Constraining Dynamical Dark Energy with Tomographic Galaxy and CMB Weak Lensing Through Higher-Order Statistics
Abstract
Tomographic weak gravitational lensing probes cosmic structure growth and geometry, making it a powerful probe of dynamical dark energy. We forecast information beyond the lensing power spectrum from non-Gaussian statistics of tomographic galaxy and CMB lensing convergence maps. Using the DDELenS suite of ray-traced N-body simulations, we build Gaussian process emulators for power spectra, Minkowski functionals, moments, peak and minima counts, and the wavelet scattering transform, varying Ωm, σ8, w0, and wa. We consider Rubin-like galaxy lensing and Simons Observatory-like CMB lensing over 15,000 deg2, and validate the analysis using a withheld fiducial cosmology, analytical power-spectrum forecasts, and Gaussian random-field null tests. As an initial step, we neglect baryonic effects and intrinsic alignments and approximate galaxy sources as discrete redshift planes. Using all source redshifts at zs={0.5, 1, 1.5, 2, 2.5, 1100}, combining all five non-Gaussian statistics reduces uncertainties on w0 and wa by 24.3% and 28.0%, and on Ωm and σ8 by 41.9% and 45.8%, relative to the power-spectrum-only baseline. The resulting w0 and wa uncertainties are 34.7% and 48.7% smaller than current DESI+DES constraints. If the DESI+DES best-fit values remain unchanged, this precision would increase the significance of the departure from ΛCDM from 3.0σ to 5.2σ, compared with 3.8σ from the power spectrum alone, assuming a Gaussian posterior and unchanged w0--wa correlation. Minkowski functionals and moments provide comparable constraining power, while combining them with the other summaries gives the strongest constraints. Broad galaxy-lensing redshift coverage is particularly important for dynamical dark energy, while CMB lensing provides complementary information.
Related
- DDELenS: Tomographic Weak Lensing Simulations with Dynamical Dark Energy
- Neural Posterior Estimation for Tomographic Weak Lensing Mass Mapping
- Weak-Lensing Shear Response for Photometric Redshift-Based Tomographic Binning
- Constraining the Inner Dark Matter Profiles of Strong-Lensing Galaxy Clusters
- Cosmological constraining power of the redshifts, heights, and angular clustering of weak gravitational lensing peaks
BibTeX
@misc{chen2026constraining,
title = {{Constraining Dynamical Dark Energy with Tomographic Galaxy and CMB Weak Lensing Through Higher-Order Statistics}},
author = {Shu-Fan Chen and J. Colin Hill and Zoltán Haiman},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.29937},
eprint = {2610.29937},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.29937},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Constraining Dynamical Dark Energy with Tomographic Galaxy and CMB Weak Lensing Through Higher-Order Statistics
AU - Shu-Fan Chen
AU - J. Colin Hill
AU - Zoltán Haiman
PY - 2026
DA - 2026/10/21
PB - arXiv
DO - 10.48550/arxiv.2610.29937
UR - https://arxiv.org/abs/2610.29937
AB - Tomographic weak gravitational lensing probes cosmic structure growth and geometry, making it a powerful probe of dynamical dark energy. We forecast information beyond the lensing power spectrum from non-Gaussian statistics of tomographic galaxy and CMB lensing convergence maps. Using the DDELenS suite of ray-traced N-body simulations, we build Gaussian process emulators for power spectra, Minkowski functionals, moments, peak and minima counts, and the wavelet scattering transform, varying Ω_m, σ_8, w_0, and w_a. We consider Rubin-like galaxy lensing and Simons Observatory-like CMB lensing over 15,000 deg^2, and validate the analysis using a withheld fiducial cosmology, analytical power-spectrum forecasts, and Gaussian random-field null tests. As an initial step, we neglect baryonic effects and intrinsic alignments and approximate galaxy sources as discrete redshift planes. Using all source redshifts at z_s={0.5, 1, 1.5, 2, 2.5, 1100}, combining all five non-Gaussian statistics reduces uncertainties on w_0 and w_a by 24.3% and 28.0%, and on Ω_m and σ_8 by 41.9% and 45.8%, relative to the power-spectrum-only baseline. The resulting w_0 and w_a uncertainties are 34.7% and 48.7% smaller than current DESI+DES constraints. If the DESI+DES best-fit values remain unchanged, this precision would increase the significance of the departure from ΛCDM from 3.0σ to 5.2σ, compared with 3.8σ from the power spectrum alone, assuming a Gaussian posterior and unchanged w_0--w_a correlation. Minkowski functionals and moments provide comparable constraining power, while combining them with the other summaries gives the strongest constraints. Broad galaxy-lensing redshift coverage is particularly important for dynamical dark energy, while CMB lensing provides complementary information.
ER -