Multicomponent Dark Matter in Supersymmetric Hidden Sector Extensions

Most analyses of dark matter within supersymmetry assume the entire cold dark matter arising only from weakly interacting neutralinos. We study a new class of models consisting of $U(1)^n$ hidden sector extensions of the MSSM that includes several stable particles, both fermionic and bosonic, which can be interpreted as constituents of dark matter. In one such class of models, dark matter is made up of both a Majorana dark matter particle, i.e., a neutralino, and a Dirac fermion with the current relic density of dark matter as given by WMAP being composed of the relic density of the two species. These models can explain the PAMELA positron data and are consistent with the anti-proton flux data, as well as the photon data from FERMI-LAT. Further, it is shown that such models can also simultaneously produce spin independent cross sections which can be probed in CDMS-II, XENON-100 and other ongoing dark matter experiments. The implications of the models at the LHC and at the NLC are also briefly discussed.Comment: Journal: Physical Review D, Latex 32 pages, 4 eps figure

Using effective field theory to analyse low-energy Compton scattering data from protons and light nuclei

Compton scattering provides important insight into the structure of the nucleon. For photons up to about 300 MeV, it is parameterised by six dynamical dipole polarisabilities which characterise the response of the nucleon to a monochromatic photon of fixed frequency and multipolarity. Their zero-energy limit yields the well-known static electric and magnetic dipole polarisabilities \alpha and \beta, and the four dipole spin polarisabilities. Chiral Effective Field Theory (ChiEFT) describes nucleon, deuteron and 3-He Compton scattering, using consistent nuclear currents, rescattering and wave functions. It can thus also be used to extract useful information on the neutron amplitude from Compton scattering on light nuclei. We summarise past work in ChiEFT on all of these reactions and compare with other theoretical approaches. We also discuss all proton experiments up to about 400 MeV, as well as the three modern elastic deuteron data sets, paying particular attention to precision and accuracy of each set. Constraining the Delta(1232) parameters from the resonance region, we then perform new fits to the proton data up to omega(lab)=170 MeV, and a new fit to the deuteron data. After checking in each case that a two-parameter fit is compatible with the respective Baldin sum rules, we obtain, using the sum-rule constraints in a one-parameter fit, \alpha=10.7\pm0.3(stat)\pm0.2(Baldin)\pm0.8(theory), \beta=3.1\mp0.3(stat)\pm0.2(Baldin)\pm0.8(theory), for the proton polarisabilities, and \alpha =10.9\pm 0.9(stat)\pm0.2(Baldin)\pm0.8(theory), \beta =3.6\mp 0.9(stat)\pm0.2(Baldin)\pm0.8(theory), for the isoscalar polarisabilities, each in units of 10^(-4) fm^3. We discuss plans for polarised Compton scattering, their promise as tools to access spin polarisabilities, and other future avenues for theoretical and experimental investigation.Comment: 82 pages LaTeX2e including 24 figures as .eps file embedded with includegraphicx; review for Prog. Part Nucl Phys. Final version identical to published areticle; spelling and grammar correcte

Low Mass Gluino within the Sparticle Landscape, Implications for Dark Matter, and Early Discovery Prospects at LHC-7

We analyze supergravity models that predict a low mass gluino within the landscape of sparticle mass hierarchies. The analysis includes a broad class of models that arise in minimal and in non-minimal supergravity unified frameworks and in extended models with additional $U(1)^n_X$ hidden sector gauge symmetries. Gluino masses in the range $(350-700)$ GeV are investigated. Masses in this range are promising for early discovery at the LHC at $\sqrt s =7$ TeV (LHC-7). The models exhibit a wide dispersion in the gaugino-Higgsino eigencontent of their LSPs and in their associated sparticle mass spectra. A signature analysis is carried out and the prominent discovery channels for the models are identified with most models needing only $\sim 1 \rm fb^{-1}$ for discovery at LHC-7. In addition, significant variations in the discovery capability of the low mass gluino models are observed for models in which the gluino masses are of comparable size due to the mass splittings in different models and the relative position of the light gluino within the various sparticle mass hierarchies. The models are consistent with the current stringent bounds from the Fermi-LAT, CDMS-II, XENON100, and EDELWEISS-2 experiments. A subclass of these models, which include a mixed-wino LSP and a Higgsino LSP, are also shown to accommodate the positron excess seen in the PAMELA satellite experiment.Comment: 37 pages, 8 figures, Published in PR

Nonparametric Copula Models for Mixed Data with Informative Missingness

Modern datasets commonly feature both substantial missingness and variables of mixed data types, which present significant challenges for estimation and inference. Complete case analysis, which proceeds using only the observations with fully-observed variables, is often severely biased, while model-based imputation of missing values is limited by the ability of the model to capture complex dependencies and accommodate mixed data types. To address these challenges, we develop a novel Bayesian mixture copula for joint and nonparametric modelling of count, continuous, ordinal, and unordered categorical variables, and deploy this model for inference, prediction, and imputation of missing data. Most uniquely, we introduce a new and efficient strategy for marginal distribution estimation, which eliminates the need to specify any marginal models yet delivers strong posterior consistency for both the marginal distributions and the copula parameters even in the presence of informative missingness (i.e., missingness-at-random). Extensive simulation studies demonstrate exceptional modeling and imputation capabilities relative to competing methods, especially with mixed data types, complex missingness mechanisms, and nonlinear dependencies. We conclude with a data analysis that highlights how improper treatment of missing data can distort a statistical analysis, and how the proposed approach offers a resolution.Comment: 60 pages, 18 figures, 2 table

PAMELA Positron Excess as a Signal from the Hidden Sector

The recent positron excess observed in the PAMELA satellite experiment strengthens previous experimental findings. We give here an analysis of this excess in the framework of the Stueckelberg extension of the standard model which includes an extra $U(1)_X$ gauge field and matter in the hidden sector. Such matter can produce the right amount of dark matter consistent with the WMAP constraints. Assuming the hidden sector matter to be Dirac fermions it is shown that their annihilation can produce the positron excess with the right positron energy dependence seen in the HEAT, AMS and the PAMELA experiments. Further test of the proposed model can come at the Large Hadron Collider. The predictions of the $\bar p/p$ flux ratio also fit the data.Comment: 9 pages,3 figures; Breit-Wigner enhancement emphasized; published in PR

Excess Observed in CDF Bs0→μ+μ−B^0_s \to \mu^{+} \mu^{-} and SUSY at the LHC

The recent excess observed by CDF in $B^0_s \to \mu^{+} \mu^{-}$ is interpreted in terms of a possible supersymmetric origin. An analysis is given of the parameter space of mSUGRA and non-universal SUGRA models under the combined constraints from LHC-7 with 165 pb$^{-1}$ of integrated luminosity, under the new XENON-100 limits on the neutralino-proton spin independent cross section and under the CDF $B^0_s \to \mu^{+} \mu^{-}$ 90% C.L. limit reported to arise from an excess number of dimuon events. It is found that the predicted value of the branching ratio $B^0_s \to \mu^{+} \mu^{-}$ consistent with all the constraints contains the following set of NLSPs: chargino, stau, stop or CP odd (even) Higgs. The lower bounds of sparticles, including those from the LHC, XENON and CDF $B^0_s\to \mu^+\mu^-$ constraint, are exhibited and the shift in the allowed range of sparticle masses arising solely due to the extra constraint from the CDF result is given. It is pointed out that the two sided CDF 90% C.L. limit puts upper bounds on sparticle masses. An analysis of possible signatures for early discovery at the LHC is carried out corresponding to the signal region in $B^0_s \to \mu^{+} \mu^{-}$. Implications of GUT-scale non-universalities in the gaugino and Higgs sectors are discussed. If the excess seen by the CDF Collaboration is supported by further data from LHCb or D0, this new result could be a harbinger for the discovery of supersymmetry.Comment: References added, text update

Time‐Dependent Cryospheric Longwave Surface Emissivity Feedback in the Community Earth System Model

Frozen and unfrozen surfaces exhibit different longwave surface emissivities with different spectral characteristics, and outgoing longwave radiation and cooling rates are reduced for unfrozen scenes relative to frozen ones. Here physically realistic modeling of spectrally resolved surface emissivity throughout the coupled model components of the Community Earth System Model (CESM) is advanced, and implications for model high‐latitude biases and feedbacks are evaluated. It is shown that despite a surface emissivity feedback amplitude that is, at most, a few percent of the surface albedo feedback amplitude, the inclusion of realistic, harmonized longwave, spectrally resolved emissivity information in CESM1.2.2 reduces wintertime Arctic surface temperature biases from −7.2 ± 0.9 K to −1.1 ± 1.2 K, relative to observations. The bias reduction is most pronounced in the Arctic Ocean, a region for which Coupled Model Intercomparison Project version 5 (CMIP5) models exhibit the largest mean wintertime cold bias, suggesting that persistent polar temperature biases can be lessened by including this physically based process across model components. The ice emissivity feedback of CESM1.2.2 is evaluated under a warming scenario with a kernel‐based approach, and it is found that emissivity radiative kernels exhibit water vapor and cloud cover dependence, thereby varying spatially and decreasing in magnitude over the course of the scenario from secular changes in atmospheric thermodynamics and cloud patterns. Accounting for the temporally varying radiative responses can yield diagnosed feedbacks that differ in sign from those obtained from conventional climatological feedback analysis methods.Plain Language SummaryClimate models have exhibited a persistent cold‐pole bias, whereby they systematically underestimate the average temperature and the amplification of climate change at high latitudes. A number of different explanations have been advanced for cold‐pole biases, which can be broadly divided into radiative and dynamic explanations. Here we explore in detail a relatively novel radiative explanation for the cold‐pole bias: the ice emissivity feedback. Similar to the difference in shortwave reflectivity of unfrozen and frozen surfaces, recent literature has shown that unfrozen surfaces are less emissive than frozen surfaces, which can induce a positive radiative feedback. We first present the highly nontrivial implementation of this feedback in a global circulation model (GCM) and show how to harmonize the disjointed representation of surface emissivity within the radiative transfer calculated by atmospheric and land components of a GCM. With this modified model, we show how this ice emissivity feedback depends on atmospheric water vapor and thus varies on time scales ranging from seasonal to centennial. We also show that the ice emissivity feedback is seasonally complementary to the well‐known ice‐albedo feedback, where the former is most influential during polar night. Finally, we show that including this feedback essentially eliminates the cold‐pole bias on the model we used.Key PointsLW spectral surface emissivity improves CESM Arctic surface temperature bias by 6.1 ± 1.9 degrees KelvinSpectral emissivity kernels computed for 200+ period are nonlinear in timeTemporally and spatially localized atmospheric dynamics show decreased climatological seasonal sea ice emissivity radiative response in ArcticPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142486/1/jgrd54377_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142486/2/jgrd54377.pd

Constructing a Man-Made Oyster Reef in the Little Hellgate Salt Marsh, Randall\u27s Island, New York: A Project Overview

Atlantic oyster beds provide instrumental estuarine infrastructure, shaping waterways and mediating the impacts of storm surge. In addition, the reefs provide habitat for numerous species. The oysters themselves are expert filter feeders, remediating poor water quality at little cost to the organism. As the free-swimming oyster larvae (spat) only settle on the shells of their forbears, the reefs are essential in perpetuation of the species, as well as for the continuation of such invaluable ecosystem services. Oyster reefs of the New York City waterway system have long been subject to environmental degradation, from water pollution and sedimentation to dredging. Randall’s Island Park Alliance’s Natural Areas crew received a donation of six hundred oysters from the New York Harbor School to conduct a test for the viability of a manmade oyster garden in 2014. Three hundred oysters were placed in each cage, which were then established in different parts of Randall’s Island Park’s Harlem River shoreline. One was hung by the 103rd Street footbridge seawall and the other was placed on the seawall by the Little Hellgate Salt Marsh inlet. The cages were monitored monthly for oyster growth and mortality rate, and water quality was tested as well. After a year of monitoring, it was determined that the Little Hellgate Salt Marsh was the ideal site for a man-made oyster reef—oysters had shown significantly more growth and a lower mortality rate than those in the cage at the 103rd St. Bridge, most likely due to the protective shape of the salt marsh inlet. The cages that will serve as the reef framework were constructed in the spring of this year and await the placement of oyster shells, which are being treated and sterilized (completion is projected to be late fall 2015). Future monitoring of oyster colonization and growth are expected, with the aim that water quality will measurably improve

The Functional Microarchitecture of the Mouse Barrel Cortex

Cortical maps, consisting of orderly arrangements of functional columns, are a hallmark of the organization of the cerebral cortex. However, the microorganization of cortical maps at the level of single neurons is not known, mainly because of the limitations of available mapping techniques. Here, we used bulk loading of Ca2+ indicators combined with two-photon microscopy to image the activity of multiple single neurons in layer (L) 2/3 of the mouse barrel cortex in vivo. We developed methods that reliably detect single action potentials in approximately half of the imaged neurons in L2/3. This allowed us to measure the spiking probability following whisker deflection and thus map the whisker selectivity for multiple neurons with known spatial relationships. At the level of neuronal populations, the whisker map varied smoothly across the surface of the cortex, within and between the barrels. However, the whisker selectivity of individual neurons recorded simultaneously differed greatly, even for nearest neighbors. Trial-to-trial correlations between pairs of neurons were high over distances spanning multiple cortical columns. Our data suggest that the response properties of individual neurons are shaped by highly specific subcolumnar circuits and the momentary intrinsic state of the neocortex

The Thermal Properties of Solar Flares Over Three Solar Cycles Using GOES X-ray Observations

Solar flare X-ray emission results from rapidly increasing temperatures and emission measures in flaring active region loops. To date, observations from the X-Ray Sensor (XRS) onboard the Geostationary Operational Environmental Satellite (GOES) have been used to derive these properties, but have been limited by a number of factors, including the lack of a consistent background subtraction method capable of being automatically applied to large numbers of flares. In this paper, we describe an automated temperature and emission measure-based background subtraction method (TEBBS), which builds on the methods of Bornmann (1990). Our algorithm ensures that the derived temperature is always greater than the instrumental limit and the pre-flare background temperature, and that the temperature and emission measure are increasing during the flare rise phase. Additionally, TEBBS utilizes the improved estimates of GOES temperatures and emission measures from White et al. (2005). TEBBS was successfully applied to over 50,000 solar flares occurring over nearly three solar cycles (1980-2007), and used to create an extensive catalog of the solar flare thermal properties. We confirm that the peak emission measure and total radiative losses scale with background subtracted GOES X-ray flux as power-laws, while the peak temperature scales logarithmically. As expected, the peak emission measure shows an increasing trend with peak temperature, although the total radiative losses do not. While these results are comparable to previous studies, we find that flares of a given GOES class have lower peak temperatures and higher peak emission measures than previously reported. The resulting TEBBS database of thermal flare plasma properties is publicly available on Solar Monitor (www.solarmonitor.org/TEBBS/) and will be available on Heliophysics Integrated Observatory (www.helio-vo.eu)