scholarly journals Optimizing galaxy samples for clustering measurements in photometric surveys

2019 ◽  
Vol 491 (3) ◽  
pp. 3535-3552 ◽  
Author(s):  
Dimitrios Tanoglidis ◽  
Chihway Chang ◽  
Joshua Frieman
Keyword(s):  
Cold Dark Matter ◽  
Sample Selection ◽  
Gaussian Model ◽  
Small Subset ◽  
Data Sets ◽  
Trade Off ◽  
Cosmological Constraints ◽  
Dark Energy Survey ◽  
Galaxy Sample ◽  
Cross Correlations

ABSTRACT When analysing galaxy clustering in multiband imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision, which generally includes only a small subset of galaxies. In this paper, we systematically explore this trade-off. Our analysis is targeted towards the third-year data of the Dark Energy Survey (DES), but our methods hold generally for other data sets. Using a simple Gaussian model for the redshift uncertainties, we carry out a Fisher matrix forecast for cosmological constraints from angular clustering in the redshift range z = 0.2–0.95. We quantify the cosmological constraints using a figure of merit (FoM) that measures the combined constraints on Ωm and σ8 in the context of Λ cold dark matter (ΛCDM) cosmology. We find that the trade-off between sample size and photo-z precision is sensitive to (1) whether cross-correlations between redshift bins are included or not, and (2) the ratio of the redshift bin width δz to the photo-z precision σz. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when δz ∼ σz. We find that for the typical case of 5−10 redshift bins, optimal results are reached when we use larger, less precise photo-z samples, provided that we include cross-correlations. For samples with higher σz, the overlap between redshift bins is larger, leading to higher cross-correlation amplitudes. This leads to the self-calibration of the photo-z parameters and therefore tighter cosmological constraints. These results can be used to help guide galaxy sample selection for clustering analysis in ongoing and future photometric surveys.

scholarly journals The mass and galaxy distribution around SZ-selected clusters

2021 ◽  
Author(s):  
T Shin ◽  
B Jain ◽  
S Adhikari ◽  
E J Baxter ◽  
C Chang ◽  
...  
Keyword(s):  
Cold Dark Matter ◽  
Theoretical Models ◽  
Weak Lensing ◽  
Mass Selection ◽  
Atacama Cosmology Telescope ◽  
Cluster Mass ◽  
Dark Energy Survey ◽  
Radial Profiles ◽  
The Galaxy ◽  
Galaxy Sample

Abstract We present measurements of the radial profiles of the mass and galaxy number density around Sunyaev-Zel’dovich (SZ)-selected clusters using both weak lensing and galaxy counts. The clusters are selected from the Atacama Cosmology Telescope Data Release 5 and the galaxies from the Dark Energy Survey Year 3 dataset. With signal-to-noise of 62 (45) for galaxy (weak lensing) profiles over scales of about 0.2 − 20h−1 Mpc, these are the highest precision measurements for SZ-selected clusters to date. Because SZ selection closely approximates mass selection, these measurements enable several tests of theoretical models of the mass and light distribution around clusters. Our main findings are: 1. The splashback feature is detected at a consistent location in both the mass and galaxy profiles and its location is consistent with predictions of cold dark matter N-body simulations. 2. The full mass profile is also consistent with the simulations. 3. The shapes of the galaxy and lensing profiles are remarkably similar for our sample over the entire range of scales, from well inside the cluster halo to the quasilinear regime. We measure the dependence of the profile shapes on the galaxy sample, redshift and cluster mass. We extend the Diemer & Kravtsov model for the cluster profiles to the linear regime using perturbation theory and show that it provides a good match to the measured profiles. We also compare the measured profiles to predictions of the standard halo model and simulations that include hydrodynamics. Applications of these results to cluster mass estimation, cosmology and astrophysics are discussed.

scholarly journals Concordance cosmology?

2020 ◽  
Vol 499 (4) ◽  
pp. 4638-4645
Author(s):  
Youngsoo Park ◽  
Eduardo Rozo
Keyword(s):  
Cold Dark Matter ◽  
Hubble Constant ◽  
Big Bang ◽  
New Physics ◽  
Current Data ◽  
Data Sets ◽  
Late Time ◽  
Acoustic Oscillations ◽  
Dark Energy Survey ◽  
The Difference

ABSTRACT We propose a new intuitive metric for evaluating the tension between two experiments, and apply it to several data sets. While our metric is non-optimal, if evidence of tension is detected, this evidence is robust and easy to interpret. Assuming a flat Lambda cold dark matter (ΛCDM) cosmological model, we find that there is a modest 2.2σ tension between the Dark Energy Survey (DES) Year 1 results and the Planck measurements of the cosmic microwave background. This tension is driven by the difference between the amount of structure observed in the late-time Universe and that predicted from fitting the Planck data, and appears to be unrelated to the tension between Planck and local estimates of the Hubble rate. In particular, combining DES, baryon acoustic oscillations, big bang nucleosynthesis, and supernovae measurements recover a Hubble constant and sound horizon consistent with Planck, and in tension with local distance–ladder measurements. If the tension between these various data sets persists, it is likely that reconciling all current data will require breaking the flat ΛCDM model in at least two different ways: one involving new physics in the early Universe, and one involving new late-time Universe physics.

scholarly journals Trade-off Predictivity and Explainability for Machine-Learning Powered Predictive Toxicology: An in-Depth Investigation with Tox21 Data Sets

2021 ◽  
Vol 34 (2) ◽  
pp. 541-549 ◽  
Author(s):  
Leihong Wu ◽  
Ruili Huang ◽  
Igor V. Tetko ◽  
Zhonghua Xia ◽  
Joshua Xu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Sets ◽  
Predictive Toxicology ◽  
Trade Off

scholarly journals Producing a BOSS CMASS sample with DES imaging

2019 ◽  
Vol 489 (2) ◽  
pp. 2887-2906 ◽  
Author(s):  
S Lee ◽  
E M Huff ◽  
A J Ross ◽  
A Choi ◽  
C Hirata ◽  
...  
Keyword(s):  
Sloan Digital Sky Survey ◽  
Joint Analysis ◽  
Dark Energy Survey ◽  
Sky Survey ◽  
Angular Correlation Function ◽  
Galaxy Sample ◽  
Celestial Equator ◽  
The Difference ◽  
Galaxy Bias ◽  
Validation Tests

ABSTRACT We present a sample of galaxies with the Dark Energy Survey (DES) photometry that replicates the properties of the BOSS CMASS sample. The CMASS galaxy sample has been well characterized by the Sloan Digital Sky Survey (SDSS) collaboration and was used to obtain the most powerful redshift-space galaxy clustering measurements to date. A joint analysis of redshift-space distortions (such as those probed by CMASS from SDSS) and a galaxy–galaxy lensing measurement for an equivalent sample from DES can provide powerful cosmological constraints. Unfortunately, the DES and SDSS-BOSS footprints have only minimal overlap, primarily on the celestial equator near the SDSS Stripe 82 region. Using this overlap, we build a robust Bayesian model to select CMASS-like galaxies in the remainder of the DES footprint. The newly defined DES-CMASS (DMASS) sample consists of 117 293 effective galaxies covering $1244\,\deg ^2$. Through various validation tests, we show that the DMASS sample selected by this model matches well with the BOSS CMASS sample, specifically in the South Galactic cap (SGC) region that includes Stripe 82. Combining measurements of the angular correlation function and the clustering-z distribution of DMASS, we constrain the difference in mean galaxy bias and mean redshift between the BOSS CMASS and DMASS samples to be $\Delta b = 0.010^{+0.045}_{-0.052}$ and $\Delta z = \left(3.46^{+5.48}_{-5.55} \right) \times 10^{-3}$ for the SGC portion of CMASS, and $\Delta b = 0.044^{+0.044}_{-0.043}$ and $\Delta z= (3.51^{+4.93}_{-5.91}) \times 10^{-3}$ for the full CMASS sample. These values indicate that the mean bias of galaxies and mean redshift in the DMASS sample are consistent with both CMASS samples within 1σ.

scholarly journals ANALISIS KEPUTUSAN PENDANAAN TERHADAP STRUKTUR MODAL MELALUI TRADE OFF THEORY

2020 ◽  
Vol 8 (2) ◽  
pp. 143
Author(s):  
Nana Umdiana ◽  
Dyah Lupita Sari
Keyword(s):  
Real Estate ◽  
Stock Exchange ◽  
Sample Selection ◽  
Secondary Data ◽  
Annual Reports ◽  
Financial Reports ◽  
Trade Off ◽  
Return On Equity ◽  
Fixed Assets ◽  
Equity Ratio

This study aims to analyze funding decisions on capital structure through trade off theory in property and real estate companies listed on the Indonesia Stock Exchange for the period 2015-2018. Profitability is measured using the return on equity ratio, asset structure is measured by fixed assets ratio and funding decisions are measured by debt. to equity ratio. The population of this research is property and real estate companies listed on the Indonesia Stock Exchange for the period 2015-2018. The data analyzed is secondary data in financial reports or annual reports. The sample selection used purposive sampling method and the sample obtained in this study were 40 data from 10 companies. In this research, the analytical method used is descriptive statistics, classical assumption test, multiple regression analysis and statistical test. The results of the analysis in this study indicate that there is no effect of profitability on funding decisions, there is an effect of asset structure on funding decisions. This shows that the asset structure influences the company's decision making in funding.

scholarly journals Dark Energy Survey Year 1 Results: Cosmological constraints from cluster abundances and weak lensing

2020 ◽  
Vol 102 (2) ◽  
Author(s):  
T. M. C. Abbott ◽  
M. Aguena ◽  
A. Alarcon ◽  
S. Allam ◽  
S. Allen ◽  
...  
Keyword(s):  
Dark Energy ◽  
Weak Lensing ◽  
Cosmological Constraints ◽  
Dark Energy Survey ◽  
Energy Survey

scholarly journals Can assembly bias explain the lensing amplitude of the BOSS CMASS sample in a Planck cosmology?

2020 ◽  
Vol 493 (4) ◽  
pp. 5551-5564
Author(s):  
Sihan Yuan ◽  
Daniel J Eisenstein ◽  
Alexie Leauthaud
Keyword(s):  
Cold Dark Matter ◽  
Cosmological Parameters ◽  
Bias Parameter ◽  
Projected Clustering ◽  
The Galaxy ◽  
Satellite Velocity ◽  
Galaxy Sample ◽  
Best Fitting ◽  
Galaxy Assembly ◽  
Halo Occupation Distribution

ABSTRACT In this paper, we investigate whether galaxy assembly bias can reconcile the 20–40 ${{\ \rm per\ cent}}$ disagreement between the observed galaxy projected clustering signal and the galaxy–galaxy lensing signal in the Baryon Oscillation Spectroscopic Survey CMASS galaxy sample. We use the suite of abacuscosmos lambda cold dark matter simulations at Planck best-fitting cosmology and two flexible implementations of extended halo occupation distribution (HOD) models that incorporate galaxy assembly bias to build forward models and produce joint fits of the observed galaxy clustering signal and the galaxy–galaxy lensing signal. We find that our models using the standard HODs without any assembly bias generalizations continue to show a 20–40 ${{\ \rm per\ cent}}$ overprediction of the observed galaxy–galaxy lensing signal. We find that our implementations of galaxy assembly bias do not reconcile the two measurements at Planck best-fitting cosmology. In fact, despite incorporating galaxy assembly bias, the satellite distribution parameter, and the satellite velocity bias parameter into our extended HOD model, our fits still strongly suggest a $\sim \! 34{{\ \rm per\ cent}}$ discrepancy between the observed projected clustering and galaxy–galaxy lensing measurements. It remains to be seen whether a combination of other galaxy assembly bias models, alternative cosmological parameters, or baryonic effects can explain the amplitude difference between the two signals.

scholarly journals Dark Energy Survey Year 1 results: measurement of the baryon acoustic oscillation scale in the distribution of galaxies to redshift 1

2018 ◽  
Vol 483 (4) ◽  
pp. 4866-4883 ◽  
Author(s):  
T M C Abbott ◽  
F B Abdalla ◽  
A Alarcon ◽  
S Allam ◽  
F Andrade-Oliveira ◽  
...  
Keyword(s):  
Dark Energy ◽  
Cold Dark Matter ◽  
Angular Diameter ◽  
Acoustic Oscillations ◽  
Distance Measurements ◽  
Angular Diameter Distance ◽  
Dark Energy Survey ◽  
Trade Offs ◽  
Physical Scale ◽  
Energy Survey

ABSTRACT We present angular diameter distance measurements obtained by locating the baryon acoustic oscillations (BAO) scale in the distribution of galaxies selected from the first year of Dark Energy Survey data. We consider a sample of over 1.3 million galaxies distributed over a footprint of 1336 deg2 with 0.6 < $z$photo < 1 and a typical redshift uncertainty of 0.03(1 + $z$). This sample was selected, as fully described in a companion paper, using a colour/magnitude selection that optimizes trade-offs between number density and redshift uncertainty. We investigate the BAO signal in the projected clustering using three conventions, the angular separation, the comoving transverse separation, and spherical harmonics. Further, we compare results obtained from template-based and machine-learning photometric redshift determinations. We use 1800 simulations that approximate our sample in order to produce covariance matrices and allow us to validate our distance scale measurement methodology. We measure the angular diameter distance, DA, at the effective redshift of our sample divided by the true physical scale of the BAO feature, rd. We obtain close to a 4 per cent distance measurement of DA($z$eff = 0.81)/rd = 10.75 ± 0.43. These results are consistent with the flat Λ cold dark matter concordance cosmological model supported by numerous other recent experimental results.

scholarly journals Risk Surface: A Visualization of Data Sharing Risk for Enterprise Users

2019 ◽  
Vol 63 (1) ◽  
pp. 297-301
Author(s):  
Mark F. St. John ◽  
Woodrow Gustafson ◽  
April Martin ◽  
Ronald A. Moore ◽  
Christopher A. Korkos
Keyword(s):  
Data Sharing ◽  
Data Sets ◽  
Surface Design ◽  
Trade Off ◽  
Shared Data ◽  
Risks And Benefits ◽  
Trade Offs ◽  
Different Types ◽  
Risk Visualization ◽  
Visualization Of Data

Enterprises share a wide variety of data with different partners. Tracking the risks and benefits of this data sharing is important for avoiding unwarranted risks of data exploitation. Data sharing risk can be characterized as a combination of trust in data sharing partners to not exploit shared data and the sensitivity, or potential for harm, of the data. Data sharing benefits can be characterized as the value likely to accrue to the enterprise from sharing the data by making the enterprise’s objectives more likely to succeed. We developed a risk visualization concept called a risk surface to support users monitoring for high risks and poor risk-benefit trade-offs. The risk surface design was evaluated in a series of two focus groups conducted with human factors professionals. Across the two studies, the design was improved and ultimately rated as highly useful. A risk surface needs to 1) convey which data, as joined data sets, are shared with which partners, 2) convey the degree of risk due to sharing that data, 3) convey the benefits of the data sharing and the trade-off between risk and benefits, and 4) be easy to scan at scale, since enterprises are likely to share many different types of data with many different partners.

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