Related papers: Deep learning optimal molecular scintillators for …
Direct detection of Sub-GeV dark matter (DM) is challenging because the recoil energy of the nuclei or electron from the elastic scattering of a sub-GeV DM off the target can hardly reach the detector threshold. In this paper, we present a…
Machine learning in drug discovery has been focused on virtual screening of molecular libraries using discriminative models. Generative models are an entirely different approach that learn to represent and optimize molecules in a continuous…
To reach ultra-low detection thresholds necessary to probe unprecedentedly low Dark Matter masses, target material alternatives and novel detector designs are essential. One such target material is superfluid $^4$He which has the potential…
We present a new class of direct detection signals; absorption of fermionic dark matter. We enumerate the operators through dimension six which lead to fermionic absorption, study their direct detection prospects, and summarize additional…
Drug discovery projects entail cycles of design, synthesis, and testing that yield a series of chemically related small molecules whose properties, such as binding affinity to a given target protein, are progressively tailored to a…
We consider the nuclear absorption of dark matter as an alternative to the typical indirect detection search channels of dark matter decay or annihilation. In this scenario, an atomic nucleus transitions to an excited state by absorbing a…
We perform the first comprehensive analysis of the prospects for direct detection of dark matter with future ton-scale detectors in the general 11-dimensional effective theory of isoscalar dark matter-nucleon interactions mediated by a…
We study the possible indirect neutrino signal from dark matter annihilations inside the solar interior for relatively light dark matter masses in the O(10) GeV range. Due to their excellent energy reconstruction capabilities, we focus on…
Direct detection experiments for light (sub-GeV) dark matter are making enormous leaps in reaching previously unexplored theory space. The need for accurate characterizations of target responses has led to a growing interplay between…
Organic scintillators are widely used for fast neutron detection and spectroscopy. Several effects complicate the interpretation of results from detectors based upon these materials. First, fast neutrons will often leave a detector before…
Deep Learning has been shown to learn efficient representations for structured data such as image, text or audio. In this chapter, we present neural network architectures that are able to learn efficient representations of molecules and…
Existing xenon dark matter (DM) direct detection experiments can probe the DM-nucleon interaction of DM with a sub-GeV mass through a search for photon emission from the recoiling xenon atom. We show that LUX's constraints on sub-GeV DM,…
Organic semiconductors are promising materials for cheap, scalable and sustainable electronics, light-emitting diodes and photovoltaics. For organic photovoltaic cells, it is a challenge to find compounds with suitable properties in the…
Sub-GeV mass dark matter particles whose collisions with nuclei would not deposit sufficient energy to be detected, could instead be revealed through their interaction with electrons. Analyses of data from direct detection experiments…
Direct detection is a powerful means of searching for particle physics evidence of dark matter (DM) heavier than about a GeV with $\mathcal O(kiloton)$ volume, low-threshold detectors. In many scenarios, some fraction of the DM may be…
The possibility of searching for dark matter with quantum sensors has recently received a lot of attention. In this short paper, we discuss the possibility of searching for gravitational dark matter with quantum sensors and identify a very…
Deep generative models are able to suggest new organic molecules by generating strings, trees, and graphs representing their structure. While such models allow one to generate molecules with desirable properties, they give no guarantees…
We study a fermionic dark matter candidate that couples to the standard model particles exclusively through electric and magnetic dipole operators mediated by a massive dark photon. Such dipole portals naturally arise in dark sectors where…
We observe that sub-GeV Dark Matter (DM) induces Casimir-Polder forces between nucleons, that can be accessed by experiments from nuclear to molecular scales. We calculate the nucleon-nucleon potentials arising in the DM effective theory…
A wide variety of celestial bodies have been considered as dark matter detectors. Which stands the best chance of delivering the discovery of dark matter? Which is the most powerful dark matter detector? We investigate a range of objects,…