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SCiMMA and SNEWS Collaborations(Baxter, A. L. et al), & Colomer, M. (2022). Collaborative experience between scientific software projects using Agile Scrum development. Softw.-Pract. Exp., 52, 2077–2096.
Abstract: Developing sustainable software for the scientific community requires expertise in software engineering and domain science. This can be challenging due to the unique needs of scientific software, the insufficient resources for software engineering practices in the scientific community, and the complexity of developing for evolving scientific contexts. While open-source software can partially address these concerns, it can introduce complicating dependencies and delay development. These issues can be reduced if scientists and software developers collaborate. We present a case study wherein scientists from the SuperNova Early Warning System collaborated with software developers from the Scalable Cyberinfrastructure for Multi-Messenger Astrophysics project. The collaboration addressed the difficulties of open-source software development, but presented additional risks to each team. For the scientists, there was a concern of relying on external systems and lacking control in the development process. For the developers, there was a risk in supporting a user-group while maintaining core development. These issues were mitigated by creating a second Agile Scrum framework in parallel with the developers' ongoing Agile Scrum process. This Agile collaboration promoted communication, ensured that the scientists had an active role in development, and allowed the developers to evaluate and implement the scientists' software requirements. The collaboration provided benefits for each group: the scientists actuated their development by using an existing platform, and the developers utilized the scientists' use-case to improve their systems. This case study suggests that scientists and software developers can avoid scientific computing issues by collaborating and that Agile Scrum methods can address emergent concerns.
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Aliaga, R. J., & Guirao, A. J. (2019). On the preserved extremal structure of Lipschitz-free spaces. Studia Math., 245(1), 1–14.
Abstract: We characterize preserved extreme points of the unit ball of Lipschitz-free spaces F (X) in terms of simple geometric conditions on the underlying metric space (X, d). Namely, the preserved extreme points are the elementary molecules corresponding to pairs of points p, q in X such that the triangle inequality d (p, q) <= d (p, r) + d (q, r) is uniformly strict for r away from p, q. For compact X, this condition reduces to the triangle inequality being strict. As a consequence, we give an affirmative answer to a conjecture of N. Weaver that compact spaces are concave if and only if they have no triple of metrically aligned points, and we show that all extreme points are preserved for several classes of compact metric spaces X, including Holder and countable compacta.
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Ferrer-Sanchez, A., Martin-Guerrero, J., Ruiz de Austri, R., Torres-Forne, A., & Font, J. A. (2024). Gradient-annihilated PINNs for solving Riemann problems: Application to relativistic hydrodynamics. Comput. Meth. Appl. Mech. Eng., 424, 116906–18pp.
Abstract: We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that forces the model to partially ignore high-gradients in the physical variables, achieved by introducing a suitable weighting function. The method relies on a set of hyperparameters that control how gradients are treated in the physical loss. The performance of our methodology is demonstrated by solving Riemann problems in special relativistic hydrodynamics, extending earlier studies with PINNs in the context of the classical Euler equations. The solutions obtained with the GA-PINN model correctly describe the propagation speeds of discontinuities and sharply capture the associated jumps. We use the relative l(2) error to compare our results with the exact solution of special relativistic Riemann problems, used as the reference ''ground truth'', and with the corresponding error obtained with a second-order, central, shock-capturing scheme. In all problems investigated, the accuracy reached by the GA-PINN model is comparable to that obtained with a shock-capturing scheme, achieving a performance superior to that of the baseline PINN algorithm in general. An additional benefit worth stressing is that our PINN-based approach sidesteps the costly recovery of the primitive variables from the state vector of conserved variables, a well-known drawback of grid-based solutions of the relativistic hydrodynamics equations. Due to its inherent generality and its ability to handle steep gradients, the GA-PINN methodology discussed in this paper could be a valuable tool to model relativistic flows in astrophysics and particle physics, characterized by the prevalence of discontinuous solutions.
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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.
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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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Liang, J., Singh, B., McCutchan, E. A., Dillmann, I., Birch, M., Sonzogni, A. A., et al. (2020). Compilation and Evaluation of Beta-Delayed Neutron Emission Probabilities and Half-Lives for Z > 28 Precursors. Nucl. Data Sheets, 168, 1–116.
Abstract: We present a compilation and evaluation of experimental beta-delayed neutron emission probabilities (P-n) and half-lives (T-1/2) for known or potential beta-delayed neutron precursors with atomic number Z > 28 (Cu-73 – Fr-233). This article includes the recommended values of both of these quantities, together with a compilation of experimental measurements when available. Some notable cases, as well as proposed standards for beta-delayed neutron measurements are also discussed. Evaluated data has also been compared to systematics using three different approaches. The literature cut-off date for this work is August 15, 2020.
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Dimitriou, P. et al, Tain, J. L., & Algora, A. (2021). Development of a Reference Database for Beta-Delayed Neutron Emission. Nucl. Data Sheets, 173, 144–238.
Abstract: Beta-delayed neutron emission is important for nuclear structure and astrophysics as well as for reactor applications. Significant advances in nuclear experimental techniques in the past two decades have led to a wealth of new measurements that remain to be incorporated in the databases. We report on a coordinated effort to compile and evaluate all the available beta-delayed neutron emission data. The different measurement techniques have been assessed and the data have been compared with semi-microscopic and microscopic-macroscopic models. The new microscopic database has been tested against aggregate total delayed neutron yields, time-dependent group parameters in 6-and 8-group re-presentation, and aggregate delayed neutron spectra. New recommendations of macroscopic delayed-neutron data for fissile materials of interest to applications are also presented.
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Clausse, A., Soto, L., & Tarifeño-Saldivia, A. (2015). Influence of the Anode Length on the Neutron Emission of a 50 J Plasma Focus: Modeling and Experiment. IEEE Trans. Plasma Sci., 43(2), 629–636.
Abstract: A comprehensive set of electric data measured in a small plasma focus (PF) device of 50 J correlated with the corresponding neutron emissions is taken as the base for developing a semiempirical model of the current sheet dynamics and the neutron yield. The model is able to explain the dependence of the neutron yield with the pressure and anode length with good accuracy, and suggests a physical interpretation of the drive parameter commonly used in PF design.
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Aguiar, P., Rafecas, M., Ortuño, J. E., Kontaxakis, G., Santos, A., Pavia, J., et al. (2010). Geometrical and Monte Carlo projectors in 3D PET reconstruction. Med. Phys., 37(11), 5691–5702.
Abstract: Purpose: In the present work, the authors compare geometrical and Monte Carlo projectors in detail. The geometrical projectors considered were the conventional geometrical Siddon ray-tracer (S-RT) and the orthogonal distance-based ray-tracer (OD-RT), based on computing the orthogonal distance from the center of image voxel to the line-of-response. A comparison of these geometrical projectors was performed using different point spread function (PSF) models. The Monte Carlo-based method under consideration involves an extensive model of the system response matrix based on Monte Carlo simulations and is computed off-line and stored on disk. Methods: Comparisons were performed using simulated and experimental data of the commercial small animal PET scanner rPET. Results: The results demonstrate that the orthogonal distance-based ray-tracer and Siddon ray-tracer using PSF image-space convolutions yield better images in terms of contrast and spatial resolution than those obtained after using the conventional method and the multiray-based S-RT. Furthermore, the Monte Carlo-based method yields slight improvements in terms of contrast and spatial resolution with respect to these geometrical projectors. Conclusions: The orthogonal distance-based ray-tracer and Siddon ray-tracer using PSF image-space convolutions represent satisfactory alternatives to factorizing the system matrix or to the conventional on-the-fly ray-tracing methods for list-mode reconstruction, where an extensive modeling based on Monte Carlo simulations is unfeasible.
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Valdes-Cortez, C., Niatsetski, Y., Perez-Calatayud, J., Ballester, F., & Vijande, J. (2022). A Monte Carlo study of the relative biological effectiveness in surface brachytherapy. Med. Phys., 49, 5576–5588.
Abstract: Purpose This work aims to simulate clustered DNA damage from ionizing radiation and estimate the relative biological effectiveness (RBE) for radionuclide (rBT)- and electronic (eBT)-based surface brachytherapy through a hybrid Monte Carlo (MC) approach, using realistic models of the sources and applicators. Methods Damage from ionizing radiation has been studied using the Monte Carlo Damage Simulation algorithm using as input the primary electron fluence simulated using a state-of-the-art MC code, PENELOPE-2018. Two Ir-192 rBT applicators, Valencia and Leipzig, one Co-60 source with a Freiburg Flap applicator (reference source), and two eBT systems, Esteya and INTRABEAM, have been included in this study implementing full realizations of their geometries as disclosed by the manufacturer. The role played by filtration and tube kilovoltage has also been addressed. Results For rBT, an RBE value of about 1.01 has been found for the applicators and phantoms considered. In the case of eBT, RBE values for the Esteya system show an almost constant RBE value of about 1.06 for all depths and materials. For INTRABEAM, variations in the range of 1.12-1.06 are reported depending on phantom composition and depth. Modifications in the Esteya system, filtration, and tube kilovoltage give rise to variations in the same range. Conclusions Current clinical practice does not incorporate biological effects in surface brachytherapy. Therefore, the same absorbed dose is administered to the patients independently on the particularities of the rBT or eBT system considered. The almost constant RBE values reported for rBT support that assumption regardless of the details of the patient geometry, the presence of a flattening filter in the applicator design, or even significant modifications in the photon energy spectra above 300 keV. That is not the case for eBT, where a clear dependence on the eBT system and the characteristics of the patient geometry are reported. A complete study specific for each eBT system, including detailed applicator characteristics (size, shape, filtering, among others) and common anatomical locations, should be performed before adopting an existing RBE value.
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