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Residual foreground contamination in the WMAP data and bias in non-Gaussianity estimation
We analyze whether there is any residual foreground contamination in the cleaned WMAP 7 years data for the differential assemblies, Q, V and W. We calculate the correlation between the foreground map, from which long wavelength correlations have been subtracted, and the foreground reduced map for each differential assembly after applying the Galaxy and point sources masks. We find positive correlations for all the differential assemblies, with high statistical significance. For Q and V, we find that a large fraction of the contamination comes from pixels where the foreground maps have positive values larger than three times the rms values. These findings imply the presence of residual contamination from Galactic emissions and unresolved point sources. We redo the analysis after masking the extended point sources cataloque of Scodeller et al. [7] and find a drop in the correlation and corresponding significance values. To quantify the effect of the residual contamination on the search for primordial non-Gaussianity in the CMB we add estimated contaminant fraction to simulated Gaussian CMB maps and calculate the characteristic non-Gaussian deviation shapes of Minkowski Functionals that arise due to the contamination. We find remarkable agreement of these deviation shapes with those measured from WMAP data, which imply that a major fraction of the observed non-Gaussian deviation comes from residual foreground contamination. We also compute non-Gaussian deviations of Minkowski Functionals after applying the point sources mask of Scodeller et al. and find a decrease in the overall amplitudes of the deviations which is consistent with a decrease in the level of contamination.
Local gravitational redshifts can bias cosmological measurements
Measurements of cosmological parameters via the distance-redshift relation usually rely on models that assume a homogenous universe. It is commonly presumed that the large-scale structure evident in our Universe has a negligible impact on the measurement if distances probed in observations are sufficiently large (compared to the scale of inhomogeneities) and are averaged over different directions on the sky. This presumption does not hold when considering the effect of the gravitational redshift caused by our local gravitational potential, which alters light coming from all distances and directions in the same way. Despite its small magnitude, this local gravitational redshift gives rise to noticeable effects in cosmological inference using SN Ia data. Assuming conservative prior knowledge of the local potential given by sampling a range of gravitational potentials at locations of Milky-Way-like galaxies identified in cosmological simulations, we show that ignoring the gravitational redshift effect in a standard data analysis leads to an additional systematic error of ∼1% in the determination of density parameters and the dark energy equation of state. We conclude that our local gravitational field affects our cosmological inference at a level that is important in future observations aiming to achieve percent-level accuracy.
Aemulus $\nu$: precise predictions for matter and biased tracer power spectra in the presence of neutrinos
Here we present the Aemulusν simulations: a suite of 150 (1.05 h -1 Gpc) 3 N-body simulations with a mass resolution of 3.51 × 10 10 Ω cb /0.3 h -1 M ⊙ in a wνCDM cosmological parameter space. The simulations have been explicitly designed to span a broad range in σ8 to facilitate investigations of tension between large scale structure and cosmic microwave background cosmological probes. Neutrinos are treated as a second particle species to ensure accuracy to 0.5 eV, the maximum neutrino mass that we have simulated. By employing Zel'dovich control variates, we increase the effective volume of our simulations by factors of 10-10 5 depending on the statistic in question. As a first application of these simulations, we build new hybrid effective field theory and matter power spectrum surrogate models, demonstrating that they achieve ≤ 1% accuracy for k ≤ 1 hMpc -1 and 0 ≤ z ≤ 3, and ≤ 2% accuracy for k ≤ 4 hMpc -1 for the matter power spectrum. We publicly release the trained surrogate models, and estimates of the surrogate model errors in the hope that they will be broadly applicable to a range of cosmological analyses for many years to come.
Surface biasing influence on the physical sputtering in fusion devices
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THE ACS LCID PROJECT: ON THE ORIGIN OF DWARF GALAXY TYPES—A MANIFESTATION OF THE HALO ASSEMBLY BIAS?
We discuss how knowledge of the whole evolutionary history of dwarf galaxies, including details on the early star formation events, can provide insight on the origin of the different dwarf galaxy types. We suggest that these types may be imprinted by the early conditions of formation rather than only being the result of a recent morphological transformation driven by environmental effects. We present precise star formation histories of a sample of Local Group dwarf galaxies, derived from color–magnitude diagrams reaching the oldest main-sequence turnoffs. We argue that these galaxies can be assigned to two basic types: fast dwarfs that started their evolution with a dominant and short star formation event and slow dwarfs that formed a small fraction of their stars early and have continued forming stars until the present time (or almost). These two different evolutionary paths do not map directly onto the present-day morphology (dwarf spheroidal versus dwarf irregular). Slow and fast dwarfs also differ in their inferred past location relative to the Milky Way and/or M31, which hints that slow dwarfs were generally assembled in lower-density environments than fast dwarfs. We propose that the distinction between a fast and slow dwarf galaxy primarily reflects the characteristic density of the environment where they form. At a later stage, interaction with a large host galaxy may play a role in the final gas removal and ultimate termination of star formation.
Combining variational autoencoders and physical bias for improved microscopy data analysis *
Electron and scanning probe microscopy produce vast amounts of data in the form of images or hyperspectral data, such as electron energy loss spectroscopy or 4D scanning transmission electron microscope, that contain information on a wide range of structural, physical, and chemical properties of materials. To extract valuable insights from these data, it is crucial to identify physically separate regions in the data, such as phases, ferroic variants, and boundaries between them. In order to derive an easily interpretable feature analysis, combining with well-defined boundaries in a principled and unsupervised manner, here we present a physics augmented machine learning method which combines the capability of variational autoencoders to disentangle factors of variability within the data and the physics driven loss function that seeks to minimize the total length of the discontinuities in images corresponding to latent representations. Our method is applied to various materials, including NiO-LSMO, BiFeO 3 , and graphene. The results demonstrate the effectiveness of our approach in extracting meaningful information from large volumes of imaging data. The customized codes of the required functions and classes to develop phyVAE is available at https://github.com/arpanbiswas52/phy-VAE.
Orientation Bias of Optically Selected Galaxy Clusters and Its Impact on Stacked Weak Lensing Analyses
Abstract Not Provided
Measuring linear and non-linear galaxy bias using counts-in-cells in the Dark Energy Survey Science Verification data
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First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases
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Spin reorientation driven exchange bias in hematite/permalloy heterostructures
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Compact − 300 kV dc inverted insulator photogun with biased anode and alkali-antimonide photocathode
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Dy-V magnetic interaction and local structure bias on the complex spin and orbital ordering in Dy₁₋ x Tb x VO₃ (x=0 and 0.2)
The spin and orbital ordering in Dy₁₋ x Tb x VO₃ (x=0 and 0.2) was studied by measuring x-ray powder diffraction, magnetization, specific heat, and neutron single-crystal diffraction. The results show that G-OO/C-AF and C-OO/G-AF phases coexist in Dy 0.8 Tb 0.20 VO 3 in the temperature range 2–60 K, and the volume fraction of each phase is temperature and field dependent. The ordering of Dy moments at T* = 12 K induces a transition from G-OO/C-AF to a C-OO/G-AF phase. Magnetic fields suppress the long-range order of Dy moments and thus the C-OO/G-AF phase below T*. The polarized moments induced at the Dy sublattice by external magnetic fields couple to the V 3d moments, and this coupling favors the G-OO/C-AF state. Also discussed is the effect of the Dy-V magnetic interaction and local structure distortion on the spin and orbital ordering in Dy₁₋ x Tb x VO₃.
Negative exchange bias in single-phase D y 1 − x N d x Cr O 3 induced by Nd doping
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Tunable photonic cavity coupled to a voltage-biased double quantum dot system: Diagrammatic nonequilibrium Green's function approach
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