David G. Cerdeno

We investigate the freeze-in of MeV-scale fermionic dark matter (DM) that couples to the Standard Model via a new vector mediator to assess the potential that future direct detection experiments have to observe new physics in either the DM or neutrino sectors. We study the minimal kinetic mixing dark photon of a secluded U(1) _D as well as gauge bosons of the anomaly-free U(1) _{L i -L j} , with i,j=e,μ,τ, and U(1) _B-L gauge extensions, exploring the impact of low reheating temperatures on the DM production rates. For the ultralight dark photon scenario, we show that current experimental constraints from electron recoil data in DAMIC-M and PandaX-4T can be avoided if the DM fermion is only a subcomponent (smaller than 40%) of the total cold DM and that future detectors can be sensitive to a DM fraction below 1% for masses above 1 MeV. For a massive dark photon, there are allowed regions of the parameter space with masses in the range 50 MeV ≤ m _DM ≤ 500 MeV that can be within the reach of direct detection experiments through nuclear recoils if freeze-in occurred at a low reheating temperature. Finally, the case of U(1) _{L i -L j} and U(1) _B-L is particularly interesting since the discovery of new physics can come from either the DM or the neutrino sector, which features new interactions. We find that freeze-in at low reheating temperatures can reproduce the observed abundance in large parts of the parameter space up to gauge couplings of g _X ∼10 ^-2 for MeV DM. Most notably, direct detection experiments will be sensitive to considerable parts of this parameter space in nuclear recoils for 50 MeV ≤ m _DM ≤ 500 MeV. Additionally, the enhanced signal from solar neutrino coherent scattering is observable in these scenarios, which can serve as a further handle to identify the underlying particle physics model.

A bstract: Dark matter direct detection experiments can observe solar neutrinos via coherent elastic neutrino-nucleus scattering, making it possible to test new physics in the neutrino sector. In this article, we study the sensitivity of RES-NOVA, a novel cryogenic calorimetric experiment employing PbWO ₄ crystals grown from archaeological lead, to neutrino non-standard interactions (NSI). We perform a sensitivity study for a benchmark setup with a nominal energy threshold of 1 keV and an exposure of 1 ton·yr, both for a conservative (only heat readout) and ideal (heat and scintillation) background rejection scenario. We find that, in its nominal configuration, while not being sensitive to Standard Model solar ν interactions, RES-NOVA can reach sensitivities to NSI at the level of current global fits. With moderate or significant improvements of the threshold down to 0 . 5 keV and 0 . 2 keV, RES-NOVA will be able to achieve sensitivities beyond NSI global fit results, testing new areas of the parameter space in the electron and tau sectors, ε _ee , ε _ττ , and ε _eτ . A similar improvement in sensitivities is expected when instead increasing the exposure to 10 ton·yr.

New exotic particles with MeV masses, such as axion-like particles or light dark matter, can be emitted from core-collapse supernovae (SNe) with semi-relativistic velocities. Due to their speed dispersion, they would arrive at Earth as an extended packet with a time spread that can be as large as tens of millennia for typical detectors. It has been argued in the literature that the superposition of packets from all galactic SNe would give rise to a smooth and stationary diffuse flux that could be observable on terrestrial experiments. In this article, we critically examine this hypothesis by carrying out a numerical simulation of the galactic history of SN explosions. We show that, although the particle packets do overlap, due to the short observational time window, each of them only contributes with a very narrow range of energies and with an intensity that depends on the SN distance. As a consequence, the energy dependence of the resulting flux is extremely sensitive to the stochastic nature of the SN population and far from smooth. This has profound implications for the expected signature in terrestrial experiments, which displays a spectral shape that is not properly described by the smooth approximation. We develop a numerical tool to compute this stochastic galactic flux for generic semi-relativistic particles, which also allows us to explore sub-MeV particles, where the smooth diffuse flux approach does not hold. To test this framework, we revisit existing bounds on axion-like particles and fermionic dark matter, finding weaker constraints than previously reported.

We present constraints on low-mass dark matter electron scattering and absorption interactions using a SuperCDMS high-voltage eV-resolution (HVeV) detector. Data were taken underground in the NEXUS facility located at Fermilab with an overburden of 225 meters of water equivalent. The experiment benefits from the minimizing of luminescence from the printed circuit boards in the detector holder used in all previous HVeV studies. A blind analysis of 6.1 g · days of exposure produces exclusion limits for dark matter-electron scattering cross sections for masses as low as 1 MeV / c 2 , as well as on the photon-dark photon mixing parameter and the coupling constant between axionlike particles and electrons for particles with masses > 1.2 eV / c 2 probed via absorption processes.

In this work, we show that, if axionlike particles (ALPs) from core-collapse supernovae (SNe) couple to protons, they would produce very characteristic signatures in neutrino water Cherenkov detectors through their scattering off free protons via a p → p γ interactions. Specifically, sub-MeV ALPs would generate photons with energies ∼ 30 MeV , which could be observed by Super-Kamiokande and Hyper-Kamiokande as a delayed signal after a future detection of SN neutrinos. We apply this to a hypothetical neighboring SN (at a maximum distance of 100 kpc) and demonstrate that the region in the parameter space with ALP masses between 10 − 4 and 1 MeV and ALP-proton couplings in the range 3 × 10 − 6 – 4 × 10 − 5 could be probed. We argue that this new signature, combined with the one expected at ∼ 7 MeV from oxygen deexcitation, would allow us to disentangle ALP-neutron and ALP-proton couplings.

In this article, we claim that axionlike particles (ALPs) with MeV masses can be produced with semirelativistic velocities in core-collapse supernovae (SNe), generating a diffuse galactic flux. We show that these ALPs can be detected in neutrino water Cherenkov detectors via a p → p γ interactions. Using Super-Kamiokande data, we derive new constraints on the ALP parameter space, excluding a region spanning more than one order of magnitude in the ALP-proton coupling above cooling bounds for ALP masses in the range of 1–80 MeV and ALP-proton couplings between 8 × 10 − 6 – 2 × 10 − 4 . We show that the future Hyper-Kamiokande will be able to probe couplings as small as 2.5 × 10 − 6 , fully closing the allowed region above SN 1987A cooling bounds.

We carry out a Bayesian analysis of dark matter (DM) direct detection data to determine particle model parameters using the Truncated Marginal Neural Ratio Estimation (TMNRE) machine learning technique. TMNRE avoids an explicit calculation of the likelihood, which instead is estimated from simulated data, unlike in traditional Markov Chain Monte Carlo (MCMC) algorithms. This considerably speeds up, by several orders of magnitude, the computation of the posterior distributions, which allows to perform the Bayesian analysis of an otherwise computationally prohibitive number of benchmark points. In this article we demonstrate that, in the TMNRE framework, it is possible to include, combine, and remove different datasets in a modular fashion, which is fast and simple as there is no need to re-train the machine learning algorithm or to define a combined likelihood. In order to assess the performance of this method, we consider the case of WIMP DM with spin-dependent and independent interactions with protons and neutrons in a xenon experiment. After validating our results with MCMC, we employ the TMNRE procedure to determine the regions where the DM parameters can be reconstructed. Finally, we present CADDENA, a Python package that implements the modular Bayesian analysis of direct detection experiments described in this work.