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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., et al. (2020). Search for the HH ->b bbar b bbar process via vector-boson fusion production using proton-proton collisions at root s=13 TeV with the ATLAS detector. J. High Energy Phys., 07(7), 108–37pp.
Abstract: A search for Higgs boson pair production via vector-boson fusion (VBF) in the b bbar b bbar final state is carried out with the ATLAS experiment using 126 fb(-1) of proton- proton collision data delivered at root s = 13 TeV by the Large Hadron Collider. This search is sensitive to VBF production of additional heavy bosons that may decay into Higgs boson pairs, and in a non-resonant topology it can constrain the quartic coupling between the Higgs bosons and vector bosons. No significant excess relative to the Standard Model expectation is observed, and limits on the production cross-section are set at the 95% confidence level for a heavy scalar resonance in the context of an extended Higgs sector, and for non-resonant Higgs boson pair production. Interpretation in terms of the coupling between a Higgs boson pair and two vector bosons is also provided: coupling values normalised to the Standard Model expectation of kappa (2V)< -0.76 and <kappa>(2V)> 2.90 are excluded at the 95% confidence level in data.
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Vijande, J., Tedgren, A. C., Ballester, F., Baltas, D., Papagiannis, P., Rivard, M. J., et al. (2021). Source strength determination in iridium-192 and cobalt-60 brachytherapy: A European survey on the level of agreement between clinical measurements and manufacturer certificates. Phys. Imag. Radiat. Oncol., 19, 108–111.
Abstract: Background and purpose: Brachytherapy treatment outcomes depend on the accuracy of the delivered dose distribution, which is proportional to the reference air-kerma rate (RAKR). Current societal recommendations require the medical physicist to compare the measured RAKR values to the manufacturer source calibration certificate. The purpose of this work was to report agreement observed in current clinical practice in the European Union. Materials and methods: A European survey was performed for high- and pulsed-dose-rate (HDR and PDR) highenergy sources (Ir-192 and Co-60), to quantify observed RAKR differences. Medical physicists at eighteen hospitals from eight European countries were contacted, providing 1,032 data points from 2001 to 2020. Results: Over the survey period, 77% of the Ir-192 measurements used a well chamber instead of the older Krieger phantom method. Mean differences with the manufacturer calibration certificate were 0.01% +/- 1.15% for Ir-192 and -0.1% +/- 1.3% for Co-60. Over 95% of RAKR measurements in the clinic were within 3% of the manufacturer calibration certificate. Conclusions: This study showed that the agreement level was generally better than that reflected in prior societal recommendations positing 5%. Future recommendations on high-energy HDR and PDR source calibrations in the clinic may consider tightened agreements levels.
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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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Perez-Calatayud, J., Ballester, F., Tedgren, C., DeWerd, L. A., Papagiannis, P., Rivard, M. J., et al. (2022). GEC-ESTRO ACROP recommendations on calibration and traceability of HE HDR-PDR photon-emitting brachytherapy sources at the hospital level. Radiother. Oncol., 176, 108–117.
Abstract: The vast majority of radiotherapy departments in Europe using brachytherapy (BT) perform temporary implants of high-or pulsed-dose rate (HDR-PDR) sources with photon energies higher than 50 keV. Such techniques are successfully applied to diverse pathologies and clinical scenarios. These recommen-dations are the result of Working Package 21 (WP-21) initiated within the BRAchytherapy PHYsics Quality Assurance System (BRAPHYQS) GEC-ESTRO working group with a focus on HDR-PDR source cal-ibration. They provide guidance on the calibration of such sources, including practical aspects and issues not specifically accounted for in well-accepted societal recommendations, complementing the BRAPHYQS WP-18 Report dedicated to low energy BT photon emitting sources (seeds). The aim of this report is to provide a European-wide standard in HDR-PDR BT source calibration at the hospital level to maintain high quality patient treatments.
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Stoppa, F., Ruiz de Austri, R., Vreeswijk, P., Bhattacharyya, S., Caron, S., Bloemen, S., et al. (2023). AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation. Astron. Astrophys., 680, A108–14pp.
Abstract: Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities.
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Yao, D. L., Alvarez-Ruso, L., & Vicente Vacas, M. J. (2019). Neutral-current weak pion production off the nucleon in covariant chiral perturbation theory. Phys. Lett. B, 794, 109–113.
Abstract: Neutral current single pion production induced by neutrinos and antineutrinos on nucleon targets has been investigated in manifestly relativistic baryon chiral perturbation theory with explicit Delta(1232) degrees of freedom up to O(p(3)). At low energies, where chiral perturbation theory is applicable, the total cross sections for the different reaction channels exhibit a sizable non-resonant contribution, which is not present in event generators of broad use in neutrino oscillation and cross section experiments such as GENIE and NuWro.
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Searches for rare B-s(0) and B-0 decays into four muons. J. High Energy Phys., 03(3), 109–27pp.
Abstract: Searches for rare B-s(0) and B-0 decays into four muons are performed using proton-proton collision data recorded by the LHCb experiment, corresponding to an integrated luminosity of 9 fb(-1). Direct decays and decays via light scalar and J/psi resonances are considered. No evidence for the six decays searched for is found and upper limits at the 95% confidence level on their branching fractions ranging between 1.8 x 10(-10) and 2.6 x 10(-9) are set.
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Stoppa, F., Vreeswijk, P., Bloemen, S., Bhattacharyya, S., Caron, S., Johannesson, G., et al. (2022). AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian. Astron. Astrophys., 662, A109–8pp.
Abstract: Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.
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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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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., et al. (2020). Measurement of the Lambda(0)(b) -> J/psi Lambda angular distribution and the Lambda(0)(b) polarisation in pp collisions. J. High Energy Phys., 06(6), 110–30pp.
Abstract: This paper presents an analysis of the Lambda(0)(b) -> J/psi Lambda angular distribution and the transverse production polarisation of Lambda(0)(b) baryons in proton-proton collisions at centre-of-mass energies of 7, 8 and 13TeV. The measurements are performed using data corresponding to an integrated luminosity of 4.9 fb(-1), collected with the LHCb experiment. The polarisation is determined in a fiducial region of Lambda(0)(b) transverse momentum and pseudorapidity of 1 < p(T) < 20 GeV/c and 2 < eta < 5, respectively. The data are consistent with Lambda(0)(b) baryons being produced unpolarised in this region. The parity-violating asymmetry parameter of the Lambda -> p pi(-) decay is also determined from the data and its value is found to be consistent with a recent measurement by the BES III collaboration.
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