Abstract: Solar neutrinos induce elastic neutrino-electron scattering in dark matter direct detection experiments, resulting in detectable event rates at current facilities. We analyze recent data from the XENONnT, LUX-ZEPLIN, and PandaX-4T experiments and we derive stringent constraints on several U(1) ' extensions of the Standard Model, accommodating new neutrino-electron interactions. We provide bounds on the relevant coupling and mass of light vector mediators for a variety of models, including the anomaly-free B – L model, lepton flavor-dependent interactions like L alpha – L beta , B – 2L e – L mu,tau , B – 3L alpha , and B + 2L μ+ 2L tau models. We compare our results with other limits obtained in the literature from both terrestrial and astrophysical experiments. Finally, we present forecasts for improving current bounds with a future experiment like DARWIN.

Abstract: Current cosmological tensions show that it is crucial to test the predictions from the canonical ACDM paradigm at different cosmic times. One very appealing test of structure formation in the Universe is the growth rate of structure in our universe f, usually parametrized via the growth index gamma, with f equivalent to Omega(m)(a)gamma and gamma similar or equal to 0.55 in the standard ACDM case. Recent studies have claimed a suppression of the growth of structure from a variety of cosmological observations, characterized by gamma > 0.55. By employing different self-consistent growth parametrizations schemes, we show here that gamma < 0.55, obtaining instead an enhanced growth of structure today. This preference reaches the 3 sigma significance using cosmic microwave background observations, supernova Ia and baryon acoustic oscillation measurements. The addition of cosmic microwave background lensing data relaxes such a preference to the 2 sigma level, since a larger lensing effect can always be compensated with a smaller structure growth, or, equivalently, with gamma > 0.55. We have also included the lensing amplitude AL as a free parameter in our data analysis, showing that the preference for AL > 1 still remains, except for some particular parametrizations when lensing observations are included. We also do not find any significant preference for an oscillatory dependence of AL, AL + Am sin l. To further reassess the effects of a nonstandard growth, we have computed by means of N-body simulations the dark matter density fields, the dark matter halo mass functions and the halo density profiles for different values of gamma. Future observations from the Square Kilometer Array, reducing by a factor of 3 the current errors on the gamma parameter, further confirm or refute with a strong statistical significance the deviation of the growth index from its standard value.

Abstract: A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied.