相关论文: Poincare dodecahedral space parameter estimates
We update a previously-proposed set of supersymmetric benchmark scenarios, taking into account the precise constraints on the cold dark matter density obtained by combining WMAP and other cosmological data, as well as the LEP and b -> s…
Compressive Sensing (CS) theory states that real-world signals can often be recovered from much fewer measurements than those suggested by the Shannon sampling theorem. Nevertheless, recoverability does not only depend on the signal, but…
We present a non-conforming least squares method for approximating solutions of second order elliptic problems with discontinuous coefficients. The method is based on a general Saddle Point Least Squares (SPLS) method introduced in previous…
A search for matched circle pairs of similar temperature fluctuations in the final WMAP 9yr data is carried out. Such a signature is expected if the space of the Universe is multiply connected. We investigate the relation between the pixel…
We illustrate the constraints that a possible detection of a non-trivial spatial topology may place on the cosmological density parameters by considering the $\Lambda$CDM model Poincar\'e dodecahedal space (PDS) topology as a…
Fisher Information Matrix methods are commonly used in cosmology to estimate the accuracy that cosmological parameters can be measured with a given experiment, and to optimise the design of experiments. However, the standard approach…
Two years ago, the AMS collaboration released the most precise measurement of the cosmic ray positron flux. It confirms that pure secondary predictions fall below the data above 10 GeV, suggesting the presence of a primary component, e.g.…
We perform a cross-correlation of the Cosmic Microwave Background (CMB) using the third year Wilkinson Microwave Anisotropy Probe (WMAP) data with the 2 Micron All Sky Survey (2MASS) galaxy map (about 828 000 galaxies with median redshift z…
In the low-altitude wireless networks, the simultaneous sensing data acquisition and sharing (SDAS) through an ISAC signaling strategy becomes a typical application scenario. In this paper, we mainly investigate three primary aspects of the…
To date, the comparison of Statistical Shape Models (SSMs) is often solely performance-based, carried out by means of simplistic metrics such as compactness, generalization, or specificity. Any similarities or differences between the actual…
Weak-lensing mass-mapping algorithms, which reconstruct the convergence field from galaxy shear measurements, are crucial for extracting higher-order statistics to constrain cosmological parameters. However, only limited research has…
We reconstruct the dark matter density field from spatially overlapping spectroscopic and photometric redshift catalogs through a forward modelling approach. Instead of directly inferring the underlying density field, we find the best…
In this paper, we propose a Gaussian Process (GP) emulator for the calculation of a) tomographic weak lensing band-power spectra, and b) coefficients of summary data massively compressed with the MOPED algorithm. In the former case…
We offer a method of correlations mapping on the full celestial sphere that allows to check the quality of reconstructed maps, their non-Gaussianity and conduct experiments in various frequency ranges. The method was evaluated on the WMAP…
The advent of next-generation imaging telescopes such as LSST and Pan-STARRS has revitalized the need for deep and precise reference frames. The proposed weak-lensing observations with these facilities put the highest demands on image…
If dark matter interacts, even weakly, via non-gravitational forces, simulations predict that it will be preferentially scattered towards the trailing edge of the halo during collisions between galaxy clusters. This will temporarily create…
We present a fully parallelized grid-based parameter estimation algorithm for investigating multidimensional likelihoods called Snake, and apply it to cosmological parameter estimation. The basic idea is to map out the likelihood grid-cell…
We propose a learning-based method for light-path construction in path tracing algorithms, which iteratively optimizes and samples from what we refer to as spatio-directional Gaussian mixture models (SDMMs). In particular, we approximate…
We present an approximate calculation of the full Bayesian posterior probability distribution for the local non-Gaussianity parameter $f_{\text{nl}}$ from observations of cosmic microwave background anisotropies within the framework of…
In health-pollution cohort studies, accurate predictions of pollutant concentrations at new locations are needed, since the locations of fixed monitoring sites and study participants are often spatially misaligned. For multi-pollution data,…