Pith. sign in

REVIEW 4 major objections 5 minor 1 cited by

The paper argues that the ultraviolet excess seen in a deep, wide-field narrow-band image taken by the Condor Array Telescope is Lyman-α emission from the cosmic web at redshift z≈2.5, a claim supported by synthetic maps built from five ind

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

T0 review · deepseek-v4-flash

2026-08-04 10:58 UTC pith:2MM66EGC

load-bearing objection A useful multi-simulation Lyα forecast whose claimed validation of the Condor excess is asserted, not demonstrated — and the paper's own final caveat admits unresolved sources. the 4 major comments →

arxiv 2510.07259 v2 pith:2MM66EGC submitted 2025-10-08 astro-ph.CO astro-ph.GA

The cosmic web's Lyman-α glow at z approx 2.5; hydrodynamic models, dust, and wide-field, narrow-band detection

Oleksii Sokoliuk , John K. Webb , Kenneth M. Lanzetta , Michael M. Shara , Stefan Gromoll , James S. Bolton , Robert F. Carswell , Gaspar Galaz
show 7 more authors
C\'edric Ledoux Gaspare Lo Curto Alain Smette David Valls-Gabaud Anja von der Linden Frederick M. Walter Joris Witstok
This is my paper
classification astro-ph.CO astro-ph.GA
keywords Lyman-alpha emissioncosmic webintergalactic mediumnarrow-band imagingsurface brightnesshydrodynamic simulationsdust attenuationCondor Array Telescope
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The authors set out to show that the faint UV excess detected in the deep Condor narrow-band image is the long-sought Lyman-α glow of the cosmic web, not a foreground contaminant or artifact. They construct synthetic Lyman-α surface-brightness maps from five hydrodynamic simulations, modeling recombination, collisional excitation, star formation, and dust attenuation, and find that the simulated brightness distributions match the statistical shape of the observed excess. If correct, this would be the first wide-field, narrow-band detection of the cosmic web in emission at z≈2.5, opening a new observational window onto the gas that underpins large-scale structure.

Core claim

On the paper's own terms, the central discovery is that the surface-brightness distribution of narrow-band Lyman-α emission predicted by hydrodynamic simulations of the z≈2.5 cosmic web is statistically consistent with the UV excess in the Condor Array Telescope image reported by Lanzetta et al. (2024). Using the Anderson-Darling statistic, the authors show that three of the four simulations that include dust predict a 5σ deviation from pure Gaussian noise for fluxes brighter than roughly 8×10^-17 erg s^-1 cm^-2 arcsec^-2, and that isolating the low-density diffuse component requires noise below about 2×10^-19 erg s^-1 cm^-2 arcsec^-2, reachable only by the most optimistic simulation (Illust

What carries the argument

The central machinery is a set of synthetic Lyman-α surface-brightness maps produced by post-processing five full-physics hydrodynamic simulations (IllustrisTNG, EAGLE, CROCODILE, SIMBA, Sherwood) onto a common grid, using semi-analytic separation of hydrogen species and emissivities from recombination, collisional excitation, and star formation. Dust attenuation is treated particle-by-particle via a slab-geometry escape fraction with an SMC extinction curve and a dust-to-baryon scaling. The Anderson-Darling statistic, which weights the tails of the brightness distribution, is then applied to noisy simulated maps to quantify detection thresholds against pure Gaussian noise.

Load-bearing premise

The local-universe dust escape model—SMC extinction with dust-to-baryon proportionality—correctly describes how Lyman-α photons escape from z≈2.5 gas, even though no dust constraints exist at those redshifts on simulation-particle scales.

What would settle it

A narrow-band image of the same COSMOS field taken with a filter offset by a few ångströms (so Lyα at z=2.4754 falls outside but [OII] at z=0.1332 remains inside) should show the excess vanish if it is Lyα; if it persists, the signal is not the cosmic-web glow. Alternatively, a future 5σ detection of the diffuse component at noise ~2×10^-19 erg s^-1 cm^-2 arcsec^-2 would confirm the most optimistic simulation.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • If the simulations are right, the Condor UV excess is Lyman-α emission from intergalactic and circumgalactic gas at z≈2.48, making it the first wide-field detection of the cosmic web in emission.
  • Wide-field narrow-band surveys with sensitivities around 10^-17 erg s^-1 cm^-2 arcsec^-2 or better can statistically detect the total cosmic-web Lyman-α glow over volumes of hundreds of thousands of cubic megaparsecs.
  • Detecting the truly diffuse, low-density component requires roughly two orders of magnitude deeper imaging (noise below ~2×10^-19 erg s^-1 cm^-2 arcsec^-2 in the most optimistic case), a target for next-generation facilities.
  • The broad agreement across four independent simulations, despite large differences in subgrid physics, suggests the statistical detection is not an artifact of a single baryon model, though the bright end is dust-sensitive.
  • Contaminating lines such as [OII] at z≈0.13 are shown to contribute at most a few tenths of a percent of the signal, so the 422 nm narrow-band excess is effectively pure Lyman-α.

Where Pith is reading between the lines

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

  • If a follow-up observation with a detuned filter (a few ångströms off the Lyα redshift) shows the excess disappearing, the cosmic-web interpretation is strongly confirmed; this is the most direct test the paper leaves implicit.
  • The paper's own caveat that the signal is likely unresolved sources rather than diffuse gas implies that 'cartographic mapping' of the filamentary network may first require separating a population of faint, clustered emitters before the diffuse component becomes visible.
  • The same semi-analytic pipeline could be adapted to other redshifts and emission lines, turning wide-field imagers into systematic probes of diffuse baryons, provided dust models can be validated at those epochs.
  • The markedly different surface-brightness PDFs produced by the dust-escape model versus high-density culling indicate that the claimed 5σ threshold for the total component is not yet pinned down; calibrating dust-to-gas at z~2.5 would materially sharpen the forecasts.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 5 minor

Summary. The paper post-processes five cosmological hydrodynamic simulations (IllustrisTNG, EAGLE, CROCODILE, SIMBA, Sherwood) at redshifts 2.0–2.74 to predict narrow-band Lyman-α surface brightness from the cosmic web. Emission is computed from recombination, collisional excitation, and star formation, with hydrogen species separated using published fitting functions (Rahmati et al.; Gnedin & Kravtsov). High-density gas is treated either with an SMC-based dust attenuation model (Eqs. 15–18) or by culling particles above a self-shielding density threshold (Sec. 2.8). The projected surface-brightness maps are then degraded by Gaussian noise, and the Anderson-Darling statistic is used to estimate detection thresholds. The authors report that a 5σ detection of total intergalactic/circumgalactic Lyman-α emission should be possible at fluxes brighter than ≈8×10^-17 erg s^-1 cm^-2 arcsec^-2, while the low-density cosmic-web component requires noise below ≈2×10^-19. The abstract and conclusions further claim that these predictions are consistent with the UV excess detected in the Condor Array Telescope narrow-band image reported by Lanzetta et al. (2024).

Significance. If the central consistency claim could be substantiated, the paper would provide a useful framework for planning wide-field narrow-band surveys of diffuse Lyman-α emission and for quantifying the sensitivity needed to map the cosmic web in emission. The multi-simulation comparison is a genuine strength: five independent hydrodynamic codes are processed through a common pipeline, and the derived neutral-hydrogen CDDFs are checked against quasar absorption measurements. The paper is also unusually candid about the limitations of the dust model and about inter-simulation scatter. However, the headline claim of consistency with the Condor detection is not demonstrated by the statistical analysis actually presented, and the conclusions contain an admission that the observed UV excess may be dominated by unresolved sources rather than diffuse Lyman-α. With a direct comparison to the observed image or a reframing as forward predictions only, the simulation methodology and threshold estimates would still be a useful contribution.

major comments (4)
  1. [§3.3.2, Fig. 6] The Anderson-Darling statistic is computed only between (simulated map + Gaussian noise) and pure Gaussian noise. It is never computed for the actual masked Condor narrow-band-minus-luminance image described in §3.3.1, nor is the observed pixel PDF compared with the simulated PDFs. The statement in §3.3.1 that the two datasets can be 'compared meaningfully' is not followed by a comparison. Therefore the abstract and §4 claim that the simulation predictions are 'consistent with' the Condor UV excess is not supported by the analysis shown. Please either compute A2 (or an equivalent statistic) for the observed masked difference image, or explicitly downgrade the consistency claim to simulation-only detectability predictions.
  2. [§4, concluding paragraphs] The paper itself states that Fig. 6 suggests that Condor has not detected the diffuse component but 'more likely the statistical effect of unresolved sources.' This directly undermines the central claim that the Condor UV excess validates diffuse Lyman-α cosmic-web emission. If unresolved sources dominate the measured excess, then agreement with diffuse-emission simulations is not evidence for detection of the diffuse cosmic web. The manuscript must distinguish between (a) a claimed detection of diffuse IGM/CGM Lyman-α, and (b) a UV excess consistent with unresolved sources plus perhaps a subdominant diffuse component. The current wording conflates the two, and the conclusions should be revised to state precisely which claim is intended.
  3. [§2.7, Eqs. 15–18; §2.8; Fig. 6] The dust escape model is derived from local-universe relations, and the paper concedes in §2.1 that no dust constraints exist at z≈2.5 on simulation-particle scales. This model controls the bright end of the surface-brightness distribution and hence the quoted 5σ threshold near 8×10^-17 in the left panel of Fig. 6. The alternative density-culling treatment in §2.8 yields 'dramatically different' PDFs and threshold curves (right panel of Fig. 6). Because no observed comparison anchors the choice between these treatments, the central threshold claim is sensitive to an unvalidated modeling assumption. Please quantify the dependence of the 5σ threshold on dust-model parameters (e.g., albedo, metallicity scaling, SMC vs. LMC curve) and state whether the threshold is robust across the two adopted treatments or only a property of the fiducial dust prescription.
  4. [§3.2.1, Table 2] The factor-of-six spread in predicted diffuse IGM temperatures is presented as an inter-simulation result, but the paper also notes that all five simulations overestimate the observationally inferred Lyman-α forest temperature. This is more than a diagnostic aside: the temperature enters the emissivity calculations directly, so the bright-end predictions inherit this systematic scatter. A quantitative statement of how much of the simulation-to-simulation spread in Fig. 6 is driven by temperature differences (as opposed to density/star-formation prescriptions) would strengthen the paper and help the reader judge whether the claimed consistency threshold is robust.
minor comments (5)
  1. [§1; §3.3.1] Section 1 states that the Condor narrow-band filter probes z=2.24754±0.0030, while §3.3.1 and §4 use z=2.4754. For λ_Lyα=121.567 nm and λ_filter=422.5 nm, z≈2.4754. The first value appears to be a typo and should be corrected.
  2. [Fig. 3 text vs caption] The main text says 'the intensity scaling is kept the same for all panels,' but the figure caption says 'each simulation has its own colour map... numerical display ranges are not the same.' Please reconcile these statements.
  3. [Eq. (17)] The summation notation in Eq. (17) is undefined: the sums over Z_i and Z_i,0 are not specified (over which elements? per particle? solar abundances?). Please define all indices and reference abundances explicitly.
  4. [Fig. 6] The horizontal '5 sd.' threshold is attributed to SciPy but the corresponding Anderson-Darling critical value or p-value conversion is not given. Please state the numerical threshold used so the claim is reproducible.
  5. [Throughout] Small typos include 'Anderson-Darling statistical text' (§3.3.2), 'observational and stimulation data' (§3.1), and the bibliographic entry 'Lanzetta et al K. M., 2024', which should be formatted consistently.

Circularity Check

0 steps flagged

No equation-level circularity: the Lyα surface-brightness predictions are computed from simulation physics and external fitting functions, not fitted to the Condor image; the main weakness is that the claimed consistency with the Condor UV excess is asserted rather than demonstrated.

full rationale

The derivation chain is not circular by construction. Equations (1)–(26) compute Lyα emissivities, hydrogen fractions, dust escape fractions, and surface brightness from hydrodynamic simulation outputs using external fits (Rahmati et al. 2013a; Gnedin & Kravtsov 2011; Laursen et al. 2009b; Pei 1992; Haardt & Madau 2012), with no parameter fitted to the Condor measurement. The Anderson–Darling thresholds in Fig. 6 are computed from simulated maps plus Gaussian noise versus a Gaussian null; they are predictions, not fits to the observed UV excess. The paper does not compute A² for the actual masked Condor difference image (the comparison is only described in §3.3.1, where the authors say 'we are nevertheless able to compare the two meaningfully' without performing an observed-versus-simulated A² test). Its own concluding paragraph weakens the discovery claim: 'Fig.6 suggests that Condor has not detected the diffuse component, but more likely the statistical effect of unresolved sources' — a support gap, not a circular reduction. The observational target is taken from Lanzetta et al. (2024), a companion paper with overlapping authors; this is a self-referential evidentiary link, but the theoretical result does not reduce to that citation. The CDDF comparison against external quasar absorption measurements provides independent benchmark support. No self-definitional, fitted-input-as-prediction, uniqueness-imported, ansatz-smuggled, or renaming circularity was found. Score 1 reflects the minor self-referential observational anchor and the unquantified 'consistency' assertion, not derivation-level circularity.

Axiom & Free-Parameter Ledger

4 free parameters · 7 axioms · 0 invented entities

The central claim rests on a chain of external fitting functions and simplified physical models rather than a self-contained derivation. The most load-bearing are the dust-escape prescription (Eq. 15-18) and the star-formation emissivity normalization (Eq. 3). The cross-simulation spread is the main independent support; there are no new entities.

free parameters (4)
  • Star-formation Ly-alpha emissivity normalization = 10^42 erg s^-1 per (M_sun/yr)
    Assumed linear conversion from SFR to Ly-alpha luminosity for unresolved star-forming gas; from Byrohl et al. 2021. Not calibrated at z~2.5 and directly sets the bright-end flux.
  • Rahmati et al. HI-fraction fit parameters = alpha1=-2.28, alpha2=-0.84, f=0.02, kappa=1.64, n0=1.003 n_H,SSh
    Fit to radiative-transfer simulations at z≳2; controls the neutral fraction and thus emissivity and dust optical depth (Eqs. 6-8).
  • Dust escape fit coefficients and albedo = zeta'=2.048, eta'=0.71, A=0.32
    Local-universe Ly-alpha/dust transfer fit (Laursen et al. 2009b; Li & Draine 2001) used at z~2.5 where no constraints exist; controls the escape fraction in Eq. (15).
  • Gnedin-Kravtsov H2 prescription parameters = Sigma_c=20 M_sun pc^-2 with D, U dependencies
    Empirical molecular-hydrogen prescription (Eq. 9-10) affecting only high-column dense gas; minor for faint diffuse component.
axioms (7)
  • domain assumption Semi-analytic post-processing without full Monte Carlo radiative transfer is adequate for surface brightness PDFs.
    Central to the entire method; cited to Byrohl & Nelson (2023) in §2.1.
  • domain assumption The Rahmati et al. fitting functions are valid for z≳2 and the ignored helium contribution to electron density is small.
    Used to compute HI fractions in §2.3; small effect asserted from Rahmati et al. (2013a).
  • domain assumption Case B recombination is appropriate because high-column-density gas (N_HI≳1e18 cm^-2) dominates the bright-end surface brightness.
    Stated in §2.2; affects the recombination emissivity coefficient.
  • domain assumption The observed masked difference image traces only photon noise plus cosmic-web line emission; [OII] and other line contamination are negligible.
    §3.3.1 and §3.4; the [OII] estimate is an upper limit with several optimistic assumptions, and if wrong the central attribution fails.
  • domain assumption Local-universe SMC dust properties apply at z≈2.5.
    Adopted in §2.7 because no dust opacity/albedo constraints exist at z~2.5 on simulation-particle scales.
  • domain assumption Matter is homogeneous within each simulation particle; real clumpiness would make the cosmic web easier to detect.
    §2.7; direction of the bias is known, but the absolute normalization of the predicted surface brightness depends on it.
  • domain assumption The five simulation snapshots at z=2.00–2.74 are treated as comparable predictions for the single Condor narrow-band shell at z=2.4754 without correction for redshift evolution or box-size differences.
    Table 1 and §2.1; the paper asserts cosmology differences are subdominant, but the redshift spread is large for a 1-nm filter.

pith-pipeline@v1.3.0-alltime-deepseek · 29710 in / 16192 out tokens · 136727 ms · 2026-08-04T10:58:37.438405+00:00 · methodology

0 comments
read the original abstract

The diffuse Lyman-$\alpha$ glow of the cosmic web has long been predicted but has so far eluded direct detection over cosmologically significant volumes. We construct synthetic Lyman-$\alpha$ surface-brightness maps using five state-of-the-art hydrodynamic simulations (\texttt{IllustrisTNG, EAGLE, CROCODILE, SIMBA, and Sherwood}), modeling recombination, collisional excitation, star formation, and localized dust attenuation. Our study focuses on the redshift range $2.0<z<2.7$, motivated by the numerous detailed studies of the COSMOS region. Significant variations are seen in the results obtained from these independent simulations. Using the Anderson-Darling statistic to probe these statistical differences, we demonstrate that a $5\sigma$ statistical detection of the total intergalactic and circumgalactic Lyman-$\alpha$ emission is achievable with current facilities at flux thresholds brighter than $\sim 8 \times 10^{-17} \text{ erg s}^{-1}\text{ cm}^{-2}\text{ arcsec}^{-2}$. Conversely, isolating the underlying low-density component of the cosmic web requires ultra-deep sensitivity, with the most optimistic simulation (IllustrisTNG) reaching a 5$\sigma$ detection only for background noise levels below $\sigma \sim 2 \times 10^{-19} \text{ erg s}^{-1}\text{ cm}^{-2}\text{ arcsec}^{-2}$. These quantitative limits validate the feasibility of ongoing wide-field narrow-band campaigns, opening a new era of empirical intergalactic cartography.

Figures

Figures reproduced from arXiv: 2510.07259 by Alain Smette, Anja von der Linden, C\'edric Ledoux, David Valls-Gabaud, Frederick M. Walter, Gaspare Lo Curto, Gaspar Galaz, James S. Bolton, John K. Webb, Joris Witstok, Kenneth M. Lanzetta, Michael M. Shara, Oleksii Sokoliuk, Robert F. Carswell, Stefan Gromoll.

Figure 1
Figure 1. Figure 1: Comoving HI Column Density Distribution Function and its probability distribution for each simulation. 3.2 Physical insights from the log𝑇-log 𝑛H and logS-log 𝑁HI phase diagrams [PITH_FULL_IMAGE:figures/full_fig_p008_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Left column (a): Temperature vs. hydrogen number density relation. Note the abrupt 𝑛H cutoff for some simulations, a consequence of the switch to a stochastic Kennicutt–Schmidt star formation law. Right column (b): HI column density vs. Lyman-𝛼 surface brightness. Power-law fits for this relation are shown as dotted lines, offset from the image data for visualisation. See Sections 3.2.1 to 3.2. The colour … view at source ↗
Figure 3
Figure 3. Figure 3: Lyman-𝛼 surface brightness map for each simulation. Middle and right panels show 5× and 10× zoom-ins on arbitrarily selected regions. See Section 3.3. Each simulation has its own colour map, i.e. the numerical display ranges are not the same for each simulation. Instead, each colour map is set by the minimum and maximum count in each image. MNRAS 000, 1–19 (2025) [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 4
Figure 4. Figure 4 [PITH_FULL_IMAGE:figures/full_fig_p014_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Surface brightness map from the EAGLE simulation made using the dust calculation (Section 2.7), for various Gaussian noise models (Section 3.3.2), emulating (in part, Section 3.3.1) real observational data. The standard deviation 𝜎 of the Gaussian noise added is shown in each panel. The panels in this figure correspond to the left hand panels in [PITH_FULL_IMAGE:figures/full_fig_p015_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Anderson-Darling 𝐴 2 statistic (Eq. 35) for each simulation, for different values of added Gaussian noise 𝜎. The left panel here corresponds to the left panel in [PITH_FULL_IMAGE:figures/full_fig_p016_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Metallicity and Lyman-𝛼 escape fraction vs. hydrogen density. Sherwood does not provide metallicity per particle so is not shown. The wedge-like feature observed in the left column is a consequence of the artificial relation between gas density and temperature imposed in these models at log(𝑛H/cm−3 ) ≳ 0 by the sub-grid star formation prescription. However, [PITH_FULL_IMAGE:figures/full_fig_p017_7.png] view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. FEASTS and MHONGOOSE: HI Column Density Distribution at $z=0$ for $N_\mathrm{HI}>10^{17.8}\, \mathrm{cm}^{-2}$

    astro-ph.GA 2026-03 conditional novelty 7.0

    The z=0 HI column-density distribution function has been measured for the first time down to 10^17.8 cm^-2 from 1-kpc-resolution 21-cm images, showing modest evolution since z~3 at LLS-like densities.

Reference graph

Works this paper leans on

153 extracted references · 29 canonical work pages · cited by 1 Pith paper · 4 internal anchors

  1. [1]

    Altay G., Theuns T., Schaye J., Crighton N. H. M., Dalla Vecchia C., 2011, @doi [The Astrophysical Journal Letters] 10.1088/2041-8205/737/2/L37 , 737, L37

    doi:10.1088/2041-8205/737/2/l37 2011

  2. [2]

    W., Darling D

    Anderson T. W., Darling D. A., 1952, @doi [Annals of Mathematical Statistics] 10.1214/aoms/1177729437 , 23, 193

    arXiv 1952

  3. [5]

    & Astrophys.] 10.1051/0004-6361/202039887 , https://ui.adsabs.harvard.edu/abs/2021A&A...647A.107B 647, A107

    Bacon R., et al., 2021, @doi [Astron. & Astrophys.] 10.1051/0004-6361/202039887 , https://ui.adsabs.harvard.edu/abs/2021A&A...647A.107B 647, A107

    doi:10.1051/0004-6361/202039887 2021

  4. [6]

    Bacon R., et al., 2023, @doi [ ] 10.1051/0004-6361/202244187 , https://ui.adsabs.harvard.edu/abs/2023A&A...670A...4B 670, A4

    doi:10.1051/0004-6361/202244187 2023

  5. [7]

    Bacon R., Mainieri V., Randich S., et al., 2024, arXiv e-prints

    2024

  6. [8]

    D., 2024, MUSEQuBES: Unveiling Cosmic Web Filaments at z 3.6 through Dual Absorption and Emission Line Analysis ( @eprint arXiv 2412.04546 ), https://arxiv.org/abs/2412.04546

    Banerjee E., Muzahid S., Schaye J., Cantalupo S., Johnson S. D., 2024, MUSEQuBES: Unveiling Cosmic Web Filaments at z 3.6 through Dual Absorption and Emission Line Analysis ( @eprint arXiv 2412.04546 ), https://arxiv.org/abs/2412.04546

    Pith/arXiv arXiv 2024

  7. [9]

    Bauer A., Springel V., Vogelsberger M., Genel S., Torrey P., Sijacki D., Nelson D., Hernquist L., 2015, @doi [MNRAS] 10.1093/mnras/stv1893 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.453.3593B 453, 3593

    doi:10.1093/mnras/stv1893 2015

  8. [10]

    Bird S., Vogelsberger M., Haehnelt M., Sijacki D., Genel S., Torrey P., Springel V., Hernquist L., 2014, @doi [ ] 10.1093/mnras/stu1923 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.445.2313B 445, 2313

    doi:10.1093/mnras/stu1923 2014

  9. [11]

    Boess L., 2024, SPHtoGrid.jl homepage: https://github.com/LudwigBoess/SPHtoGrid.jl

    2024

  10. [12]

    Distinguish dark matter theories with the cosmic web and next-generation surveys I: an alternative theory of gravity

    Boldrini P., Laigle C., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2402.04837 , https://ui.adsabs.harvard.edu/abs/2024arXiv240204837B p. arXiv:2402.04837

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2402.04837 2024

  11. [13]

    S., Puchwein E., Sijacki D., Haehnelt M

    Bolton J. S., Puchwein E., Sijacki D., Haehnelt M. G., Kim T.-S., Meiksin A., Regan J. A., Viel M., 2017, @doi [MNRAS] 10.1093/mnras/stw2397 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.464..897B 464, 897

    doi:10.1093/mnras/stw2397 2017

  12. [14]

    Bonatto C., Bica E., 2011, @doi [MNRAS] 10.1111/j.1365-2966.2011.18901.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.415.2827B 415, 2827

    arXiv 2011

  13. [15]

    R., Kofman L., Pogosyan D., 1996, @doi [Nature] 10.1038/380603a0 , https://ui.adsabs.harvard.edu/abs/1996Natur.380..603B 380, 603

    Bond J. R., Kofman L., Pogosyan D., 1996, @doi [Nature] 10.1038/380603a0 , https://ui.adsabs.harvard.edu/abs/1996Natur.380..603B 380, 603

    doi:10.1038/380603a0 1996

  14. [16]

    Brough S., et al., 2024, @doi [Monthly Notices of the Royal Astronomical Society] 10.1093/mnras/stac2045 , 528, 771

    work page doi:10.1093/mnras/stac2045 2024

  15. [17]

    N., Elek O., Tejos N., Prochaska J

    Burchett J. N., Elek O., Tejos N., Prochaska J. X., Tripp T. M., Bordoloi R., Forbes A. G., 2020, @doi [ ] 10.3847/2041-8213/ab700c , https://ui.adsabs.harvard.edu/abs/2020ApJ...891L..35B 891, L35

    work page doi:10.3847/2041-8213/ab700c 2020

  16. [18]

    Byrohl C., Nelson D., 2023, @doi [MNRAS] 10.1093/mnras/stad1779 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.5248B 523, 5248

    doi:10.1093/mnras/stad1779 2023

  17. [19]

    Byrohl C., et al., 2021, @doi [ ] 10.1093/mnras/stab1958 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.506.5129B 506, 5129

    doi:10.1093/mnras/stab1958 2021

  18. [20]

    Caddy S., Spitler L., Ellis S., 2024, @doi [Publications of the Astronomical Society of Australia] 10.1017/pasa.2024.25 , 41, e025

    doi:10.1017/pasa.2024.25 2024

  19. [21]

    J., Miniati F., 2005, @doi [ApJ] 10.1086/430758 , https://ui.adsabs.harvard.edu/abs/2005ApJ...628...61C 628, 61

    Cantalupo S., Porciani C., Lilly S. J., Miniati F., 2005, @doi [ApJ] 10.1086/430758 , https://ui.adsabs.harvard.edu/abs/2005ApJ...628...61C 628, 61

    doi:10.1086/430758 2005

  20. [22]

    J., 2008, @doi [Astrophysical Journal] 10.1086/523298 , https://ui.adsabs.harvard.edu/abs/2008ApJ...672...48C 672, 48

    Cantalupo S., Porciani C., Lilly S. J., 2008, @doi [Astrophysical Journal] 10.1086/523298 , https://ui.adsabs.harvard.edu/abs/2008ApJ...672...48C 672, 48

    doi:10.1086/523298 2008

  21. [23]

    X., Hennawi J

    Cantalupo S., Arrigoni-Battaia F., Prochaska J. X., Hennawi J. F., Madau P., 2014, @doi [Nature] 10.1038/nature12898 , https://ui.adsabs.harvard.edu/abs/2014Natur.506...63C 506, 63

    doi:10.1038/nature12898 2014

  22. [24]

    F., 2024, VPFIT homepage: https://people.ast.cam.ac.uk/ rfc/, https://people.ast.cam.ac.uk/ rfc/

    Carswell R. F., 2024, VPFIT homepage: https://people.ast.cam.ac.uk/ rfc/, https://people.ast.cam.ac.uk/ rfc/

    2024

  23. [25]

    F., Webb J

    Carswell R. F., Webb J. K., 2014, VPFIT: Voigt profile fitting program, http://adsabs.harvard.edu/abs/2014ascl.soft08015C , Astrophysics Source Code Library ( @eprint ascl 1408.015 )

    2014

  24. [26]

    Cautun M., van de Weygaert R., Jones B. J. T., Frenk C. S., 2014, @doi [ ] 10.1093/mnras/stu768 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.441.2923C 441, 2923

    doi:10.1093/mnras/stu768 2014

  25. [27]

    G., 2018, @doi [MNRAS] 10.1093/mnras/sty992 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.1065C 478, 1065

    Chardin J., Kulkarni G., Haehnelt M. G., 2018, @doi [MNRAS] 10.1093/mnras/sty992 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.1065C 478, 1065

    doi:10.1093/mnras/sty992 2018

  26. [28]

    Chen S., et al., 2024, @doi [arXiv preprint arXiv:2406.15101] 10.48550/arXiv.2406.15101

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2406.15101 2024

  27. [29]

    Chia-Yu H., 2024, ParticleGridMapper.jl homepage: https://github.com/huchiayu/ParticleGridMapper.jl, https://github.com/huchiayu/ParticleGridMapper.jl

    2024

  28. [30]

    Codis S., Pogosyan D., Pichon C., 2018, @doi [MNRAS] 10.1093/mnras/sty1643 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479..973C 479, 973

    doi:10.1093/mnras/sty1643 2018

  29. [31]

    Collaboration D., Aghamousa A., Aguilar J., Ahlen S., et al., 2016, arXiv e-prints

    2016

  30. [32]

    arXiv:2409.16952

    Connor L., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2409.16952 , https://ui.adsabs.harvard.edu/abs/2024arXiv240916952C p. arXiv:2409.16952

    Pith/arXiv arXiv doi:10.48550/arxiv.2409.16952 2024

  31. [33]

    Science Cases for the Keck Wide-Field Imager

    Cooke J., et al., 2022, @doi [arXiv e-prints] 10.48550/arXiv.2207.11698 , https://ui.adsabs.harvard.edu/abs/2022arXiv220711698C p. arXiv:2207.11698

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2207.11698 2022

  32. [34]

    A., et al., 2015, @doi [MNRAS] 10.1093/mnras/stv725 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.1937C 450, 1937

    Crain R. A., et al., 2015, @doi [MNRAS] 10.1093/mnras/stv725 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.1937C 450, 1937

    doi:10.1093/mnras/stv725 2015

  33. [35]

    A., et al., 2017, @doi [MNRAS] 10.1093/mnras/stw2586 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.464.4204C 464, 4204

    Crain R. A., et al., 2017, @doi [MNRAS] 10.1093/mnras/stw2586 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.464.4204C 464, 4204

    doi:10.1093/mnras/stw2586 2017

  34. [36]

    & Astrophys.] 10.1051/0004-6361/201833655 , https://ui.adsabs.harvard.edu/abs/2018A&A...619A..49C 619, A49

    Cucciati O., et al., 2018, @doi [Astron. & Astrophys.] 10.1051/0004-6361/201833655 , https://ui.adsabs.harvard.edu/abs/2018A&A...619A..49C 619, A49

    doi:10.1051/0004-6361/201833655 2018

  35. [37]

    H., Katz N., 1997, @doi [ ] 10.1086/303712 , https://ui.adsabs.harvard.edu/abs/1997ApJ...477...21D 477, 21

    Dav \'e R., Hernquist L., Weinberg D. H., Katz N., 1997, @doi [ ] 10.1086/303712 , https://ui.adsabs.harvard.edu/abs/1997ApJ...477...21D 477, 21

    doi:10.1086/303712 1997

  36. [38]

    H., 1999, @doi [ ] 10.1086/306722 , https://ui.adsabs.harvard.edu/abs/1999ApJ...511..521D 511, 521

    Dav \'e R., Hernquist L., Katz N., Weinberg D. H., 1999, @doi [ ] 10.1086/306722 , https://ui.adsabs.harvard.edu/abs/1999ApJ...511..521D 511, 521

    doi:10.1086/306722 1999

  37. [39]

    H., Appleby S., 2019, @doi [MNRAS] 10.1093/mnras/stz937 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.486.2827D 486, 2827

    Dav \'e R., Angl \'e s-Alc \'a zar D., Narayanan D., Li Q., Rafieferantsoa M. H., Appleby S., 2019, @doi [MNRAS] 10.1093/mnras/stz937 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.486.2827D 486, 2827

    doi:10.1093/mnras/stz937 2019

  38. [40]

    S., White S

    Davis M., Efstathiou G., Frenk C. S., White S. D. M., 1985, @doi [ ] 10.1086/163168 , https://ui.adsabs.harvard.edu/abs/1985ApJ...292..371D 292, 371

    doi:10.1086/163168 1985

  39. [41]

    B., 2016, @doi [ ] 10.1051/0004-6361/201527895 , https://ui.adsabs.harvard.edu/abs/2016A&A...596A..97D 596, A97

    De Cia A., Ledoux C., Mattsson L., Petitjean P., Srianand R., Gavignaud I., Jenkins E. B., 2016, @doi [ ] 10.1051/0004-6361/201527895 , https://ui.adsabs.harvard.edu/abs/2016A&A...596A..97D 596, A97

    doi:10.1051/0004-6361/201527895 2016

  40. [42]

    Dietrich J. P., Werner N., Clowe D., Finoguenov A., Kitching T., Miller L., Simionescu A., 2012, @doi [Nature] 10.1038/nature11224 , https://ui.adsabs.harvard.edu/abs/2012Natur.487..202D 487, 202

    doi:10.1038/nature11224 2012

  41. [43]

    Dijkstra M., 2014, @doi [PASA] 10.1017/pasa.2014.33 , https://ui.adsabs.harvard.edu/abs/2014PASA...31...40D 31, e040

    doi:10.1017/pasa.2014.33 2014

  42. [44]

    Dome T., Fialkov A., Sartorio N., Mocz P., 2023, @doi [MNRAS] 10.1093/mnras/stad2276 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.525..348D 525, 348

    doi:10.1093/mnras/stad2276 2023

  43. [45]

    T., 2011, Physics of the Interstellar and Intergalactic Medium

    Draine B. T., 2011, Physics of the Interstellar and Intergalactic Medium . Princeton University Press

    2011

  44. [46]

    Duval F., Schaerer D., \"O stlin G., Laursen P., 2014, @doi [ ] 10.1051/0004-6361/201220455 , https://ui.adsabs.harvard.edu/abs/2014A&A...562A..52D 562, A52

    doi:10.1051/0004-6361/201220455 2014

  45. [47]

    A., 2015, @doi [ ] 10.1093/mnrasl/slv085 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452L..36D 452, L36

    Dvorkin I., Silk J., Vangioni E., Petitjean P., Olive K. A., 2015, @doi [ ] 10.1093/mnrasl/slv085 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452L..36D 452, L36

    work page doi:10.1093/mnrasl/slv085 2015

  46. [48]

    Eckert D., et al., 2015, @doi [ ] 10.1038/nature16058 , https://ui.adsabs.harvard.edu/abs/2015Natur.528..105E 528, 105

    doi:10.1038/nature16058 2015

  47. [49]

    Efstathiou G., Davis M., White S. D. M., Frenk C. S., 1985, @doi [ ] 10.1086/191003 , https://ui.adsabs.harvard.edu/abs/1985ApJS...57..241E 57, 241

    doi:10.1086/191003 1985

  48. [50]

    J., Stanway E

    Eldridge J. J., Stanway E. R., Xiao L., McClelland L. A. S., Taylor G., Ng M., Greis S. M. L., Bray J. C., 2017, @doi [ ] 10.1017/pasa.2017.51 , https://ui.adsabs.harvard.edu/abs/2017PASA...34...58E 34, e058

    doi:10.1017/pasa.2017.51 2017

  49. [51]

    Elias L. M., Genel S., Sternberg A., Devriendt J., Slyz A., Visbal E., Bouch \'e N., 2020, @doi [MNRAS] 10.1093/mnras/staa1059 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.5439E 494, 5439

    work page doi:10.1093/mnras/staa1059 2020

  50. [52]

    Euclid Collaboration 2025, @doi [ ] 10.1051/0004-6361/202450810 , https://ui.adsabs.harvard.edu/abs/2025A&A...697A...1E 697, A1

    doi:10.1051/0004-6361/202450810 2025

  51. [53]

    Faucher-Gigu \`e re C.-A., Kere s D., Dijkstra M., Hernquist L., Zaldarriaga M., 2010, @doi [Astrophysical Journal] 10.1088/0004-637X/725/1/633 , https://ui.adsabs.harvard.edu/abs/2010ApJ...725..633F 725, 633

    doi:10.1088/0004-637x/725/1/633 2010

  52. [54]

    Fossati M., et al., 2019, @doi [ ] 10.1093/mnras/stz2693 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.1451F 490, 1451

    doi:10.1093/mnras/stz2693 2019

  53. [55]

    R., Schaye J., Springel V., Hernquist L., 2003, @doi [ ] 10.1086/381140 , https://ui.adsabs.harvard.edu/abs/2003ApJ...599L...1F 599, L1

    Furlanetto S. R., Schaye J., Springel V., Hernquist L., 2003, @doi [ ] 10.1086/381140 , https://ui.adsabs.harvard.edu/abs/2003ApJ...599L...1F 599, L1

    work page doi:10.1086/381140 2003

  54. [56]

    Gaikwad P., et al., 2023, @doi [ ] 10.1093/mnras/stad2566 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.525.4093G 525, 4093

    doi:10.1093/mnras/stad2566 2023

  55. [57]

    J., Huchra J

    Geller M. J., Huchra J. P., 1989, @doi [Science] 10.1126/science.246.4932.897 , https://ui.adsabs.harvard.edu/abs/1989Sci...246..897G 246, 897

    doi:10.1126/science.246.4932.897 1989

  56. [58]

    Y., Kravtsov A

    Gnedin N. Y., Kravtsov A. V., 2011, @doi [Astrophysical Journal] 10.1088/0004-637X/728/2/88 , https://ui.adsabs.harvard.edu/abs/2011ApJ...728...88G 728, 88

    doi:10.1088/0004-637x/728/2/88 2011

  57. [59]

    H., 1996, @doi [ApJ] 10.1086/177707 , https://ui.adsabs.harvard.edu/abs/1996ApJ...468..462G 468, 462

    Gould A., Weinberg D. H., 1996, @doi [ApJ] 10.1086/177707 , https://ui.adsabs.harvard.edu/abs/1996ApJ...468..462G 468, 462

    doi:10.1086/177707 1996

  58. [60]

    J.] 10.3847/1538-4357/835/2/175 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835..175G 835, 175

    Gurvich A., Burkhart B., Bird S., 2017, @doi [Astrophys. J.] 10.3847/1538-4357/835/2/175 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835..175G 835, 175

    doi:10.3847/1538-4357/835/2/175 2017

  59. [61]

    Haardt F., Madau P., 2012, @doi [Astrophysical Journal] 10.1088/0004-637X/746/2/125 , https://ui.adsabs.harvard.edu/abs/2012ApJ...746..125H 746, 125

    doi:10.1088/0004-637x/746/2/125 2012

  60. [62]

    J., 1968, Bulletin of the Astronomical Institutes of the Netherlands, https://ui.adsabs.harvard.edu/abs/1968BAN....19..421H 19, 421

    Habing H. J., 1968, Bulletin of the Astronomical Institutes of the Netherlands, https://ui.adsabs.harvard.edu/abs/1968BAN....19..421H 19, 421

    1968

  61. [63]

    R., et al., 2020, @doi [Nature] 10.1038/s41586-020-2649-2 , 585, 357

    Harris C. R., et al., 2020, @doi [Nature] 10.1038/s41586-020-2649-2 , 585, 357

    doi:10.1038/s41586-020-2649-2 2020

  62. [64]

    M., Atek H., Kunth D., 2011, @doi [ ] 10.1088/0004-637X/730/1/8 , https://ui.adsabs.harvard.edu/abs/2011ApJ...730....8H 730, 8

    Hayes M., Schaerer D., \"O stlin G., Mas-Hesse J. M., Atek H., Kunth D., 2011, @doi [ ] 10.1088/0004-637X/730/1/8 , https://ui.adsabs.harvard.edu/abs/2011ApJ...730....8H 730, 8

    doi:10.1088/0004-637x/730/1/8 2011

  63. [65]

    H., Miralda-Escud \'e J., 1996, @doi [ ] 10.1086/309899 , https://ui.adsabs.harvard.edu/abs/1996ApJ...457L..51H 457, L51

    Hernquist L., Katz N., Weinberg D. H., Miralda-Escud \'e J., 1996, @doi [ ] 10.1086/309899 , https://ui.adsabs.harvard.edu/abs/1996ApJ...457L..51H 457, L51

    doi:10.1086/309899 1996

  64. [66]

    F., O \ n orbe J., O'Meara J

    Hiss H., Walther M., Hennawi J. F., O \ n orbe J., O'Meara J. M., Rorai A., Luki \'c Z., 2018, @doi [ ] 10.3847/1538-4357/aada86 , https://ui.adsabs.harvard.edu/abs/2018ApJ...865...42H 865, 42

    doi:10.3847/1538-4357/aada86 2018

  65. [67]

    J., Weymann R

    Hogan C. J., Weymann R. J., 1987, @doi [MNRAS] 10.1093/mnras/225.1.1P , https://ui.adsabs.harvard.edu/abs/1987MNRAS.225P...1H 225, 1P

    work page doi:10.1093/mnras/225.1.1p 1987

  66. [68]

    Y., 1997, @doi [ ] 10.1093/mnras/292.1.27 , https://ui.adsabs.harvard.edu/abs/1997MNRAS.292...27H 292, 27

    Hui L., Gnedin N. Y., 1997, @doi [ ] 10.1093/mnras/292.1.27 , https://ui.adsabs.harvard.edu/abs/1997MNRAS.292...27H 292, 27

    doi:10.1093/mnras/292.1.27 1997

  67. [69]

    D., 2007, @doi [Computing in Science & Engineering] 10.1109/MCSE.2007.55 , 9, 90

    Hunter J. D., 2007, @doi [Computing in Science & Engineering] 10.1109/MCSE.2007.55 , 9, 90

    doi:10.1109/mcse.2007.55 2007

  68. [70]

    Kaiser N., Burgett W., Chambers K., et al., 2010, in Ground-based and Airborne Telescopes III. p. 77330E, @doi 10.1117/12.859188

    doi:10.1117/12.859188 2010

  69. [71]

    H., Hernquist L., 1996, @doi [Astrophysical Journal Supplements] 10.1086/192305 , https://ui.adsabs.harvard.edu/abs/1996ApJS..105...19K 105, 19

    Katz N., Weinberg D. H., Hernquist L., 1996, @doi [Astrophysical Journal Supplements] 10.1086/192305 , https://ui.adsabs.harvard.edu/abs/1996ApJS..105...19K 105, 19

    doi:10.1086/192305 1996

  70. [72]

    S., Partl A

    Kim T. S., Partl A. M., Carswell R. F., M \"u ller V., 2013, @doi [Astron. & Astrophys.] 10.1051/0004-6361/201220042 , https://ui.adsabs.harvard.edu/abs/2013A&A...552A..77K 552, A77

    doi:10.1051/0004-6361/201220042 2013

  71. [73]

    Kim J., et al., 2022, @doi [Astrophysical Journal] 10.3847/1538-4357/ac4750 , https://ui.adsabs.harvard.edu/abs/2022ApJ...926..179K 926, 179

    work page doi:10.3847/1538-4357/ac4750 2022

  72. [74]

    S., Sinigaglia F., Balaguera-Antol \' nez A., Favole G., 2024, @doi [AAP] 10.1051/0004-6361/202345876 , https://ui.adsabs.harvard.edu/abs/2024A&A...683A.215K 683, A215

    Kitaura F. S., Sinigaglia F., Balaguera-Antol \' nez A., Favole G., 2024, @doi [AAP] 10.1051/0004-6361/202345876 , https://ui.adsabs.harvard.edu/abs/2024A&A...683A.215K 683, A215

    doi:10.1051/0004-6361/202345876 2024

  73. [75]

    A., Shandarin S

    Klypin A. A., Shandarin S. F., 1983, @doi [MNRAS] 10.1093/mnras/204.3.891 , https://ui.adsabs.harvard.edu/abs/1983MNRAS.204..891K 204, 891

    doi:10.1093/mnras/204.3.891 1983

  74. [76]

    A., Zasowski G., Rix H.-W., Johns M., Anderson S

    Kollmeier J. A., Zasowski G., Rix H.-W., Johns M., Anderson S. F., et al., 2017, arXiv e-prints

    2017

  75. [77]

    arXiv:2407.16489

    Kugel R., van de Weygaert R., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.16489 , https://ui.adsabs.harvard.edu/abs/2024arXiv240716489K p. arXiv:2407.16489

    Pith/arXiv arXiv doi:10.48550/arxiv.2407.16489 2024

  76. [78]

    Lagos C. d. P., et al., 2015, @doi [MNRAS] 10.1093/mnras/stv1488 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.452.3815L 452, 3815

    doi:10.1093/mnras/stv1488 2015

  77. [79]

    M., Bowen D

    Lanzetta K. M., Bowen D. V., Tytler D., Webb J. K., 1995, @doi [ ] 10.1086/175459 , https://ui.adsabs.harvard.edu/abs/1995ApJ...442..538L 442, 538

    doi:10.1086/175459 1995

  78. [80]

    M., Gromoll S., Shara M

    Lanzetta K. M., Gromoll S., Shara M. M., Berg S., Valls-Gabaud D., Walter F. M., Webb J. K., 2023, @doi [PASP] 10.1088/1538-3873/acaee6 , https://ui.adsabs.harvard.edu/abs/2023PASP..135a5002L 135, 015002

    doi:10.1088/1538-3873/acaee6 2023

  79. [81]

    M., 2024, arXiv e-prints, p

    Lanzetta et al K. M., 2024, arXiv e-prints, p. arXiv:2412.10081

    Pith/arXiv arXiv 2024

  80. [82]

    O., Sommer-Larsen J., 2009a, @doi [Astrophysical Journal] 10.1088/0004-637X/696/1/853 , https://ui.adsabs.harvard.edu/abs/2009ApJ...696..853L 696, 853

    Laursen P., Razoumov A. O., Sommer-Larsen J., 2009a, @doi [Astrophysical Journal] 10.1088/0004-637X/696/1/853 , https://ui.adsabs.harvard.edu/abs/2009ApJ...696..853L 696, 853

    doi:10.1088/0004-637x/696/1/853

Showing first 80 references.