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PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier

T0 review · 4 major / 5 minor · reviewed 2026-08-04 · deepseek-v4-flash

Pith's one-line read The stellar–halo mass relation turns upward at about 10^10 solar masses, implying that star formation is more efficient in small dark-matter haloes than previously thought.

desk verdict A careful, honest push of SHAM to M_h~1e8, but the claimed SHMR upturn is hinge on an unvalidated scatter prior — worth refereeing, not yet established. read the letter →

arxiv 2603.29331 v2 pith:D4ARYF26 submitted 2026-03-31 astro-ph.GA astro-ph.CO

classification astro-ph.GAastro-ph.CO
keywords galaxy–haloconnectionstellarmass–halomassrelationdwarfgalaxiessubhaloabundancematchingreionizationgalaxyclusteringminimumhalostar-formationefficiency
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper tries to establish that the relation between galaxy stellar mass and dark-matter halo mass does not keep falling toward low masses, but turns upward: below about 10^10 solar masses, smaller haloes become progressively more efficient at turning gas into stars. It models 349 measurements of the excess surface density of photometric galaxies around spectroscopic ones (the PAC method) from the DESI and DECaLS surveys, reaching stellar masses of 10^6.4 solar masses and halo masses of about 10^8 solar masses. If true, the result implies a second characteristic scale in galaxy formation and motivates a picture in which low-mass haloes formed stars efficiently before reionization and were then quenched into the red dwarf galaxies seen today. The same data place a 5-sigma upper bound of about 10^8.7 solar masses on the smallest dark-matter haloes that must exist.

What carries the argument

The central machinery is the combination of the PAC measurement and a SHMR-based subhalo abundance matching (SHAM) framework. PAC converts angular cross-correlations between a spectroscopic sample and a deep photometric sample into n_bar2 w_p(r_p), the excess surface density of photometric objects around spectroscopic tracers, which encodes both abundance and clustering information. SHAM then maps observed stellar masses to (sub)halo masses in two high-resolution N-body simulations via log-normal conditional distributions P(M_*|M_h), with constant or mass-dependent scatter. The argument is carried by tabulated halo–halo, halo–subhalo, and subhalo–subhalo projected correlation functions in fi

What would settle it

A direct measurement of the bias of 10^8–10^9 solar-mass haloes — for instance, from the clustering of a spectroscopically complete dwarf sample or from gravitational lensing magnification by dwarf hosts — would show whether the bias is actually flat. If it rises or falls by more than ~10% toward lower masses, the extrapolation that underlies the upturn and the mass bound is wrong.

Watch

Extended reading notes

Core claim

Using the PAC method — angular cross-correlations that recover the three-dimensional excess surface density n_bar2 w_p(r_p) of photometric galaxies around spectroscopic ones — the authors constrain the central galaxy–halo connection down to halo masses of order 10^8 h^-1 M_sun and stellar masses of 10^6.4 M_sun. They find that the mean stellar mass at fixed halo mass, and hence the star-formation efficiency, exhibits a clear upturn at M_h ~ 10^10 h^-1 M_sun: toward lower masses the SHMR becomes shallower and the stellar-to-halo mass ratio rises. This feature persists when the model is extended to allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction,

Load-bearing premise

The load-bearing assumption is that below the simulation resolution of about 10^8.7 solar masses, the halo abundance follows the extrapolated mass function and the halo bias stays roughly constant; if either deviates by more than about ten percent at 10^8 solar masses, the inferred upturn and the minimum-halo-mass bounds could shift substantially.

Editorial extensions

If this is right

  • If the upturn is real, star-formation efficiency in haloes below 10^10 M_sun is higher than standard SHMRs predict, and a second characteristic mass scale around 10^10 M_sun needs to be explained.
  • The dominance of central red dwarfs at the faint end supports a scenario of efficient pre-reionization star formation in small haloes followed by UV quenching; this predicts old, metal-poor red dwarfs and may explain the discrepancy between void-affected local surveys and average-universe stellar mass functions.
  • The 5-sigma upper bound on the minimum halo mass (10^8.71 h^-1 M_sun) directly constrains dark-matter models that suppress small-scale structure, such as warm dark matter.
  • The apparent ~15% internal tension between the derived galaxy stellar mass function and the model-independent PAC I result can be resolved either by a cosmology with lower matter density and sigma_8, or by an error in the assumed effective redshift; this points to a concrete test using BGS clustering.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • An implication the authors leave implicit: the upturn's shape is degenerate with the scatter in the SHMR at low masses, so confirming it will require measurements at smaller radii or lensing signals that are more sensitive to halo mass than abundance alone.
  • The minimum-halo-mass bound rests on the assumption of flat low-mass bias. A testable extension is to measure dwarf-galaxy clustering around isolated low-mass hosts; if the bias changes by more than ~10% below 10^9 M_sun, the inferred upturn and the lower bound would shift.
  • The pre-reionization hypothesis has a direct, observationally accessible signature: the central red dwarfs should be very metal-poor and ancient. Spectroscopy of those specific galaxies, which the authors say they are pursuing, would test the picture independently of the clustering model.
  • The cosmology test suggests a way to pin down the effective redshift: splitting the PAC measurements into finer redshift bins, or combining them with galaxy-galaxy lensing, would determine whether the low-Omega_m solution is real or an artefact of the z_eff assumption.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. This paper applies the PAC method to DESI Y1 BGS and DECaLS data, measuring 349 nbar2 w_p(r_p) cross-correlation measurements across stellar-mass bins down to M_* = 10^6.4 M_sun. The measurements are modeled with a tabulated SHAM framework built from the Jiutian N-body simulations, and the authors infer separate central and satellite SHMRs down to M_h ~ 10^8 h^-1 M_sun. The headline result is an upturn in the central SHMR below ~10^10 h^-1 M_sun, interpreted as rising star-formation efficiency in dwarf-scale haloes. The paper tests robustness to mass-dependent scatter, reionization-suppressed halo occupation, galaxy assembly bias, and alternative cosmologies, and derives 3-sigma and 5-sigma upper bounds on the minimum halo mass.

Significance. If the upturn is real, it would be a new empirical feature in the z=0 SHMR and would motivate a picture in which pre-reionization star formation is efficient in low-mass haloes, with subsequent UV quenching producing the red central dwarf population. The paper is methodologically ambitious: it makes the PAC measurements public, uses both non-parametric and parametric SHMR models, and explicitly tests several extensions. However, the central interpretation is currently entangled with the constant-scatter prior (Sec. 4.4), the sub-resolution HMF/bias extrapolation (Sec. 4.1 and Appendix A), and an internal nbar2-w_p tension (Sec. 4.6). These are load-bearing for the paper's main claims, so the result is not yet established at the level the abstract asserts, although the measurement itself is a valuable contribution.

major comments (4)
  1. [Sec. 4.4, Fig. 11] The central claim of a clear upturn below M_h ~ 10^10 h^-1 M_sun is not decoupled from the assumed constant scatter. In the varying-scatter run, the posterior is explicitly bimodal: one branch has smaller scatter, steeper low-mass slope, and larger M_2; the other has larger scatter, shallower slope, and smaller M_2. The text states that this degeneracy is difficult to break with only the nbar2 w_p measurements and that additional observables are required. The fiducial constant-scatter prior selects the first branch, which is precisely the branch exhibiting the pronounced upturn. Since the headline claim concerns the low-mass slope, please provide a quantitative assessment of the evidence for an upturn under the varying-scatter model — for example, the posterior probability of S_low >= 1, or a Bayes factor between the upturn and no-upturn branches — and/or a mock-recovery test showing tha
  2. [Sec. 4.1, Appendix A] The inference below M_vir ~ 10^8.7 h^-1 M_sun relies on an analytic HMF extrapolation and an assumed approximately constant halo bias. Appendix A validates the constancy of w_p within the resolved mass range, but a 10% normalization offset in the HMF or a 10% monotonic bias trend below the resolution limit would translate directly into the inferred SHMR near M_h ~ 10^8 h^-1 M_sun and into the minimum-halo-mass bounds in Sec. 5.4. Because the paper claims to constrain the SHMR down to ~10^8 h^-1 M_sun and presents 3-sigma/5-sigma lower-mass bounds, please add explicit sensitivity tests: vary the HMF normalization by +/-10% and allow a +/-10% monotonic bias variation over the extrapolated range, and report the resulting shifts in the central SHMR and in M_lim.
  3. [Secs. 4.6, 5 and Fig. 22] The manuscript states in Sec. 4.6 that within Planck18 cosmology no SHAM model can simultaneously fit both nbar2 and w_p, indicating a degree of internal tension; the derived GSMF is ~15% above DESI PAC I. The paper explores assembly bias and cosmology as possible sources, but does not show whether the low-mass SHMR upturn is robust under the cosmology/redshift that actually removes the tension. Because the SHMR is fitted to nbar2 w_p, a mismatch in the separate components could allow compensating errors that bias the fitted relation. Please quantify how the central SHMR and the upturn change under the WMAP9-at-z=0 model that resolves the tension, or otherwise demonstrate explicitly that the tension is confined to high stellar/halo masses and cannot affect the low-mass slope.
  4. [Sec. 5.4, Fig. 32] The minimum-halo-mass bounds are derived by fixing the SHMR to the MAP of the no-cutoff model and scanning M_lim, then interpreting Delta chi^2 = 9 and 25 as 3-sigma and 5-sigma for a single degree of freedom. Since imposing a cutoff is a nested modification of an otherwise refittable model, the SHMR should be re-optimized at each M_lim, or the paper should explicitly justify why fixing the SHMR gives a conservative upper bound. As written, the Delta chi^2 values are not profile-likelihood statements and the bounds may be overstated.
minor comments (5)
  1. [Abstract (first paragraph) vs Sec. 6/Fig. 32] The initial abstract gives minimum-halo-mass upper bounds of 10^8.80 h^-1 M_sun and 10^10.24 h^-1 M_sun, while the full-text abstract, Sec. 6, and Fig. 32 give 10^8.38 h^-1 M_sun and 10^8.71 h^-1 M_sun. Please reconcile this discrepancy; the latter set is the one supported by the figure.
  2. [Sec. 4.3] The text says the reduced chi^2 values lie in the range 0.5-2, but Appendix B lists many values below 0.5 (e.g., 0.08, 0.12). Please clarify whether the Appendix values are computed differently, e.g., with the full covariance rather than the PCA-truncated covariance, or correct the summary statement.
  3. [Sec. 4.4, Eq. (29)] The asymptotic low-mass slope is quoted as alpha - beta/(2 ln 10). Expanding f_low in Eq. (29) for x -> -infinity gives f_low ~ -beta x / ln 10, so the f_low contribution to the slope is -beta/ln 10, not -beta/(2 ln 10). Please check the derivation or clarify the definition of beta.
  4. [Fig. 6] The y-axis label appears garbled ('1 2 chi^2/N'). It should presumably read chi^2/N or similar. Please clean up the label.
  5. [Sec. 4.2] The specification '43 anchor points in M_* for M_vir in [10^7,10^15.4]' is ambiguous about whether the anchors are defined in linear or logarithmic stellar mass and whether they are in log M_* or log M_h. Please make the anchor-space convention explicit.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity; central SHMR is a fit with an acknowledged scatter–slope degeneracy, not an equation-level reduction.

full rationale

The derivation chain is self-contained: the 349 nbar2 w_p measurements are forward-modelled from an SHMR-based SHAM framework using tabulated correlation functions from the Jiutian simulations, and the SHMR is constrained by fitting, not predicted from an input. The upturn at M_h ~ 10^10 h^-1 M_sun is a property of the best-fit SHMR, and the paper explicitly acknowledges the degeneracy between the low-mass SHMR slope and the scatter (Sec. 4.4, Fig. 11), stating that it is difficult to break using only the nbar2 w_p measurements. This is a stated limitation, not a circular reduction. The HMF and bias extrapolations below the resolved mass limit (Sec. 4.1, Appendix A) are explicit assumptions with validation inside the resolved range; they are inputs to the forward model, not outputs derived from the claimed result. The minimum-halo-mass bounds are nested Delta-chi^2 comparisons with the SHMR held fixed, which is a standard model-comparison procedure rather than renaming a fitted parameter as a prediction. Self-citations (SDSS PAC IV, DESI PAC I, Xu 2025) provide the PAC method, measurements, and orphan treatment, but the present analysis uses new DESI/DECaLS data and independent model variants, so these citations are not load-bearing in the sense of forcing the central conclusion. No equation reduces to itself, and no fitted quantity is relabelled as a prediction. Overall the paper is not circular, though the robustness of the upturn is weaker than the abstract suggests because of the acknowledged scatter degeneracy.

Assumptions & free parameters 8 free parameters · 7 assumptions · 0 invented entities

The paper's central claim rests on standard ΛCDM cosmology, the SHAM ansatz, and an extrapolation of halo bias and abundance below the simulation resolution. No new particles or forces are introduced. The free parameters are the many SHMR anchor/parametric parameters and a few covariance-regularization hyperparameters. The key model assumptions are tested in the paper itself, but the low-mass bias extrapolation and the z_eff/cosmology choice remain the most fragile inputs.

free parameters (8)
  • Non-parametric central SHMR anchor points (43) = posterior distributions shown in figures, not tabulated
    Mean relation between M_* and M_vir at 43 anchor points; fitted to the 349 PAC measurements.
  • Non-parametric satellite SHMR anchor points (34) = posterior distributions shown in figures, not tabulated
    Mean relation between M_* and m_peak for subhaloes; fitted.
  • Scatter σ_c (fiducial) = 0.22^{+0.01}_{-0.02}
    Constant log-normal scatter of the central SHMR, fitted to data.
  • Scatter σ_s (fiducial) = 0.37^{+0.02}_{-0.03}
    Constant log-normal scatter of the satellite SHMR, fitted to data.
  • Parametric central SHMR parameters = e.g. log10(M2,c)=9.96^{+0.21}_{-0.32}; see Figure 7
    Parameters of the modified Behroozi et al. (2013) form (Eq. 29); fitted.
  • Parametric satellite SHMR parameters = see Figure 7
    Parameters of the Behroozi-like form for satellites; fitted.
  • Covariance shrinkage factor α = largest value giving a positive-definite covariance (not reported numerically)
    Hand-chosen to make the 1454-dimensional covariance invertible; affects the likelihood and parameter uncertainties.
  • PCA/SVD thresholds and rank = τ=0.97, τ_gh=0.9, k_max=8
    Hyperparameters chosen to balance information retention and numerical conditioning of the covariance.
assumptions (7)
  • domain assumption Flat ΛCDM with Planck18 parameters (Ω_m=0.3111, σ_8=0.8102, h=0.6766)
    Used for all distance conversions and as the fiducial simulation cosmology; variations around it are tested in Section 4.7.
  • domain assumption SHAM: one-to-one monotonic relation between stellar mass and (sub)halo mass with log-normal scatter (Eq. 25)
    The core model assumption; assembly bias is treated as a perturbation in Section 4.6.
  • domain assumption Halo bias depends only on halo mass for the tabulated correlation functions (no assembly bias in fiducial tables)
    Used to construct the w_p tables; assembly bias is tested separately and is not included in the fiducial model.
  • domain assumption Low-mass halo bias is approximately constant below M_vir=10^8.7 h^-1 M_sun, allowing extrapolation of w_p tables to 10^7 h^-1 M_sun
    Validated in Appendix A only down to the resolved range [10^8.7,10^9.9]; the extrapolation below 10^8.7 is an assumption.
  • domain assumption Jiang et al. (2008) merger timescale model for orphan subhalo treatment
    Needed to recover the subhalo abundance after numerical disruption; the model choice is tested in Xu (2025).
  • standard math Flat-sky approximation and Eq. (4) relating the angular cross-correlation to \bar n_2 w_p hold at percent level
    Validated in DESI PAC I at z~0.01–0.02 for scales up to ~10 h^-1 Mpc.
  • domain assumption Fiducial model assumes every (sub)halo hosts a galaxy (halo occupation fraction = 1)
    Relaxed in Section 4.5 with HOF models; the upturn persists but with larger uncertainties.

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Cite this review

Pith. "Pith review of PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier." pith.science (2026). https://pith.science/paper/D4ARYF26

@misc{pith2026260329331,
  author       = {Pith},
  title        = {Pith review of: PAC in DESI. II. Galaxy-halo connection into the $10^6\rm M_\odot$ frontier},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/D4ARYF26}},
  note         = {Machine review of arXiv:2603.29331}
}
abstract

Understanding dwarf galaxy formation is crucial for testing dark matter models and reionization physics. However, constructing stellar-mass complete spectroscopic samples at low masses is increasingly difficult, and the potential existence of a local void complicates studies in an average environment. The Photometric object Around Cosmic webs (PAC) method, which combines deep photometric and spectroscopic data to measure the excess surface density $\bar{n}_2w_{{\rm{p}}}(r_{\rm{p}})$ of photometric objects around spectroscopic tracers, offers a promising path forward. We model 349 $\bar{n}_2w_{{\rm{p}}}(r_{\rm{p}})$ measurements from DESI Y1 BGS and DECaLS, reaching $M_*=10^{6.4}\,{\rm M}_{\odot}$, using a stellar mass-halo mass relation (SHMR)-based subhalo abundance matching framework applied to two high-resolution $N$-body simulations from the Jiutian suite. The resulting SHMR is constrained down to $M_{\rm h}\simeq10^{8.0}\,h^{-1}{\rm M}_{\odot}$, revealing a clear upturn at $\sim10^{10.0}\,h^{-1}{\rm M}_{\odot}$ toward lower masses, indicating rising star-formation efficiency (SFE) in small haloes. This feature persists under extensions of the model that allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction, galaxy assembly bias, and alternative cosmologies. Combining with the results from Paper I, we find that central red galaxies dominate the low-mass regime. Our results motivate a hypothesis in which SFE is significantly higher than previously thought prior to reionization, enabling relatively massive galaxies to form in small haloes. These systems are subsequently quenched by the UV background, producing the central red dwarf galaxies observed. Finally, we obtain $3\sigma$ and $5\sigma$ upper mass bounds of $10^{8.80}\,h^{-1}{\rm M}_{\odot}$ and $10^{10.24}\,h^{-1}{\rm M}_{\odot}$ on the smallest haloes required to exist.

Figures

Figures reproduced from arXiv: 2603.29331 by the authors.

Figure 1
Figure 1. The 95% completeness stellar mass limits 𝑀c95 (𝑧) for DECaLS and BGS samples. The quantized appearance of the results arises from the compar￾ison of stellar mass functions in bins with a width of Δ log10 (𝑀∗/M⊙) = 0.2. and selection, but because their assumed distance is incorrect, their inferred stellar masses are wrong. However, these galaxies are not clustered with the spectroscopic object at 𝑟1 and thus only add… view at source ↗
Figure 2
Figure 2. Total signal-to-noise ratio of each 𝑛¯2𝑤p (𝑟p ) measurement in bins of 𝑀 spec ∗ and 𝑀 photo ∗ . 3.3 Covariance estimation, compression, and stabilization Because our 𝑛¯2𝑤p measurements extend to small 𝑟p and are affected by complex noise from foreground and background sources at each redshift, it is difficult to derive the covariance matrix analytically or semi-analytically. Generating a large number of high-resolut… view at source ↗
Figure 3
Figure 3. Normalized covariance matrices of 𝑛¯2𝑤p (𝑟p ) measurements for samples with 𝑀 photo ∗ and 𝑀 spec ∗ fixed at 1010.6 M⊙, with the other sample spanning 12 stellar mass bins in the range [109.4 , 1011.6 ] M⊙. Each small square represents the cross-covariance of 𝑛¯2𝑤p (𝑟p ) measurements between two stellar mass bins, each containing 10 radial bins. Stellar mass increases from top to bottom and from left to right. bin ar… view at source ↗
Figures from the paper (26 more)
Figure 4
Figure 4. Figure 4: Estimated covariance matrix of the normalized 𝑛¯2𝑤p (𝑟p ) data vector A˜ in the PCA-truncated space (total dimension 1454), obtained from intra-group PCA and a low-rank approximation of inter-group covariances via truncated SVD. Each rectangle represents the cross-cova…
Figure 5
Figure 5. Figure 5: Mean stellar–halo mass relations (top) and stellar-to-halo mass ratios (bottom) for central (blue) and satellite (orange) galaxies constrained by the fiducial models. Results from both the non-parametric and parametric models are shown. Dots with error bars and curves …
Figure 6
Figure 6. Figure 6: Reduced 𝜒 2 values of the fits to each 𝑛¯2𝑤p (𝑟p ) measurement from the fiducial model. Results for the non-parametric model (top) and the parametric model (bottom) are shown. The top and right marginal panels in each plot display the reduced 𝜒 2 values aggregated over…
Figure 7
Figure 7. Figure 7: Posterior distributions of the parameters for the parametric fiducial SHMR model based on Equation 29. The contours show the joint distributions for each parameter pair, with levels corresponding to the 39.3%, 86.5%, and 98.9% confidence intervals. The MAP estimates an…
Figure 8
Figure 8. Figure 8: Illustration of the contributions of 𝑓low, 𝑓mid, and 𝑓high to the fiducial parametric central SHMR. The curves are shown using the MAP parameter values. NumPyro package (Phan et al. 2019), an adaptive variant of HMC that automatically tunes the trajectory length and st…
Figure 9
Figure 9. Figure 9: GSMFs derived from the fiducial non-parametric SHAM model. Results for central galaxies, satellite galaxies, and the total population are shown. For comparison, the GSMFs of the total, red, and blue populations from DESI PAC I are also included. the relation becomes a …
Figure 11
Figure 11. Figure 11: Posterior distributions of key parameters that determine the central SHMR at the low-mass end (𝑀h < 𝑀2), including the low-mass slope 𝑆low = 𝛼−𝛽/(2 ln 10), the characteristic halo mass 𝑀2 and its corresponding mean stellar mass 𝑀∗ (𝑀2 ), and the stellar-mass scatter 𝜎…
Figure 10
Figure 10. Figure 10: Same as [PITH_FULL_IMAGE:figures/full_fig_p014_10.png]
Figure 13
Figure 13. Figure 13: GSMFs derived from the fiducial and varying-scatter non￾parametric models. For comparison, the total GSMF from DESI PAC I is also shown. To better illustrate the degeneracy at the low-mass end, we show in [PITH_FULL_IMAGE:figures/full_fig_p015_13.png]
Figure 17
Figure 17. Figure 17: GSMFs derived from the non-parametric SHAM models incor￾porating different HOF prescriptions. Results obtained with and without ac￾counting for assembly bias are shown. The fiducial non-parametric model and the GSMF from DESI PAC I are included for comparison. dominat…
Figure 16
Figure 16. Figure 16: Total Δ𝜒 2 for the 𝑛¯2𝑤p (𝑟p ) measurements in each 𝑀 photo ∗ bin, comparing various HOF models to the non-parametric fiducial model. The resulting HOFs at 𝑧 = 0 are shown in [PITH_FULL_IMAGE:figures/full_fig_p016_16.png]
Figure 18
Figure 18. Figure 18: Comparison of 𝑛¯2𝑤p (𝑟p ) predictions for 𝑀 photo ∗ = 1010.6 ℎ −2 70 M⊙ and various 𝑀 spec ∗ bins, generated from mocks with different cosmologies and galaxy assembly bias assumptions. Shown are predictions from Planck18 cosmology with no assembly bias (𝜌 = 0) and wit…
Figure 19
Figure 19. Figure 19: Same as [PITH_FULL_IMAGE:figures/full_fig_p017_19.png]
Figure 20
Figure 20. Figure 20: Tests of how galaxy assembly bias and assumed cosmology affect SHMR inference using mocks. (a) MAP SHMRs (green) obtained by fitting Jiutian-1G mocks with maximal assembly bias (𝜌 = 1) using non-parametric models without assembly bias (𝜌 = 0). (b) MAP SHMRs (green) ob…
Figure 21
Figure 21. Figure 21: Examples of fits to 𝑛¯2𝑤p (𝑟p ) measurements from the Jiutian-1G mock with maximal assembly bias (𝜌 = 1; points with error bars), using a 𝜌 = 0 SHAM model (solid lines), shown for several stellar-mass bins. For comparison, 𝑛¯2𝑤p (𝑟p ) measurements from the 𝜌 = 0 mocks…
Figure 22
Figure 22. Figure 22: Tests of how assembly bias and the assumed cosmology affect the derived GSMFs. (a) Comparison of GSMFs from the MAP fiducial models in Jiutian–1G (Planck18 cosmology) and CosmicGrowth (WMAP9-like cosmology) with those from DESI PAC I. We also include results obtained …
Figure 23
Figure 23. Figure 23: Dependence of 𝑛h𝑏 2 h , 𝑛h, and 𝑏 2 h on 𝜎8 and Ωm around the Planck18 cosmology at 𝑧 = 0.1, shown as a function of 𝑀vir. The top panel shows the fractional derivatives with respect to each parameter separately. The bottom panel shows the gradient amplitude |𝐺| and th…
Figure 26
Figure 26. Figure 26: SHMRs constrained by fitting 𝑛¯2𝑤p (𝑟p ) measurements under different assumed cosmologies using the fiducial non-parametric model. Re￾sults are shown for Planck18 and WMAP9 cosmologies at 𝑧 = 0.1. We also include fits obtained using the WMAP9 cosmology at 𝑧 = 0, which…
Figure 24
Figure 24. Figure 24: Similar to [PITH_FULL_IMAGE:figures/full_fig_p021_24.png]
Figure 25
Figure 25. Figure 25: 𝑛h–𝑏 2 h relation for cosmologies with 𝜎8 and Ωm varied around the Planck18 baseline. Grey lines indicate contours of constant 𝑛h𝑏 2 h . 4.7 Effects of the assumed cosmology Another factor worth examining is the assumed Planck18 cosmology used in both the measurements…
Figure 27
Figure 27. Figure 27: Examples of fits to observational 𝑛¯2𝑤p (𝑟p ) measurements using different cosmologies, shown for several stellar-mass bins. Results are shown for Planck18 and WMAP9 cosmologies at 𝑧 = 0.1. We also include fits obtained using the WMAP9 cosmology at 𝑧 = 0, which, when …
Figure 28
Figure 28. Figure 28: Comparison of our fiducial parametric SHMRs with previous studies. Results from Yang et al. (2012), Behroozi et al. (2013), Moster et al. (2013), and SDSS PAC IV are shown. All halo masses are converted to the virial definition 𝑀vir using the concentration model of Is…
Figure 29
Figure 29. Figure 29: Comparison of the scatter in the central SHMR from our varying￾scatter model with that from Tinker (2021). Results are from the non￾parametric model. The 1𝜎 interval for Tinker (2021) is obtained by con￾verting their reported 95% confidence range assuming Gaussian err…
Figure 30
Figure 30. Figure 30: Comparison of the GSMF from our fiducial non-parametric model with previous measurements. Results from DESI PAC I at 𝑧 < 0.2, GAMA DR4 (Driver et al. 2022) at 𝑧 < 0.08, DESI BGS DR1 using the 𝑉max method (Moore et al. 2025) at 𝑧 < 0.2, and COSMOS-Web (Shuntov et al. 2…
Figure 31
Figure 31. Figure 31: (a) Subhalo fraction from Jiutian-300 as a function of (sub)halo mass. (b) Satellite fraction as a function of stellar mass from the fiducial non￾parametric model in this work. Results from Wang et al. (2024), based on a DESI Y1 group catalogue (Yang et al. 2021), as …
Figure 32
Figure 32. Figure 32: Δ𝜒 2 of the fits to 𝑛¯2𝑤p (𝑟p ) measurements as a function of the imposed minimum halo mass in the Planck18 cosmology at 𝑧 ≃ 0.1, relative to the case with no minimum–mass cutoff. All fits use the MAP fiducial non￾parametric SHMR model. ing a minimum halo mass 𝑀lim in…

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    AldoPontremoli

    D16 × 0.9 Jiutian 300 Jiutian 1G Figure A1.Comparison of the HMFs from Jiutian-1G and Jiutian-300 with thosefromamodifiedDespalietal.(2016)model,rescaledbyafactorof0.9 to achieve the best match to the Jiutian results. Yang X., et al., 2021, ApJ, 909, 143 York D. G., et al., 2000, AJ, 120, 1579 Yuan S., Hadzhiyska B., Bose S., Eisenstein D. J., Guo H., 202...

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Reviewed August 4, 2026 · model on record in the stance chip above.