Pith. sign in

REVIEW 3 major objections 5 minor 1 cited by

High-Significance Detection of Correlation Between the Unresolved Gamma-Ray Background and the Large Scale Cosmic Structure

T0 review · 3 major / 5 minor · reviewed 2026-08-10 · deepseek-v4-flash

Pith's one-line read The unresolved gamma-ray background traces the Universe's large-scale mass distribution.

desk verdict A credible 8.9 sigma UGRB-lensing detection, but the blazar halo-mass interpretation is a post-fit story rather than an independent test. read the letter →

arxiv 2501.10506 v2 pith:WMLJDBQT submitted 2025-01-17 astro-ph.CO astro-ph.HE

classification astro-ph.COastro-ph.HE
keywords UGRBgamma-raybackgroundcross-correlationweaklensingblazarshalomasslog-parabolicspectrumlarge-scalestructure
topics Dark Matter
open problems Dark Matter
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

This paper claims a high-significance correlation, at signal-to-noise ratio of 8.9, between the unresolved gamma-ray background measured by Fermi-LAT over 12 years and the gravitational lensing shear measured by DES over its first three years. The paper argues that most of the signal comes from large angular scales, meaning a substantial fraction of the UGRB follows the large-scale clustering of matter rather than being dominated by rare bright sources. It interprets the signal as unresolved blazars hosted in halos of roughly $10^{14}\,M_\odot$, contributing about 30-40% of the UGRB above 10 GeV, and reports a preference for a curved log-parabolic gamma-ray spectrum over a power law at $\Delta\chi^2 \simeq 27$. If correct, this would be the first demonstration that the unresolved gamma-ray sky traces cosmic mass structure, and it would constrain the properties of the faint blazar population.

What carries the argument

The central observable is the two-point angular cross-correlation function between gamma-ray flux in nine energy bins and tangential shear in four redshift bins, computed via a Legendre transform of the harmonic cross-power spectrum with the Fermi-LAT point-spread function included. The theoretical interpretation uses a halo model that splits the signal into a 1-halo term, which follows the detector PSF, and a 2-halo term, which follows linear large-scale clustering, with the 2-halo term carrying most of the detection significance. The physical model for blazars relies on the blazar gamma-ray luminosity function and a halo mass-luminosity relation $M(L) = 2\times 10^{13}\,M_\odot \,(L/10^{47}\,\mathrm{erg\,s^{-1}})^{0.23}(1+z)^{-0.9}$, with free normalizations $A_{\rm 1h}^{\rm BLZ}$ and $A_{\rm 2h}^{\rm BLZ}$; the fitted large value $A_{\rm 2h}^{\rm BLZ}\simeq 6.6$ drives the paper toward halos of approximately $10^{14}\,M_\odot$.

What would settle it

A direct calculation of the unresolved blazar number counts and UGRB auto-correlation using the best-fit parameters from this paper, which requires $A_{\rm 2h}^{\rm BLZ}\simeq 6.6$ while the reference model allows values below about 2, would falsify the blazar interpretation if it is inconsistent with the measured source counts.

Watch

Extended reading notes

Core claim

The central claim is a detection: the UGRB and weak-lensing shear are cross-correlated at SNR 8.9, with most of the significance coming from large scales, demonstrating for the first time that a substantial portion of the UGRB aligns with the mass clustering of the Universe as traced by weak lensing. The paper shows that a blazar population with a hard spectrum, residing in halos of about $10^{14}\,M_\odot$ and contributing 30-40% of the UGRB above 10 GeV, plausibly explains the signal, and that a log-parabolic energy spectrum is strongly favored over a power law at $\Delta\chi^2 \sim 27$. It also finds negligible contributions from star-forming galaxies and misaligned AGNs under standard models, and notes that a WIMP dark-matter component could mimic the curvature but requires an annihilation cross-section in tension with other probes.

Load-bearing premise

The physical interpretation rests on the accuracy of the adopted blazar gamma-ray luminosity function and on the relation between blazar luminosity and host halo mass; if either is wrong, the inferred halo mass and the 30-40% UGRB fraction do not follow.

Editorial extensions

If this is right

  • A substantial portion of the UGRB above 10 GeV would originate from unresolved blazars clustered with large-scale structure, not from rare bright sources.
  • The blazars responsible for the signal would need to reside in cluster-size halos of about $10^{14}\,M_\odot$, reconciling the lensing signal with existing source-count and auto-correlation constraints.
  • The strong preference for a log-parabolic spectrum would point either to intrinsic spectral curvature, stronger ultraviolet extragalactic background light, or an additional component such as dark-matter annihilation.
  • Star-forming galaxies and misaligned AGNs, modeled with their standard spectra, would contribute negligibly to the measured cross-correlation.
  • If dark-matter annihilation is invoked to explain the curvature, the required cross-section would be in tension with dwarf satellite and Large Magellanic Cloud constraints.

Reading between the lines

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

  • The predicted cluster-size halos imply that cross-correlating the UGRB with galaxy cluster catalogs or thermal Sunyaev-Zeldovich maps should reveal a matching signal at a comparable amplitude, a test that could be performed with existing data.
  • The log-parabolic preference could alternatively be absorbed by a different extragalactic background light model; a precise measurement of the UV background would discriminate between the EBL explanation and an intrinsic blazar curvature.
  • The claim that unresolved blazars live in more massive halos than typical resolved blazars could be checked by comparing the clustering length of the faint, lensing-selected population with that of 4FGL blazars.
  • The DM-inclusive fit, with best-fit mass around 363 GeV and annihilation rate about 32 times the thermal value, could be tested by a joint analysis with Fermi-LAT dwarf spheroidal limits, which would likely rule out that interpretation.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper measures the real-space two-point cross-correlation between Fermi-LAT 12-year unresolved gamma-ray background maps in nine energy bins (0.63-1000 GeV) and DES Y3 metacalibration weak-lensing shear in four redshift bins, using the estimator in Eq. (4.1). It fits phenomenological power-law and log-parabola halo-model templates (Eqs. 2.2-2.3) and a physical blazar model based on the GLF of Ref. [27] and the halo mass-luminosity relation of Ref. [4]. The authors report a detection at SNR=8.9 (log-parabola) and Delta chi^2=78.9 over null, with the significance concentrated at large angular scales and high energy; they report a preference for log-parabolic over power-law energy spectrum (Delta chi^2 ~ 27). They interpret the signal as blazars in ~1e14 M_sun halos contributing 30-40% of the UGRB above 10 GeV. Appendices treat star-forming galaxies, misaligned AGNs, and WIMP dark matter.

Significance. The pipeline is unusually thorough: blinding, B-mode null tests, rotated-shape and reshuffled-map controls, quadrant tests, jackknife comparison, and Hartlap-corrected covariance. If the detection holds, it is the first large-scale correlation of the UGRB with matter traced by weak lensing and provides a valuable new probe of the UGRB source populations. However, the headline significance is a matched-filter SNR evaluated at the best-fit model to the same data, which needs calibration, and the blazar halo-mass interpretation is conditional on external GLF and M(L) relations and is partly circular. These issues are fixable in revision and do not undermine the value of the measurement itself.

major comments (3)
  1. [Section 4, Eq. (4.3), Table 2] The quoted SNR_mod is computed with Eq. (4.3) evaluated at the best-fit parameters P*_mod obtained from the same data vector used to compute Xi_data. This "matched filter at the best fit" is known to overstate significance because the template is optimized on the noise realization. The blinded null tests in Appendix E show that the estimator does not produce spurious detections for a fixed model, but they do not calibrate the distribution of SNR_mod under the null when the model parameters are fitted. Please provide the null distribution of SNR_mod from the 2000 simulated covariance realizations (or from shape-noise-only maps) and report the resulting p-value, or use a split-sample procedure in which the template is fit on one half and evaluated on the other. This calibration is needed to support the headline "8.9 sigma" claim.
  2. [Section 5, Fig. 8] The inference that unresolved blazars reside in halos of mass ~1e14 M_sun and contribute 30-40% of the UGRB above 10 GeV is not an independent test. With the reference GLF of Ref. [27] and M(L) of Ref. [4], the fit yields A2h_BLZ = 6.59(+0.11,-2.23) (Table 4); the paper states that consistency with Ref. [27] would require A2h_BLZ <~ 2, about 3 sigma lower. The paper then frees M0 and alpha in M(L) and fits them to the same cross-correlation data that produced this tension, obtaining log10 M0 ~ 14.1 and ABLZ ~ 2, and presents this as evidence for cluster-size halos. Because the same data are used to relieve the tension, the fitted M0 is not an independent validation of the model. The 30-40% UGRB fraction and the halo-mass conclusion should either be validated against source counts, UGRB intensity, or UGRB auto-correlation for the generalized M(L), or be explicitly presented as conditional on the external GLF and M(L) relations.
  3. [Section 4, Table 2; Section 5] The Delta chi^2 ~ 27 preference for the log-parabola over the power-law phenomenological model is quoted from best fits without accounting for the two additional free parameters gamma1 and gamma2. Please report an information criterion (AIC/BIC) or a likelihood-ratio test with the appropriate degrees of freedom, and confirm whether the preference survives when the SNR template is fixed a priori. This matters because the claimed spectral curvature drives the discussion of SFG, EBL, and DM interpretations in Section 5 and Appendices B-D.
minor comments (5)
  1. [Fig. 8 caption] In the Fig. 8 caption the generalized M(L) is written with (1+z)^0.9, while the text and the main equation use (1+z)^{-0.9}; the sign typo should be corrected.
  2. [Appendix D] The thermal annihilation cross-section is written as 3e-26 cm^{-2} s^{-1}; the correct units for <sigma v> are cm^3 s^{-1}.
  3. [Abstract and Section 5] "Misalinged" should be "misaligned" in the abstract and in Section 5.
  4. [Fig. 3 caption] The statement about the second angular bin and second-highest energy bin being shown as 2-sigma upper limits with downward arrows is confusing; please specify the exact bins and the convention used for negative measurements.
  5. [Section 3.2] The terms "sourceveto v2" and "ultracleanveto v6" should be typeset consistently (e.g., "SourceVeto v2", "UltracleanVeto v6") for readability.

Circularity Check

0 steps flagged · score 2.0 of 10

No circularity in the 8.9σ cross-correlation measurement; the blazar halo-mass interpretation is a conditional fit, not an independent prediction.

full rationale

The central detection (SNR 8.9, Δχ² ≈ 79) is derived directly from Fermi-LAT and DES Y3 data with a covariance built from shape-noise rotations, Gaussian large-scale structure terms, and blinded null tests (Appendix E); none of these steps presupposes the blazar model or the halo-mass result. The physical interpretation in Section 5 is model-dependent: the reference blazar GLF comes from Ref. [27] and the M(L) relation from Ref. [4], both with overlapping authorship, and the paper explicitly fits M0 and α to the same cross-correlation after reporting a 3σ tension in A2h_BLZ. However, this is not a circular derivation. The paper does not claim that M0 is an external prediction; it states 'In order to test this scenario we allow for a more generic M(L) relation... with M0 and α being free parameters', and the conclusion is explicitly conditional: 'if the BLZ-only model is the correct interpretation of our measurement, the weak lensing signal has to be provided by cluster-size halos.' The 30–40% UGRB fraction is likewise taken from Ref. [27], not measured here, and the abstract frames it as 'especially if those contributing... account for approximately 30-40%'. These are parameter estimates under stated astrophysical assumptions, not equations defined in terms of the target claim. The self-citations are to published, external benchmarks (number counts and auto-correlation analyses), and the paper quantifies its disagreement with them rather than using them to forbid alternatives. Therefore no circular step meets the required evidentiary bar, and the detection claim itself is self-contained.

Assumptions & free parameters 13 free parameters · 9 assumptions · 0 invented entities

The measurement itself uses public data and standard estimators, but the interpretation leans on a chain of external models (blazar GLF, M(L), EBL) that are not independently tested here; two of these come from closely related papers by the same group, and the key halo mass and UGRB fraction are fitted parameters rather than model-independent measurements.

free parameters (13)
  • A1 (phenomenological PSF-like amplitude) = PL: 17.3e-12; LP: 1.48e-12
    Normalization of the point-spread-function-like term in Eqs. (2.2)-(2.3); fit to the cross-correlation data.
  • A2 (phenomenological 2-halo-like amplitude) = PL: 0.077; LP: 0.20
    Normalization of the large-scale (2-halo-like) term in Eqs. (2.2)-(2.3); drives the large-scale SNR.
  • alpha1, alpha2 (phenomenological spectral indices) = PL: 2.13, 2.01; LP: 0.87, 1.94
    Energy power-law slopes of the two angular components in Eqs. (2.2)-(2.3).
  • beta1, beta2 (redshift evolution indices) = PL: 4.63, 4.83; LP: 5.17, 4.83
    Redshift scaling (1+z)^beta of the two components in Eqs. (2.2)-(2.3).
  • gamma1, gamma2 (log-parabola curvature indices) = LP: 0.073, 1.61
    Curvature terms in Eq. (2.3); the LP model is preferred over PL by Delta chi2 ~27.
  • A1h_BLZ (blazar 1-halo normalization) = 34.17 (68% C.I. [7.51, 49.22])
    Free normalization of the blazar 1-halo term in Eq. (2.9); fitted to the data.
  • A2h_BLZ (blazar 2-halo normalization) = 6.59 (68% C.I. [4.36, 6.70])
    Free normalization of the blazar 2-halo term; about 3 sigma above the value compatible with Ref [27], prompting the M(L) fit.
  • mu_BLZ (blazar spectral index) = 2.07 (68% C.I. [1.91, 2.22])
    Mean photon spectral index of the blazar GLF in Eq. (2.6); fitted with prior [1.5, 3.0].
  • p1 (blazar redshift evolution) = 1.02 (68% C.I. [1.02, 5.46])
    Redshift evolution parameter in Eq. (2.7).
  • M0 (halo mass-luminosity normalization) = log10(M0/Msun) = 14.1 (+0.98/-0.61)
    Normalization of the generalized M(L) relation, fitted in Section 5 to reconcile the large A2h_BLZ; the resulting cluster-scale halo mass is presented as a finding.
  • alpha (halo mass-luminosity slope) = 0.44 (+0.30/-0.34)
    Slope of the generalized M(L) relation, fitted in the same step.
  • ADM (dark matter annihilation amplitude) = 32 (+10/-8) times thermal cross-section
    Amplitude of the WIMP annihilation term in Eq. (D.1), fitted to the data; in tension with dwarf spheroidal constraints.
  • mDM (dark matter particle mass) = 363 (+138/-39.5) GeV
    WIMP mass for the b-bbar annihilation channel, fitted in Appendix D.
assumptions (9)
  • standard math Halo model: all mass resides in virialized halos; 1-halo and 2-halo terms capture small- and large-scale correlations
    Invoked in Section 2 for the phenomenological and physical models, following Cooray and Sheth (2002).
  • standard math Limber approximation and Legendre transform relations between real-space and harmonic-space correlations
    Eqs. (2.1) and (2.4); standard in angular correlation analyses.
  • domain assumption Blazar gamma-ray luminosity function from Ref [27] (BLL 4FGL+CP best fit) describes the unresolved blazar population
    Section 2, Eqs. (2.5)-(2.7); parameters are taken from the authors' earlier work [27], whose best fit was obtained from number counts and auto-correlation.
  • domain assumption Halo mass-luminosity relation M(L) = 2e13 Msun (L/1e47 erg/s)^0.23 (1+z)^-0.9 from Ref [4] connects blazar luminosity to host halo mass
    Section 5; this relation is the anchor for the inferred ~1e14 Msun halos and is later generalized with fitted M0 and alpha.
  • domain assumption Galactic foreground template subtraction (gll_iem_v07) removes Galactic emission without biasing the extragalactic cross-correlation
    Section 3.2; residual Galactic emission could correlate with the DES shear field, though it mostly adds noise.
  • domain assumption DES Y3 metacalibration shear catalog and SOMPZ/WZ redshift distributions are accurate for this cross-correlation
    Section 3.1; the blending shear bias is not propagated (stated as negligible in Section 3.1).
  • ad hoc to paper The log-parabola phenomenological model (Eq. 2.3) is a valid fitting function for the signal's energy curvature
    Introduced to capture the observed curvature; not derived from a physical source model.
  • domain assumption The covariance matrix from 2000 shape-noise realizations plus Gaussian LSS terms, with Hartlap correction, is unbiased
    Appendix A; validated against jackknife and chi2 of cross-shear (430 vs 432 expected).
  • domain assumption The 2-halo term is computed assuming a constant bias ratio embodied in the fitted A2h_BLZ and linear theory
    Section 2; the physical model sets the halo-matter bias normalization as a free parameter.

how reviews work

0 comments
Cite this review

Pith. "Pith review of High-Significance Detection of Correlation Between the Unresolved Gamma-Ray Background and the Large Scale Cosmic Structure." pith.science (2026). https://pith.science/paper/WMLJDBQT

@misc{pith2026250110506,
  author       = {Pith},
  title        = {Pith review of: High-Significance Detection of Correlation Between the Unresolved Gamma-Ray Background and the Large Scale Cosmic Structure},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/WMLJDBQT}},
  note         = {Machine review of arXiv:2501.10506}
}
abstract

Our understanding of the $\gamma$-ray sky has improved dramatically in the past decade, however, the unresolved $\gamma$-ray background (UGRB) still has a potential wealth of information about the faintest $\gamma$-ray sources pervading the Universe. Statistical cross-correlations with tracers of cosmic structure can indirectly identify the populations that most characterize the $\gamma$-ray background. In this study, we analyze the angular correlation between the $\gamma$-ray background and the matter distribution in the Universe as traced by gravitational lensing, leveraging more than a decade of observations from the Fermi-Large Area Telescope (LAT) and 3 years of data from the Dark Energy Survey (DES). We detect a correlation at signal-to-noise ratio of 8.9. Most of the statistical significance comes from large scales, demonstrating, for the first time, that a substantial portion of the UGRB aligns with the mass clustering of the Universe as traced by weak lensing. Blazars provide a plausible explanation for this signal, especially if those contributing to the correlation reside in halos of large mass ($\sim 10^{14} M_{\odot}$) and account for approximately 30-40 % of the UGRB above 10 GeV. Additionally, we observe a preference for a curved $\gamma$-ray energy spectrum, with a log-parabolic shape being favored over a power-law. We also discuss the possibility of modifications to the blazar model and the inclusion of additional $gamma$-ray sources, such as star-forming galaxies or particle dark matter.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Constraints on Annihilating Dark Matter from Gamma-Ray Background-Galaxy Shape Correlations: Model-independent Null Results and Moderate Template-based Signals

    astro-ph.CO 2026-07 accept novelty 5.5 of 10

    Fourier-space gamma-ray–cosmic-shear cross-correlations give model-independent null results that exclude thermal WIMP annihilation for 7–40 GeV masses under high substructure boost and wino-like 2–3 TeV scenarios unde...

Reference graph

Works this paper leans on

89 extracted references · 56 canonical work pages · cited by 1 Pith paper

  1. [27]

    Flat-spectrum radio quasars and bl lacs dominate the anisotropy of the unresolved gamma-ray background

    Michael Korsmeier, Elena Pinetti, Michela Negro, Marco Regis, and Nicolao Fornengo. Flat-spectrum radio quasars and bl lacs dominate the anisotropy of the unresolved gamma-ray background. The Astrophysical Journal, 933(2):221, 2022

  2. [4]

    Tomographic-spectral approach for dark matter detection in the cross-correlation between cosmic shear and diffuse γ-ray emission

    Stefano Camera, Mattia Fornasa, Nicolao Fornengo, and Marco Regis. Tomographic-spectral approach for dark matter detection in the cross-correlation between cosmic shear and diffuse γ-ray emission. Journal of Cosmology and Astroparticle Physics, 2015(06):029, 2015

  3. [1]

    Planck 2018 results-vi

    Nabila Aghanim, Yashar Akrami, Mark Ashdown, Jonathan Aumont, Carlo Baccigalupi, Mario Ballardini, Anthony J Banday, RB Barreiro, Nicola Bartolo, S Basak, et al. Planck 2018 results-vi. cosmological parameters. Astronomy & Astrophysics, 641:A6, 2020

  4. [2]

    Cosmological dark matter annihilations into γ rays: A closer look

    Piero Ullio, Lars Bergstr¨ om, Joakim Edsj¨ o, and Cedric Lacey. Cosmological dark matter annihilations into γ rays: A closer look. Physical Review D, 66(12):123502, 2002

  5. [3]

    A novel approach in the weakly interacting massive particle quest: Cross-correlation of gamma-ray anisotropies and cosmic shear

    Stefano Camera, Mattia Fornasa, Nicolao Fornengo, and Marco Regis. A novel approach in the weakly interacting massive particle quest: Cross-correlation of gamma-ray anisotropies and cosmic shear. The Astrophysical Journal Letters, 771(1):L5, 2013

  6. [5]

    Cross correlation of cosmic shear and extragalactic gamma-ray background: Constraints on the dark matter annihilation cross section

    Masato Shirasaki, Shunsaku Horiuchi, and Naoki Yoshida. Cross correlation of cosmic shear and extragalactic gamma-ray background: Constraints on the dark matter annihilation cross section. Physical Review D, 90(6):063502, 2014

  7. [6]

    Cosmological constraints on dark matter annihilation and decay: Cross-correlation analysis of the extragalactic γ-ray background and cosmic shear

    Masato Shirasaki, Oscar Macias, Shunsaku Horiuchi, Satoshi Shirai, and Naoki Yoshida. Cosmological constraints on dark matter annihilation and decay: Cross-correlation analysis of the extragalactic γ-ray background and cosmic shear. Physical Review D, 94(6):063522, 2016

  8. [7]

    Cross-correlation of weak lensing and gamma rays: implications for the nature of dark matter

    Tilman Tr¨ oster, Stefano Camera, Mattia Fornasa, Marco Regis, Ludovic Van Waerbeke, Joachim Harnois-D´ eraps, Shin’ichiro Ando, Maciej Bilicki, Thomas Erben, Nicolao Fornengo, et al. Cross-correlation of weak lensing and gamma rays: implications for the nature of dark matter. Monthly Notices of the Royal Astronomical Society, 467(3):2706–2722, 2017

Show all 89 references
  1. [8]

    Ammazzalorso et al

    S. Ammazzalorso et al. Detection of Cross-Correlation between Gravitational Lensing and γ Rays. Phys. Rev. Lett., 124(10):101102, 2020

  2. [9]

    Tomography of the fermi-lat γ-ray diffuse extragalactic signal via cross correlations with galaxy catalogs

    Jun-Qing Xia, Alessandro Cuoco, Enzo Branchini, and Matteo Viel. Tomography of the fermi-lat γ-ray diffuse extragalactic signal via cross correlations with galaxy catalogs. The Astrophysical Journal Supplement Series, 217(1):15, 2015

  3. [10]

    Particle dark matter searches outside the local group

    Marco Regis, Jun-Qing Xia, Alessandro Cuoco, Enzo Branchini, Nicolao Fornengo, and Matteo Viel. Particle dark matter searches outside the local group. Physical Review Letters, 114(24):241301, 2015

  4. [11]

    Dark matter searches in the gamma-ray extragalactic background via cross-correlations with galaxy catalogs

    Alessandro Cuoco, Jun-Qing Xia, Marco Regis, Enzo Branchini, Nicolao Fornengo, and Matteo Viel. Dark matter searches in the gamma-ray extragalactic background via cross-correlations with galaxy catalogs. The Astrophysical Journal Supplement Series, 221(2):29, 2015

  5. [12]

    Cross-correlation of the extragalactic gamma-ray background with luminous red galaxies

    Masato Shirasaki, Shunsaku Horiuchi, and Naoki Yoshida. Cross-correlation of the extragalactic gamma-ray background with luminous red galaxies. Physical Review D, 92(12):123540, 2015

  6. [13]

    Tomographic imaging of the fermi-lat γ-ray sky through cross-correlations: A wider and deeper look

    Alessandro Cuoco, Maciej Bilicki, Jun-Qing Xia, and Enzo Branchini. Tomographic imaging of the fermi-lat γ-ray sky through cross-correlations: A wider and deeper look. The Astrophysical Journal Supplement Series, 232(1):10, 2017

  7. [14]

    Characterizing the local gamma-ray Universe via angular cross-correlations

    Simone Ammazzalorso, Nicolao Fornengo, Shunsaku Horiuchi, and Marco Regis. Characterizing the local gamma-ray Universe via angular cross-correlations. Phys. Rev. D, 98(10):103007, 2018

  8. [15]

    Constraints on dark matter and astrophysics from tomographic γ-ray cross-correlations

    Anya Paopiamsap, David Alonso, Deaglan J Bartlett, and Maciej Bilicki. Constraints on dark matter and astrophysics from tomographic γ-ray cross-correlations. Physical Review D, 109(10):103517, 2024. – 23 –

  9. [16]

    Cross-correlating the γ-ray sky with catalogs of galaxy clusters

    Enzo Branchini, Stefano Camera, Alessandro Cuoco, Nicolao Fornengo, Marco Regis, Matteo Viel, and Jun-Qing Xia. Cross-correlating the γ-ray sky with catalogs of galaxy clusters. The Astrophysical Journal Supplement Series, 228(1):8, 2017

  10. [17]

    Nishizawa

    Masato Shirasaki, Oscar Macias, Shunsaku Horiuchi, Naoki Yoshida, Chien-Hsiu Lee, and Atsushi J. Nishizawa. Correlation of extragalactic γ rays with cosmic matter density distributions from weak gravitational lensing. Physical Review D, 97(12):123015, 2018

  11. [18]

    Measurement of redshift-dependent cross-correlation of hsc clusters and fermi γ-rays

    Daiki Hashimoto, Atsushi J Nishizawa, Masato Shirasaki, Oscar Macias, Shunsaku Horiuchi, Hiroyuki Tashiro, and Masamune Oguri. Measurement of redshift-dependent cross-correlation of hsc clusters and fermi γ-rays. Monthly Notices of the Royal Astronomical Society, 484(4):5256–5...

  12. [19]

    Searching for gamma-ray emission from galaxy clusters at low redshift

    Manuel Colavincenzo, Xiuhui Tan, Simone Ammazzalorso, Stefano Camera, Marco Regis, Jun-Qing Xia, and Nicolao Fornengo. Searching for gamma-ray emission from galaxy clusters at low redshift. Monthly Notices of the Royal Astronomical Society, 491(3):3225–3244, 2020

  13. [20]

    Bounds on wimp dark matter from galaxy clusters at low redshift

    Xiuhui Tan, Manuel Colavincenzo, and Simone Ammazzalorso. Bounds on wimp dark matter from galaxy clusters at low redshift. Monthly Notices of the Royal Astronomical Society, 495(1):114–122, 2020

  14. [21]

    Evidence of cross-correlation between the cmb lensing and the γ-ray sky

    Nicolao Fornengo, Laurence Perotto, Marco Regis, and Stefano Camera. Evidence of cross-correlation between the cmb lensing and the γ-ray sky. The Astrophysical journal letters, 802(1):L1, 2015

  15. [22]

    Mapping dark matter in the gamma-ray sky with galaxy catalogs

    Shin’ichiro Ando, Aur´ elien Benoit-L´ evy, and Eiichiro Komatsu. Mapping dark matter in the gamma-ray sky with galaxy catalogs. Physical Review D, 90(2):023514, 2014

  16. [23]

    Particle dark matter searches in the anisotropic sky

    Nicolao Fornengo and Marco Regis. Particle dark matter searches in the anisotropic sky. Frontiers in Physics, 2:6, 2014

  17. [24]

    Gaskins, Miguel A

    Mattia Fornasa, Alessandro Cuoco, Jes´ us Zavala, Jennifer M. Gaskins, Miguel A. S´ anchez-Conde, German Gomez-Vargas, Eiichiro Komatsu, Tim Linden, Francisco Prada, Fabio Zandanel, et al. Angular power spectrum of the diffuse gamma-ray emission as measured by the fermi large ...

  18. [25]

    Planck lensing and cosmic infrared background cross-correlation with fermi-lat: Tracing dark matter signals in the gamma-ray background

    Chang Feng, Asantha Cooray, and Brian Keating. Planck lensing and cosmic infrared background cross-correlation with fermi-lat: Tracing dark matter signals in the gamma-ray background. The Astrophysical Journal, 836(1):127, 2017

  19. [26]

    Ajello, D

    M. Ajello, D. Gasparrini, Miguel S´ anchez-Conde, G. Zaharijas, M. Gustafsson, J. Cohen-Tanugi, CD Dermer, Yoshiyuki Inoue, D. Hartmann, M. Ackermann, et al. The origin of the extragalactic gamma-ray background and implications for dark matter annihilation. The Astrophysical J...

  20. [28]

    Diehl, T.M.C

    H.T. Diehl, T.M.C. Abbott, J. Annis, R. Armstrong, L. Baruah, A. Bermeo, G. Bernstein, E. Beynon, C. Bruderer, E.J. Buckley-Geer, et al. The dark energy survey and operations: Year 1. In Observatory Operations: Strategies, Processes, and Systems V, volume 9149, pages 332–346. ...

  21. [29]

    Abdollahi et al

    S. Abdollahi et al. F ermiLarge Area Telescope Fourth Source Catalog. Astrophys. J. Suppl., 247(1):33, 2020

  22. [30]

    Blandford, et al

    Soheila Abdollahi, Fabio Acero, Luca Baldini, Jean Ballet, Denis Bastieri, Ronaldo Bellazzini, Bijan Berenji, Alessandra Berretta, Elisabetta Bissaldi, Roger D. Blandford, et al. Incremental fermi large area telescope fourth source catalog. The Astrophysical Journal Supplement...

  23. [31]

    Andrade-Oliveira, Hugo Camacho, O

    Oliver Friedrich, F. Andrade-Oliveira, Hugo Camacho, O. Alves, R. Rosenfeld, J. Sanchez, Xiao Fang, Tim F. Eifler, E. Krause, C. Chang, et al. Dark energy survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit. Monthly Notices of ...

  24. [32]

    Ackermann et al

    M. Ackermann et al. Unresolved Gamma-Ray Sky through its Angular Power Spectrum. Physical Review Letters, 121(24):241101, December 2018

  25. [33]

    Cooray and R

    A. Cooray and R. Sheth. Halo models of large scale structure. Phys. Rep., 372:1–129, December 2002

  26. [34]

    Eisenstein and Wayne Hu

    Daniel J. Eisenstein and Wayne Hu. Power spectra for cold dark matter and its variants. Astrophys. J., 511:5, 1997

  27. [35]

    Mead, and Catherine Heymans

    Marika Asgari, Alexander J. Mead, and Catherine Heymans. The halo model for cosmology: a pedagogical review. arXiv preprint arXiv:2303.08752, 2023

  28. [36]

    Fornengo and M

    N. Fornengo and M. Regis. Particle dark matter searches in the anisotropic sky. Frontiers in Physics, 2:6, 2014

  29. [37]

    T. M. C. Abbott et al. Dark Energy Survey Year 3 results: Cosmological constraints from galaxy clustering and weak lensing. Phys. Rev. D, 105(2):023520, 2022

  30. [38]

    Mukherjee, S.D

    R. Mukherjee, S.D. Bertsch, D.L .and Bloom, B.L. Dingus, J.A. Esposito, C.E. Fichtel, R.C. Hartman, S.D. Hunter, G. Kanbach, D.A. Kniffen, et al. Egret observations of high-energy gamma-ray emission from blazars: an update. The Astrophysical Journal, 490(1):116, 1997

  31. [39]

    Diehl, K

    Brenna Flaugher, H.T. Diehl, K. Honscheid, T.M.C. Abbott, O. Alvarez, R. Angstadt, J.T. Annis, M. Antonik, O. Ballester, L. Beaufore, et al. The dark energy camera. The Astronomical Journal, 150(5):150, 2015

  32. [40]

    Marco Gatti, Erin Sheldon, A. Amon, M. Becker, M. Troxel, A. Choi, Cyrille Doux, Niall MacCrann, A. Navarro-Alsina, Ian Harrison, et al. Dark energy survey year 3 results: weak lensing shape catalogue. Monthly Notices of the Royal Astronomical Society, 504(3):4312–4336, 2021

  33. [41]

    Becker, Jamie McCullough, Alexandra Amon, Daniel Gruen, Michael Jarvis, Ami Choi, Michael A

    Niall MacCrann, Matthew R. Becker, Jamie McCullough, Alexandra Amon, Daniel Gruen, Michael Jarvis, Ami Choi, Michael A. Troxel, Erin Sheldon, Brian Yanny, et al. Dark energy survey y3 results: blending shear and redshift biases in image simulations. Monthly Notices of the Roya...

  34. [42]

    Practical weak-lensing shear measurement with metacalibration

    Erin S Sheldon and Eric M Huff. Practical weak-lensing shear measurement with metacalibration. The Astrophysical Journal, 841(1):24, 2017

  35. [43]

    Metacalibration: direct self-calibration of biases in shear measurement

    Eric Huff and Rachel Mandelbaum. Metacalibration: direct self-calibration of biases in shear measurement. arXiv preprint arXiv:1702.02600, 2017

  36. [44]

    Dark energy survey year 3 results: Photometric data set for cosmology

    Ignacio Sevilla-Noarbe, K Bechtol, M Carrasco Kind, A Carnero Rosell, MR Becker, Alex Drlica-Wagner, RA Gruendl, ES Rykoff, E Sheldon, B Yanny, et al. Dark energy survey year 3 results: Photometric data set for cosmology. The Astrophysical Journal Supplement Series, 254(2):24, 2021

  37. [45]

    Gruen, J

    Romain Buchs, Chris Davis, D. Gruen, J. DeRose, A. Alarcon, G.M. Bernstein, C. S´ anchez, J. Myles, A. Roodman, S. Allen, et al. Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing. Monthly N...

  38. [46]

    Bernstein, A

    Marco Gatti, Giulia Giannini, Gary M. Bernstein, A. Alarcon, Justin Myles, A. Amon, R Cawthon, M Troxel, J. DeRose, S. Everett, et al. Dark energy survey year 3 results: clustering redshifts–calibration of the weak lensing source redshift distributions with redmagic and boss/e...

  39. [47]

    Everett, B

    S. Everett, B. Yanny, N. Kuropatkin, E.M. Huff, Y. Zhang, J. Myles, A. Masegian, J. Elvin-Poole, S. Allam, G.M. Bernstein, et al. Dark energy survey year 3 results: measuring the survey transfer function with balrog. The Astrophysical Journal Supplement Series, 258(1):15, 2022

  40. [48]

    Suchyta, E.M

    E. Suchyta, E.M. Huff, J. Aleksi´ c, P. Melchior, S. Jouvel, N. MacCrann, A.J. Ross, M. Crocce, E. Gaztanaga, K. Honscheid, et al. No galaxy left behind: accurate measurements with the faintest objects in the dark energy survey. Monthly Notices of the Royal Astronomical Societ...

  41. [49]

    Dark energy survey year 3 results: Exploiting small-scale information with lensing shear ratios

    Carles S´ anchez, Judit Prat, G Zacharegkas, S Pandey, E Baxter, GM Bernstein, J Blazek, R Cawthon, C Chang, E Krause, et al. Dark energy survey year 3 results: Exploiting small-scale information with lensing shear ratios. Physical Review D, 105(8):083529, 2022

  42. [50]

    Dark energy survey year 3 results: redshift calibration of the weak lensing source galaxies

    Justin Myles, Alex Alarcon, Alexandra Amon, Carles S´ anchez, Spencer Everett, Joseph DeRose, J McCullough, Daniel Gruen, Gary M Bernstein, Michael A Troxel, et al. Dark energy survey year 3 results: redshift calibration of the weak lensing source galaxies. Monthly Notices of ...

  43. [51]

    McCullough, A

    J. McCullough, A. Amon, E. Legnani, D. Gruen, A. Roodman, O. Friedrich, N. MacCrann, M.R. Becker, J. Myles, S. Dodelson, et al. Dark energy survey year 3: Blue shear. arXiv preprint arXiv:2410.22272, 2024

  44. [52]

    Dark energy survey year 3 results: Curved-sky weak lensing mass map reconstruction

    Niall Jeffrey, Marco Gatti, Chihway Chang, Lorne Whiteway, Umut Demirbozan, Andr´ as Kov´ acs, Giorgia Pollina, David Bacon, Nico Hamaus, Tomasz Kacprzak, et al. Dark energy survey year 3 results: Curved-sky weak lensing mass map reconstruction. Monthly Notices of the Royal As...

  45. [53]

    Ackermann et al

    M. Ackermann et al. THE SPECTRUM OF ISOTROPIC DIFFUSE GAMMA-RAY EMISSION BETWEEN 100 MeV AND 820 GeV. The Astrophysical Journal, 799(1):86, jan 2015

  46. [54]

    Gorski, Eric Hivon, Anthony J

    Krzysztof M. Gorski, Eric Hivon, Anthony J. Banday, Benjamin D. Wandelt, Frode K. Hansen, Mstvos Reinecke, and Matthia Bartelmann. Healpix: A framework for high-resolution discretization and fast analysis of data distributed on the sphere. The Astrophysical Journal, 622(2):759, 2005

  47. [55]

    Friedrich, E

    Daniel Gruen, O. Friedrich, E. Krause, J. DeRose, R. Cawthon, C. Davis, J. Elvin-Poole, E.S. Rykoff, R.H. Wechsler, A. Alarcon, et al. Density split statistics: Cosmological constraints from counts and lensing in cells in des y1 and sdss data. Physical Review D, 98(2):023507, 2018

  48. [56]

    Galaxy–galaxy lensing estimators and their covariance properties

    Sukhdeep Singh, Rachel Mandelbaum, Uroˇ s Seljak, Anˇ ze Slosar, and Jose Vazquez Gonzalez. Galaxy–galaxy lensing estimators and their covariance properties. Monthly Notices of the Royal Astronomical Society, 471(4):3827–3844, 2017

  49. [57]

    The skewness of the aperture mass statistic

    Mike Jarvis, Gary Bernstein, and Bhuvnesh Jain. The skewness of the aperture mass statistic. Monthly Notices of the Royal Astronomical Society, 352(1):338–352, 2004

  50. [58]

    Treecorr: Two-point correlation functions

    Mike Jarvis. Treecorr: Two-point correlation functions. Astrophysics Source Code Library, pages ascl–1508, 2015

  51. [59]

    Hogg, Dustin Lang, and Jonathan Goodman

    Daniel Foreman-Mackey, David W. Hogg, Dustin Lang, and Jonathan Goodman. emcee: the mcmc hammer. Publications of the Astronomical Society of the Pacific, 125(925):306, 2013

  52. [60]

    Samuel R. Hinton. Chainconsumer. The Journal of Open Source Software, 1(4):00045, 2016

  53. [61]

    Ensemble samplers with affine invariance

    Jonathan Goodman and Jonathan Weare. Ensemble samplers with affine invariance. Communications in applied mathematics and computational science, 5(1):65–80, 2010

  54. [62]

    Becker, M.A

    Matthew R. Becker, M.A. Troxel, N. MacCrann, E. Krause, T.F. Eifler, O. Friedrich, A. Nicola, A. Refregier, A. Amara, D. Bacon, et al. Cosmic shear measurements with dark energy survey science verification data. Physical Review D, 94(2):022002, 2016. – 26 –

  55. [63]

    Ackermann et al

    M. Ackermann et al. The spectrum of isotropic diffuse gamma-ray emission between 100 MeV and 820 GeV. Astrophys. J., 799:86, 2015

  56. [64]

    Tev emission from gamma ray bursts, checking the hadronic model

    Dafne Guetta, Silvia Gagliardini, Silvia Celli, Angela Zegarelli, Antonio Capone, Stefano Campion, and Irene DiPalma. Tev emission from gamma ray bursts, checking the hadronic model. In EPJ Web of Conferences, volume 280, page 01005. EDP Sciences, 2023

  57. [65]

    Contribution of γ-ray burst afterglow emissions to the isotropic diffuse γ-ray background

    Fang-Sheng Min, Yu-Hua Yao, Ruo-Yu Liu, Shi Chen, Hong Lu, and Yi-Qing Guo. Contribution of γ-ray burst afterglow emissions to the isotropic diffuse γ-ray background. The Astrophysical Journal, 964(2):195, 2024

  58. [66]

    Contribution of high-energy grb emissions to the spectrum of the isotropic diffuse γ-ray background

    Yu-Hua Yao, Xiao-Chuan Chang, Hong-Bo Hu, Yi-Bin Pan, Hai-Ming Zhang, Hua-Yang Li, Bing-Qiang Qiao, Ming-Ming Kang, Chao-Wen Yang, Wei Liu, et al. Contribution of high-energy grb emissions to the spectrum of the isotropic diffuse γ-ray background. The Astrophysical Journal, 90...

  59. [67]

    Roth, Mark R

    Matt A. Roth, Mark R. Krumholz, Roland M. Crocker, and Silvia Celli. The diffuse γ-ray background is dominated by star-forming galaxies. Nature, 597(7876):341–344, 2021

  60. [68]

    Ajello et al

    M. Ajello et al. 3FHL: The Third Catalog of Hard Fermi-LAT Sources. Astrophys. J. Suppl., 232(2):18, 2017

  61. [69]

    de Gouveia Dal Pino, and Klaus Dolag

    Saqib Hussain, Rafael Alves Batista, Elisabete M. de Gouveia Dal Pino, and Klaus Dolag. The diffuse gamma-ray flux from clusters of galaxies. Nature Communications, 14(1):2486, 2023

  62. [70]

    Extragalactic background light measurements and applications

    Asantha Cooray. Extragalactic background light measurements and applications. Royal Society Open Science, 3(3):150555, 2016

  63. [71]

    J. D. Finke, S. Razzaque, and C. D. Dermer. Modeling the Extragalactic Background Light from Stars and Dust. ApJ, 712:238–249, March 2010

  64. [72]

    Finke, Marco Ajello, Alberto Dominguez, Abhishek Desai, Dieter H

    Justin D. Finke, Marco Ajello, Alberto Dominguez, Abhishek Desai, Dieter H. Hartmann, Vaidehi S. Paliya, and Alberto Saldana-Lopez. Modeling the Extragalactic Background Light and the Cosmic Star Formation History. Astrophys. J., 941(1):33, 2022

  65. [73]

    Stecker, Sean T

    Floyd W. Stecker, Sean T. Scully, and Matthew A. Malkan. An Empirical Determination of the Intergalactic Background Light from UV to FIR Wavelengths Using FIR Deep Galaxy Surveys and the Gamma-ray Opacity of the Universe. Astrophys. J., 827(1):6, 2016. [Erratum: Astrophys.J. 8...

  66. [74]

    Cross-correlating the γ-ray sky with Catalogs of Galaxy Clusters

    Enzo Branchini, Stefano Camera, Alessandro Cuoco, Nicolao Fornengo, Marco Regis, Matteo Viel, and Jun-Qing Xia. Cross-correlating the γ-ray sky with Catalogs of Galaxy Clusters. Astrophys. J. Suppl., 228(1):8, 2017

  67. [75]

    Searching for gamma-ray emission from galaxy clusters at low redshift

    Manuel Colavincenzo, Xiuhui Tan, Simone Ammazzalorso, Stefano Camera, Marco Regis, Jun-Qing Xia, and Nicolao Fornengo. Searching for gamma-ray emission from galaxy clusters at low redshift. Mon. Not. Roy. Astron. Soc., 491(3):3225–3244, 2020

  68. [76]

    Clustering of γ-ray selected 2LAC Fermi Blazars

    Viola Allevato, Alexis Finoguenov, and Nico Cappelluti. Clustering of γ-ray selected 2LAC Fermi Blazars. Astrophys. J., 797(2):96, 2014

  69. [77]

    Cosmology from cosmic shear power spectra with subaru hyper suprime-cam first-year data

    Chiaki Hikage, Masamune Oguri, Takashi Hamana, Surhud More, Rachel Mandelbaum, Masahiro Takada, Fabian K¨ ohlinger, Hironao Miyatake, Atsushi J Nishizawa, Hiroaki Aihara, et al. Cosmology from cosmic shear power spectra with subaru hyper suprime-cam first-year data. Publicatio...

  70. [78]

    Constraints on the mass–richness relation from the abundance and weak lensing of sdss clusters

    Ryoma Murata, Takahiro Nishimichi, Masahiro Takada, Hironao Miyatake, Masato Shirasaki, Surhud More, Ryuichi Takahashi, and Ken Osato. Constraints on the mass–richness relation from the abundance and weak lensing of sdss clusters. The Astrophysical Journal, 854(2):120, 2018. – 27 –

  71. [79]

    Hartlap, Patrick Simon, and P

    J. Hartlap, Patrick Simon, and P. Schneider. Why your model parameter confidences might be too optimistic. unbiased estimation of the inverse covariance matrix. Astronomy & Astrophysics, 464(1):399–404, 2007

  72. [80]

    Blazek, C

    Judit Prat, J. Blazek, C. S´ anchez, I. Tutusaus, S. Pandey, J. Elvin-Poole, E. Krause, M.A. Troxel, L.F. Secco, A. Amon, et al. Dark energy survey year 3 results: High-precision measurement and modeling of galaxy-galaxy lensing. Physical Review D, 105(8):083528, 2022

  73. [81]

    Troxel, Elisabeth Krause, Chihway Chang, Tim F

    Michael A. Troxel, Elisabeth Krause, Chihway Chang, Tim F. Eifler, Oliver Friedrich, Daniel Gruen, Niall MacCrann, A. Chen, Christopher Davis, Joseph DeRose, et al. Survey geometry and the internal consistency of recent cosmic shear measurements. Monthly Notices of the Royal A...

  74. [82]

    The extragalactic gamma-ray background from core-dominated radio galaxies

    Floyd W Stecker, Chris R Shrader, and Matthew A Malkan. The extragalactic gamma-ray background from core-dominated radio galaxies. The Astrophysical Journal, 879(2):68, 2019

  75. [83]

    Determining the core radio luminosity function of radio agns via copula

    Zunli Yuan, Jiancheng Wang, DM Worrall, Bin-Bin Zhang, and Jirong Mao. Determining the core radio luminosity function of radio agns via copula. The Astrophysical Journal Supplement Series, 239(2):33, 2018

  76. [84]

    Flat-spectrum Radio Quasars and BL Lacs Dominate the Anisotropy of the Unresolved Gamma-Ray Background

    Michael Korsmeier, Elena Pinetti, Michela Negro, Marco Regis, and Nicolao Fornengo. Flat-spectrum Radio Quasars and BL Lacs Dominate the Anisotropy of the Unresolved Gamma-Ray Background. ApJ, 933(2):221, July 2022

  77. [85]

    Ackermann, A

    M. Ackermann, A. Albert, Brandon Anderson, W.B. Atwood, Luca Baldini, G. Barbiellini, Denis Bastieri, K. Bechtol, R. Bellazzini, E. Bissaldi, et al. Searching for dark matter annihilation from milky way dwarf spheroidal galaxies with six years of fermi large area telescope dat...

  78. [86]

    The EMU view of the Large Magellanic Cloud: troubles for sub-TeV WIMPs

    Marco Regis et al. The EMU view of the Large Magellanic Cloud: troubles for sub-TeV WIMPs. JCAP, 11(11):046, 2021

  79. [87]

    Limits on dark matter annihilation signals from the fermi lat 4-year measurement of the isotropic gamma-ray background

    Fermi LAT Collaboration et al. Limits on dark matter annihilation signals from the fermi lat 4-year measurement of the isotropic gamma-ray background. Journal of Cosmology and Astroparticle Physics, 2015(09):008, 2015. A Covariance matrix The covariance matrix used for the pre...

  80. [88]

    for an example of its use in nondiagonal covariances). Using the simulated covariance, the cross-shear measurements returned a chi-squared value of 430, indicating a very close (<1σ) agreement with the expected value of 432 for the noise component that is represented by the cr...

  81. [89]

    Only Z shows a large preference for the models, with X and Y compatible with null signals

    We find that W, X, and Y yield extremely low SNRs and ∆ χ2 values, while Z has values W X Y Z ∆χ2 2.07 4.78 3.36 78.64 SNR 1.44 2.19 1.83 8.86 T able 5: The SNR and ∆ χ2 results for the log-parabola phenomenological model with respect to the null hypothesis for each data vecto...

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.