redMaPPer III: A Detailed Comparison of the Planck 2013 and SDSS DR8 RedMaPPer Cluster Catalogs

We compare the Planck Sunyaev-Zeldovich (SZ) cluster sample (PSZ1) to the Sloan Digital Sky Survey (SDSS) redMaPPer catalog, finding that all Planck clusters within the redMaPPer mask and within the redshift range probed by redMaPPer are contained in the redMaPPer cluster catalog. These common clusters define a tight scaling relation in the richness-SZ mass ($\lambda$--$M_{SZ}$) plane, with an intrinsic scatter in richness of $\sigma_{\lambda|M_{SZ}} = 0.266 \pm 0.017$. The corresponding intrinsic scatter in true cluster halo mass at fixed richness is $\approx 21\%$. The regularity of this scaling relation is used to identify failures in both the redMaPPer and Planck cluster catalogs. Of the 245 galaxy clusters in common, we identify three failures in redMaPPer and 36 failures in the PSZ1. Of these, at least 12 are due to clusters whose optical counterpart was correctly identified in the PSZ1, but where the quoted redshift for the optical counterpart in the external data base used in the PSZ1 was incorrect. The failure rates for redMaPPer and the PSZ1 are $1.2\%$ and $14.7\%$ respectively, or 9.8% in the PSZ1 after subtracting the external data base errors. We have further identified 5 PSZ1 sources that suffer from projection effects (multiple rich systems along the line-of-sight of the SZ detection) and 17 new high redshift ($z\gtrsim 0.6$) cluster candidates of varying degrees of confidence. Should all of the high-redshift cluster candidates identified here be confirmed, we will have tripled the number of high redshift Planck clusters in the SDSS region. Our results highlight the power of multi-wavelength observations to identify and characterize systematic errors in galaxy cluster data sets, and clearly establish photometric data both as a robust cluster finding method, and as an important part of defining clean galaxy cluster samples.Comment: comments welcom

Scattered Pilots and Virtual Carriers Based Frequency Offset Tracking for OFDM Systems: Algorithms, Identifiability, and Performance Analysis

In this paper, we propose a novel carrier frequency offset (CFO) tracking algorithm for orthogonal frequency division multiplexing (OFDM) systems by exploiting scattered pilot carriers and virtual carriers embedded in the existing OFDM standards. Assuming that the channel remains constant during two consecutive OFDM blocks and perfect timing, a CFO tracking algorithm is proposed using the limited number of pilot carriers in each OFDM block. Identifiability of this pilot based algorithm is fully discussed under the noise free environment, and a constellation rotation strategy is proposed to eliminate the c-ambiguity for arbitrary constellations. A weighted algorithm is then proposed by considering both scattered pilots and virtual carriers. We find that, the pilots increase the performance accuracy of the algorithm, while the virtual carriers reduce the chance of CFO outlier. Therefore, the proposed tracking algorithm is able to achieve full range CFO estimation, can be used before channel estimation, and could provide improved performance compared to existing algorithms. The asymptotic mean square error (MSE) of the proposed algorithm is derived and simulation results agree with the theoretical analysis

A Public, K-Selected, Optical-to-Near-Infrared Catalog of the Extended Chandra Deep Field South (ECDFS) from the MUltiwavelength Survey by Yale-Chile (MUSYC)

We present a new K-selected, optical-to-near-infrared photometric catalog of the Extended Chandra Deep Field South (ECDFS), making it publicly available to the astronomical community. The dataset is founded on publicly available imaging, supplemented by original zJK imaging data obtained as part of the MUltiwavelength Survey by Yale-Chile (MUSYC). The final photometric catalog consists of photometry derived from nine band U-K imaging covering the full 0.5x0.5 sq. deg. of the ECDFS, plus H band data for approximately 80% of the field. The 5sigma flux limit for point-sources is K = 22.0 (AB). This is also the nominal completeness and reliability limit of the catalog: the empirical completeness for 21.75 < K < 22.00 is 85+%. We have verified the quality of the catalog through both internal consistency checks, and comparisons to other existing and publicly available catalogs. As well as the photometric catalog, we also present catalogs of photometric redshifts and restframe photometry derived from the ten band photometry. We have collected robust spectroscopic redshift determinations from published sources for 1966 galaxies in the catalog. Based on these sources, we have achieved a (1sigma) photometric redshift accuracy of Dz/(1+z) = 0.036, with an outlier fraction of 7.8%. Most of these outliers are X-ray sources. Finally, we describe and release a utility for interpolating restframe photometry from observed SEDs, dubbed InterRest. Particularly in concert with the wealth of already publicly available data in the ECDFS, this new MUSYC catalog provides an excellent resource for studying the changing properties of the massive galaxy population at z < 2. (Abridged)Comment: Re-submitted to ApJSS after a first referee report. 27 pages, 17 figures. MUSYC data is freely available from http://astro.yale.edu/MUSYC . Links to phot-z and restframe photometry catalogs, as well as to InterRest access and documentation, including a full walkthrough, can be found at http://www.strw.leidenuniv.nl/~ent

Teaching old sensors New tricks: archetypes of intelligence

In this paper a generic intelligent sensor software architecture is described which builds upon the basic requirements of related industry standards (IEEE 1451 and SEVA BS- 7986). It incorporates specific functionalities such as real-time fault detection, drift compensation, adaptation to environmental changes and autonomous reconfiguration. The modular based structure of the intelligent sensor architecture provides enhanced flexibility in regard to the choice of specific algorithmic realizations. In this context, the particular aspects of fault detection and drift estimation are discussed. A mixed indicative/corrective fault detection approach is proposed while it is demonstrated that reversible/irreversible state dependent drift can be estimated using generic algorithms such as the EKF or on-line density estimators. Finally, a parsimonious density estimator is presented and validated through simulated and real data for use in an operating regime dependent fault detection framework

Proposal Flow: Semantic Correspondences from Object Proposals

Finding image correspondences remains a challenging problem in the presence of intra-class variations and large changes in scene layout. Semantic flow methods are designed to handle images depicting different instances of the same object or scene category. We introduce a novel approach to semantic flow, dubbed proposal flow, that establishes reliable correspondences using object proposals. Unlike prevailing semantic flow approaches that operate on pixels or regularly sampled local regions, proposal flow benefits from the characteristics of modern object proposals, that exhibit high repeatability at multiple scales, and can take advantage of both local and geometric consistency constraints among proposals. We also show that the corresponding sparse proposal flow can effectively be transformed into a conventional dense flow field. We introduce two new challenging datasets that can be used to evaluate both general semantic flow techniques and region-based approaches such as proposal flow. We use these benchmarks to compare different matching algorithms, object proposals, and region features within proposal flow, to the state of the art in semantic flow. This comparison, along with experiments on standard datasets, demonstrates that proposal flow significantly outperforms existing semantic flow methods in various settings.Comment: arXiv admin note: text overlap with arXiv:1511.0506