Fingerprinting dark energy

Dark energy perturbations are normally either neglected or else included in a purely numerical way, obscuring their dependence on underlying parameters like the equation of state or the sound speed. However, while many different explanations for the dark energy can have the same equation of state, they usually differ in their perturbations so that these provide a fingerprint for distinguishing between different models with the same equation of state. In this paper we derive simple yet accurate approximations that are able to characterize a specific class of models (encompassing most scalar-field models) which is often generically called "dark energy". We then use the approximate solutions to look at the impact of the dark energy perturbations on the dark matter power spectrum and on the integrated Sachs-Wolfe effect in the cosmic microwave background radiation.Comment: 11 pages, 5 figures, minor changes to match published versio

Use of Rearing Cover by Mearns Cottontail

Intensive research on the Mearns cottontail was conducted from March 26 to September 18, 1954, on an 80-acre tract of the Floyd Fleming farm in Decatur County, Iowa. The cover on the 80 acres was alfalfa for hay 13 acres, alfalfa in pasture 21 acres, grass in pasture 8 acres, corn 22 acres, fallow grassland 11 acres, and trees, shrubs and vines along fencelines and gullies and in a catalpa planting about 5 acres. The plants of the fallow grassland, fencelines and gullies were listed by Hubbard and Hendrickson (1952) in some detail

Standards of Capacity

In order to calibrate with precision condensers for use in radio frequency measurements, three standard condensers of coaxial cylindrical plates were made after the manner described by the former Lord Rayleigh. The three condensers were of capacities 25, 50, and 100 micro-micro-farads. By means of continuous wave radio frequency currents from an electron tube generator a variable air condenser with a vernier was calibrated by a step by step method. This was used as a secondary standard. The measurements were accurate to less than one-half micro-micro-farad, and the calibration was correct to considerably less than one per cent, for capacities greater than twenty micro-micro-farads. Measurements showed that isolated metal spheres and metal discs could not be readily used as standards, that is, their calculated and measured capacities were not in agreement because of unavoidable capacity effects. On the other hand, the capacities of small parallel plate variable condensers were found to be in close agreement with the values calculated from the dimensions of the plates and the distance apart of the plates. The plates were of brass 2.5 mm in thickness, the back surfaces being beveled until the edges were thin. The plates were circular, those of one condenser being 7 cms in diameter, of another 10 cms. The distance apart of the plates was varied by a slow screw adjustment

MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation

Heatmap representations have formed the basis of human pose estimation systems for many years, and their extension to 3D has been a fruitful line of recent research. This includes 2.5D volumetric heatmaps, whose X and Y axes correspond to image space and Z to metric depth around the subject. To obtain metric-scale predictions, 2.5D methods need a separate post-processing step to resolve scale ambiguity. Further, they cannot localize body joints outside the image boundaries, leading to incomplete estimates for truncated images. To address these limitations, we propose metric-scale truncation-robust (MeTRo) volumetric heatmaps, whose dimensions are all defined in metric 3D space, instead of being aligned with image space. This reinterpretation of heatmap dimensions allows us to directly estimate complete, metric-scale poses without test-time knowledge of distance or relying on anthropometric heuristics, such as bone lengths. To further demonstrate the utility our representation, we present a differentiable combination of our 3D metric-scale heatmaps with 2D image-space ones to estimate absolute 3D pose (our MeTRAbs architecture). We find that supervision via absolute pose loss is crucial for accurate non-root-relative localization. Using a ResNet-50 backbone without further learned layers, we obtain state-of-the-art results on Human3.6M, MPI-INF-3DHP and MuPoTS-3D. Our code will be made publicly available to facilitate further research.Comment: See project page at https://vision.rwth-aachen.de/metrabs . Accepted for publication in the IEEE Transactions on Biometrics, Behavior, and Identity Science (TBIOM), Special Issue "Selected Best Works From Automated Face and Gesture Recognition 2020". Extended version of FG paper arXiv:2003.0295

Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose Estimation

Heatmap representations have formed the basis of 2D human pose estimation systems for many years, but their generalizations for 3D pose have only recently been considered. This includes 2.5D volumetric heatmaps, whose X and Y axes correspond to image space and the Z axis to metric depth around the subject. To obtain metric-scale predictions, these methods must include a separate, explicit post-processing step to resolve scale ambiguity. Further, they cannot encode body joint positions outside of the image boundaries, leading to incomplete pose estimates in case of image truncation. We address these limitations by proposing metric-scale truncation-robust (MeTRo) volumetric heatmaps, whose dimensions are defined in metric 3D space near the subject, instead of being aligned with image space. We train a fully-convolutional network to estimate such heatmaps from monocular RGB in an end-to-end manner. This reinterpretation of the heatmap dimensions allows us to estimate complete metric-scale poses without test-time knowledge of the focal length or person distance and without relying on anthropometric heuristics in post-processing. Furthermore, as the image space is decoupled from the heatmap space, the network can learn to reason about joints beyond the image boundary. Using ResNet-50 without any additional learned layers, we obtain state-of-the-art results on the Human3.6M and MPI-INF-3DHP benchmarks. As our method is simple and fast, it can become a useful component for real-time top-down multi-person pose estimation systems. We make our code publicly available to facilitate further research (see https://vision.rwth-aachen.de/metro-pose3d).Comment: Accepted for publication at the 2020 IEEE Conference on Automatic Face and Gesture Recognition (FG

Faraday Rotation Spectroscopy of Quantum-Dot Quantum Wells

Time-resolved Faraday rotation studies of CdS/CdSe/CdS quantum-dot quantum wells have recently shown that the Faraday rotation angle exhibits several well-defined resonances as a function of probe energy close to the absorption edge. Here, we calculate the Faraday rotation angle from the eigenstates of the quantum-dot quantum well obtained with k.p theory. We show that the large number of narrow resonances with comparable spectral weight observed in experiment is not reproduced by the level scheme of a quantum-dot quantum well with perfect spherical symmetry. A simple model for broken spherical symmetry yields results in better qualitative agreement with experiment.Comment: 9 pages, 4 figure