The electric field dependence of single electron emission in the PIXeY two-phase xenon detector

Dual phase xenon detectors are widely used in experimental searches for galactic dark matter particles. The origin of single electron backgrounds following prompt scintillation and proportional scintillation signals in these detectors is not fully understood, although there has been progress in recent years. In this paper, we describe single electron backgrounds in 83mKr calibration events and their correlation with drift and extraction fields, using the Particle Identification in Xenon at Yale (PIXeY) dual-phase xenon time projection chamber. The single electron background induced by the Fowler-Nordheim (FN) effect is measured, and its electric field dependence is quantified. The photoionization of grids and impurities by prompt scintillation and proportional scintillation also contributes to the single electron background.

Hybrid analytic and machine-learned baryonic property insertion into galactic dark matter haloes

While cosmological dark matter-only simulations relying solely on gravitational effects are comparably fast to compute, baryonic properties in simulated galaxies require complex hydrodynamic simulations that are computationally costly to run. We explore the merging of an extended version of the equilibrium model, an analytic formalism describing the evolution of the stellar, gas, and metal content of galaxies, into a machine learning framework. In doing so, we are able to recover more properties than the analytic formalism alone can provide, creating a high-speed hydrodynamic simulation emulator that populates galactic dark matter haloes in N-body simulations with baryonic properties. While there exists a trade-off between the reached accuracy and the speed advantage this approach offers, our results outperform an approach using only machine learning for a subset of baryonic properties. We demonstrate that this novel hybrid system enables the fast completion of dark matter-only information by mimicking the properties of a full hydrodynamic suite to a reasonable degree, and discuss the advantages and disadvantages of hybrid versus machine learning-only frameworks. In doing so, we offer an acceleration of commonly deployed simulations in cosmology.

On the Electromagnetic Vacuum Origins of Dark Energy, Dark Matter, and Astrophysical Jets

We use a semiclassical version of the Nexus paradigm of quantum gravity in which the quantum vacuum at large scales is dominated by the second quantized electromagnetic field to demonstrate that a virtual photon field can affect the geometric evolution of Einstein manifolds or Ricci solitons. This phenomenon offers a cogent explanation of the origins of astrophysical jets, the cosmological constant, and a means of detecting galactic dark matter.