Hawai`i Supernova Flows: Bulk Flow Measurements using SNe Ia in the Optical and NIR
Aaron Do, Kaisey S. Mandel, Benjamin J. Shappee, R. Brent Tully, John L. Tonry, David Rubin, David O. Jones, Mitchell Dixon, Thomas de Jaeger, Dan Scolnic, Erik R. Peterson, Christopher R. Burns
astro-ph.CO
Submitted: 2026-06-15
Comments: 20 pages, 7 figures. All code available at https://github.com/ado8/hsf_bulkflows
Code: https://github.com/ado8/hsf_bulkflows
License: http://creativecommons.org/licenses/by-sa/4.0/
The gist: The present day peculiar velocity-field was sourced by primordial density fluctuations and sculpted over the lifespan of the Universe.
Terminology
Abstract
The present day peculiar velocity-field was sourced by primordial density fluctuations and sculpted over the lifespan of the Universe. Cosmological models such as CDM make predictions for various statistical properties of peculiar velocities. Bulk flow, the average velocity within a given volume, has an expectation value of due to isotropy, and a variance directly tied to the Hubble constant, the growth-rate of structure, and the matter power spectrum. In this paper, we use the redshifts and optical and near-infrared distance estimates to Type Ia Supernovae (SNe Ia) within subsets of the Hawai`i Supernova Flows dataset to infer the bulk flow within z 0.1. The inferred speeds vary between 100 to 400 km/s but are all consistent with the predictions of CDM. As a secondary focus, we discuss the systematic uncertainty introduced by the discrete choice of methodology using two bulk flow estimators, two types of SN Ia distance estimators, and data covering two distinct regimes in wavelength space.
Sources
- Accounting for Selection Effects in Supernova Cosmology with Simulation-Based Inference and Hierarchical Bayesian Modelling
- FlowSN: Neural Simulation-Based Inference under Realistic Selection Effects applied to Supernova Cosmology
- The subtle statistics of the distance ladder: On the distance prior and selection effects
- Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro
- SALT3-NIR: Taking the Open-Source Type Ia Supernova Model to Longer Wavelengths for Next-Generation Cosmological Measurements
- Union Through UNITY: Cosmology with 2,000 SNe Using a Unified Bayesian Framework
- Banana Split: Improved Cosmological Constraints with Two Light-Curve-Shape and Color Populations Using Union3.1+UNITY1.8
- The Artificial Intelligence Disclosure (AID) Framework: An Introduction
Related papers
- Angular clustering and bias of photometric quasars in the Kilo-Degree Survey Data Release 4
- A Novel kinetic Sunyaev-Zel'dovich Estimator for Electron-Electron Correlations
- Magnetic fields at the dawn of structure formation I. The CARLA J1510+5958 proto-cluster
- Dark Energy Survey Year 6 Results: Weak Lensing and Galaxy Clustering Cosmological Analysis Framework
- Exploring the Impact of Systematic Bias in Type Ia Supernova Cosmology Across Diverse Dark Energy Parametrizations
- Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation