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Astrophysics Data System
INSPIRE
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Association between optically identified galaxy clusters and the underlying dark matter halos.
Cao, Wu, et al. (2025)
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Dark Energy Survey Year 3 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Clustering.
DES Collaboration (2025)
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Dark Energy Survey: Modeling strategy for multiprobe cluster cosmology and validation for the Full Six-year Dataset.
To et al. (2025)
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Optical galaxy cluster mock catalogs with realistic projection effects: Validations with the SDSS clusters.
Lee, Wu, et al. (2024), PRD
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Forecasting the constraints on optical selection bias and projection effects of galaxy cluster lensing with multiwavelength data.
Zhou, Wu, et al. (2023), PRD Editors' Suggestion, Astrobites
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Dark Energy Survey Year 1 Clusters are Consistent with Planck.
Salcedo, Wu, et al. (2023), PRL
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Not empty enough: a local void cannot solve the H0 tension.
Huterer & Wu (2023), Hubble Constant Tension book chapter
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Buzzard to Cardinal: Improved Mock Catalogs for Large Galaxy Surveys.
To et al. (2023), ApJ
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LINNA: Likelihood Inference Neural Network Accelerator.
To et al. (2023), JCAP
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Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations.
Zeng et al. (2023), MNRAS
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Optical selection bias and projection effects in stacked galaxy cluster weak lensing.
Wu et al. (2022), MNRAS
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Incorporating galaxy cluster triaxiality in stacked cluster weak lensing analyses.
Zhang et al. (2022), MNRAS
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Exploring the contamination of the DES-Y1 cluster sample with SPT-SZ selected clusters.
Grandis et al. (2021), MNRAS
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Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations.
To et al. (2021), PRL
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Combination of cluster number counts and two-point correlations: validation on mock Dark Energy Survey.
To et al. (2021), MNRAS
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Cosmology with Galaxy Cluster Weak Lensing: Statistical Limits and Experimental Design.
Wu et al. (2021), ApJ
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Probing galaxy evolution in massive clusters using ACT and DES: splashback as a cosmic clock.
Adhikari et al. (2020), MNRAS
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Illuminating Dark Matter Halo Density Profiles Without Subhaloes.
Fielder et al. (2020), MNRAS
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Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing.
DES Collaboration (2020), MNRAS
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Cosmology with Stacked Cluster Weak Lensing and Cluster-Galaxy Cross-Correlations.
Salcedo et al. (2020), MNRAS
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Covariance matrices for galaxy cluster weak lensing: from virial regime to uncorrelated large-scale structure.
Wu et al. (2019), MNRAS
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Measurement of the splashback feature around SZ-selected Galaxy clusters with DES, SPT, and ACT.
Shin et al. (2019), MNRAS
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Substructure and merger detection in resolved NIKA Sunyaev-Zel'dovich images of distant clusters.
Adam et al. (2018), A&A
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RHAPSODY-G simulations - I. The cool cores, hot gas and stellar content of massive galaxy clusters.
Hahn et al. (2017), MNRAS
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RHAPSODY-G simulations - II. Baryonic growth and metal enrichment in massive galaxy clusters.
Martizzi et al. (2016), MNRAS
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RHAPSODY-G simulations: galaxy clusters as baryonic closed boxes and the covariance between hot gas and galaxies.
Wu et al. (2015), MNRAS
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Virial scaling of galaxies in clusters: bright to faint is cool to hot.
Wu et al. (2013), MNRAS
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Halo-to-halo Similarity and Scatter in the Velocity Distribution of Dark Matter.
Mao et al. (2013), ApJ
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Rhapsody. II. Subhalo Properties and the Impact of Tidal Stripping From a Statistical Sample of Cluster-size Halos.
Wu et al. (2013), ApJ
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Rhapsody. I. Structural Properties and Formation History from a Statistical Sample of Re-simulated Cluster-size Halos.
Wu et al. (2013), ApJ
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Gravitationally Consistent Halo Catalogs and Merger Trees for Precision Cosmology.
Behroozi et al. (2013), ApJ
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The ROCKSTAR Phase-space Temporal Halo Finder and the Velocity Offsets of Cluster Cores.
Behroozi, Wechsler and Wu (2013), ApJ
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Extrinsic Sources of Scatter in the Richness-mass Relation of Galaxy Clusters.
Rozo et al. (2011), ApJ
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Stacked Weak Lensing Mass Calibration: Estimators, Systematics, and Impact on Cosmological Parameter Constraints.
Rozo, Wu and Schmidt (2011), ApJ
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Annealing a Follow-up Program: Improvement of the Dark Energy Figure of Merit for Optical Galaxy Cluster Surveys.
Wu, Rozo and Wechsler (2010), ApJ
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The Impact of Theoretical Uncertainties in the Halo Mass Function and Halo Bias on Precision Cosmology.
Wu, Zentner and Wechsler (2010), ApJ
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The Effects of Halo Assembly Bias on Self-Calibration in Galaxy Cluster Surveys.
Wu, Rozo and Wechsler (2008), ApJ
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Cosmology with the Roman Space Telescope - synergies with the Rubin Observatory Legacy Survey of Space and Time.
Eifler et al. (2021), MNRAS
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Cosmology with the Roman Space Telescope - multiprobe strategies.
Eifler al. (2020), MNRAS, submitted
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Cosmic Dawn Intensity Mapper.
Cooray et al. (2019), Astro2020
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Partnering space and ground observatories - Synergies in cosmology from LSST and WFIRST.
Eifler et al. (2019), Astro2020
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Tomography of the Cosmic Dawn and Reionization Eras with Multiple Tracers.
Chang et al. (2019), Astro2020
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CDIM: Cosmic Dawn Intensity Mapper Final Report.
Cooray et al. (2019), arXiv
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The Wide Field Infrared Survey Telescope: 100 Hubbles for the 2020s.
Akeson et al. (2019), arXiv
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WFIRST: The Essential Cosmology Space Observatory for the Coming Decade.
Doré et al. (2019), Astro2020
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WFIRST Science Investigation Team "Cosmology with the High Latitude Survey" Annual Report 2017.
Doré et al. (2018), arXiv
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The Dark Energy Survey: Data Release 1.
Abbott et al. (2018), ApJS
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The Dark Energy Spectrometer (DESpec): A Multi-Fiber Spectroscopic Upgrade of the Dark Energy Camera and Survey for the Blanco Telescope.
Abdalla et al. (2012), arXiv