In the Next-to-Minimal-Supersymmetric-Standard-Model (NMSSM) the lightest supersymmetric particle (LSP) is a candidate for the dark matter (DM) in the universe. It is a mixture from the various ...gauginos and Higgsinos and can be bino-, Higgsino- or singlino-dominated. Singlino-dominated LSPs can have very low cross sections below the neutrino background from coherent neutrino scattering which is limiting the sensitivity of future direct DM search experiments. However, previous studies suggested that the combination of both, the spin-dependent (SD) and spin-independent (SI) searches are sensitive in complementary regions of parameter space, so considering both searches will allow to explore practically the whole parameter space of the NMSSM. In this letter, the different scenarios are investigated with a new scanning technique, which reveals that significant regions of the NMSSM parameter space cannot be explored, even if one considers both, SI and SD, searches.
In the CMSSM the heaviest scalar and pseudo-scalar Higgs bosons decay largely into b-quarks and tau-leptons because of the large tanβ values favored by the relic density. In the NMSSM the number of ...possible decay modes is much richer. In addition to the CMSSM-like scenarios, the decay of the heavy Higgs bosons is preferentially into top quark pairs (if kinematically allowed), lighter Higgs bosons or neutralinos, leading to invisible decays. We provide a scan over the NMSSM parameter space to project the 6D parameter space of the Higgs sector on the 3D space of the Higgs masses to determine the range of branching ratios as function of the Higgs boson mass for all Higgs bosons. Specific LHC benchmark points are proposed, which represent the salient NMSSM features.
If new phenomena beyond the Standard Model will be discovered at the LHC, the properties of the new particles could be determined with data from the High-Luminosity LHC and from a future linear ...collider like the ILC. We discuss the possible interplay between measurements at the two accelerators in a concrete example, namely a full SUSY model which features a small
τ
~
1
-LSP mass difference. Various channels have been studied using the Snowmass 2013 combined LHC detector implementation in the Delphes simulation package, as well as simulations of the ILD detector concept from the Technical Design Report. We investigate both the LHC and the ILC capabilities for discovery, separation and identification of various parts of the spectrum. While some parts would be discovered at the LHC, there is substantial room for further discoveries at the ILC. We finally highlight examples where the precise knowledge about the lower part of the mass spectrum which could be acquired at the ILC would enable a more in-depth analysis of the LHC data with respect to the heavier states.
In the Next-to-Minimal-Supersymmetric-Standard-Model (NMSSM) the lightest supersymmetric particle (LSP) is a candidate for the dark matter (DM) in the universe. It is a mixture from the various ...gauginos and Higgsinos and can be bino-, Higgsino- or singlino-dominated. Singlino-dominated LSPs can have very low cross sections below the neutrino background from coherent neutrino scattering which is limiting the sensitivity of future direct DM search experiments. However, previous studies suggested that the combination of both, the spin-dependent (SD) and spin-independent (SI) searches are sensitive in complementary regions of parameter space, so considering both searches will allow to explore practically the whole parameter space of the NMSSM. In this letter, the different scenarios are investigated with a new scanning technique, which reveals that significant regions of the NMSSM parameter space cannot be explored, even if one considers both, SI and SD, searches.
In the CMSSM the heaviest scalar and pseudo-scalar Higgs bosons decay largely into b-quarks and tau-leptons because of the large \(\tan\beta\) values favored by the relic density. In the NMSSM the ...number of possible decay modes is much richer. In addition to the CMSSM-like scenarios, the decay of the heavy Higgs bosons is preferentially into top quark pairs (if kinematically allowed), lighter Higgs bosons or neutralinos, leading to invisible decays. We provide a scan over the NMSSM parameter space to project the 6D parameter space of the Higgs sector on the 3D space of the Higgs masses to determine the range of branching ratios as function of the Higgs boson mass for all Higgs bosons. Specific LHC benchmark points are proposed, which represent the salient NMSSM features.
If new phenomena beyond the Standard Model will be discovered at the LHC, the properties of the new particles could be determined with data from the High-Luminosity LHC and from a future linear ...collider like the ILC. We discuss the possible interplay between measurements at the two accelerators in a concrete example, namely a full SUSY model which features a small stau_1-LSP mass difference. Various channels have been studied using the Snowmass 2013 combined LHC detector implementation in the Delphes simulation package, as well as simulations of the ILD detector concept from the Technical Design Report. We investigate both the LHC and ILC capabilities for discovery, separation and identification of various parts of the spectrum. While some parts would be discovered at the LHC, there is substantial room for further discoveries at the ILC. We finally highlight examples where the precise knowledge about the lower part of the mass spectrum which could be acquired at the ILC would enable a more in-depth analysis of the LHC data with respect to the heavier states.
The interaction of mountain terrain with meteorological processes causes substantial temporal and spatial variability in snow accumulation and ablation. Processes impacted by complex terrain include ...large-scale orographic enhancement of snowfall, small-scale processes such as gravitational and wind-induced transport of snow, and variability in the radiative balance such as through terrain shadowing. In this study, a multi-scale modelling approach is proposed to simulate the temporal and spatial evolution of high-mountain snowpacks. The multi-scale approach combines atmospheric data from a numerical weather prediction system at the kilometre scale with process-based downscaling techniques to drive the Canadian Hydrological Model (CHM) at spatial resolutions allowing for explicit snow redistribution modelling. CHM permits a variable spatial resolution by using the efficient terrain representation by unstructured triangular meshes. The model simulates processes such as radiation shadowing and irradiance to slopes, blowing-snow transport (saltation and suspension) and sublimation, avalanching, forest canopy interception and sublimation, and snowpack melt. Short-term, kilometre-scale atmospheric forecasts from Environment and Climate Change Canada's Global Environmental Multiscale Model through its High Resolution Deterministic Prediction System (HRDPS) drive CHM and are downscaled to the unstructured mesh scale. In particular, a new wind-downscaling strategy uses pre-computed wind fields from a mass-conserving wind model at 50 m resolution to perturb the mesoscale HRDPS wind and to account for the influence of topographic features on wind direction and speed. HRDPS-CHM was applied to simulate snow conditions down to 50 m resolution during winter 2017/2018 in a domain around the Kananaskis Valley (∼1000 km2) in the Canadian Rockies. Simulations were evaluated using high-resolution airborne light detection and ranging (lidar) snow depth data and snow persistence indexes derived from remotely sensed imagery. Results included model falsifications and showed that both wind-induced and gravitational snow redistribution need to be simulated to capture the snowpack variability and the evolution of snow depth and persistence with elevation across the region. Accumulation of windblown snow on leeward slopes and associated snow cover persistence were underestimated in a CHM simulation driven by wind fields that did not capture lee-side flow recirculation and associated wind speed decreases. A terrain-based metric helped to identify these lee-side areas and improved the wind field and the associated snow redistribution. An overestimation of snow redistribution from windward to leeward slopes and subsequent avalanching was still found. The results of this study highlight the need for further improvements of snowdrift-permitting models for large-scale applications, in particular the representation of subgrid topographic effects on snow transport.
Point observations and previous basin modeling efforts have suggested that snowmelt may be a significant input of water for runoff during extreme rain‐on‐snow floods within western U.S. basins. ...Quantifying snowmelt input over entire basins is difficult given sparse observations of snowmelt. In order to provide a range of snowmelt contributions for water managers, a physically based snow model coupled with an idealized basin representation was evaluated in point simulations and used to quantify the maximum basin‐wide input from snowmelt volume during flood events. Maximum snowmelt basin contributions and uncertainty ranges were estimated as 29% (11–47%), 29% (8–37%), and 7% (2–24%) of total rain plus snowmelt input, within the Snoqualmie, East North Fork Feather, and Upper San Joaquin basins, respectively, during historic flooding events between 1980 and 2008. The idealized basin representation revealed that both hypsometry and forest cover of a basin had similar magnitude of impacts on the basin‐wide snowmelt totals. However, the characteristics of a given storm (antecedent SWE and available energy for melt) controlled how much hypsometry and forest cover impacted basin‐wide snowmelt. These results indicate that for watershed managers, flood forecasting efforts should prioritize rainfall prediction first, but cannot neglect snowmelt contributions in some cases. Efforts to reduce the uncertainty in the above snowmelt simulations should focus on improving the meteorological forcing data (especially air temperature and wind speed) in complex terrain.
Key Points:
Simulated snowmelt spanned 0–29% of basin input during floods, with rainfall making up the majority
Storm variability influences how basin characteristics control basin melt
Snowmelt magnitude was invariant with rainfall amount
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