🔭 astrophysics

Detection of supernova magnitude fluctuations induced by large-scale structure

This study detects a cross-correlation between large-scale structure and Type Ia supernova magnitude fluctuations at low redshifts, confirming that these fluctuations are induced by peculiar velocities and yielding a growth rate of structure measurement ( $f \sigma_8 = 0.384^{+0.094}_{-0.157}$ ) consistent with the Planck $\Lambda$ CDM model.

Original authors: A. Nguyen, C. Blake, R. J. Turner, V. Aronica, J. Bautista, J. Aguilar, S. Ahlen, S. BenZvi, D. Bianchi, D. Brooks, A. Carr, T. Claybaugh, A. Cuceu, A. de la Macorra, B. Dey, P. Doel, K. Douglass, S.

Published 2026-05-06

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: A. Nguyen, C. Blake, R. J. Turner, V. Aronica, J. Bautista, J. Aguilar, S. Ahlen, S. BenZvi, D. Bianchi, D. Brooks, A. Carr, T. Claybaugh, A. Cuceu, A. de la Macorra, B. Dey, P. Doel, K. Douglass, S. Ferraro, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho, G. Gutierrez, J. Guy, K. Honscheid, C. Howlett, D. Huterer, M. Ishak, R. Joyce, R. Kehoe, A. G. Kim, A. Kremin, O. Lahav, M. Landriau, L. Le Guillou, A. Leauthaud, M. E. Levi, M. Manera, P. Martini, A. Meisner, R. Miquel, E. Mueller, S. Nadathur, N. Palanque-Delabrouille, W. J. Percival, C. Poppett, F. Prada, F. Qin, A. J. Ross, C. Ross, G. Rossi, E. Sanchez, D. Schlegel, M. Schubnell, D. Sprayberry, G. Tarlé, B. A. Weaver, P. Zarrouk, R. Zhou, H. Zou

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Big Picture: Ripples in a Cosmic Pond

Imagine the Universe as a giant, calm pond. Usually, we think of the water (space) expanding smoothly, like a balloon inflating. But in reality, the water isn't perfectly still. It has currents and ripples caused by heavy rocks (galaxies and dark matter) sitting in it.

When a galaxy moves because of these currents, it's called a peculiar velocity. It's not just moving away because the pond is expanding; it's being pushed or pulled by the gravity of its neighbors.

This paper is about measuring those currents. The authors used two different tools to do this:

Supernovae: Exploding stars that act like "standard candles" (they all have the same true brightness).
Galaxies: The massive clusters of stars that create the gravity currents.

The Problem: The "Flickering" Light

Usually, astronomers use supernovae to measure how far away things are. They look at how bright a supernova appears. If it looks dim, it's far away.

However, there is a glitch. Sometimes a supernova looks slightly brighter or dimmer than it should be, even after accounting for distance. The paper argues that this "flickering" isn't random noise. It's actually caused by the supernova's host galaxy moving toward or away from us due to the gravitational pull of the large-scale structure of the Universe.

The Analogy: Imagine you are watching a lighthouse from a boat. If the lighthouse is on a steady dock, its brightness tells you exactly how far away it is. But if the lighthouse is on a boat bobbing up and down in a current, its apparent brightness changes slightly. The authors are trying to measure the "bobbing" (the velocity) to understand the strength of the "current" (the growth of cosmic structure).

The Tools: A New Map and a New Telescope

To measure this, the team needed two things:

A Map of the Currents: They used data from the DESI (Dark Energy Spectroscopic Instrument) survey. Think of this as a high-resolution map showing the positions of over 500,000 nearby galaxies.
The "Bobbing" Lights: They used the Pantheon+ catalog, which contains data on 510 nearby supernovae.

They looked at the area where these two datasets overlap (relatively close to Earth, in cosmic terms) to see if the brightness of the supernovae was correlated with the density of the galaxies around them.

The Experiment: Testing the Theory

The authors didn't just look at the real data; they built a massive simulation (a "virtual universe" inside a computer) to make sure their math was right.

The Simulation: They created 675 different virtual universes using a supercomputer. In these worlds, they placed galaxies and supernovae exactly as they appear in the real world, including all the messy details like survey limitations and measurement errors.
The Test: They ran their analysis on these fake universes. Since they knew the "true" answer in the simulation, they could check if their method correctly recovered the growth rate of the universe.
The Result: The method worked perfectly. It successfully found the "true" growth rate in the fake universes, proving the math holds up even with real-world messiness.

The Findings: A "Yes, But..."

When they applied this method to the real data (DESI galaxies + Pantheon+ supernovae), they found a signal.

The Detection: They successfully detected a correlation between the galaxies and the supernova brightness fluctuations. This confirms that the "flickering" is indeed caused by the gravitational pull of the large-scale structure (the peculiar velocities).
The Measurement: They calculated a specific number called $f\sigma_8$ , which represents how fast cosmic structures are growing. Their result was 0.384.
The Comparison: This number matches the predictions of the standard "Big Bang" model (called $\Lambda$ CDM) very well. It also matches other recent measurements made by the DESI team using different methods.

The Limitations and Future

The authors are careful to note that while they found a signal, the "noise" (uncertainty) is still quite high. It's like hearing a whisper in a noisy room; you can tell someone is speaking, but you can't hear every word clearly yet.

Current Status: The measurement is consistent with our current understanding of the Universe, but the error bars are too wide to prove if the Universe is behaving exactly as the standard model predicts or if there are slight deviations.
The Future: The paper forecasts that as new telescopes (like the Rubin Observatory) find thousands of more supernovae, the "noise" will drop. They predict that future surveys could improve the precision of this measurement by a factor of 10.

Summary

In short, this paper is a proof-of-concept. It says:

Supernovae brightness fluctuations are caused by galaxy movements.
We can measure these movements by comparing supernovae to galaxy maps.
Our method works (proven by simulations).
Our first real measurement matches the standard model of the Universe.
With more data in the future, this could become a powerful new way to test how gravity and dark energy work.

Technical Summary: Detection of Supernova Magnitude Fluctuations Induced by Large-Scale Structure

Problem and Motivation
Type Ia supernovae (SNe Ia) serve as standardisable candles for measuring cosmic expansion. However, the scatter in their magnitude-redshift relation contains coherent fluctuations induced by the peculiar velocities (PVs) of their host galaxies. These velocities arise from gravitational instability acting on large-scale structure (LSS) overdensities. While PVs are a known source of noise in cosmological distance measurements, they also encode information about the growth rate of structure, $f\sigma_8$ . Previous constraints on $f\sigma_8$ using SNe Ia have been limited by small sample sizes and inhomogeneous sky coverage compared to other distance indicators like the Tully-Fisher relation or Fundamental Plane. This study aims to measure the correlation between SN Ia magnitude fluctuations and the LSS density field to constrain the growth rate of structure, testing the $\Lambda$ CDM model and potential modified gravity theories.

Methodology
The authors utilize a cross-correlation approach combining two distinct datasets:

Large-Scale Structure Tracers: The Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) Data Release 1 (DR1), restricted to the redshift range $z < 0.1$ . This sample includes 578,576 galaxies.
Supernova Magnitudes: The Pantheon+ compilation, restricted to 510 unique SNe Ia at $z < 0.1$ .

The theoretical framework links magnitude fluctuations ( $\delta m$ ) to radial peculiar velocities ( $v_r$ ) via a redshift-dependent scaling factor $\alpha(z)$ . The authors employ three correlation statistics derived from Gorski (1988) and Turner et al. (2021):

$\psi_1$ and $\psi_2$ : Magnitude auto-correlation functions, sensitive to the parallel and perpendicular components of the velocity field relative to the line of sight.
$\psi_3$ : The galaxy-magnitude cross-correlation function, linking galaxy overdensity to SN magnitude fluctuations.
$\xi_{gg}$ : The galaxy auto-correlation function, used to constrain galaxy bias.

The analysis involves fitting these measured statistics to linear theory models parameterized by the normalised growth rate $f\sigma_8$ and the normalised galaxy bias $b\sigma_8$ . To validate the methodology and assess systematic uncertainties, the authors generated 675 mock catalogues using the AbacusSummit N-body simulation suite. These mocks incorporated realistic DESI BGS selection functions, galaxy bias models, and a "A+B" model for SN Ia rates dependent on stellar mass and star formation rate. Crucially, the authors tested the impact of SN selection effects (magnitude cuts) by applying various thresholds ( $m < 16.0, 16.5, 17.0$ ) to the simulations.

Key Results

Detection of Correlation: The study reports a detection of the cross-correlation signal between galaxy positions and SN Ia magnitude fluctuations. The difference in $\chi^2$ between the best-fit model and a zero-correlation model corresponds to a $\sim 2\sigma$ detection for individual statistics, accumulating significance across the combined dataset.
Growth Rate Constraint: Fitting the combined auto- and cross-correlation functions yields a measurement of the normalised growth rate at an effective redshift of $z_{eff} = 0.03$ :
$f\sigma_8 = 0.384^{+0.094}_{-0.157}$
The corresponding galaxy bias constraint is $b\sigma_8 = 0.998^{+0.035}_{-0.036}$ .
Consistency with $\Lambda$ CDM: The measured value of $f\sigma_8$ is consistent with the Planck $\Lambda$ CDM prediction ( $f\sigma_8 \approx 0.429$ ) and agrees with the DESI full-shape redshift-space distortion analysis of the BGS sample ( $f\sigma_8 = 0.38 \pm 0.09$ ).
Validation: The analysis pipeline was validated using the Abacus mocks, successfully recovering the fiducial input growth rate ( $f\sigma_8 = 0.428$ ) within statistical errors. The study demonstrates that SN selection effects introduce negligible bias (offsets $< 0.03$ ) relative to the statistical uncertainties of the current dataset.
Robustness: The results are shown to be insensitive to the choice of minimum separation scale in the fitting range ( $10-45 \, h^{-1}\text{Mpc}$ ), confirming the robustness of the linear model assumptions at these scales.

Significance and Claims
The paper claims the first detection of the correlation between SN magnitude fluctuations and the large-scale structure density field. While the current constraints on $f\sigma_8$ are not yet competitive with other methods due to large uncertainties, the study establishes the viability of using SN Ia magnitude correlations as a probe of peculiar velocities and structure growth. The authors emphasize that this methodology is distinct because it does not rely on redshift-space distortions in the galaxy correlation function but rather on the direct coupling between the velocity field and the SN magnitude.

The authors modestly conclude that while current samples yield modest detections, the methodology holds significant potential for future surveys. They forecast that next-generation transient surveys (e.g., ZTF, Rubin-LSST) combined with improved LSS tracers (e.g., DESI Peculiar Velocity survey) could improve $f\sigma_8$ constraints by an order of magnitude, necessitating future work on non-linear modelling and more precise treatment of selection effects.