Related papers: Deep learning for Directional Dark Matter search
By correlating nuclear recoil directions with the Earth's direction of motion through the Galaxy, a directional dark matter detector can unambiguously detect Weakly Interacting Massive Particles (WIMPs), even in the presence of backgrounds.…
Particles weakly interacting with ordinary matter, with an associated mass of the order of an atomic nucleus (WIMPs), are plausible candidates for Dark Matter. The direct detection of an elastic collision of a target nuclei induced by one…
We present a new suite of over 1,500 cosmological N-body simulations with varied Warm Dark Matter (WDM) models ranging from 2.5 to 30 keV. We use these simulations to train Convolutional Neural Networks (CNNs) to infer WDM particle masses…
Direct detection dark matter experiments, lead by the CDMS collaboration, have placed increasingly stronger constraints on the cross sections for elastic scattering of WIMPs on nucleons. These results impact the prospects for the indirect…
The nature of dark matter (DM) remains one of the most fundamental open questions in physics. Among the main DM candidates are Weakly Interacting Massive Particles (WIMPs), expected to interact with matter through scattering. Directional…
Directional detection is a promising search strategy to discover galactic Dark Matter. Taking advantage on the rotation of the Solar system around the Galactic center through the Dark Matter halo, it allows to show a direction dependence of…
In this study, we are doing R&D for directional dark matter search with nuclear emulsion. First of all, higher resolution nuclear emulsion with fine silver halide crystals was developed in the production facility of emulsion at Nagoya…
A study of the current status of WIMP dark matter searches has been made in the context of scientific and technical planning for a Deep Underground Science and Engineering Laboratory (DUSEL) in the U.S. The table of contents follows: 1.…
There is currently vast evidence for Dark Matter (DM) from astronomical observations. However, in spite of tremendous efforts by large experimental groups, there is no confirmed direct detection of the dark matter in our galaxy. Recent…
Present and planned dark matter detection experiments search for WIMP-induced nuclear recoils in poorly known background conditions. In this environment, the maximum gap statistical method provides a way of setting more sensitive cross…
We present a first proof-of-principle study for using deep neural networks (DNNs) as a novel search method for continuous gravitational waves (CWs) from unknown spinning neutron stars. The sensitivity of current wide-parameter-space CW…
Dynamical dark matter (DDM) is an alternative framework for dark-matter physics in which the dark-matter candidate is an ensemble of constituent fields with differing masses, lifetimes, and cosmological abundances. In this framework, it is…
The signals from outer space and their detection have been playing an important role in particle physics, especially in discoveries of and searches for physics beyond the Standard Model (BSM); beyond the evidence of dark matter (DM), for…
Directional detection is a promising search strategy to discover galactic Dark Matter. We present a Bayesian analysis framework dedicated to Dark Matter phenomenology using directional detection. The interest of directional detection as a…
We investigate the sensitivity of a large, underground LArTPC-based neutrino detector to dark matter in the Galactic Center annihilating into neutrinos. Such a detector could have the ability to resolve the direction of the electron in a…
The existence of the coherent neutrino-nucleus scattering reaction requires to evaluate, for any detector devoted to WIMP searches, the irreducible background due to conventional neutrino sources and at same time, it gives a unique chance…
Directional detection of galactic Dark Matter is a promising search strategy for discriminating geniune WIMP events from background ones. We present technical progress on gaseous detectors as well as recent phenomenological studies,…
The detection of Dark Matter (DM) remains a significant challenge in particle physics. This study exploits advanced machine learning models to improve detection capabilities of liquid xenon time projection chamber experiments, utilizing…
Direct dark matter searches are promising techniques to identify the nature of dark matter particles. I describe the future of this field of research, focussing on the question of what can be achieved in the next decade. I will present the…
MadDM is an automated numerical tool for the computation of dark-matter observables for generic new physics models. We announce version 3.1 and summarize its features. Notably, the code goes beyond the mere cross-section computation for…