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Allanach, B. C., Martin, S. P., Robertson, D. G., & Ruiz de Austri, R. (2017). The inclusion of two-loop SUSYQCD corrections to gluino and squark pole masses in the minimal and next-to-minimal supersymmetric standard model: SOFTSUSY3.7. Comput. Phys. Commun., 219, 339–345.
Abstract: We describe an extension of the SOFTSUSY spectrum calculator to include two-loop supersymmetric QCD (SUSYQCD) corrections of order O(alpha(2)(s)) to gluino and squark pole masses, either in the minimal supersymmetric standard model (MSSM) or the next-to-minimal supersymmetric standard model (NMSSM). This document provides an overview of the program and acts as a manual for the new version of SOFTSUSY, which includes the increase in accuracy in squark and gluino pole mass predictions. Program summary Program title: SOFTSUSY Program Files doi: http://dx.doLorg/10.17632/sh77x9j7hs.1 Licensing provisions: GNU GPLv3 Programming language: C++, fortran, C Nature of problem: Calculating supersymmetric particle spectrum, mixing parameters and couplings in the MSSM or the NMSSM. The solution to the renormalization group equations must be consistent with theoretical boundary conditions on supersymmetry breaking parameters, as well as a weak-scale boundary condition on gauge couplings, Yukawa couplings and the Higgs potential parameters. Solution method: Nested fixed point iteration. Restrictions: SOFTSUSY will provide a solution only in the perturbative regime and it assumes that all couplings of the model are real (i.e. CP-conserving). If the parameter point under investigation is nonphysical for some reason (for example because the electroWeak potential does not have an acceptable minimum), SOFTSUSY returns an error message. The higher order corrections included are for the MSSM (R-parity conserving or violating) or the real R-parity conserving NMSSM only. Journal reference of previous version: Comput. Phys. Comm. 189 (2015) 192. Does the new version supersede the previous version?: Yes. Reasons for the new version: It is desirable to improve the accuracy of the squark and gluinos mass predictions, since they strongly affect supersymmetric particle production cross-sections at colliders. Summary of revisions: The calculation of the squark and gluino pole masses is extended to be of next-to next-to leading order in SUSYQCD, i.e. including terms up to O(g(s)(4)/(16 pi(2))(2)). Additional comments: Program obtainable from http://softsusy.hepforge.org/
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Gomez, M. E., Lola, S., Ruiz de Austri, R., & Shafi, Q. (2018). Confronting SUSY GUT With Dark Matter, Sparticle Spectroscopy and Muon (g – 2). Front. Physics, 6, 127–9pp.
Abstract: We explore the implications of LHC and cold dark matter searches for supersymmetric particle mass spectra in two different grand unified models with left-right symmetry, SO(10) and SU(4)(c) x SU(2)(L) x SU(2)(R) (4-2-2). We identify characteristic differences between the two scenarios, which imply distinct correlations between experimental measurements and the particular structure of the GUT group. The gauge structure of 4-2-2 enhances significantly the allowed parameter space as compared to SO(10), giving rise to a variety of coannihilation scenarios compatible with the LHC data, LSP dark matter and the ongoing muon g-2 experiment.
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Fidalgo, J., Lopez-Fogliani, D. E., Muñoz, C., & Ruiz de Austri, R. (2011). The Higgs sector of the μnu SSM and collider physics. J. High Energy Phys., 10(10), 020–33pp.
Abstract: The μnu SSM is a supersymmetric standard model that accounts for light neutrino masses and solves the μproblem of the MSSM by simply using right-handed neutrino superfields. Since this mechanism breaks R-parity, a peculiar structure for the mass matrices is generated. The neutral Higgses are mixed with the right- and left-handed sneutrinos producing 8x8 neutral scalar mass matrices. We analyse the Higgs sector of the μnu SSM in detail, with special emphasis in possible signals at colliders. After studying in general the decays of the Higges, we focus on those processes that are genuine of the μnu SSM, and could serve to distinguish it form other supersymmetric models. In particular, we present viable benchmark points for LHC searches. For example, we find decays of a MSSM-like Higgs into two lightest neutralinos, with the latter decaying inside the detector leading to displaced vertices, and producing final states with 4 and 8 b-jets plus missing energy. Final states with leptons and missing energy are also found.
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Stoppa, F., Bhattacharyya, S., Ruiz de Austri, R., Vreeswijk, P., Caron, S., Zaharijas, G., et al. (2023). AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information. Astron. Astrophys., 680, A109–16pp.
Abstract: Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.
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Casas, J. A., Moreno, J. M., Rius, N., Ruiz de Austri, R., & Zaldivar, B. (2011). Fair scans of the seesaw. Consequences for predictions on LFV processes. J. High Energy Phys., 03(3), 034–22pp.
Abstract: We give a straightforward procedure to scan the seesaw parameter-space, using the common “R-parametrization”, in a complete way. This includes a very simple rule to incorporate the perturbativity requirement as a condition for the entries of the R-matrix. As a relevant application, we show that the somewhat propagated belief that BR(mu -> e, gamma) in supersymmetric seesaw models depends strongly on the value of theta(13) is an “optical effect” produced by incomplete scans, and does not hold after a careful analytical and numerical study. When the complete scan is done, BR(mu -> e, gamma) gets very insensitive to theta(13). This holds even if the right-handed neutrino masses are kept constant or under control (as is required for succesful leptogenesis). In most cases the values of BR(mu -> e, gamma) are larger than the experimental upper bound. Including (unflavoured) leptogenesis does not introduce any further dependence on theta(13), although decreases the typical value of BR(mu -> e, gamma).
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Cannoni, M., Ellis, J., Gomez, M. E., Lola, S., & Ruiz de Austri, R. (2016). Supersymmetry searches in GUT models with non-universal scalar masses. J. Cosmol. Astropart. Phys., 03(3), 041–23pp.
Abstract: We study SO(10). SU(5) and flipped SU(5) GUT models with non-universal soft supersynrimetry-breaking scalar masses, exploring how they are constrained by LIIC super-synrimetry searches and cold dark matter experiments, and how they can be probed and distinguished in future experiments. We find characteristic differences between the-various GUT scenarios, particularly in the coannihilation region, which is very sensitive to changes of parameters. For example, the flipped SU(5) GUT predicts the possibility of (t) over tilde (1-chi) coannihilation, which is absent in the regions of the SO(10) and SU(5) GUT parameter spaces that we study. We use the relic density predictions in different models to determine upper bounds for the neutralino masses, and we find large differences between different GUT models in the sparticle spectra for the same LSP mass, leading to direct connections of distinctive possible experimental measurements with the structure of the GUT group. We find that future LHC searches for generic missing E-T, charginos and stops will be able to constrain the different GUT models in complementary ways, as will the Xenon 1 ton and Darwin dark matter scattering experiments and future FERMI or CIA gamma-ray searches.
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van Beekveld, M., Caron, S., Hendriks, L., Jackson, P., Leinweber, A., Otten, S., et al. (2021). Combining outlier analysis algorithms to identify new physics at the LHC. J. High Energy Phys., 09(9), 024–33pp.
Abstract: The lack of evidence for new physics at the Large Hadron Collider so far has prompted the development of model-independent search techniques. In this study, we compare the anomaly scores of a variety of anomaly detection techniques: an isolation forest, a Gaussian mixture model, a static autoencoder, and a beta-variational autoencoder (VAE), where we define the reconstruction loss of the latter as a weighted combination of regression and classification terms. We apply these algorithms to the 4-vectors of simulated LHC data, but also investigate the performance when the non-VAE algorithms are applied to the latent space variables created by the VAE. In addition, we assess the performance when the anomaly scores of these algorithms are combined in various ways. Using supersymmetric benchmark points, we find that the logical AND combination of the anomaly scores yielded from algorithms trained in the latent space of the VAE is the most effective discriminator of all methods tested.
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Balazs, C. et al, Mamuzic, J., & Ruiz de Austri, R. (2021). A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications. J. High Energy Phys., 05(5), 108–46pp.
Abstract: Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.
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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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Allanach, B. C., Bednyakov, A., & Ruiz de Austri, R. (2015). Higher order corrections and unification in the minimal supersymmetric standard model: SOFTSUSY3.5. Comput. Phys. Commun., 189, 192–206.
Abstract: We explore the effects of three-loop minimal supersymmetric standard model renormalisation group equation terms and some leading two-loop threshold corrections on gauge and Yukawa unification: each being one loop higher order than current public spectrum calculators. We also explore the effect of the higher order terms (often 2-3 GeV) on the lightest CP even Higgs mass prediction. We illustrate our results in the constrained minimal supersymmetric standard model. Neglecting threshold corrections at the grand unified scale, the discrepancy between the unification scale alpha(s) and the other two unified gauge couplings changes by 0.1% due to the higher order corrections and the difference between unification scale bottom-tau Yukawa couplings neglecting unification scale threshold corrections changes by up to 1%. The difference between unification scale bottom and top Yukawa couplings changes by a few percent. Differences due to the higher order corrections also give an estimate of the size of theoretical uncertainties in the minimal supersymmetric standard model spectrum. We use these to provide estimates of theoretical uncertainties in predictions of the dark matter relic density (which can be of order one due to its strong dependence on sparticle masses) and the LHC sparticle production cross-section (often around 30%). The additional higher order corrections have been incorporated into SOFTSUSY, and we provide details on how to compile and use the program. We also provide a summary of the approximations used in the higher order corrections. Program Summary Nature of problem: Calculating supersymmetric particle spectrum and mixing parameters in the minimal supersymmetric standard model. The solution to the renormalisation group equations must be consistent with boundary conditions on supersymmetry breaking parameters, as well as the weak-scale boundary condition on gauge couplings, Yukawa couplings and the Higgs potential parameters. Program title: SOFTSUSY Catalogue identifier: ADPMv50 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ADPMv50.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 240528 No. of bytes in distributed program, including test data, etc.: 2597933 Distribution format: tar.gz Programming language: C++, Fortran. Computer: Personal computer. Operating system: Tested on Linux 3.4.6. Word size: 64 bits. Classification: 11.1, 11.6. External routines: At least GiNaC1.3.5 [1] and CLN1.3.1 (both freely obtainable from http://www.ginac.de). Does the new version supersede the previous version?: Yes Catalogue identifier of previous version: ADPMv40 Journal reference of previous version: Comput. Phys. Comm. 185 (2014) 2322 Solution method: Nested iterative algorithm. Reasons for new version: Extension to include additional two and three-loop terms. Summary of revisions: All quantities in the minimal supersymmetric standard model are extended to have three-loop renormalisation group equations (including 3-family mixing) in the limit of real parameters and some leading two-loop threshold corrections are incorporated to the third family Yukawa couplings and the strong gauge coupling. Restrictions: SOFTSUSY will provide a solution only in the perturbative regime and it assumes that all couplings of the model are real (i.e. CP-conserving). If the parameter point under investigation is non-physical for some reason (for example because the electroweak potential does not have an acceptable minimum), SOFTSUSY returns an error message. The higher order corrections included are for the real R-parity conserving minimal supersymmetric standard model (MSSM) only. Running time: A minute per parameter point. The tests provided with the package only take a few seconds to run.
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