KiLeR combines shear ratios with kinematic intrinsic shapes to mitigate first-order lensing systematics and forecasts a 192% improvement in dark energy constraints from the Roman telescope.
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DESI DR2 BAO data exhibits 2.3 sigma tension with CMB in Lambda-CDM but prefers evolving dark energy (w0 > -1, wa < 0) at 3.1 sigma with CMB and 2.8-4.2 sigma when including supernovae.
First-year DESI BAO data are consistent with flat LambdaCDM and, when combined with CMB, show a 2.5-3.9 sigma preference for evolving dark energy (w0 > -1, wa < 0) that strengthens with certain supernova datasets.
Kinetic Sunyaev-Zel'dovich reconstruction from WISExSuperCOSMOS and unWISE galaxies with Planck data yields tight upper limits on bulk velocities consistent with LambdaCDM out to 2000 h^{-1} Mpc while showing tension with a quasar dipole interpretation.
Rotational averages of the angular correlation function isolate non-statistical isotropy components in the CMB sky as a real-space complement to BipoSH coefficients.
Bayesian GPR recovers the 21cm signal within 2σ credible intervals for most k-modes (0.06 to 1.0 h/Mpc) in SKA1-Low simulations that include realistic residual foregrounds and systematics.
Early dark energy resolves CMB-BAO tension and, combined with thawing quintessence, reduces overall cosmological tensions without phantom crossing.
Recent CMB datasets tighten 95% CL upper bounds on vector-mode amplitude r_v to 1.3e-4 (neutrino isocurvature), 6.8 (octupole), and 4.2 (sourced) at k=0.05 Mpc^-1, with no significant detection.
CMB data limits the s-wave annihilation cross section of thermal dark matter particles to ≲ 10^{-30} cm³/s scaled by PBH fraction and mass for PBHs heavier than ~10^{-10} solar masses.
BROOM is a Python package that applies ILC and GILC techniques for model-independent separation of CMB, SZ, and foreground signals in microwave data along with diagnostic and simulation utilities.
A 0.19 mag step in supernova absolute magnitude at 20 Mpc improves data fit and increases the Hubble constant by 2% while leaving matter density and dark energy parameters stable.
Extended analysis of DESI DR2 data confirms robust evidence for dynamical dark energy with phantom crossing preference, stable under parametric and non-parametric modeling.
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.
citing papers explorer
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Kinematic Lensing Ratio: Reviving Weak Lensing Cosmography as a Geometric Dark Energy Probe
KiLeR combines shear ratios with kinematic intrinsic shapes to mitigate first-order lensing systematics and forecasts a 192% improvement in dark energy constraints from the Roman telescope.
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DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints
DESI DR2 BAO data exhibits 2.3 sigma tension with CMB in Lambda-CDM but prefers evolving dark energy (w0 > -1, wa < 0) at 3.1 sigma with CMB and 2.8-4.2 sigma when including supernovae.
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DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations
First-year DESI BAO data are consistent with flat LambdaCDM and, when combined with CMB, show a 2.5-3.9 sigma preference for evolving dark energy (w0 > -1, wa < 0) that strengthens with certain supernova datasets.
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Measuring cosmic bulk flow with kinetic Sunyaev-Zel'dovich velocity reconstruction
Kinetic Sunyaev-Zel'dovich reconstruction from WISExSuperCOSMOS and unWISE galaxies with Planck data yields tight upper limits on bulk velocities consistent with LambdaCDM out to 2000 h^{-1} Mpc while showing tension with a quasar dipole interpretation.
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Capturing statistical isotropy violation with rotational averages
Rotational averages of the angular correlation function isolate non-statistical isotropy components in the CMB sky as a real-space complement to BipoSH coefficients.
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Mitigating residual foregrounds and systematic errors in SKA1-Low AA* EoR observations via Bayesian Gaussian Process Regression
Bayesian GPR recovers the 21cm signal within 2σ credible intervals for most k-modes (0.06 to 1.0 h/Mpc) in SKA1-Low simulations that include realistic residual foregrounds and systematics.
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Disentangling cosmic distance tensions with early and late dark energy
Early dark energy resolves CMB-BAO tension and, combined with thawing quintessence, reduces overall cosmological tensions without phantom crossing.
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The Status of Gravitational Vector Perturbations with Recent CMB Data
Recent CMB datasets tighten 95% CL upper bounds on vector-mode amplitude r_v to 1.3e-4 (neutrino isocurvature), 6.8 (octupole), and 4.2 (sourced) at k=0.05 Mpc^-1, with no significant detection.
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In-depth analysis of the clustering of dark matter particles around primordial black holes. Part III: CMB constraints
CMB data limits the s-wave annihilation cross section of thermal dark matter particles to ≲ 10^{-30} cm³/s scaled by PBH fraction and mass for PBHs heavier than ~10^{-10} solar masses.
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BROOM: a python package for model-independent analysis of microwave astronomical data
BROOM is a Python package that applies ILC and GILC techniques for model-independent separation of CMB, SZ, and foreground signals in microwave data along with diagnostic and simulation utilities.
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Impact of the SNe Ia Magnitude Transition at 20 Mpc on Cosmological Parameter Estimation
A 0.19 mag step in supernova absolute magnitude at 20 Mpc improves data fit and increases the Hubble constant by 2% while leaving matter density and dark energy parameters stable.
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Extended Dark Energy analysis using DESI DR2 BAO measurements
Extended analysis of DESI DR2 data confirms robust evidence for dynamical dark energy with phantom crossing preference, stable under parametric and non-parametric modeling.
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Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.