380,738 research outputs found

    Constraints on the Neutrino Mass from SZ Surveys

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    Statistical measures of galaxy clusters are sensitive to neutrino masses in the sub-eV range. We explore the possibility of using cluster number counts from the ongoing PLANCK/SZ and future cosmic-variance-limited surveys to constrain neutrino masses from CMB data alone. The precision with which the total neutrino mass can be determined from SZ number counts is limited mostly by uncertainties in the cluster mass function and intracluster gas evolution; these are explicitly accounted for in our analysis. We find that projected results from the PLANCK/SZ survey can be used to determine the total neutrino mass with a (1\sigma) uncertainty of 0.06 eV, assuming it is in the range 0.1-0.3 eV, and the survey detection limit is set at the 5\sigma significance level. Our results constitute a significant improvement on the limits expected from PLANCK/CMB lensing measurements, 0.15 eV. Based on expected results from future cosmic-variance-limited (CVL) SZ survey we predict a 1\sigma uncertainty of 0.04 eV, a level comparable to that expected when CMB lensing extraction is carried out with the same experiment. A few percent uncertainty in the mass function parameters could result in up to a factor \sim 2-3 degradation of our PLANCK and CVL forecasts. Our analysis shows that cluster number counts provide a viable complementary cosmological probe to CMB lensing constraints on the total neutrino mass.Comment: Replaced with a revised version to match the MNRAS accepted version. arXiv admin note: text overlap with arXiv:1009.411

    Neutrino Mass from SZ Surveys

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    The expected sensitivity of cluster SZ number counts to neutrino mass in the sub-eV range is assessed. We find that from the ongoing {\it Planck}/SZ measurements the (total) neutrino mass can be determined at a (1-sigma) precision of 0.06 eV, if the mass is in the range 0.1-0.3 eV, and the survey detection limit is set at the 5-sigma significance level. The mass uncertainty is predicted to be lower by a factor ~2/3, if a similar survey is conducted by a cosmic-variance-limited experiment, a level comparable to that projected if CMB lensing extraction is accomplished with the same experiment. At present, the main uncertainty in modeling cluster statistical measures reflects the difficulty in determining the mass function at the high-mass end.Comment: 8 pages, Proceedings of the 13th Marcel Grossmann Meetin

    Self-Calibration of Cluster Dark Energy Studies: Observable-Mass Distribution

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    The exponential sensitivity of cluster number counts to the properties of the dark energy implies a comparable sensitivity to not only the mean but also the actual_distribution_ of an observable mass proxy given the true cluster mass. For example a 25% scatter in mass can provide a ~50% change in the number counts at z~2 for the upcoming SPT survey. Uncertainty in the scatter of this amount would degrade dark energy constraints to uninteresting levels. Given the shape of the actual mass function, the properties of the distribution may be internally monitored by the shape of the_observable_ mass function. An arbitrary evolution of the scatter of a mass-independent Gaussian distribution may be self-calibrated to allow a measurement of the dark energy equation of state of Delta w ~0.1. External constraints on the mass_variance_ of the distribution that are more accurate than Delta var < 0.01 at z~1 can further improve constraints by up to a factor of 2. More generally, cluster counts and their sample variance measured as a function of the observable provide internal consistency checks on the assumed form of the observable-mass distribution that will protect against misinterpretation of the dark energy constraints.Comment: 6 pages, 6 figures, submitted to PR

    Possibilistic Granular Count: Derivation and Extension to Granular Sum

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    Counting data in presence of uncertainty leads to granular counts that can be represented in terms of possibility distributions. The formula of granular count is derived on the basis of two weak assumptions that can be applied in a wide variety of problems involving uncertain data. The formulation is further extended to introduce the granular sum of counts, by taking into account the interactivity of granular counts. Numerical results show the differences in terms of specificity between granular sum and a direct application of the extension principle to sum granular counts

    Conservation implications of sea turtle nesting trends: elusive recovery of a globally important loggerhead population

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    Abstract Understanding population status and trends is important for developing and evaluating management and conservation actions for threatened species. Monitoring population status of marine organisms is especially challenging. Because sea turtles come ashore to lay their eggs and nests are easily counted, these counts are commonly used as an index of abundance and population trends. Nest counts do not provide a direct index of adult female population abundance because females typically lay more than one nest per year and most do not reproduce every year. This study attempts for the first time to investigate the likelihood that observed fluctuations of nest counts represent inter‐annual changes of the adult female population by accounting for uncertainty in reproductive rate parameters. We analyzed 30 yr of reproductive data from the largest nesting loggerhead sea turtle population worldwide, breeding in Florida (USA), and for the three Recovery Units and seven Management Units therein. Nest counts followed a general non‐monotonic trend with wide fluctuations that corresponded to decreasing and increasing trends during short intervals. When we accounted for uncertainty in both clutch frequency and remigration interval, there was no evidence for an increasing or a declining trend in the breeding female population across the entire period. Despite extensive conservation efforts and protections for loggerheads in Florida and the wider USA, we did not find evidence of a strong population recovery. We recommend maintaining a high level of protection, addressing persistent anthropogenic threats, continued collection of rigorous nest‐count data, and monitoring reproductive parameters to better link nest counts to adult female population abundance. Our results demonstrate the need for caution in using nest counts as a direct proxy for adult female population status, as it may lead to unsupported conclusions potentially detrimental to conservation. Therefore, we recommend to always translating nest trends to at least adult female trends, including uncertainty in reproductive parameters. Our approach can be exported to other populations, even where reproductive parameters are not available. Applying high parameter uncertainty obtained from other populations can help identifying unequivocal population changes; that is, nest trends unlikely justified by uncertainty and poor knowledge of reproductive parameters

    Precision Determination of the Mass Function of Dark Matter Halos

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    The predicted mass function of dark matter halos is essential in connecting observed galaxy cluster counts and models of galaxy clustering to the properties of the primordial density field. We determine the mass function in the concordance Λ\LambdaCDM cosmology, as well as its uncertainty, using sixteen 102431024^3-particle nested-volume dark-matter simulations, spanning a mass range of over five orders of magnitude. Using the nested volumes and single-halo tests, we find and correct for a systematic error in the friends-of-friends halo-finding algorithm. We find a fitting form and full error covariance for the mass function that successfully describes the simulations' mass function and is well-behaved outside the simulations' resolutions. Estimated forecasts of uncertainty in cosmological parameters from future cluster count surveys have negligible contribution from remaining statistical uncertainties in the central cosmology multiplicity function. There exists a potentially non-negligible cosmological dependence (non-universality) of the halo multiplicity function.Comment: 4 pages, 3 figures, submitted to ApJ
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