Relic Abundance of Inert Fermion Doublet Dark Matter

The nature of dark matter (DM) and the mechanism that provides its measured relic abundance are currently unknown and demand physics beyond the Standard Model(SM) of particle physics. In this thesis after giving a brief introduction to the theory of DM we consider a particle physics model in which a vector-like fermion doublet and a triplet scalar are added to the SM spectrum. We also impose Z2 symmetry under which the vector-like fermion doublet is odd, while all other fields are even. As a result the resulting model explains the relic abundance of DM and neutrino masses simultaneously. The mass of DM particle is calculated by taking into account of observed relic abundance of DM. From the observed DM abundance we also obtain a correlation between DM and scalar triplet mass in a certain parameter space

Search for Signals of Decaying Dark Matter and Spectral Features in the Flux of Electron and Positron Cosmic-Rays Measured with CALET on the ISS

早稲田大学博士(理学)早大学位記番号:新8186doctoral thesi

AutoSourceID-FeatureExtractor

Aims: In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources\u27 features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data. Methods: The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment. Results: We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities

Interpretation of the CALET Electron+Positron Spectrum concerning Dark Matter Signatures

CALET (CALorimetric Electron Telescope) is in operation on the ISS since October 2015 and directly measures the electron+positron cosmic-ray spectrum up into the TeV-region with fine energy resolution and good proton rejection. Interpretations of the latest results published in [O. Adriani et al. PRL 120, 261102] regarding Dark Matter signatures are presented. Limits on annihilation and decay of Dark Matter were calculated based on an analytic parametrization of the local electron and positron spectra, including a term representing the flux from nearby pulsars as the extra electron-positron-pair source responsible for the positron excess, which is fitted to CALET data and positron flux/fraction data of AMS-02. The expected flux from Dark Matter is calculated with PYTHIA and DRAGON and added to the parametrization with increasing scale factor until reaching 95%CL exclusion, returning a limit on the annihilation cross-section or lifetime. By treating systematic uncertainties with known energy dependence as corrections to the fit function, limits were improved compared to all-random errors. Structures appear in the spectrum, which have been investigated as potential Dark Matter signatures by looking for an improvement of the fit quality with addition of flux from Dark Matter. Thereby, annihilation of ~350 GeV or decay of ~700 GeV Dark Matter to electron-positron pairs is identified as a possible explanation of a step-like structure around 350 GeV. The significance of this signature, Dark Matter explanations of other spectral features and possible astrophysical alternatives are discussed

Searching for Anisotropy in Electron+Positron Cosmic Rays with CALET

The ISS-based Calorimetric Electron Telescope (CALET) is directly measuring the energy spectrum and direction distribution of electron+positron cosmic-rays up to 20 TeV. A main goal of CALET is to identify a signature of a nearby supernova remnant (SNR) in electron+positron cosmic-rays. The Vela SNR has the highest potential to cause a spectral feature in the TeV region and/or a detectable anisotropy. Using the numerical cosmic-ray propagation code DRAGON, the spectrum and expected anisotropy of the Vela SNR together with background from more distant SNR was calculated depending on injection and propagation conditions. The results of these calculations were used to simulate CALET event sky-maps on which several analysis methods were employed to estimate the CALET sensitivity. Assuming that there is no anisotropy, the expected limits on the dipole amplitude from an all-sky search were calculated as a function of the selected energy range and the shape of the predicted spectra. However for the detection of a dipole anisotropy, the direction towards Vela is predetermined, and sensitivity is strongly boosted by a directed search. It is shown that with this method, CALET has a significant probability to identify an anisotropy signature from Vela. As it may disturb the Vela signature, the contribution to the local cosmic-ray anisotropy from several other nearby SNR and pulsars, as well as from the general source distribution in the galaxy was studied. It was found that Vela is expected to dominate and have a detectable signature, though there is some influence from other sources on direction and strength of the anisotropy. Furthermore, the implications of detecting an dipole anisotropy directed towards Vela for the local propagation parameters, such as the diffusion coefficient, are explained

Time-Series Analysis of Oxygen as an Important Environmental Parameter for Monitoring Diversity Hotspot Ecosystems: An Example of a River Sinking into the Karst Underground

Predicting variations in dissolved oxygen concentration (DO) is important for management and environmental monitoring of aquatic ecosystems. Regression analyses and univariate and multivariate time-series analyses based on autoregressive methods were performed to investigate oxygen conditions in the Pivka River, Slovenia. The monitoring site was established upstream where the river sinks into the karst cave Postojnska jama, which hosts one of the richest subterranean faunas yet studied worldwide. It was found that abnormal variations of DO started to be noticeable at values of DO < 3 mg/L and became more pronounced until the ecosystem reached fully anoxic conditions. The abnormal fluctuations during the critical summer period were due to environmental conditions, organic load and resident biota. Predictions for future detection of anomalies in DO values were made from stable residuals of the measured data, and it was demonstrated that the model could be used to obtain a reliable estimate for a short period, such as one day. The example presented an analysis pipeline based on specific and established threshold DO values, and it is particularly important for ecosystems with diversity hotspots where prolonged low DO values can pose a threat to their biota