Strong detection of the CMB lensing and galaxy weak lensing cross-correlation from ACT-DR4, Planck Legacy, and KiDS-1000

We measured the cross-correlation between galaxy weak lensing data from the Kilo Degree Survey (KiDS-1000, DR4) and cosmic microwave background (CMB) lensing data from the Atacama Cosmology Telescope (ACT, DR4) and the Planck Legacy survey. We used two samples of source galaxies, selected with photometric redshifts, (0.1 < zB < 1.2) and (1.2 < zB < 2), which produce a combined detection significance of the CMB lensing and weak galaxy lensing cross-spectrum of 7.7σ. With the lower redshift galaxy sample, for which the cross-correlation was detected at a significance of 5.3σ, we present joint cosmological constraints on the matter density parameter, Ωm, and the matter fluctuation amplitude parameter, σ8, marginalising over three nuisance parameters that model our uncertainty in the redshift and shear calibration as well as the intrinsic alignment of galaxies. We find our measurement to be consistent with the best-fitting flat ΛCDM cosmological models from both Planck and KiDS-1000. We demonstrate the capacity of CMB weak lensing cross-correlations to set constraints on either the redshift or shear calibration by analysing a previously unused high-redshift KiDS galaxy sample (1.2 < zB < 2), with the cross-correlation detected at a significance of 7σ. This analysis provides an independent assessment for the accuracy of redshift measurements in a regime that is challenging to calibrate directly owing to known incompleteness in spectroscopic surveys

Data Validation Beyond Big Data

From KiDs to Euclid OU-Ext to Euclid data validation. For the OmegaCAM@VST datahandling we have build and operated the distributed information system Astro-WISE. Astro-WISE was successfully used for the processing of KiDS data and particularly its built in extreme data-lineage facilitated the quality control and re-processing of the data with improved calibrations and improved code. Many of the aspects of the Astro-WISE approach will be applied in the data centric information system being build for the data processing for the Euclid satellite. However, the large amounts of data from Euclid in combination with the required much higher accuracies and danger of plural hidden systematics and biases forces to anticipate a new era beyond the Big data hype: data validation. In popular terms discriminating facts and fakes. I will discuss some new steps towards advanced data validation, such as build in dynamical reference systems in the OU-Ext approach, the validation of and by machine learning, and applying extreme data lineage to trace the roots and dependencies of data products

Extinction in the Galaxy from surface brightnesses of ESO-LV galaxies: testing 'standard' extinction maps

The relative extinction in the Galaxy computed with our new method (Choloniewski and Valentijn 2003, CV) is compared with three patterns: Schlegel, Finkbeiner and Davis (1998, SFD), Burstein and Heiles (1978, BH) and the cosecans law. It is shown that extinction of SFD is more reliable then that of BH since it stronger correlates with our new extinction. The smallest correlation coeffcient have been obtained for the cosecans law. Linear regression analysis show that SFD overestimate the extinction by a factor of 1.4. Our results clearly indicate that there is non-zero extinction at the Galactic South pole and that the extinction near the Galactic equator ($|b|<40^o$) is significantly larger in the Southern hemisphere than in the Northern.Comment: 15 pages, 10 figures, submitted to Acta Astronomic

Query Driven Visualization

The request driven way of deriving data in Astro-WISE is extended to a query driven way of visualization. This allows scientists to focus on the science they want to perform, because all administration of their data is automated. This can be done over an abstraction layer that enhances control and flexibility for the scientist.Comment: 4 pages, Procedings ADASS XXI, ASP Conference Serie

The Astro-WISE approach to quality control for astronomical data

We present a novel approach to quality control during the processing of astronomical data. Quality control in the Astro-WISE Information System is integral to all aspects of data handing and provides transparent access to quality estimators for all stages of data reduction from the raw image to the final catalog. The implementation of quality control mechanisms relies on the core features in this Astro-WISE Environment (AWE): an object-oriented framework, full data lineage, and both forward and backward chaining. Quality control information can be accessed via the command-line awe-prompt and the web-based Quality-WISE service. The quality control system is described and qualified using archive data from the 8-CCD Wide Field Imager (WFI) instrument (http://www.eso.org/lasilla/instruments/wfi/) on the 2.2-m MPG/ESO telescope at La Silla and (pre-)survey data from the 32-CCD OmegaCAM instrument (http://www.astro-wise.org/~omegacam/) on the VST telescope at Paranal.Comment: Accepted for publication in topical issue of Experimental Astronomy on Astro-WISE information syste

Young stellar populations in early-type dwarf galaxies; occurrence, radial extent and scaling relations

To understand the stellar population content of dwarf early-type galaxies (dEs) and its environmental dependence, we compare the slopes and intrinsic scatter of color-magnitude relations (CMRs) for three nearby clusters, Fornax, Virgo and Coma. Additionally we present and compare internal color profiles of these galaxies to identify central blue regions with younger stars. We use the imaging of the HST/ACS Fornax cluster in the magnitude range of -18.7 <= M_g' <= -16.0, to derive magnitudes, colors and color profiles, which we compare with literature measurements. Based on analysis of the color profiles, we report a large number of dEs with young stellar populations in their center in all three clusters. While for Virgo and Coma the number of blue-cored dEs is found to be 85 +/- 2% and 53 +/- 3% respectively, for Fornax, we find that all galaxies have a blue core. We show that bluer cores reside in fainter dEs, similar to the trend seen in nucleated dEs. We find no correlation between the luminosity of the galaxy and the size of its blue core. Moreover, a comparison of the CMRs of the three clusters shows that the scatter in Virgo's CMR is considerably larger than in the Fornax and Coma clusters. Presenting adaptive smoothing we show that the galaxies on the blue side of the CMR often show evidence for dust extinction, which strengthens the interpretation that the bluer colors are due to young stellar populations. We also find that outliers on the red side of the CMR are more compact than expected for their luminosity. We find several of these red outliers in Virgo, often close to more massive galaxies. No red outlying compact early-types are found in Fornax and Coma in this magnitude range while we find three in the Virgo cluster. We suggest that the large number of outliers and larger scatter found for the Virgo cluster CMR is a result of Virgo's different assembly history.Comment: 24 pages, accepted for publication in Astronomy and Astrophysic

Structure-Tags Improve Text Classification for Scholarly Document Quality Prediction

Training recurrent neural networks on long texts, in particular scholarly documents, causes problems for learning. While hierarchical attention networks (HANs) are effective in solving these problems, they still lose important information about the structure of the text. To tackle these problems, we propose the use of HANs combined with structure-tags which mark the role of sentences in the document. Adding tags to sentences, marking them as corresponding to title, abstract or main body text, yields improvements over the state-of-the-art for scholarly document quality prediction. The proposed system is applied to the task of accept/reject prediction on the PeerRead dataset and compared against a recent BiLSTM-based model and joint textual+visual model as well as against plain HANs. Compared to plain HANs, accuracy increases on all three domains. On the computation and language domain our new model works best overall, and increases accuracy 4.7% over the best literature result. We also obtain improvements when introducing the tags for prediction of the number of citations for 88k scientific publications that we compiled from the Allen AI S2ORC dataset. For our HAN-system with structure-tags we reach 28.5% explained variance, an improvement of 1.8% over our reimplementation of the BiLSTM-based model as well as 1.0% improvement over plain HANs.Comment: This new version of the paper brings the paper up-to-date with the improved paper, published at the First Workshop on Scholarly Document Processing, at EMNLP 2020. .Additionally, minor corrections were made including addition of color to Figures 1,2. The changes in comparison to the first arXiv version are substantial, including various additional results, and substantial improvements to the tex

DenseLens -- Using DenseNet ensembles and information criteria for finding and rank-ordering strong gravitational lenses,

Convolutional neural networks (CNNs) are the state-of-the-art technique for identifying strong gravitational lenses. Although they are highly successful in recovering genuine lens systems with a high true-positive rate, the unbalanced nature of the data set (lens systems are rare), still leads to a high false positive rate. For these techniques to be successful in upcoming surveys (e.g. with Euclid) most emphasis should be set on reducing false positives, rather than on reducing false negatives. In this paper, we introduce densely connected neural networks (DenseNets) as the CNN architecture in a new pipeline-ensemble model containing an ensemble of classification CNNs and regression CNNs to classify and rank-order lenses, respectively. We show that DenseNets achieve comparable true positive rates but considerably lower false positive rates (when compared to residual networks; ResNets). Thus, we recommend DenseNets for future missions involving large data sets, such as Euclid, where low false positive rates play a key role in the automated follow-up and analysis of large numbers of strong gravitational lens candidates when human vetting is no longer feasibl