ABSTRACT
Cosmological parameter constraints from recent galaxy imaging surveys are reaching percent-level accuracy on the effective amplitude of the lensing signal, S8. The upcoming Legacy Survey of ...Space and Time (LSST) of the Vera C. Rubin Observatory will produce subpercent level measurements of cosmological parameters, providing a milestone test of the ΛCDM model. To supply guidance to the upcoming LSST analysis, it is important to understand thoroughly the results from different recent galaxy imaging surveys and assess their consistencies. In this work, we perform a unified catalogue-level reanalysis of three cosmic shear data sets: the first year data from the Dark Energy Survey (DES-Y1), the 1000 deg2 data set from the Kilo-Degree Survey (KiDS-1000), and the first year data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-Y1). We utilize a pipeline developed and rigorously tested by the LSST Dark Energy Science Collaboration to perform the reanalysis and assess the robustness of the results to analysis choices. We find the S8 constraint to be robust to two different small-scale modelling approaches, and varying choices of cosmological priors. Our unified analysis allows the consistency of the surveys to be rigorously tested, and we find the three surveys to be statistically consistent. Due to the partially overlapping footprint, we model the cross-covariance between KiDS-1000 and HSC-Y1 approximately when combining all three data sets, resulting in a 1.6–1.9 per cent constraint on S8 given different assumptions on the cross-covariance.
Cosmological parameter constraints from recent galaxy imaging surveys are reaching \(2-3\%\)-level accuracy. The upcoming Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will ...produce sub-percent level measurements of cosmological parameters, providing a milestone test of the \(\Lambda\)CDM model. To supply guidance to the upcoming LSST analysis, it is important to understand thoroughly the results from different recent galaxy imaging surveys and assess their consistencies. In this work we perform a unified catalog-level reanalysis of three cosmic shear datasets: the first year data from the Dark Energy Survey (DES-Y1), the 1,000 deg\(^{2}\) dataset from the Kilo-Degree Survey (KiDS-1000), and the first year data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-Y1). We utilize a pipeline developed and rigorously tested by the LSST Dark Energy Science Collaboration to perform the reanalysis and assess the robustness of the results to analysis choices. We find the \(S_{8}\) constraint to be robust to two different small-scale modeling approaches, and varying choices of cosmological priors. Our unified analysis allows the consistency of the surveys to be rigorously tested and we find the three surveys to be statistically consistent. Due to the partially overlapping footprint, we model the cross-covariance between KiDS-1000 and HSC-Y1 approximately when combining all three datasets, resulting in a \(1.6-1.9\%\) constraint on \(S_8\) given different assumptions on the cross-covariance.
Kaplan-Meier (KM) survival analyses based on complex patient categorization due to the burgeoning volumes of genomic, molecular and phenotypic data, are an increasingly important aspect of the ...biomedical researcher's toolkit. Commercial statistics and graphing packages for such analyses are functionally limited, whereas open-source tools have a high barrier-to-entry in terms of understanding of methodologies and computational expertise. We developed surviveR to address this unmet need for a survival analysis tool that can enable users with limited computational expertise to conduct routine but complex analyses. surviveR is a cloud-based Shiny application, that addresses our identified unmet need for an easy-to-use web-based tool that can plot and analyse survival based datasets. Integrated customization options allows a user with limited computational expertise to easily filter patients to enable custom cohort generation, automatically calculate log-rank test and Cox hazard ratios. Continuous datasets can be integrated, such as RNA or protein expression measurements which can be then used as categories for survival plotting. We further demonstrate the utility through exemplifying its application to a clinically relevant colorectal cancer patient dataset. surviveR is a cloud-based web application available at https://generatr.qub.ac.uk/app/surviveR , that can be used by non-experts users to perform complex custom survival analysis.
The LSST DESC DC2 Simulated Sky Survey Abolfathi, Bela; Alonso, David; Armstrong, Robert ...
The Astrophysical journal. Supplement series,
03/2021, Letnik:
253, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Abstract
We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time ...(LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large
N
-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin’s LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep area of approximately 300 deg
2
, as well as a deep drilling field of approximately 1 deg
2
. We simulate 5 yr of the planned 10 yr survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the data set to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic test bed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time domain cosmology.
This clinical trial compared surgical treatment with nonsurgical treatment of spondylolisthesis. Because of extensive patient crossover, the data were essentially nonrandomized, and as-treated ...analyses were performed. During 2 years of follow-up, patients treated surgically had greater improvement in pain and function than those treated nonsurgically. Patients treated nonsurgically showed moderate improvement over time.
This clinical trial compared surgical treatment with nonsurgical treatment of spondylolisthesis. During 2 years of follow-up, patients treated surgically had greater improvement in pain and function than those treated nonsurgically.
Degenerative spondylolisthesis is the slipping forward of one lumbar vertebra on another with an intact neural arch. It rarely occurs before the age of 50 years, and it disproportionately affects women, particularly black women, with a male:female ratio of approximately 1:6.
1
Slippage most commonly occurs at the L4–L5 level and rarely exceeds 30% of vertebral width.
1
Degenerative spondylolisthesis is generally asymptomatic, but it can be associated with symptomatic spinal stenosis.
1
Spinal stenosis, the most common reason for lumbar surgery in adults over the age of 65, is a narrowing of the spinal canal with encroachment on the neural structures by . . .
DESC DC2 Data Release Note LSST Dark Energy Science Collaboration; Abolfathi, Bela; Armstrong, Robert ...
arXiv (Cornell University),
06/2022
Paper, Journal Article
Odprti dostop
In preparation for cosmological analyses of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the LSST Dark Energy Science Collaboration (LSST DESC) has created a 300 deg\(^2\) ...simulated survey as part of an effort called Data Challenge 2 (DC2). The DC2 simulated sky survey, in six optical bands with observations following a reference LSST observing cadence, was processed with the LSST Science Pipelines (19.0.0). In this Note, we describe the public data release of the resulting object catalogs for the coadded images of five years of simulated observations along with associated truth catalogs. We include a brief description of the major features of the available data sets. To enable convenient access to the data products, we have developed a web portal connected to Globus data services. We describe how to access the data and provide example Jupyter Notebooks in Python to aid first interactions with the data. We welcome feedback and questions about the data release via a GitHub repository.
The LSST DESC DC2 Simulated Sky Survey LSST Dark Energy Science Collaboration; Abolfathi, Bela; Alonso, David ...
arXiv.org,
01/2021
Paper, Journal Article
Odprti dostop
We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the ...LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep (WFD) area of approximately 300 deg^2 as well as a deep drilling field (DDF) of approximately 1 deg^2. We simulate 5 years of the planned 10-year survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the dataset to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic testbed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time-domain cosmology.
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