Aiola, S., Amhis, Y., Billoir, P., Jashal, B. K., Henry, L., Oyanguren, A., et al. (2021). Hybrid seeding: A standalone track reconstruction algorithm for scintillating fibre tracker at LHCb. Comput. Phys. Commun., 260, 107713–5pp.
Abstract: We describe the Hybrid seeding, a stand-alone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by exploiting the knowledge of the LHCb magnetic field and the position of energy deposits in the scintillating fibre tracker detector. Moreover, we achieve a low fake rate and a small contribution to the overall timing budget of the LHCb real-time data processing.
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Rinaldi, M., & Vento, V. (2024). Hybrid spectroscopy within the graviton soft-wall model. Phys. Rev. D, 109(11), 114030–13pp.
Abstract: In this analysis, the so-called holographic graviton soft-wall (GSW) model, first developed to investigate the glueball spectrum, has been adopted to predict the masses of hybrids with different quantum numbers. Results have been compared with other models and lattice calculations. We have extended the GSW model by introducing two modifications based on anomalous dimensions in order to improve our agreement with other calculations and to remove the initial degeneracy not accounted for by lattice predictions. These modifications do not involve new parameters. The next step has been to identify which of our calculated states agree with the PDG data, leading to experimental hybrids. The procedure has been extended to include hybrids made of heavy quarks by incorporating the quark masses into the model.
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Blanton, T. D., Romero-Lopez, F., & Sharpe, S. R. (2020). I=3 Three-Pion Scattering Amplitude from Lattice QCD. Phys. Rev. Lett., 124(3), 032001–7pp.
Abstract: We analyze the spectrum of two- and three-pion states of maximal isospin obtained recently for isosymmetric QCD with pion mass M approximate to 200 MeV in Horz and Hanlon, [Phys. Rev. Lett. 123, 142002 (2019)]. Using the relativistic three-particle quantization condition, we find similar to 2 sigma evidence for a nonzero value for the contact part of the 3 pi(+) (I = 3) scattering amplitude. We also compare our results to leading-order chiral perturbation theory. We find good agreement at threshold and some tension in the energy dependent part of the 3 pi(+) scattering amplitude. We also find that the 2 pi(+) (I = 2) spectrum is fit well by an s-wave phase shift that incorporates the expected Adler zero.
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Bertolez-Martinez, T., Arguelles, C., Esteban, I., Lopez-Pavon, J., Martinez-Soler, I., & Salvado, J. (2023). IceCube and the origin of ANITA-IV events. J. High Energy Phys., 07(7), 005–24pp.
Abstract: Recently, the ANITA collaboration announced the detection of new, unsettling upgoing Ultra-High-Energy (UHE) events. Understanding their origin is pressing to ensure success of the incoming UHE neutrino program. In this work, we study their internal consistency and the implications of the lack of similar events in IceCube. We introduce a generic, simple parametrization to study the compatibility between these two observatories in Standard Model-like and Beyond Standard Model scenarios: an incoming flux of particles that interact with Earth nucleons with cross section sigma, producing particle showers along with long-lived particles that decay with lifetime iota and generate a shower that explains ANITA observations. We find that the ANITA angular distribution imposes significant constraints, and when including null observations from IceCube only iota similar to 10(-3)-10(-2) s and sigma similar to 10(-33) -10(-32) cm(2) can explain the data. This hypothesis is testable with future IceCube data. Finally, we discuss a specific model that can realize this scenario. Our analysis highlights the importance of simultaneous observations by high-energy optical neutrino telescopes and new UHE radio detectors to uncover cosmogenic neutrinos or discover new physics.
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Coloma, P. (2019). Icecube/DeepCore tests for novel explanations of the MiniBooNE anomaly. Eur. Phys. J. C, 79(9), 748–7pp.
Abstract: While the low-energy excess observed at MiniBooNE remains unchallenged, it has become increasingly difficult to reconcile it with the results from other sterile neutrino searches and cosmology. Recently, it has been shown that non-minimal models with new particles in a hidden sector could provide a better fit to the data. As their main ingredients they require a GeV-scale kinetically mixed with the photon, and an unstable heavy neutrino with a mass in the 150 MeV range that mixes with the light neutrinos. In this letter we point out that atmospheric neutrino experiments (and, in particular, IceCube/DeepCore) could probe a significant fraction of the parameter space of such models by looking for an excess of “double-bang” events at low energies, as proposed in our previous work (Coloma et al., Phys Rev Lett 119(20):201804, 10.1103/PhysRevLett.119.20180, 2017). Such a search would probe exactly the same production and decay mechanisms required to explain the anomaly.
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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). Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector. Phys. Rev. D, 107(9), 092012–22pp.
Abstract: Measurements of electrons from ?e interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectra is derived, and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.
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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. (2019). Identification of boosted Higgs bosons decaying into b-quark pairs with the ATLAS detector at 13 TeV. Eur. Phys. J. C, 79(10), 836–38pp.
Abstract: This paper describes a study of techniques for identifying Higgs bosons at high transverse momenta decaying into bottom-quark pairs, H -> b (b) over bar, for proton-proton collision data collected by the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy root s = 13 TeV. These decays are reconstructed from calorimeter jets found with the anti-k(t) R = 1.0 jet algorithm. To tag Higgs bosons, a combination of requirements is used: b-tagging of R = 0.2 track-jets matched to the large-R calorimeter jet, and requirements on the jet mass and other jet substructure variables. The Higgs boson tagging efficiency and corresponding multijet and hadronic top-quark background rejections are evaluated using Monte Carlo simulation. Several benchmark tagging selections are defined for different signal efficiency targets. The modelling of the relevant input distributions used to tag Higgs bosons is studied in 36 fb(-1) of data collected in 2015 and 2016 using g -> b (b) over bar and Z(-> b (b) over bar)gamma event selections in data. Both processes are found to be well modelled within the statistical and systematic uncertainties.
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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). Identification of charm jets at LHCb. J. Instrum., 17(2), P02028–23pp.
Abstract: The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a dijet calibration dataset recorded by the LHCb detector and selected such that the jets are unbiased in quantities used in the tagging algorithm. The charm-tagging efficiency is reported as a function of the transverse momentum of the jet. The measured efficiencies are compared to those obtained from simulation and found to be in good agreement.
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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.
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Roser, J., Muñoz, E., Barrientos, L., Barrio, J., Bernabeu, J., Borja-Lloret, M., et al. (2020). Image reconstruction for a multi-layer Compton telescope: an analytical model for three interaction events. Phys. Med. Biol., 65(14), 145005–17pp.
Abstract: Compton Cameras are electronically collimated photon imagers suitable for sub-MeV to few MeV gamma-ray detection. Such features are desirable to enablein vivorange verification in hadron therapy, through the detection of secondary Prompt Gammas. A major concern with this technique is the poor image quality obtained when the incoming gamma-ray energy is unknown. Compton Cameras with more than two detector planes (multi-layer Compton Cameras) have been proposed as a solution, given that these devices incorporate more signal sequences of interactions to the conventional two interaction events. In particular, three interaction events convey more spectral information as they allow inferring directly the incident gamma-ray energy. A three-layer Compton Telescope based on continuous Lanthanum (III) Bromide crystals coupled to Silicon Photomultipliers is being developed at the IRIS group of IFIC-Valencia. In a previous work we proposed a spectral reconstruction algorithm for two interaction events based on an analytical model for the formation of the signal. To fully exploit the capabilities of our prototype, we present here an extension of the model for three interaction events. Analytical expressions of the sensitivity and the System Matrix are derived and validated against Monte Carlo simulations. Implemented in a List Mode Maximum Likelihood Expectation Maximization algorithm, the proposed model allows us to obtain four-dimensional (energy and position) images by using exclusively three interaction events. We are able to recover the correct spectrum and spatial distribution of gamma-ray sources when ideal data are employed. However, the uncertainties associated to experimental measurements result in a degradation when real data from complex structures are employed. Incorrect estimation of the incident gamma-ray interaction positions, and missing deposited energy associated with escaping secondaries, have been identified as the causes of such degradation by means of a detailed Monte Carlo study. As expected, our current experimental resolution and efficiency to three interaction events prevents us from correctly recovering complex structures of radioactive sources. However, given the better spectral information conveyed by three interaction events, we expect an improvement of the image quality of conventional Compton imaging when including such events. In this regard, future development includes the incorporation of the model assessed in this work to the two interaction events model in order to allow using simultaneously two and three interaction events in the image reconstruction.
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