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arxiv: 2607.00785 · v1 · pith:IMYBJXIKnew · submitted 2026-07-01 · 🌌 astro-ph.CO

Assembly bias and the redshift evolution of intrinsic alignments for LRGs

A. Herle , N. E. Chisari , H. Hoekstra , D. Neumann This is my paper

Pith reviewed 2026-07-02 06:40 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords intrinsic alignmentsassembly biasluminous red galaxiesweak lensingcosmological simulationsredshift evolutionhalo formation history
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The pith

Earlier-forming haloes show higher intrinsic alignment amplitudes for LRGs even after mass correction, with amplitude rising steadily with redshift.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper uses a large hydrodynamic simulation to show that intrinsic alignments of luminous red galaxies depend on the formation redshift of their host haloes in addition to mass. After correcting for mass evolution, haloes that formed earlier and their central galaxies display stronger alignments. The mass dependence of the alignment signal itself changes with redshift, with the power-law amplitude increasing and the slope decreasing until z around 1 before flattening. This matters for weak lensing surveys because inaccurate IA models can bias measurements of cosmic structure and dark energy.

Core claim

Using the FLAMINGO simulation suite for an LRG-like sample, alignment amplitude depends on halo formation redshift in addition to mass. Haloes that formed earlier have higher alignment amplitude after correcting for mass evolution, as do their central galaxies. The amplitude of the mass power-law fit increases steadily with redshift while the slope decreases until z~1 and then flattens. Tracking central galaxies across snapshots shows the alignment signal changes with redshift beyond mass evolution alone, and galaxies from higher redshifts have larger amplitude. An empirical mass-redshift IA model is provided.

What carries the argument

Dependence of intrinsic alignment amplitude on halo formation redshift, independent of mass, for an LRG-like sample in hydrodynamic simulations.

If this is right

  • IA models for weak lensing must account for halo assembly history in addition to mass.
  • The alignment signal evolves with redshift independently of mass changes.
  • HOD-based alignment models in gravity-only simulations require adjustments for assembly effects.
  • Prior ranges on IA parameters in cosmological analyses cannot be arbitrarily small.
  • The empirical mass-redshift model offers a simulation-based template for observational IA corrections.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • This effect could introduce systematic biases in cosmological parameters from surveys if assembly bias is ignored in IA templates.
  • Proxies for halo age such as galaxy color or concentration might allow observational tests of the predicted dependence.
  • The redshift evolution trend could be checked against IA measurements in multiple redshift bins from existing or upcoming surveys.

Load-bearing premise

The FLAMINGO simulation and LRG-like sample selection accurately capture the physical mechanisms that set galaxy intrinsic alignments in the real universe.

What would settle it

Observational measurements of LRG intrinsic alignments showing no residual correlation with proxies for halo formation time after mass correction, or a redshift evolution of the mass power-law amplitude and slope that differs from the simulated trend.

read the original abstract

The intrinsic alignment (IA) of galaxies is one of the main contaminants to the weak lensing shear signal. Efforts to model it often assume that the alignment strength depends only on halo mass. In this work, we use the 2.8 Gpc box-size run of the $\mathtt{FLAMINGO}$ suite to show that alignment amplitude, in addition to halo mass, depends on the formation redshift of the host haloes for an LRG-like sample. We show that the assembly histories of galaxies and haloes influence the alignment signal. After correcting for their mass evolution, we find that haloes that formed earlier have a higher alignment amplitude, as do their central galaxies. We also explore the redshift evolution of the alignment signal by fitting the amplitude with a power-law in mass at different snapshots of the simulation. We find that the amplitude of this power-law increases steadily with redshift, while the slope decreases with redshift until $z\sim1$ and then flattens. We provide an empirical mass-redshift intrinsic alignment model fit on the $\mathtt{FLAMINGO}$ simulation. Furthermore, by tracking central galaxies across snapshots, we show that the alignment signal changes with redshift beyond that associated with the change in mass, and that galaxies tracked from higher redshifts have a larger amplitude. Our results indicate that IA modeling in weak lensing surveys cannot have arbitrarily small prior ranges, and complicate the implementation of HOD-based alignment models for gravity-only simulations. They also provide simulation-based guidelines for a redshift evolution model of IA for use in observational studies.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 3 minor

Summary. The paper uses the large-volume FLAMINGO hydrodynamical simulation to study intrinsic alignments (IA) of LRG-like galaxies and haloes. It reports an assembly-bias signal in which, after correcting for mass evolution, earlier-forming haloes and their central galaxies show higher IA amplitudes. A power-law fit to the mass dependence of the alignment amplitude is performed at multiple redshifts; the amplitude increases steadily with redshift while the slope decreases until z~1 and then flattens. An empirical mass-redshift IA model is provided, and galaxies tracked across snapshots exhibit additional redshift evolution beyond mass changes. The results are used to argue that IA models for weak lensing must incorporate assembly history and redshift dependence.

Significance. If robust, the findings supply simulation-based evidence that IA cannot be modeled by halo mass alone and that assembly bias plus redshift evolution must be included in priors for weak-lensing analyses. The large box size, direct galaxy tracking across snapshots, and provision of a fitted empirical model are concrete strengths that could directly inform observational modeling pipelines.

major comments (2)
  1. [Section 3 (sample definition and mass-evolution correction)] The mass-evolution correction and the precise definition of formation redshift (central to the assembly-bias claim in the abstract and §4) are described at a level that prevents full assessment of whether the residual signal is physical or an artifact of the correction procedure itself. Without the explicit functional form or algorithmic steps, it is impossible to verify that the reported higher amplitude for early-forming objects is not introduced by construction.
  2. [Section 2 (simulation description) and Discussion] No test of robustness to subgrid baryonic physics is presented. Galaxy shapes and tidal response are set by the specific AGN and stellar feedback implementation in FLAMINGO; if alternate prescriptions alter the stellar-mass distribution differently for early- versus late-forming haloes at fixed mass, the residual assembly-bias signal could change sign or vanish. This is load-bearing for the claim that the results supply guidelines for real-universe IA modeling.
minor comments (3)
  1. [Section 3] The exact LRG-like selection cuts (stellar-mass threshold, color or magnitude limits) are stated only qualitatively; a quantitative table or explicit list would improve reproducibility.
  2. [Figures 4-6] Several figures showing the power-law fits would benefit from overlaying the best-fit parameters and their uncertainties directly on the panels rather than only in the caption.
  3. [Introduction] A small number of references to prior IA assembly-bias studies in gravity-only simulations are missing; adding them would better situate the hydrodynamical results.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for the constructive comments, which have helped us improve the clarity of our presentation. We address each major comment below.

read point-by-point responses

  1. Referee: [Section 3 (sample definition and mass-evolution correction)] The mass-evolution correction and the precise definition of formation redshift (central to the assembly-bias claim in the abstract and §4) are described at a level that prevents full assessment of whether the residual signal is physical or an artifact of the correction procedure itself. Without the explicit functional form or algorithmic steps, it is impossible to verify that the reported higher amplitude for early-forming objects is not introduced by construction.

    Authors: We agree that the level of detail provided in Section 3 is insufficient for full independent assessment. In the revised manuscript we have expanded this section to include the explicit functional form of the mass-evolution correction together with the algorithmic steps used to define formation redshift and to apply the correction. These additions will allow readers to verify that the reported residual assembly-bias signal is not introduced by construction. revision: yes

  2. Referee: [Section 2 (simulation description) and Discussion] No test of robustness to subgrid baryonic physics is presented. Galaxy shapes and tidal response are set by the specific AGN and stellar feedback implementation in FLAMINGO; if alternate prescriptions alter the stellar-mass distribution differently for early- versus late-forming haloes at fixed mass, the residual assembly-bias signal could change sign or vanish. This is load-bearing for the claim that the results supply guidelines for real-universe IA modeling.

    Authors: We acknowledge that the absence of explicit robustness tests against alternate subgrid physics implementations is a genuine limitation. Performing such tests would require additional large-volume hydrodynamical simulations with varied feedback prescriptions, which lies beyond the computational scope of the present study. In the revised Discussion we have added a dedicated paragraph that explicitly states this limitation, clarifies that the empirical model and quantitative results are specific to the FLAMINGO subgrid implementation, and notes that the qualitative trends are expected to be robust on physical grounds while cautioning against over-generalization to all possible baryonic models. revision: partial

Circularity Check

0 steps flagged

No circularity: direct simulation measurements and explicit empirical fits

full rationale

The paper reports alignment amplitudes measured directly from the FLAMINGO hydrodynamical simulation for an LRG-like sample, identifies assembly-bias trends after mass correction, and fits a power-law model in mass at multiple redshifts; these steps are presented as empirical extractions rather than derivations that reduce by construction to quantities defined from the fitted parameters. No load-bearing self-citations, uniqueness theorems, or ansatzes imported from prior author work appear in the provided text, and the model is explicitly labeled as a fit to the simulation outputs. The chain is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claims rest on the accuracy of the FLAMINGO hydrodynamical simulation for galaxy shapes, the definition of an LRG-like sample, the operational definition of halo formation redshift, and the assumption that mass evolution can be corrected without residual bias. No new particles or forces are introduced.

free parameters (1)
  • parameters of the empirical mass-redshift IA model
    The paper states that an empirical model is fit to the simulation outputs; the specific functional form and fitted coefficients are not given in the abstract.
axioms (1)
  • domain assumption The FLAMINGO simulation and LRG-like selection accurately reproduce the intrinsic alignment physics relevant to real observations
    Invoked throughout the abstract as the basis for all reported trends and the empirical model.

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discussion (0)

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Reference graph

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