Related papers: Deep learning for Directional Dark Matter search

Dark matter direct detection experiments are going to touch the neutrino floor with a good chance to measure coherent elastic neutrino-nucleus scattering (CE$\nu$NS) and a probe of neutrino-related new physics ($\nu$NP). In this study, we…

This review will present the latest advances in the search for non-baryonic dark matter from an experimental point of view, focusing more particularly on the direct detection approach. After a brief reminder of the main motivations for this…

The world's leading directional dark matter experiments currently all utilize low-pressure gas Time Projection Chamber (TPC) technologies. We discuss some of the challenges for this technology, for which balancing the goal of achieving the…

In this paper, we present a deep learning-based (DL-based) algorithm, as a purely mathematical platform, for providing intuitive understanding of the properties of electromagnetic (EM) wave-matter interaction in nanostructures. This…

Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field, there is a pressing need to increase the depth and speed of the gravitational wave algorithms that have…

Dark Matter detectors with directional sensitivity have the potential of yielding an unambiguous positive observation of WIMPs as well as discriminating between galactic Dark Matter halo models. In this article, we introduce the motivation…

Recent work, using an effective field theory framework, has shown the number of possible couplings between nucleons and the dark-matter-candidate Weakly Interacting Massive Particles (WIMPs) is larger than previously thought. Inspired by an…

Neutrino detectors participate in the indirect search for the fundamental constituents of dark matter (DM) in form of weakly interacting massive particles (WIMPs). In WIMP scenarios, candidate DM particles can pair-annihilate into Standard…

Multi-dimensional parameter spaces are commonly encountered in physics theories that go beyond the Standard Model. However, they often possess complicated posterior geometries that are expensive to traverse using techniques traditional to…

The last decade was remarkable for neutrino physics. In particular, the phenomenon of neutrino flavor oscillations has been firmly established by a series of independent measurements. All parameters of the neutrino mixing are now known and…

We propose a novel mechanism, dark matter internal pair production (DIPP), to detect dark matter candidates at beam dump facilities. When energetic dark matter scatters in a material, it can create a lepton-antilepton pair by exchanging a…

In this paper, we consider the use of deep neural networks in the context of Multiple-Input-Multiple-Output (MIMO) detection. We give a brief introduction to deep learning and propose a modern neural network architecture suitable for this…

We demonstrate a machine learning approach designed to extract hidden chemistry/physics to facilitate new materials discovery. In particular, we propose a novel method for learning latent knowledge from material structure data in which…

The Cryogenic Dark Matter Search (CDMS) employs low-temperature Ge and Si detectors to search for Weakly Interacting Massive Particles (WIMPs) via their elastic-scattering interactions with nuclei while discriminating against interactions…

The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine-Learning (ML) techniques to explore WIMP radiative decays into a…

Dark Matter particles can be detected directly via their elastic scattering with nuclei. Next generation experiments can eventually find physical evidences about dark matter candidates. With this motivation in mind, we have calculated the…

Next generation direct dark matter (DM) detection experiments will have unprecedented capabilities to explore coherent neutrino-nucleus scattering (CE$\nu$NS) complementary to dedicated neutrino experiments. We demonstrate that future DM…

Dark matter plays a crucial role in our comprehension of the universe, but its mysterious nature poses challenges for direct detection. A primary obstacle in detecting dark matter is distinguishing genuine signals from the prevailing…

We present some theoretical results relevant to the direct dark matter detection experiments, paying particular attention to directional experiments, i.e. experiments in which, not only the energy but the direction of the recoiling nucleus…

Results are reported from a search for a class of composite dark matter models with feeble, long-range interactions with normal matter. We search for impulses arising from passing dark matter particles by monitoring the mechanical motion of…