Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
|
PANDA Collaboration(Singh, B. et al), & Diaz, J. (2017). Feasibility study for the measurement of pi N transition distribution amplitudes at PANDA in bar(p) p -> J/psi pi(0). Phys. Rev. D, 95(3), 032003–25pp.
Abstract: The exclusive charmonium production process in (P) over barp annihilation with an associated pi 0 meson (p) over barp -> J/psi pi(0) is studied in the framework of QCD collinear factorization. The feasibility of measuring this reaction through the J/psi -> e(+) e(-) decay channel with the AntiProton ANnihilation at DArmstadt ((P) over bar ANDA) experiment is investigated. Simulations on signal reconstruction efficiency as well as the background rejection from various sources including the (P) over barp -> pi(+)pi(-)pi(0) and (p) over barp -> J/psi pi(0)pi(0) reactions are performed with PANDAROOT, the simulation and analysis software framework of the (P) over bar ANDA experiment. It is shown that the measurement can be done at (P) over bar ANDA with significant constraining power under the assumption of an integrated luminosity attainable in four to five months of data taking at the maximum design luminosity.
|
PANDA Collaboration(Singh, B. et al), & Diaz, J. (2019). Technical design report for the (P)over-barANDA Barrel DIRC detector. J. Phys. G, 46(4), 045001–155pp.
Abstract: The (P) over bar ANDA (anti-Proton ANnihiliation at DArmstadt) experiment will be one of the four flagship experiments at the new international accelerator complex FAIR (Facility for Antiproton and Ion Research) in Darmstadt, Germany. (P) over bar ANDA will address fundamental questions of hadron physics and quantum chromodynamics using high-intensity cooled antiproton beams with momenta between 1.5 and 15 GeV/c and a design luminosity of up to 2 x 10(32) cm(-2) S-1. Excellent particle identification (PID) is crucial to the success of the (P) over bar ANDA physics program. Hadronic PID in the barrel region of the target spectrometer will be performed by a fast and compact Cherenkov counter using the detection of internally reflected Cherenkov light (DIRC) technology. It is designed to cover the polar angle range from 22 degrees to 140 degrees and will provide at least 3 standard deviations (s.d.) pi/K separation up to 3.5 GeV/c, matching the expected upper limit of the final state kaon momentum distribution from simulation. This documents describes the technical design and the expected performance of the (P) over bar ANDA Barrel DIRC detector. The design is based on the successful BaBar DIRC with several key improvements. The performance and system cost were optimized in detailed detector simulations and validated with full system prototypes using particle beams at GSI and CERN. The final design meets or exceeds the PID goal of clean pi/K separation with at least 3 s.d. over the entire phase space of charged kaons in the Barrel DIRC.
|
PANDA Collaboration(Davi, F. et al), & Diaz, J. (2022). Technical design report for the endcap disc DIRC. J. Phys. G, 49(12), 120501–128pp.
Abstract: PANDA (anti-proton annihiliation at Darmstadt) is planned to be one of the four main experiments at the future international accelerator complex FAIR (Facility for Antiproton and Ion Research) in Darmstadt, Germany. It is going to address fundamental questions of hadron physics and quantum chromodynamics using cooled antiproton beams with a high intensity and and momenta between 1.5 and 15 GeV/c. PANDA is designed to reach a maximum luminosity of 2 x 10(32) cm(-2) s. Most of the physics programs require an excellent particle identification (PID). The PID of hadronic states at the forward endcap of the target spectrometer will be done by a fast and compact Cherenkov detector that uses the detection of internally reflected Cherenkov light (DIRC) principle. It is designed to cover the polar angle range from 5 degrees to 22 degrees and to provide a separation power for the separation of charged pions and kaons up to 3 standard deviations (s.d.) for particle momenta up to 4 GeV/c in order to cover the important particle phase space. This document describes the technical design and the expected performance of the novel PANDA disc DIRC detector that has not been used in any other high energy physics experiment before. The performance has been studied with Monte-Carlo simulations and various beam tests at DESY and CERN. The final design meets all PANDA requirements and guarantees sufficient safety margins.
|
PANDA Collaboration(Barucca, G. et al), & Diaz, J. (2019). Precision resonance energy scans with the PANDA experiment at FAIR: Sensitivity study for width and line shape measurements of the X(3872). Eur. Phys. J. A, 55(3), 42–18pp.
Abstract: This paper summarises a comprehensive Monte Carlo simulation study for precision resonance energy scan measurements. Apart from the proof of principle for natural width and line shape measurements of very narrow resonances with PANDA, the achievable sensitivities are quantified for the concrete example of the charmonium-like X(3872) state discussed to be exotic, and for a larger parameter space of various assumed signal cross-sections, input widths and luminosity combinations. PANDA is the only experiment that will be able to perform precision resonance energy scans of such narrow states with quantum numbers of spin and parities that differ from JPC=1--.
|
Pakarinen, J. et al, & Algora, A. (2017). Collectivity in Pb-196, Pb-198 isotopes probed in Coulomb-excitation experiments at REX-ISOLDE. J. Phys. G, 44(6), 064009–10pp.
Abstract: The neutron-deficient Pb-196,Pb-198 isotopes have been studied in Coulomb-excitation experiments employing the Miniball gamma-ray spectrometer and radioactive ion beams from the REX-ISOLDE post-accelerator at CERN. The reduced transition probabilities of the first excited 2(+) states in Pb-196 and Pb-198 nuclei have been measured for the first time. Values of B (E2) = 18.2(-4.1)(+4.8) W. u. and B (E2) = 13.1(-3.5)(+4.9) W. u., were obtained, respectively. The experiment sheds light on the development of collectivity when moving from the regime governed by the generalised seniority scheme to a region, where intruding structures, associated with different deformed shapes, start to come down in energy and approach the spherical ground state.
|
Pajtler, M. V. et al, & Gadea, A. (2021). Excited states of Y-90,Y-92,Y-94 populated in Zr-90+Pb-208 multinucleon transfer reaction. Phys. Scr., 96(3), 035305–7pp.
Abstract: Multinucleon transfer reactions in Zr-90+Pb-208 have been studied via fragment-gamma coincidences, employing the PRISMA magnetic spectrometer coupled to the CLARA gamma-array. An analysis on Y isotopes has been carried out incorporating spectroscopic as well as reaction mechanism aspects. New gamma transitions have been observed in Y-94, confirming the findings of recent studies where nuclei were produced via fission of uranium, and a comparison with near-by Y-90,Y-92 isotopes populated in the same reaction has been discussed. Experimental cross sections have been extracted and compared with the GRAZING calculations, showing a fair agreement along the neutron pick-up side. The results confirm how multinucleon transfer reactions are a suitable mechanism for the study of neutron-rich nuclei.
|
Pagura, V. P., Gomez Dumm, D., Noguera, S., & Scoccola, N. N. (2017). Magnetic catalysis and inverse magnetic catalysis in nonlocal chiral quark models. Phys. Rev. D, 95(3), 034013–7pp.
Abstract: We study the behavior of strongly interacting matter under an external constant magnetic field in the context of nonlocal chiral quark models within the mean field approximation. We find that at zero temperature the behavior of the quark condensates shows the expected magnetic catalysis effect, our predictions being in good quantitative agreement with lattice QCD results. On the other hand, in contrast to what happens in the standard local Nambu-Jona-Lasinio model, when the analysis is extended to the case of finite temperature, our results show that nonlocal models naturally lead to the inverse magnetic catalysis effect.
|
Otten, S., Rolbiecki, K., Caron, S., Kim, J. S., Ruiz de Austri, R., & Tattersall, J. (2020). DeepXS: fast approximation of MSSM electroweak cross sections at NLO. Eur. Phys. J. C, 80(1), 12–9pp.
Abstract: We present a deep learning solution to the prediction of particle production cross sections over a complicated, high-dimensional parameter space. We demonstrate the applicability by providing state-of-the-art predictions for the production of charginos and neutralinos at the Large Hadron Collider (LHC) at the next-to-leading order in the phenomenological MSSM-19 and explicitly demonstrate the performance for pp ->(chi) over tilde (+)(1)(chi) over tilde (-)(1), (chi) over tilde (0)(2)(chi) over tilde (0)(2) and (chi) over tilde (0)(2)(chi) over tilde (+/-)(1) as a proof of concept which will be extended to all SUSY electroweak pairs. We obtain errors that are lower than the uncertainty from scale and parton distribution functions with mean absolute percentage errors of well below 0.5% allowing a safe inference at the next-to-leading order with inference times that improve the Monte Carlo integration procedures that have been available so far by a factor of O(10(7)) from O(min) to O(mu s) per evaluation.
|
Otten, S., Caron, S., de Swart, W., van Beekveld, M., Hendriks, L., van Leeuwen, C., et al. (2021). Event generation and statistical sampling for physics with deep generative models and a density information buffer. Nat. Commun., 12(1), 2985–16pp.
Abstract: Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events like Monte Carlo generators. We study three processes: a simple two-body decay, the processes e(+)e(-)-> Z -> l(+)l(-) and pp -> tt<mml:mo><overbar></mml:mover> including the decay of the top quarks and a simulation of the detector response. By buffering density information of encoded Monte Carlo events given the encoder of a Variational Autoencoder we are able to construct a prior for the sampling of new events from the decoder that yields distributions that are in very good agreement with real Monte Carlo events and are generated several orders of magnitude faster. Applications of this work include generic density estimation and sampling, targeted event generation via a principal component analysis of encoded ground truth data, anomaly detection and more efficient importance sampling, e.g., for the phase space integration of matrix elements in quantum field theories. Here, the authors report buffered-density variational autoencoders for the generation of physical events. This method is computationally less expensive over other traditional methods and beyond accelerating the data generation process, it can help to steer the generation and to detect anomalies.
|
