J. Cosmol. Astropart. Phys., 04(4), 068–15pp.
Abstract: Dark-matter particles that annihilate or decay can undergo complex sequences of processes, including strong and electromagnetic radiation, hadronisation, and hadron de-cays, before particles that are stable on astrophysical time scales are produced. Antiprotons produced in this way may leave footprints in experiments such as AMS-02. Several groups have reported an excess of events in the antiproton flux in the rigidity range of 10-20 GV. However, the theoretical modeling of baryon production is not straightforward and relies in part on phenomenological models in Monte Carlo event generators. In this work, we assess the impact of QCD uncertainties on the spectra of antiprotons from dark-matter annihila-tion. As a proof-of-principle, we show that for a two-parameter model that depends only on the thermally-averaged annihilation cross section ((o -v)) and the dark-matter mass (Mx), QCD uncertainties can affect the best-fit mass by up to ti 14% (with large uncertainties for large DM masses), depending on the choice of Mx and the annihilation channel (bb over bar or W+W-), and (o -v) by up to ti 10%. For comparison, changes to the underlying diffusion parameters are found to be within 1%-5%, and the results are also quite resilient to the choice of cosmic-ray propagation model. These findings indicate that QCD uncertainties need to be included in future DM analyses. To facilitate full-fledged analyses, we provide the spectra in tabulated form including QCD uncertainties and code snippets to perform mass interpolations and quick DM fits. The code can be found in this GitHub [1] repository.
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DUNE Collaboration(Abud, A. A. et al), Amedo, P., Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., et al. (2023). Highly-parallelized simulation of a pixelated LArTPC on a GPU. J. Instrum., 18(4), P04034–35pp.
Abstract: The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 103 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype.
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Caron, S., Eckner, C., Hendriks, L., Johannesson, G., Ruiz de Austri, R., & Zaharijas, G. (2023). Mind the gap: the discrepancy between simulation and reality drives interpretations of the Galactic Center Excess. J. Cosmol. Astropart. Phys., 06(6), 013–56pp.
Abstract: The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model (-yEM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of-yEMs with increasing parametric freedom. We calculate the fractional contribution (fsrc) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the ryEM. For the simplest ryEM, we obtain fsrc = 0.10 f 0.07, while the most complex model yields fsrc = 0.79 f 0.24. In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed ryEM. The quoted results for fsrc do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated ryEM iterations. We quantify the reality gap between our ryEMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed ryEMs have gaps to reality. Our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked “out of domain” uncertainties in future interpretations.
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Nzongani, U., Zylberman, J., Doncecchi, C. E., Perez, A., Debbasch, F., & Arnault, P. (2023). Quantum circuits for discrete-time quantum walks with position-dependent coin operator. Quantum Inf. Process., 22(7), 270–46pp.
Abstract: The aim of this paper is to build quantum circuits that implement discrete-time quantum walks having an arbitrary position-dependent coin operator. The position of the walker is encoded in base 2: with n wires, each corresponding to one qubit, we encode 2(n) position states. The data necessary to define an arbitrary position-dependent coin operator is therefore exponential in n. Hence, the exponentiality will necessarily appear somewhere in our circuits. We first propose a circuit implementing the position-dependent coin operator, that is naive, in the sense that it has exponential depth and implements sequentially all appropriate position-dependent coin operators. We then propose a circuit that “transfers” all the depth into ancillae, yielding a final depth that is linear in n at the cost of an exponential number of ancillae. Themain idea of this linear-depth circuit is to implement in parallel all coin operators at the different positions. Reducing the depth exponentially at the cost of having an exponential number of ancillae is a goal which has already been achieved for the problem of loading classical data on a quantum circuit (Araujo in Sci Rep 11:6329, 2021) (notice that such a circuit can be used to load the initial state of the walker). Here, we achieve this goal for the problem of applying a position-dependent coin operator in a discrete-time quantum walk. Finally, we extend the result of Welch (New J Phys 16:033040, 2014) from position-dependent unitaries which are diagonal in the position basis to position-dependent 2 x 2-block-diagonal unitaries: indeed, we show that for a position dependence of the coin operator (the block-diagonal unitary) which is smooth enough, one can find an efficient quantum-circuit implementation approximating the coin operator up to an error epsilon (in terms of the spectral norm), the depth and size of which scale as O(1/epsilon). A typical application of the efficient implementation would be the quantum simulation of a relativistic spin-1/2 particle on a lattice, coupled to a smooth external gauge field; notice that recently, quantum spatial-search schemes have been developed which use gauge fields as the oracle, to mark the vertex to be found (Zylberman in Entropy 23:1441, 2021), (Fredon arXiv:2210.13920). A typical application of the linear-depth circuit would be when there is spatial noise on the coin operator (and hence a non-smooth dependence in the position).
Keywords: Quantum walks; Quantum circuits; Quantum simulation
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Natochii, A. et al, & Marinas, C. (2023). Measured and projected beam backgrounds in the Belle II experiment at the SuperKEKB collider. Nucl. Instrum. Methods Phys. Res. A, 1055, 168550–21pp.
Abstract: The Belle II experiment at the SuperKEKB electron-positron collider aims to collect an unprecedented data set of 50 ab-1 to study CP-violation in the B-meson system and to search for Physics beyond the Standard Model. SuperKEKB is already the world's highest-luminosity collider. In order to collect the planned data set within approximately one decade, the target is to reach a peak luminosity of 6 x 1035 cm-2 s-1by further increasing the beam currents and reducing the beam size at the interaction point by squeezing the betatron function down to betay* = 0.3 mm. To ensure detector longevity and maintain good reconstruction performance, beam backgrounds must remain well controlled. We report on current background rates in Belle II and compare these against simulation. We find that a number of recent refinements have significantly improved the background simulation accuracy. Finally, we estimate the safety margins going forward. We predict that backgrounds should remain high but acceptable until a luminosity of at least 2.8 x 1035 cm-2 s-1is reached for betay* = 0.6 mm. At this point, the most vulnerable Belle II detectors, the Time-of-Propagation (TOP) particle identification system and the Central Drift Chamber (CDC), have predicted background hit rates from single-beam and luminosity backgrounds that add up to approximately half of the maximum acceptable rates.
Keywords: Detector background; Lepton collider; Monte-Carlo simulation
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de los Rios, M., Petac, M., Zaldivar, B., Bonaventura, N. R., Calore, F., & Iocco, F. (2023). Determining the dark matter distribution in simulated galaxies with deep learning. Mon. Not. Roy. Astron. Soc., 525(4), 6015–6035.
Abstract: We present a novel method of inferring the dark matter (DM) content and spatial distribution within galaxies, using convolutional neural networks (CNNs) trained within state-of-the-art hydrodynamical simulations (Illustris-TNG100). Within the controlled environment of the simulation, the framework we have developed is capable of inferring the DM mass distribution within galaxies of mass similar to 10(11)-10(13)M(circle dot) from the gravitationally baryon-dominated internal regions to the DM-rich, baryon-depleted outskirts of the galaxies, with a mean absolute error always below approximate to 0.25 when using photometrical and spectroscopic information. With respect to traditional methods, the one presented here also possesses the advantages of not relying on a pre-assigned shape for the DM distribution, to be applicable to galaxies not necessarily in isolation, and to perform very well even in the absence of spectroscopic observations.
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Baran, J. et al, & Brzezinski, K. (2024). Feasibility of the J-PET to monitor the range of therapeutic proton beams. Phys. Medica, 118, 103301–9pp.
Abstract: Purpose: The aim of this work is to investigate the feasibility of the Jagiellonian Positron Emission Tomography (J -PET) scanner for intra-treatment proton beam range monitoring. Methods: The Monte Carlo simulation studies with GATE and PET image reconstruction with CASToR were performed in order to compare six J -PET scanner geometries. We simulated proton irradiation of a PMMA phantom with a Single Pencil Beam (SPB) and Spread -Out Bragg Peak (SOBP) of various ranges. The sensitivity and precision of each scanner were calculated, and considering the setup's cost-effectiveness, we indicated potentially optimal geometries for the J -PET scanner prototype dedicated to the proton beam range assessment. Results: The investigations indicate that the double -layer cylindrical and triple -layer double -head configurations are the most promising for clinical application. We found that the scanner sensitivity is of the order of 10-5 coincidences per primary proton, while the precision of the range assessment for both SPB and SOBP irradiation plans was found below 1 mm. Among the scanners with the same number of detector modules, the best results are found for the triple -layer dual -head geometry. The results indicate that the double -layer cylindrical and triple -layer double -head configurations are the most promising for the clinical application, Conclusions: We performed simulation studies demonstrating that the feasibility of the J -PET detector for PET -based proton beam therapy range monitoring is possible with reasonable sensitivity and precision enabling its pre -clinical tests in the clinical proton therapy environment. Considering the sensitivity, precision and cost-effectiveness, the double -layer cylindrical and triple -layer dual -head J -PET geometry configurations seem promising for future clinical application.
Keywords: PET; Range monitoring; J-PET; Monte Carlo simulations; Proton radiotherapy
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n_TOF Collaboration(Alcayne, V. et al), Balibrea-Correa, J., Domingo-Pardo, C., Lerendegui-Marco, J., Babiano-Suarez, V., & Ladarescu, I. (2024). A Segmented Total Energy Detector (sTED) optimized for (n,γ) cross-section measurements at n_TOF EAR2. Radiat. Phys. Chem., 217, 11pp.
Abstract: The neutron time-of-flight facility nTOF at CERN is a spallation source dedicated to measurements of neutroninduced reaction cross-sections of interest in nuclear technologies, astrophysics, and other applications. Since 2014, Experimental ARea 2 (EAR2) is operational and delivers a neutron fluence of similar to 4 center dot 10(7) neutrons per nominal proton pulse, which is similar to 50 times higher than the one of Experimental ARea 1 (EAR1) of similar to 8 center dot 10(5) neutrons per pulse. The high neutron flux at EAR2 results in high counting rates in the detectors that challenged the previously existing capture detection systems. For this reason, a Segmented Total Energy Detector (sTED) has been developed to overcome the limitations in the detector's response, by reducing the active volume per module and by using a photo-multiplier (PMT) optimized for high counting rates. This paper presents the main characteristics of the sTED, including energy and time resolution, response to gamma-rays, and provides as well details of the use of the Pulse Height Weighting Technique (PHWT) with this detector. The sTED has been validated to perform neutron-capture cross-section measurements in EAR2 in the neutron energy range from thermal up to at least 400 keV. The detector has already been successfully used in several measurements at nTOF EAR2.
Keywords: Neutron capture; PHWT; Scintillation detectors; Monte Carlo simulation
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Balaudo, A., Calore, F., De Romeri, V., & Donato, F. (2024). NAJADS: a self-contained framework for the direct determination of astrophysical J-factors. J. Cosmol. Astropart. Phys., 02(2), 001–33pp.
Abstract: Cosmological simulations play a pivotal role in understanding the properties of the dark matter (DM) distribution in both galactic and galaxy -cluster environments. The characterization of DM structures is crucial for informing indirect DM searches, aiming at the detection of the annihilation (or decay) products of DM particles. A fundamental quantity in these analyses is the astrophysical J -factor. In the DM phenomenology community, J -factors are typically computed through the semi -analytical modelling of the DM mass distribution, which is affected by large uncertainties. With the scope of addressing and possibly reducing these uncertainties, we present NAJADS, a self-contained framework to derive the DM J -factor directly from the raw simulations data. We show how this framework can be used to compute all -sky maps of the J -factor, automatically accounting for the complex 3D structure of the simulated halos and for the boosting of the signal due to the density fluctuations along the line of sight. After validating our code, we present a proof -of -concept application of NAJADS to a realistic halo from the IllustrisTNG suite, and exploit it to make a thorough comparison between our numerical approach and traditional semi -analytical methods. JCAP02(2024)001
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