Neutrino oscillation and expected event rate of supernova neutrinos in adiabatic explosion model

We study how the influence of the shock wave appears in neutrino oscillations and the neutrino spectrum using density profile of adiabatic explosion model of a core-collapse supernova which is calculated in an implicit Lagrangian code for general relativistic spherical hydrodynamics. We calculate expected event rates of neutrino detection at SK and SNO for various theta_{13} values and both normal and inverted hierarchies. The predicted event rates of bar{nu}_e and nu_e depend on the mixing angle theta_{13} for the inverted and normal hierarchies, respectively, and the influence of the shock appears for about 2 - 8 s when sin^2 2 theta_{13} is larger than 10^{-3}. These neutrino signals for the shock propagation is decreased by < 30 % for bar{nu}_e in inverted (SK) or by < 15 % for nu_e in normal hierarchy (SNO) compared with the case without shock. The obtained ratio of the total event for high-energy neutrinos (20 MeV < E_{nu} < 60 MeV) to low-energy neutrinos (5 MeV < E_{nu} < 20 MeV) is consistent with the previous studies in schematic semi-analytic or other hydrodynamic models of the shock propagation. The time dependence of the calculated ratio of the event rates of high-energy to low-energy neutrinos is a very useful observable which is sensitive to theta_{13} and hierarchies. Namely, time-dependent ratio shows clearer signal of the shock propagation that exhibits remarkable decrease by at most factor \sim 2 for bar{nu}_e in inverted (SK), whereas it exhibits smaller change by \sim 10 % for nu_e in normal hierarchy (SNO). Observing time-dependent high-energy to low-energy ratio of the neutrino events thus would provide a piece of very useful information to constrain theta_{13} and mass hierarchy, and eventually help understanding the propagation how the shock wave propagates inside the star.Comment: 19 pages, 9 figures, accepted for publication in Physical Review

Probabilistic modelling of rainfall induced landslide hazard assessment

To evaluate the frequency and distribution of landslides hazards over Japan, this study uses a probabilistic model based on multiple logistic regression analysis. Study particular concerns several important physical parameters such as hydraulic parameters, geographical parameters and the geological parameters which are considered to be influential in the occurrence of landslides. Sensitivity analysis confirmed that hydrological parameter (hydraulic gradient) is the most influential factor in the occurrence of landslides. Therefore, the hydraulic gradient is used as the main hydraulic parameter; dynamic factor which includes the effect of heavy rainfall and their return period. Using the constructed spatial data-sets, a multiple logistic regression model is applied and landslide hazard probability maps are produced showing the spatial-temporal distribution of landslide hazard probability over Japan. To represent the landslide hazard in different temporal scales, extreme precipitation in 5 years, 30 years, and 100 years return periods are used for the evaluation. The results show that the highest landslide hazard probability exists in the mountain ranges on the western side of Japan (Japan Sea side), including the Hida and Kiso, Iide and the Asahi mountainous range, the south side of Chugoku mountainous range, the south side of Kyusu mountainous and the Dewa mountainous range and the Hokuriku region. The developed landslide hazard probability maps in this study will assist authorities, policy makers and decision makers, who are responsible for infrastructural planning and development, as they can identify landslide-susceptible areas and thus decrease landslide damage through proper preparation

Assessment of snowmelt triggered landslide hazard and risk in Japan

This study is pertaining to an evaluation of landslide occurrence on natural terrain due to snowmelt in Japan, using a probabilistic model based on multiple logistic regression analysis. The evaluation concerns several physical parameters such as hydraulic parameters, geographical parameters and geological parameters which are considered to be influential in the occurrence of landslides. A Snow Water Equivalent model (SWE) is utilized to estimate snowmelt and associated infiltration in light, heavy and normal snow years. Using the constructed spatial data-sets, we apply a multiple logistic regression model to produce landslide susceptibility maps showing the spatial–temporal distribution of landslide hazard probabilities throughout Japan using 1 km × 1 km resolution grid cells. The results have revealed that, over 95% landslide hazard probability exists in the mountain ranges on the western side of Japan (the Japan Sea side). In particular, this study is dealing with the Aizu region of Fukushima prefecture in order to verifying the landslide hazard probability. Verification proved that, the areas identified as high risk areas (having over 90% landslide hazard probability in numerical modeling) show 87% agreement with observed landslides in the Aizu region. Also we evaluated the relationship between landslides and snow melting process giving special concern to change of temperature in the spring

A New SUSY mass reconstruction method at the CERN LHC

We propose a new mass reconstruction technique for SUSY processes at the LHC. The idea is to completely solve the kinematics of the SUSY cascade decay by using the assumption that the selected events satisfy the same mass shell conditions of the sparticles involved in the cascade decay. Using this technique, we study the measurement of the mass of the bottom squarks in the cascade decay of the gluino. Based on the final state including two high p_T leptons and two b-jets, we investigate different possible approaches to the mass reconstruction of the gluino and the two bottom squarks. In particular we evaluate the performance of different algorithms in discriminating two bottom squark states with a mass difference as low as 5%.Comment: Revtex 16 pages, 8 figure

Distributed specific sediment yield estimations in Japan attributed to extreme-rainfall-induced slope failures under a changing climate

The objective of this study was to estimate the potential sediment yield distribution in Japan attributed to extreme-rainfall-induced slope failures in the future. For this purpose, a regression relationship between the slope failure probability and the subsequent sediment yield was developed by using sediment yield observations from 59 dams throughout Japan. The slope failure probability accounts for the effects of topography (as relief energy), geology and hydro-climate variations (hydraulic gradient changes due to extreme rainfall variations) and determines the potential slope failure occurrence with a 1-km resolution. The applicability of the developed relationship was then validated by comparing the simulated and observed sediment yields in another 43 dams. To incorporate the effects of a changing climate, extreme rainfall variations were estimated by using two climate change scenarios (the MRI-RCM20 Ver.2 model A2 scenario and the MIROC A1B scenario) for the future and by accounting for the slope failure probability through the effect of extreme rainfall on the hydraulic gradient. Finally, the developed slope failure hazard-sediment yield relationship was employed to estimate the potential sediment yield distribution under a changing climate in Japan. &lt;br&gt;&lt;br&gt; Time series analyses of annual sediment yields covering 15–20 years in 59 dams reveal that extreme sedimentation events have a high probability of occurring on average every 5–7 years. Therefore, the extreme-rainfall-induced slope failure probability with a five-year return period has a statistically robust relationship with specific sediment yield observations (with &lt;i&gt;r&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; = 0.65). The verification demonstrated that the model is effective for use in simulating specific sediment yields with &lt;i&gt;r&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; = 0.74. The results of the GCM scenarios suggest that the sediment yield issue will be critical in Japan in the future. When the spatially averaged sediment yield for all of Japan is considered, both scenarios produced an approximately 17–18% increase around the first half of the 21st century as compared to the present climate. For the second half of the century, the MIROC and MRI-RCM20 scenarios predict increased sediment yields of 22% and 14%, respectively, as compared to present climate estimations. On a regional scale, both scenarios identified several common areas prone to increased sediment yields in the future. Substantially higher specific sediment yield changes (over 1000 m&lt;sup&gt;3&lt;/sup&gt;/km&lt;sup&gt;2&lt;/sup&gt;/year) were estimated for the Hokuriku, Kinki and Shikoku regions. Out of 105 river basins in Japan, 96 will have an increasing trend of sediment yield under a changing climate, according to the predictions. Among them, five river basins will experience an increase of more than 90% of the present sediment yield in the future. This study is therefore expected to guide decision-makers in identifying the basins that are prone to sedimentation hazard under a changing climate in order to prepare and implement appropriate mitigation measures to cope with the impacts