相关论文: Deep learning for improved keV-scale recoil identi…

In the search for neutrinoless double-beta decay, the high-pressure gaseous Time Projection Chamber has a distinct advantage, because the ionization charge tracks produced by particle interactions are extended and the detector captures the…

We develop and validate a new algorithm called \textit{primary track recovery} (\ptr) that effectively deconvolves known physics and detector effects from nuclear recoil tracks in gas time projection chambers (TPCs) with high-resolution…

Deep Convolutional Neural Networks (DCNN) have been proven to be effective for various computer vision problems. In this work, we demonstrate its effectiveness on a continuous object orientation estimation task, which requires prediction of…

The Dark Matter Time Projection Chamber (DMTPC) collaboration is developing low-pressure gas TPC detectors for measuring WIMP-nucleon interactions. Optical readout with CCD cameras allows for the detection for the daily modulation in the…

Now that conventional weakly interacting massive particle (WIMP) dark matter searches are approaching the neutrino floor, there has been a resurgence of interest in detectors with sensitivity to nuclear recoil directions. A large-scale…

We report on the design, production, and performance of compact 40-cm$^3$ Time Projection Chambers (TPCs) that detect fast neutrons by measuring the three-dimensional (3D) ionization distribution of nuclear recoils in $^4$He:CO$_2$ gas at…

Classification of long sequential data is an important Machine Learning task and appears in many application scenarios. Recurrent Neural Networks, Transformers, and Convolutional Neural Networks are three major techniques for learning from…

Directional detection is the only strategy for the unambiguous identification of galactic Dark Matter (DM) even in the presence of an irreducible background such as beyond the neutrino floor. This approach requires measuring the direction…

The coherent elastic scattering of neutrinos on nuclei, also known as CEvNS, has been studied for several years by the COHERENT program of experiments using neutrinos from stopped-pion decays produced at the Spallation Neutron Source (SNS).…

The CYGNO experiment employs an optical-readout Time Projection Chamber (TPC) to search for rare low-energy interactions using finely resolved scintillation images. While the optical readout provides rich topological information, it…

Directional Dark Matter Detection (DDMD) can open a new signature for Weakly Massive Interacting Particles (WIMPs) Dark Matter. The directional signature provides in addition, an unique way to overcome the neutron and neutrino backgrounds.…

We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The…

We propose a lightweight deep convolutional neural network (lCNN) to estimate cosmological parameters from simulated three-dimensional dark matter (DM) halo distributions and associated statistics. The training dataset comprises 2000…

Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high energy physics. In this paper, we attempt to understand the potential of CNNs for event…

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme noise using Deep Learning (DL). In particular, we introduce a Convolutional Neural Network (CNN) that is trained from mutli-channel data of the true…

Directional detection is a promising direct Dark Matter (DM) search strategy. The angular distribution of the nuclear recoil tracks from WIMP events should present an anisotropy in galactic coordinates. This strategy requires both a…

The simulation of the neutron background for Phase II of the SIMPLE direct dark matter search experiment is fully reported with various improvements relative to previous estimates. The model employs the Monte Carlo MCNP neutron transport…

With the rapid development and wide application of computer, camera device, network and hardware technology, 3D object (or model) retrieval has attracted widespread attention and it has become a hot research topic in the computer vision…

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle…

Directional detection of Dark Matter is a promising search strategy. However, to perform such detection, a given set of parameters has to be retrieved from the recoiling tracks : direction, sense and position in the detector volume. In…