To explore the high frequency radio spectra of galaxies in clusters, we used NRAO's Very Large Array at four frequencies, 4.9 − 43 GHz, to observe 139 galaxies in low redshift (z < 0.25), X-ray detected, clusters. The clusters were selected from the survey conducted by Ledlow & Owen, who provided redshifts and 1.4 GHz flux densities for all the radio sources. We find that more than half of the observed sources have steep microwave spectra as generally expected (α < −0.5, in the convention S ∝ ν α ). However, 60 − 70% of the unresolved or barely resolved sources have flat or inverted spectra. Most of these show an upward turn in flux at ν > 22 GHz, implying a higher flux than would be expected from an extrapolation of the lower frequency flux measurements. Our results quantify the need for careful source subtraction in increasingly sensitive measurements of the Sunyaev-Zel'dovich effect in clusters of galaxies (as currently being conducted by, for instance, the Atacama Cosmology Telescope and South Pole Telescope groups).

The observation of objects located in inaccessible regions is a recurring challenge in a wide variety of important applications. Recent work has shown that using rare and expensive optical setups, indirect diffuse light reflections can be used to reconstruct objects and two-dimensional (2D) patterns around a corner. Here we show that occluded objects can be tracked in real time using much simpler means, namely a standard 2D camera and a laser pointer. Our method fundamentally differs from previous solutions by approaching the problem in an analysis-by-synthesis sense. By repeatedly simulating light transport through the scene, we determine the set of object parameters that most closely fits the measured intensity distribution. We experimentally demonstrate that this approach is capable of following the translation of unknown objects, and translation and orientation of a known object, in real time.

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Transient images help to analyze light transport in scenes. Besides two spatial dimensions, they are resolved in time of flight. Cost-efficient approaches for their capture use amplitude modulated continuous wave lidar systems but typically take more than a minute of capture time. We propose new techniques for measurement and reconstruction of transient images, which drastically reduce this capture time. To this end, we pose the problem of reconstruction as a trigonometric moment problem. A vast body of mathematical literature provides powerful solutions to such problems. In particular, the maximum entropy spectral estimate and the Pisarenko estimate provide two closed-form solutions for reconstruction using continuous densities or sparse distributions, respectively. Both methods can separate m distinct returns using measurements at m modulation frequencies. For m = 3 our experiments with measured data confirm this. Our GPU-accelerated implementation can reconstruct more than 100000 frames of a transient image per second. Additionally, we propose modifications of the capture routine to achieve the required sinusoidal modulation without increasing the capture time. This allows us to capture up to 18.6 transient images per second, leading to transient video. An important byproduct is a method for removal of multipath interference in range imaging.

Time-of-flight sensing with single-photon sensitivity enables new approaches for the localization of objects outside a sensor's field of view by analyzing backscattered photons. In this Letter, the authors have studied the application of Geiger-mode avalanche photodiode arrays and eye-safe infrared lasers, and provide experimental data of the direct visualization of backscattering light in flight, and direct vision and indirect vision of targets in line-of-sight and non-line-of-sight configurations at shortwave infrared wavelengths.

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even when the trees are captured in front of complex backgrounds. Moreover, although our neural networks have been trained on synthetic data with data augmentation, we show that our pipeline performs well for real tree photographs. We evaluate the reconstructed geometries with several metrics, including leaf area index and maximum radial tree distances.CCS Concepts: • Computing methodologies → Generative and developmental approaches; Shape analysis; Computer vision problems.