Because internal transfers can play a key role in radiocaesium persistence in trees, a reliable representation of radiocaesium recycling between tree organs in forest models is important for ...long-term simulations after radioactive fallout in Chernobyl and Fukushima. We developed an upgraded 2.0 version of the initial TRIPS (“Transfer of Radionuclides In Perennial vegetation System”) model involving explicit differentiation between tree organs (i.e., foliage, branches, stemwood and bark). The quality of TRIPS 2.0 was evaluated by testing model outputs against independent datasets for pine stands in Belarus and Ukraine. Scenarios involving “hot particle” deposits in forest remained challenging, but in all other scenarios generally positive verification results for soil and tree compartments indicated that the TRIPS 2.0 model adequately combines the major relevant processes. Interestingly, the response of stemwood contamination to changes in radiocaesium availability in soil, as determined by soil conditions, was shown to be more sensitive than for other tree compartments. We recommend the conceptual tree discretization of TRIPS 2.0 for generic forest modeling for two reasons: 1) regardless of different soil conditions, there was concurrent good agreement between simulations and data for individual tree compartments (foliage, branches, stemwood and bark), and 2) the measurements necessary to estimate internal tree transfers are easily accessible to usual field monitoring in forest biogeochemistry (for details, see Goor, F. & Thiry, Y., 2004. Science of the total environment, 325(1–3), 163–180).
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•There is no agreement on modeling of internal radiocesium transfers in forest trees.•An explicit differentiation between tree organs was integrated in TRIPS 2.0 model.•Stemwood contamination was the most sensitive to changes in soil conditions.•Conceptual tree discretization in TRIPS 2.0 is recommended for generic modeling.
We present cosmological parameter constraints from a tomographic weak gravitational lensing analysis of ~450 deg super( 2) of imaging data from the Kilo Degree Survey (KiDS). For a flat ... cold dark ...matter (...CDM) cosmology with a prior on H sub( 0) that encompasses the most recent direct measurements, we find S sub( 8) ... = 0.745 plus or minus 0.039. This result is in good agreement with other low-redshift probes of large-scale structure, including recent cosmic shear results, along with pre-Planck cosmic microwave background constraints. A 2.3... tension in S sub( 8) and 'substantial discordance' in the full parameter space is found with respect to the Planck 2015 results. We use shear measurements for nearly 15 million galaxies, determined with a new improved 'self-calibrating' version of lensfit validated using an extensive suite of image simulations. Four-band ugri photometric redshifts are calibrated directly with deep spectroscopic surveys. The redshift calibration is confirmed using two independent techniques based on angular cross-correlations and the properties of the photometric redshift probability distributions. Our covariance matrix is determined using an analytical approach, verified numerically with large mock galaxy catalogues. We account for uncertainties in the modelling of intrinsic galaxy alignments and the impact of baryon feedback on the shape of the non-linear matter power spectrum, in addition to the small residual uncertainties in the shear and redshift calibration. The cosmology analysis was performed blind. Our high-level data products, including shear correlation functions, covariance matrices, redshift distributions, and Monte Carlo Markov chains are available at http://kids.strw.leidenuniv.nl. (ProQuest: ... denotes formulae/symbols omitted.)
ABSTRACT
We present a new sample of galaxy-scale strong gravitational lens candidates, selected from 904 deg2 of Data Release 4 of the Kilo-Degree Survey, i.e. the ‘Lenses in the Kilo-Degree Survey’ ...(LinKS) sample. We apply two convolutional neural networks (ConvNets) to ${\sim }88\,000$ colour–magnitude-selected luminous red galaxies yielding a list of 3500 strong lens candidates. This list is further downselected via human inspection. The resulting LinKS sample is composed of 1983 rank-ordered targets classified as ‘potential lens candidates’ by at least one inspector. Of these, a high-grade subsample of 89 targets is identified with potential strong lenses by all inspectors. Additionally, we present a collection of another 200 strong lens candidates discovered serendipitously from various previous ConvNet runs. A straightforward application of our procedure to future Euclid or Large Synoptic Survey Telescope data can select a sample of ∼3000 lens candidates with less than 10 per cent expected false positives and requiring minimal human intervention.
Context. The Kilo-Degree Survey (KiDS) is an ongoing optical wide-field imaging survey with the OmegaCAM camera at the VLT Survey Telescope, specifically designed for measuring weak gravitational ...lensing by galaxies and large-scale structure. When completed it will consist of 1350 square degrees imaged in four filters (ugri). Aims. Here we present the fourth public data release which more than doubles the area of sky covered by data release 3. We also include aperture-matched ZYJHKs photometry from our partner VIKING survey on the VISTA telescope in the photometry catalogue. We illustrate the data quality and describe the catalogue content. Methods. Two dedicated pipelines are used for the production of the optical data. The ASTRO-WISE information system is used for the production of co-added images in the four survey bands, while a separate reduction of the r-band images using the THELI pipeline is used to provide a source catalogue suitable for the core weak lensing science case. All data have been re-reduced for this data release using the latest versions of the pipelines. The VIKING photometry is obtained as forced photometry on the THELI sources, using a re-reduction of the VIKING data that starts from the VISTA pawprints. Modifications to the pipelines with respect to earlier releases are described in detail. The photometry is calibrated to the Gaia DR2 G band using stellar locus regression. Results. In this data release a total of 1006 square-degree survey tiles with stacked ugri images are made available, accompanied by weight maps, masks, and single-band source lists. We also provide a multi-band catalogue based on r-band detections, including homogenized photometry and photometric redshifts, for the whole dataset. Mean limiting magnitudes (5σ in a 2″ aperture) and the tile-to-tile rms scatter are 24.23 ± 0.12, 25.12 ± 0.14, 25.02 ± 0.13, 23.68 ± 0.27 in ugri, respectively, and the mean r-band seeing is 0.″70.
We present redshift distribution estimates of galaxies selected from the fourth data release of the Kilo-Degree Survey over an area of ∼1000 deg
2
(KiDS-1000). These redshift distributions represent ...one of the crucial ingredients for weak gravitational lensing measurements with the KiDS-1000 data. The primary estimate is based on deep spectroscopic reference catalogues that are re-weighted with the help of a self-organising map (SOM) to closely resemble the KiDS-1000 sources, split into five tomographic redshift bins in the photometric redshift range 0.1 <
z
B
≤ 1.2. Sources are selected such that they only occupy that volume of nine-dimensional magnitude-space that is also covered by the reference samples (‘gold’ selection). Residual biases in the mean redshifts determined from this calibration are estimated from mock catalogues to be ≲0.01 for all five bins with uncertainties of ∼0.01. This primary SOM estimate of the KiDS-1000 redshift distributions is complemented with an independent clustering redshift approach. After validation of the clustering-
z
on the same mock catalogues and a careful assessment of systematic errors, we find no significant bias of the SOM redshift distributions with respect to the clustering-
z
measurements. The SOM redshift distributions re-calibrated by the clustering-
z
represent an alternative calibration of the redshift distributions with only slightly larger uncertainties in the mean redshifts of ∼0.01 − 0.02 to be used in KiDS-1000 cosmological weak lensing analyses. As this includes the SOM uncertainty, clustering-
z
are shown to be fully competitive on KiDS-1000 data.
Abstract
We present 97 new high-quality strong lensing candidates found in the final ∼350 deg
2
that complete the full ∼1350 deg
2
area of the Kilo-Degree Survey (KiDS). Together with our previous ...findings, the final list of high-quality candidates from KiDS sums up to 268 systems. The new sample is assembled using a new convolutional neural network (CNN) classifier applied to
r
-band (best-seeing) and
g
,
r
, and
i
color-composited images separately. This optimizes the complementarity of the morphology and color information on the identification of strong lensing candidates. We apply the new classifiers to a sample of luminous red galaxies (LRGs) and a sample of bright galaxies (BGs) and select candidates that received a high probability to be a lens from the CNN (
P
CNN
). In particular, setting
P
CNN
> 0.8 for the LRGs, the one-band CNN predicts 1213 candidates, while the three-band classifier yields 1299 candidates, with only ∼30% overlap. For the BGs, in order to minimize the false positives, we adopt a more conservative threshold,
P
CNN
> 0.9, for both CNN classifiers. This results in 3740 newly selected objects. The candidates from the two samples are visually inspected by seven coauthors to finally select 97 “high-quality” lens candidates which received mean scores larger than 6 (on a scale from 0 to 10). We finally discuss the effect of the seeing on the accuracy of CNN classification and possible avenues to increase the efficiency of multiband classifiers, in preparation of next-generation surveys from ground and space.
We present a catalog of quasars with their corresponding redshifts derived from the photometric Kilo-Degree Survey (KiDS) Data Release 4. We achieved it by training machine learning (ML) models, ...using optical
u
g
ri
and near-infrared
Z
Y
J
H
K
s
bands, on objects known from Sloan Digital Sky Survey (SDSS) spectroscopy. We define inference subsets from the 45 million objects of the KiDS photometric data limited to 9-band detections, based on a feature space built from magnitudes and their combinations. We show that projections of the high-dimensional feature space on two dimensions can be successfully used, instead of the standard color-color plots, to investigate the photometric estimations, compare them with spectroscopic data, and efficiently support the process of building a catalog. The model selection and fine-tuning employs two subsets of objects: those randomly selected and the faintest ones, which allowed us to properly fit the bias versus variance trade-off. We tested three ML models: random forest (RF), XGBoost (XGB), and artificial neural network (ANN). We find that XGB is the most robust and straightforward model for classification, while ANN performs the best for combined classification and redshift. The ANN inference results are tested using number counts,
Gaia
parallaxes, and other quasar catalogs that are external to the training set. Based on these tests, we derived the minimum classification probability for quasar candidates which provides the best purity versus completeness trade-off:
p
(QSO
cand
) > 0.9 for
r
< 22 and
p
(QSO
cand
) > 0.98 for 22 <
r
< 23.5. We find 158 000 quasar candidates in the safe inference subset (
r
< 22) and an additional 185 000 candidates in the reliable extrapolation regime (22 <
r
< 23.5). Test-data purity equals 97% and completeness is 94%; the latter drops by 3% in the extrapolation to data fainter by one magnitude than the training set. The photometric redshifts were derived with ANN and modeled with Gaussian uncertainties. The test-data redshift error (mean and scatter) equals 0.009 ± 0.12 in the safe subset and −0.0004 ± 0.19 in the extrapolation, averaged over a redshift range of 0.14 <
z
< 3.63 (first and 99th percentiles). Our success of the extrapolation challenges the way that models are optimized and applied at the faint data end. The resulting catalog is ready for cosmology and active galactic nucleus (AGN) studies.
We present the methodology for a joint cosmological analysis of weak gravitational lensing from the fourth data release of the ESO Kilo-Degree Survey (KiDS-1000) and galaxy clustering from the ...partially overlapping Baryon Oscillation Spectroscopic Survey (BOSS) and the 2-degree Field Lensing Survey (2dFLenS). Cross-correlations between BOSS and 2dFLenS galaxy positions and source galaxy ellipticities have been incorporated into the analysis, necessitating the development of a hybrid model of non-linear scales that blends perturbative and non-perturbative approaches, and an assessment of signal contributions by astrophysical effects. All weak lensing signals were measured consistently via Fourier-space statistics that are insensitive to the survey mask and display low levels of mode mixing. The calibration of photometric redshift distributions and multiplicative gravitational shear bias has been updated, and a more complete tally of residual calibration uncertainties was propagated into the likelihood. A dedicated suite of more than 20 000 mocks was used to assess the performance of covariance models and to quantify the impact of survey geometry and spatial variations of survey depth on signals and their errors. The sampling distributions for the likelihood and the
χ
2
goodness-of-fit statistic have been validated, with proposed changes for calculating the effective number of degrees of freedom. The prior volume was explicitly mapped, and a more conservative, wide top-hat prior on the key structure growth parameter
S
8
=
σ
8
(Ω
m
/0.3)
1/2
was introduced. The prevalent custom of reporting
S
8
weak lensing constraints via point estimates derived from its marginal posterior is highlighted to be easily misinterpreted as yielding systematically low values of
S
8
, and an alternative estimator and associated credible interval are proposed. Known systematic effects pertaining to weak lensing modelling and inference are shown to bias
S
8
by no more than 0.1 standard deviations, with the caveat that no conclusive validation data exist for models of intrinsic galaxy alignments. Compared to the previous KiDS analyses,
S
8
constraints are expected to improve by 20% for weak lensing alone and by 29% for the joint analysis.
We present a tomographic weak lensing analysis of the Kilo Degree Survey Data Release 4 (KiDS-1000), using a new pseudo angular power spectrum estimator (pseudo-
C
ℓ
) under development for the ESA
...Euclid
mission. Over 21 million galaxies with shape information are divided into five tomographic redshift bins, ranging from 0.1 to 1.2 in photometric redshift. We measured pseudo-
C
ℓ
using eight bands in the multipole range 76 <
ℓ
< 1500 for auto- and cross-power spectra between the tomographic bins. A series of tests were carried out to check for systematic contamination from a variety of observational sources including stellar number density, variations in survey depth, and point spread function properties. While some marginal correlations with these systematic tracers were observed, there is no evidence of bias in the cosmological inference.
B
-mode power spectra are consistent with zero signal, with no significant residual contamination from
E
/
B
-mode leakage. We performed a Bayesian analysis of the pseudo-
C
ℓ
estimates by forward modelling the effects of the mask. Assuming a spatially flat ΛCDM cosmology, we constrained the structure growth parameter
S
8
=
σ
8
(Ω
m
/0.3)
1/2
= 0.754
−0.029
+0.027
. When combining cosmic shear from KiDS-1000 with baryon acoustic oscillation and redshift space distortion data from recent Sloan Digital Sky Survey (SDSS) measurements of luminous red galaxies, as well as the Lyman-
α
forest and its cross-correlation with quasars, we tightened these constraints to
S
8
= 0.771
−0.032
+0.006
. These results are in very good agreement with previous KiDS-1000 and SDSS analyses and confirm a ∼3
σ
tension with early-Universe constraints from cosmic microwave background experiments.
A new empirical method for in situ determination of the inventory of 137Cs in soil (ACs, kBq m−2) at grasslands and forests using a field-portable NaI(Tl) scintillation spectrometer-dosimeter was ...developed. The method is based on evaluation of the ambient dose equivalent build-up factor. The practical implementation of the new method with the spectrometer-dosimeter does not require a priori knowledge of the vertical distribution of 137Cs in soil. Moreover, the method allows assessing a value of the mean migration depth of 137Cs in soil (Z) in terms of g cm−2. The 95% confidence interval for the mean value of the conversion coefficients from the ambient dose equivalent build-up factor to ACs and to Z is less than 10%. The new method has been developed and verified using published data that where obtained at territories in Russia and Belarus heavily contaminated with 137Cs (ACs > 37 kBq m−2) due to the Chernobyl accident. Therefore, the survey of less contaminated areas requires additional validation of this method.
•A novel method for in situ determination of 137Cs inventory in soil was developed.•The method is based on using the ambient dose equivalent build-up factor.•The method can be applied for the in situ measurements in open field and in forest.•The method has been verified at heavily contaminated areas in Russia and Belarus.
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