The acute effect of whole-body vibration on cycling peak power output

The aim of the present study was to determine if an acute bout of whole-body vibration (WBV) prior to sprint cycling would increase peak power output. Ten male cyclists, all familiar with maximal sprint cycling exercise performed, on two separate occasions, a ten second standing sprint on a cycle ergometer. For one trial the sprint was preceded by a 2 minute WBV intervention, requiring the participant to stand on a vibrating platform that produced sinusoidal oscillations. The frequency and amplitude of the vibration was set at 26Hz and ‘high’ (approximately 2mm) respectively. For the other trial participants stood in the same position, however the platform did not vibrate (no-WBV; 0Hz and 0mm for frequency and amplitude respectively). No significant difference was recorded for peak power output between trials (1458.0 + 283.7 W versus 1506.3 + 232.5 W for WBV and no-WBV respectively, P = 0.17). The results suggest that WBV prior to maximal standing sprint cycling does not increase peak power output

Bias to CMB Lensing Reconstruction from Temperature Anisotropies due to Large-Scale Galaxy Motions

Gravitational lensing of the cosmic microwave background (CMB) is expected to be amongst the most powerful cosmological tools for ongoing and upcoming CMB experiments. In this work, we investigate a bias to CMB lensing reconstruction from temperature anisotropies due to the kinematic Sunyaev-Zel'dovich (kSZ) effect, that is, the Doppler shift of CMB photons induced by Compton-scattering off moving electrons. The kSZ signal yields biases due to both its own intrinsic non-Gaussianity and its non-zero cross-correlation with the CMB lensing field (and other fields that trace the large-scale structure). This kSZ-induced bias affects both the CMB lensing auto-power spectrum and its cross-correlation with low-redshift tracers. Furthermore, it cannot be removed by multifrequency foreground separation techniques because the kSZ effect preserves the blackbody spectrum of the CMB. While statistically negligible for current datasets, we show that it will be important for upcoming surveys, and failure to account for it can lead to large biases in constraints on neutrino masses or the properties of dark energy. For a Stage 4 CMB experiment, the bias can be as large as $\approx$ 15% or 12% in cross-correlation with LSST galaxy lensing convergence or galaxy overdensity maps, respectively, when the maximum temperature multipole used in the reconstruction is $\ell_{\rm max} = 4000$, and about half of that when $\ell_{\rm max} = 3000$. Similarly, we find that the CMB lensing auto-power spectrum can be biased by up to several percent. These biases are many times larger than the expected statistical errors. Reducing $\ell_{\rm max}$ can significantly mitigate the bias at the cost of a decrease in the overall lensing reconstruction signal-to-noise. Polarization-only reconstruction may be the most robust mitigation strategy.Comment: Updated to match published version and fixed typo. Improved study of secondary contractions and end-to-end simulation

Rethinking CMB foregrounds: systematic extension of foreground parameterizations

Future high-sensitivity measurements of the cosmic microwave background (CMB) anisotropies and energy spectrum will be limited by our understanding and modeling of foregrounds. Not only does more information need to be gathered and combined, but also novel approaches for the modeling of foregrounds, commensurate with the vast improvements in sensitivity, have to be explored. Here, we study the inevitable effects of spatial averaging on the spectral shapes of typical foreground components, introducing a moment approach, which naturally extends the list of foreground parameters that have to be determined through measurements or constrained by theoretical models. Foregrounds are thought of as a superposition of individual emitting volume elements along the line of sight and across the sky, which then are observed through an instrumental beam. The beam and line of sight averages are inevitable. Instead of assuming a specific model for the distributions of physical parameters, our method identifies natural new spectral shapes for each foreground component that can be used to extract parameter moments (e.g., mean, dispersion, cross-terms, etc.). The method is illustrated for the superposition of power-laws, free-free spectra, gray-body and modified blackbody spectra, but can be applied to more complicated fundamental spectral energy distributions. Here, we focus on intensity signals but the method can be extended to the case of polarized emission. The averaging process automatically produces scale-dependent spectral shapes and the moment method can be used to propagate the required information across scales in power spectrum estimates. The approach is not limited to applications to CMB foregrounds but could also be useful for the modeling of X-ray emission in clusters of galaxies.Comment: 19 pages, 8 figures, accepted by MNRAS, minor revision