相关论文: Neutrino Interaction Vertex Reconstruction in DUNE…
We have developed a convolutional neural network (CNN) that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training…
One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction. Its main part is the track reconstruction procedure which consists in looking for all tracks that elementary particles…
The Deep Underground Neutrino Experiment (DUNE) is a leading-edge experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE-Dual Phase (DP) is a 6x6x6 m$^3$ liquid argon…
The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential…
At the extreme energies of the Large Hadron Collider, massive particles can be produced at such high velocities that their hadronic decays are collimated and the resulting jets overlap. Deducing whether the substructure of an observed jet…
Liquid scintillators are commonly used to detect low energy neutrinos from the reactors, sun, and earth. It is a challenge to reconstruct deposited energies for a large liquid scintillator detector. For detectors with multiple optical…
This paper proposes a non-data-driven deep neural network for spectral image recovery problems such as denoising, single hyperspectral image super-resolution, and compressive spectral imaging reconstruction. Unlike previous methods, the…
Reconstructing unstable heavy particles requires sophisticated techniques to sift through the large number of possible permutations for assignment of detector objects to the underlying partons. Anapproach based on a generalized attention…
Continued improvements on existing reconstruction methods are vital to the success of high-energy physics experiments, such as the IceCube Neutrino Observatory. In IceCube, further challenges arise as the detector is situated at the…
In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests of the Standard Model and in searches for physics beyond it. Performing kinematic reconstruction in collider events with many…
The ANTARES Collaboration is building a high-energy neutrino telescope at 2500 m depth in the Mediterranean Sea. The experiment aims to search for high-energy cosmic neutrinos through the detection of Cerenkov light induced by muons and…
We explore the capabilities of the upcoming Deep Underground Neutrino Experiment (DUNE) to measure $\nu_\tau$ charged-current interactions and the associated oscillation probability $P(\nu_\mu \to \nu_\tau)$ at its far detector,…
The Dark Matter Particle Explorer (DAMPE) is a space-based Cosmic-Ray (CR) observatory with the aim, among others, to study Cosmic-Ray Electrons (CREs) up to 10 TeV. Due to the low CRE rate at multi-TeV energies, we aim to increasing the…
Next-generation megawatt-scale neutrino beams open the way to studying neutrino-nucleus scattering using gaseous targets for the first time. This represents an opportunity to improve the knowledge of neutrino cross sections in the energy…
Deep learning has advanced efficient chemical process simulations on the surfaces, accelerating high-throughput materials screening and rational design in heterogeneous catalysis, energy storage and conversion, and gas separation. However,…
In this proceeding, we introduce deep learning technologies for studying hadron-hadron interactions. To extract parameterized hadron interaction potentials from collision experiments, we employ a supervised learning approach using…
The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment. One of the main goals is to determine the neutrino mass ordering by precisely measuring the energy spectrum of reactor antineutrinos. For reactor…
Large Liquid Argon Time Projection Chambers (LArTPCs) are being increasingly adopted in neutrino oscillation experiments because of their superb imaging capabilities through the combination of both tracking and calorimetry in a fully active…
The Jiangmen Underground Neutrino Observatory (JUNO) is a 20 kton liquid scintillator detector currently being built in a dedicated underground laboratory in China. It is a multi-purpose underground experiment with a physics program…
Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive. At the same time, the…