Hidden Physics at the Neutrino Frontier: Tridents, Dark Forces, and Hidden Particles

The unexplained origin of neutrino masses suggests that these neutral and weakly interacting particles might provide a portal to physics beyond the Standard Model. In view of the growing prospects in experimental neutrino physics, we explore new theoretical models and experimental searches that can shed light on the existence of low-scale particles with very small couplings to ordinary matter. Our efforts highlight a vast landscape of models where neutrino physics offers our best chance of discovering such hidden sectors. Along the way, we revisit the Standard Model physics of neutrino trident production with a modern calculation and explore its phenomenology at neutrino facilities. As shown here, this type of rare neutrino scattering process can probe unexplored anomaly-free extensions of the Standard Model with a complementary, and often more powerful, search strategy to to the well-known searches in neutrino-electron scattering. As to new models, we propose a novel neutrino mass model resembling the inverse seesaw, where neutrino mixing stands as the most prominent portal to dark sectors and dark matter. In our dark neutrino model, neutrino masses are generated radiatively, with the vector, scalar, and neutrino phenomenology displaying an unique interplay. Later, we devise new methods to search for these dark neutrinos using neutrino-electron scattering data, aiming to discriminate among new physics explanations of the MiniBooNE anomalous results. Finally, we discuss light and heavy conventional sterile neutrinos in the context of $\nu$STORM, an entry-level neutrino factory for precision neutrino physics

Pion decay constraints on exotic 17 MeV vector bosons

We derive constraints on the couplings of light vector particles to all first-generation Standard Model fermions using leptonic decays of the charged pion, $\pi^+\to e^+ \nu_e X_\mu$. In models where the net charge to which $X_\mu$ couples to is not conserved, no lepton helicity flip is required for the decay to happen, enhancing the decay rate by factors of ${O}(m_\pi^4/m_e^2m_X^2)$. A past search at the SINDRUM-I spectrometer severely constrains this possibility. In the context of the hypothesized $17$ MeV particle proposed to explain anomalous $^8$Be, $^4$He, and $^{12}$C nuclear transitions claimed by the ATOMKI experiment, this limit rules out vector-boson explanations and poses strong limits on axial-vector ones.Comment: 10 pages, 5 figure

A Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery

This article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.Analysis Ready Data (ARD) have undergone the most relevant pre-processing steps to satisfy most user demands. The freely available software FORCE (Framework for Operational Radiometric Correction for Environmental monitoring) is capable of generating Landsat ARD. An essential step of generating ARD is atmospheric correction, which requires water vapor data. FORCE relies on a water vapor database obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). However, two major drawbacks arise from this strategy: (1) The database has to be compiled for each study area prior to generating ARD; and (2) MODIS and Landsat commissioning dates are not well aligned. We have therefore compiled an application-ready global water vapor database to significantly increase the operational readiness of ARD production. The free dataset comprises daily water vapor data for February 2000 to July 2018 as well as a monthly climatology that is used if no daily value is available. We systematically assessed the impact of using this climatology on surface reflectance outputs. A global random sample of Landsat 5/7/8 imagery was processed twice (i) using daily water vapor (reference) and (ii) using the climatology (estimate), followed by computing accuracy, precision, and uncertainty (APU) metrics. All APU measures were well below specification, thus the fallback usage of the climatology is generally a sound strategy. Still, the tests revealed that some considerations need to be taken into account to help quantify which sensor, band, climate, and season are most or least affected by using a fallback climatology. The highest uncertainty and bias is found for Landsat 5, with progressive improvements towards newer sensors. The bias increases from dry to humid climates, whereas uncertainty increases from dry and tropic to temperate climates. Uncertainty is smallest during seasons with low variability, and is highest when atmospheric conditions progress from a dry to a wet season (and vice versa).Peer Reviewe

A generalized framework for drought monitoring across Central European grassland gradients with Sentinel-2 time series

Fractional cover time series of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil from remote sensing provide essential detail to understand how grasslands are affected by recent and future drought periods in the 21st century. In this regard, Sentinel-2A/B offer frequent large-area observations, which have not yet been fully exploited for a spatially continuous drought monitoring of highly dynamic Central European grasslands. In this study, we developed a generalized drought monitoring framework for Central European grasslands linking Sentinel-2 data, field survey information, and spectral unmixing. We first implemented a consistent and repeatable strategy to obtain a grassland spectral library supported by the Europe-wide Land Use/Cover Area frame statistical Survey (LUCAS) and multitemporal Sentinel-2 data. Our library captured the spectral variability of PV, NPV, and soil cover from 12 grassland areas distributed along typical environmental and land use gradients of Central Europe. We trained a generalized regression-based unmixing model with synthetic data generated from the spectral library and compared fractional cover estimates to a multitemporal reference dataset. PV, NPV, and soil were estimated with good accuracy, achieving MAEs of 6.54%, 13.7%, and 12.2%, respectively. Local unmixing models trained on area-specific library subsets were overall outperformed by the generalized model highlighting the value of a comprehensive grassland library for generalized spectral unmixing. Based on fractional cover time series from 2017 to 2021, we calculated time series of the grassland-specific Normalized Difference Fraction Index (NDFI) capturing proportions of NPV and soil relative to PV. Comparison of annual growing season drought metrics derived from the NDFI to annual meteorological drought statistics from the Standardized Precipitation Evapotranspiration Index (SPEI) as well as the Soil Moisture Index (SMI) revealed widespread drought impacts on grasslands during the persistent drought period in Central Europe from 2018 to 2020. While impacts on grasslands overall closely followed meteorological and soil drought conditions, regionally varying drought metrics underline that local to regional environmental and hydrological conditions shaped the drought response of Central European grasslands. Our study emphasizes the value of combining Sentinel-2 data, field survey information, and spectral unmixing to enable drought monitoring across grassland gradients of Central Europe with Sentinel-2 time series.Peer Reviewe