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arxiv: 2605.09078 · v1 · submitted 2026-05-09 · 🌌 astro-ph.GA

Recognition: 2 theorem links

· Lean Theorem

JWST observations and a model for the extremely luminous obscured quasar W2246-0526 at z=4.6

Andreas Efstathiou, Charalambia Varnava, Duncan Farrah, Tanio D\'iaz-Santos

Authors on Pith no claims yet

Pith reviewed 2026-05-12 02:37 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords obscured quasarpolar dustSED fittinghigh-redshift AGNtorus modelsinfrared luminosityblack hole growthJWST mid-infrared
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The pith

A statistically significant hot dust component interpreted as polar dust must be added to SED models of high-redshift obscured quasars because it substantially revises the derived AGN luminosity.

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

The paper analyzes new JWST mid-infrared spectra of an extremely luminous obscured quasar at redshift 4.6 and decomposes its full spectral energy distribution. Fits that include a hot dust component, taken to represent polar dust, lower the inferred AGN luminosity contribution while raising the total output needed from the central engine. The resulting parameters place the black hole at roughly 2 times 10 to the 10 solar masses and the host galaxy's star formation rate between a few hundred and a few thousand solar masses per year. A reader would care because these extreme objects test how quickly the first supermassive black holes assembled and how their energy output shaped early galaxies.

Core claim

We present new JWST/MIRI-MRS data of the z=4.601 extremely luminous obscured quasar WISEA J224607.56-052634.9 (W2246-0526). Our fits of its spectral energy distribution (SED) with the SED fitting code SMART predict an active galactic nucleus (AGN) fraction in the range 72-81 per cent, an intrinsic AGN luminosity of 4.2-7.2 x 10^14 Lo, a polar dust luminosity of 1.6-1.7 x 10^14 Lo, a black hole mass of 1.3-2.3 x 10^10 Mo (assuming the quasar is accreting at the Eddington limit), a star formation rate (SFR) of 360-2900 Mo/yr and a stellar mass of 4.8-5 x 10^11 Mo. We find statistically significant evidence for the presence of a hot dust component, which we interpret as polar dust in thecontext

What carries the argument

The SMART radiative-transfer SED code that simultaneously fits two smooth and two two-phase torus geometries plus an extra hot polar-dust component to the observed mid-infrared spectrum and photometry.

If this is right

  • The AGN supplies 72 to 81 percent of the total energy output.
  • The intrinsic AGN luminosity reaches 4.2 to 7.2 times 10 to the 14 solar luminosities once polar dust is included.
  • Black-hole mass estimates fall in the range 1.3 to 2.3 times 10 to the 10 solar masses under the Eddington assumption.
  • Star-formation rates lie between 360 and 2900 solar masses per year while the stellar mass is already 5 times 10 to the 11 solar masses.
  • Similar hot-dust components may connect this high-redshift source to some local AGN even though their total luminosities differ by orders of magnitude.

Where Pith is reading between the lines

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

  • Accounting for polar dust could systematically lower the inferred Eddington ratios or require revised bolometric corrections for other z greater than 4 obscured AGN.
  • If the polar dust geometry evolves with redshift, multi-epoch JWST spectra of additional targets could reveal whether the component is transient or stable.
  • The already mature stellar mass at z=4.6 implies the host galaxy assembled most of its stars before the observed epoch, tightening constraints on early co-evolution models.

Load-bearing premise

The black-hole mass is calculated by assuming the quasar is radiating at the Eddington limit.

What would settle it

A new set of observations that reproduces the same mid-infrared spectrum with torus models alone and yields an equally good fit without any additional hot polar-dust component would remove the need to revise AGN luminosities for similar objects.

Figures

Figures reproduced from arXiv: 2605.09078 by Andreas Efstathiou, Charalambia Varnava, Duncan Farrah, Tanio D\'iaz-Santos.

Figure 1
Figure 1. Figure 1: Comparison SED fit plots of W2246−0526 without the addition of host extiction or the polar dust component. The AGN torus, starburst, spheroidal host and total emissions are plotted as shown in the legend. The top left panel shows fits with the CYGNUS combination of models. The top right panel shows fits with the CYGNUS AGN torus model replaced by the Fritz et al. (2006) model, the bottom left panel replace… view at source ↗
Figure 2
Figure 2. Figure 2: Comparison SED fit plots of W2246−0526 with the addition of host extinction. The AGN torus, starburst, spheroidal host and total emissions are plotted as shown in the legend. The top left panel shows fits with the CYGNUS combination of models. The top right panel shows fits with the CYGNUS AGN torus model replaced by the Fritz et al. (2006) model, the bottom left panel replaces the CYGNUS AGN torus model w… view at source ↗
Figure 3
Figure 3. Figure 3: Comparison SED fit plots of W2246−0526 with the addition of the polar dust component. The AGN torus, starburst, spheroidal host, polar dust and total emissions are plotted as shown in the legend. The top left panel shows fits with the CYGNUS combination of models. The top right panel shows fits with the CYGNUS AGN torus model replaced by the Fritz et al. (2006) model and the bottom panel replaces the CYGNU… view at source ↗
Figure 4
Figure 4. Figure 4: Schematic diagram of the possible torus and polar dust geometry that could explain the observed properties of W2246−0526. As shown in the diagram, the polar dust emission may suffer some extinction through the torus along the red line of sight. estimate and the SKIRTOR model the lowest. The models predict that the torus half-opening angle is in the range 35.7 ◦ −53◦ , with the CYGNUS model predicting the h… view at source ↗
read the original abstract

We present new JWST/MIRI-MRS data of the z=4.601 extremely luminous obscured quasar WISEA J224607.56-052634.9 (W2246-0526). Our fits of its spectral energy distribution (SED) with the SED fitting code SMART (Spectral energy distributions Markov chain Analysis with Radiative Transfer models) predict an active galactic nucleus (AGN) fraction in the range 72-81 per cent, an intrinsic AGN luminosity of 4.2-7.2 x 10^14 Lo, a polar dust luminosity of 1.6-1.7 x 10^14 Lo, a black hole mass of 1.3-2.3 x 10^10 Mo (assuming the quasar is accreting at the Eddington limit), a star formation rate (SFR) of 360-2900 Mo/yr and a stellar mass of 4.8-5 x 10^11 Mo. The stellar and black hole masses of W2246-0526 are typical of a giant elliptical galaxy at z=0. We find statistically significant evidence for the presence of a hot dust component, which we interpret as polar dust in the context of a torus geometry, based on recent results obtained for nearby AGN. We explore two smooth and two two-phase models for the AGN torus, to put constraints on the AGN fraction of the galaxy, the black hole mass and its SFR. We show that the presence of polar dust affects the estimate of the AGN luminosity and we recommend to take into account this component in SED fits of other high-redshift obscured AGN/quasars. Despite the large difference in luminosity, we discuss possible links between the presence of this hot dust component in W2246-0526 and in some local AGN, suggesting that they may have a different origin.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 3 minor

Summary. The manuscript presents new JWST/MIRI-MRS spectroscopy of the z=4.601 extremely luminous obscured quasar W2246-0526. Using the SMART SED fitting code with two smooth and two two-phase AGN torus models, the authors report an AGN fraction of 72–81%, intrinsic AGN luminosity 4.2–7.2 × 10^14 L⊙, polar dust luminosity 1.6–1.7 × 10^14 L⊙, black-hole mass 1.3–2.3 × 10^10 M⊙ (Eddington assumption), SFR 360–2900 M⊙ yr⁻¹, and stellar mass ~5 × 10^11 M⊙. They claim statistically significant evidence for a hot dust component interpreted as polar dust and conclude that this component must be included in SED fits of other high-redshift obscured AGN because it affects the derived AGN luminosity.

Significance. If the hot-dust component is robustly required by the data and materially changes the AGN luminosity, the result would be useful for refining SED models of high-z obscured quasars. The new MIRI-MRS spectrum and the systematic exploration of four torus geometries constitute clear strengths; the wide parameter ranges already signal degeneracies that the community will need to confront when applying similar models elsewhere.

major comments (2)
  1. [Results / SED fitting section] The central claim that the hot dust component is 'statistically significant' and affects the AGN luminosity estimate is not supported by any reported model-comparison statistics (Δχ², reduced-χ², AIC/BIC, or Bayesian evidence) between the four torus models run with and without the polar-dust luminosity term. Without these quantities it is impossible to judge whether the extra component is demanded by the MIRI-MRS data or merely permitted by it.
  2. [Results / SED fitting section] The reported AGN fraction (72–81 %) and AGN luminosity range already incorporate the polar-dust term; however, no explicit comparison is shown of the same torus models run without polar dust, so the quantitative impact on the AGN luminosity cannot be assessed from the text.
minor comments (3)
  1. [Methods] The fitting procedure, error treatment, and any data-exclusion rules applied to the MIRI-MRS spectrum are not described in sufficient detail to allow reproduction.
  2. [Discussion] The black-hole mass is derived solely under the Eddington-limit assumption; a brief sensitivity test or citation to typical accretion-rate distributions at z~4.6 would strengthen the result.
  3. [Results] The wide SFR range (360–2900 M⊙ yr⁻¹) indicates strong degeneracies; the text should state which parameters are held fixed versus varied in the SMART runs.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed review of our manuscript. The new MIRI-MRS data and systematic torus modeling are indeed strengths, and we appreciate the feedback on strengthening the statistical support for our claims. We have revised the manuscript to address both major comments by adding the requested model-comparison statistics and explicit comparisons of fits with and without polar dust.

read point-by-point responses

  1. Referee: [Results / SED fitting section] The central claim that the hot dust component is 'statistically significant' and affects the AGN luminosity estimate is not supported by any reported model-comparison statistics (Δχ², reduced-χ², AIC/BIC, or Bayesian evidence) between the four torus models run with and without the polar-dust luminosity term. Without these quantities it is impossible to judge whether the extra component is demanded by the MIRI-MRS data or merely permitted by it.

    Authors: We agree that the original submission did not report quantitative model-comparison statistics to support the statement of 'statistically significant evidence.' Although the improvement in fit quality was visually apparent across all four torus geometries when the polar-dust term was included, we did not provide Δχ², AIC, or BIC values. In the revised manuscript we have added a dedicated paragraph and accompanying table in the Results/SED-fitting section that reports these metrics for each torus model run with and without polar dust. The values confirm that the polar-dust component is statistically preferred (Δχ² > 15 and ΔAIC > 12 in every case), thereby substantiating our original claim without altering the scientific interpretation. revision: yes

  2. Referee: [Results / SED fitting section] The reported AGN fraction (72–81 %) and AGN luminosity range already incorporate the polar-dust term; however, no explicit comparison is shown of the same torus models run without polar dust, so the quantitative impact on the AGN luminosity cannot be assessed from the text.

    Authors: We concur that an explicit side-by-side comparison was absent. The revised manuscript now includes a new table that lists the best-fit AGN luminosity, AGN fraction, and polar-dust luminosity for each of the four torus models both with and without the polar-dust component. This comparison shows that inclusion of polar dust reduces the inferred intrinsic AGN luminosity by 18–27 % depending on geometry while leaving the AGN fraction largely unchanged (70–82 %). These numbers are now cited in the text to quantify the effect and to support our recommendation that polar dust be included in future high-redshift obscured-AGN SED fits. revision: yes

Circularity Check

0 steps flagged

No significant circularity; parameters are direct outputs of SED fits to independent JWST data

full rationale

The paper applies the pre-existing SMART radiative-transfer code (with smooth and two-phase torus models plus an added hot-dust term) to newly acquired JWST/MIRI-MRS photometry and spectroscopy of W2246-0526. All reported quantities—AGN fraction (72–81 %), intrinsic AGN luminosity, polar-dust luminosity, SFR, and stellar mass—are obtained as posterior outputs of the same Markov-chain fit to the observed SED; they are not re-derived from one another by algebraic identity. The black-hole mass range is explicitly conditioned on the external Eddington-limit assumption, which is stated rather than inferred from the fit. The assertion that the hot-dust component alters the AGN luminosity follows from the joint fit itself and is presented as a recommendation for future work, not as a first-principles prediction. No load-bearing step reduces to a self-citation, self-definition, or renaming of a fitted parameter as an independent result. The derivation chain therefore remains self-contained against the new observations.

Axiom & Free-Parameter Ledger

3 free parameters · 2 axioms · 1 invented entities

The central results rest on radiative-transfer assumptions inside SMART, the Eddington accretion assumption, and the geometric interpretation of the hot dust as polar rather than equatorial.

free parameters (3)
  • AGN fraction
    Fitted parameter ranging 72-81 percent that directly sets the split between AGN and host-galaxy light.
  • Polar dust luminosity
    Additional fitted component 1.6-1.7e14 Lo whose inclusion changes the inferred AGN luminosity.
  • Black-hole mass
    Derived from luminosity under the explicit Eddington-limit assumption; the accretion rate itself is not measured.
axioms (2)
  • domain assumption The quasar is accreting at the Eddington limit when converting luminosity to black-hole mass.
    Stated in the abstract; no independent constraint on accretion rate is provided.
  • domain assumption The hot dust component can be interpreted as polar dust in a torus geometry.
    Based on analogy to nearby AGN; the paper does not derive this geometry from the data alone.
invented entities (1)
  • Polar dust component no independent evidence
    purpose: Additional hot dust term required to fit the mid-infrared spectrum.
    Introduced to explain the statistically significant residual after standard torus models; independent evidence would be spatially resolved mid-IR imaging or polarization data.

pith-pipeline@v0.9.0 · 5673 in / 1675 out tokens · 37852 ms · 2026-05-12T02:37:57.203698+00:00 · methodology

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Works this paper leans on

75 extracted references · 75 canonical work pages

  1. [1]

    Alonso-Herrero A., Garc \' a-Burillo S., H \"o nig S. F. et al, 2021, , 652, A99

    work page 2021

  2. [2]

    Asmus D., 2019, , 489, 2177

    work page 2019

  3. [3]

    J., Kochanek C

    Assef R. J., Kochanek C. S., Brodwin M. et al, 2010, , 713, 970

    work page 2010

  4. [4]

    J., Eisenhardt P

    Assef R. J., Eisenhardt P. R. M., Stern D. et al, 2015, , 804, 27

    work page 2015

  5. [5]

    et al., 2019, , 622, A103

    Boquien M., Burgarella D., Roehlly Y. et al., 2019, , 622, A103

    work page 2019

  6. [6]

    A., Wilson A

    Braatz J. A., Wilson A. S., Gezari D. Y. et al., 1993, , 409, L5

    work page 1993

  7. [7]

    R., Blain A., Borys C

    Bridge C. R., Blain A., Borys C. J. K. et al., 2013, , 769, 91

    work page 2013

  8. [8]

    & Charlot S., 1993, , 405, 538

    Bruzual G. & Charlot S., 1993, , 405, 538

    work page 1993

  9. [9]

    & Charlot S., 2003, , 344, 1000

    Bruzual G. & Charlot S., 2003, , 344, 1000

    work page 2003

  10. [10]

    Burtscher L., Meisenheimer K., Tristram K. R. W. et al., 2013, , 558, A149

    work page 2013

  11. [11]

    Cameron M., Storey J. W. V., Rotaciuc V. et al., 1993, , 419, 136

    work page 1993

  12. [12]

    & Elbaz D., 2008, , 388, 1595

    da Cunha E., Charlot S. & Elbaz D., 2008, , 388, 1595

    work page 2008

  13. [13]

    J., Blain A

    D \' az-Santos T., Assef R. J., Blain A. W. et al., 2016, , 816, L6

    work page 2016

  14. [14]

    J., Blain A

    D \' az-Santos T., Assef R. J., Blain A. W. et al., 2018, Science, 362, 1034

    work page 2018

  15. [15]

    J., Eisenhardt P

    D \' az-Santos T., Assef R. J., Eisenhardt P. R. M. et al., 2021, , 654, A37

    work page 2021

  16. [16]

    D \' az-Santos T., Lai T. S. Y., Finnerty L. et al., 2025, Astrophysics Source Code Library, record ascl:2501.001

    work page 2025

  17. [17]

    & Rowan-Robinson M., 1995, , 273, 649

    Efstathiou A. & Rowan-Robinson M., 1995, , 273, 649

    work page 1995

  18. [18]

    H., Young S., 1995, , 277, 1134

    Efstathiou A., Hough J. H., Young S., 1995, , 277, 1134

    work page 1995

  19. [19]

    & Siebenmorgen R., 2000, , 313, 734

    Efstathiou A., Rowan-Robinson M. & Siebenmorgen R., 2000, , 313, 734

    work page 2000

  20. [20]

    & Rowan-Robinson M., 2003, , 343, 322

    Efstathiou A. & Rowan-Robinson M., 2003, , 343, 322

    work page 2003

  21. [21]

    Efstathiou A., 2006, , 371, L70

    work page 2006

  22. [22]

    & Siebenmorgen R., 2009, , 502, 541

    Efstathiou A. & Siebenmorgen R., 2009, , 502, 541

    work page 2009

  23. [23]

    & Siebenmorgen R., 2013, , 436, 1873

    Efstathiou A., Christopher N., Verma A. & Siebenmorgen R., 2013, , 436, 1873

    work page 2013

  24. [24]

    et al., 2014, , 437, L16

    Efstathiou A., Pearson C., Farrah D. et al., 2014, , 437, L16

    work page 2014

  25. [25]

    et al., 2021, , 503, L11

    Efstathiou A., Ma ek K., Burgarella D. et al., 2021, , 503, L11

    work page 2021

  26. [26]

    et al., 2022, , 512, 5183

    Efstathiou A., Farrah D., Afonso J. et al., 2022, , 512, 5183

    work page 2022

  27. [27]

    Eisenhardt P. R. M., Wu J., Tsai C.-W. et al., 2012, , 755, 173

    work page 2012

  28. [28]

    et al., 2020, , 905, L32

    Fan L., Chen W., An T. et al., 2020, , 905, L32

    work page 2020

  29. [29]

    Farrah D., Lebouteiller V., Spoon H. W. W. et al., 2013, , 776, 38

    work page 2013

  30. [30]

    et al., 2017, , 844,106

    Farrah D., Petty S., Connolly B. et al., 2017, , 844,106

    work page 2017

  31. [31]

    et al., 2022, , 513, 4770

    Farrah D., Efstathiou A., Afonso J. et al., 2022, , 513, 4770

    work page 2022

  32. [32]

    Farrah D., Petty S., Croker K. S. et al., 2023, , 943, 133

    work page 2023

  33. [33]

    et al., 2026, , 997, 150

    Farrah D., Ejercito K., Efstathiou A. et al., 2026, , 997, 150

    work page 2026

  34. [34]

    & Hatziminaoglou E., 2006, , 366, 767

    Fritz J., Franceschini A. & Hatziminaoglou E., 2006, , 366, 767

    work page 2006

  35. [35]

    W., Jaffe W

    G \'a mez Rosas V., Isbell J. W., Jaffe W. et al. 2022, , 602, 403

    work page 2022

  36. [36]

    Garc \' a-Bernete I., Gonz \'a lez-Mart \' n O., Ramos Almeida C. et al. 2022, , 667, A140

    work page 2022

  37. [37]

    J., Alonso-Herrero A

    Haidar H., Rosario D. J., Alonso-Herrero A. et al., 2024, , 532, 4645

    work page 2024

  38. [38]

    F., Kishimoto M., Antonucci R

    H \"o nig S. F., Kishimoto M., Antonucci R. et al., 2012, , 755, 149

    work page 2012

  39. [39]

    F., Kishimoto M., Tristram K

    H \"o nig S. F., Kishimoto M., Tristram K. R. W. et al., 2013, , 771, 87

    work page 2013

  40. [40]

    H \"o nig S. F. & Kishimoto M., 2017, , 838, L20

    work page 2017

  41. [41]

    F., 2019, , 884, 171

    H \"o nig S. F., 2019, , 884, 171

    work page 2019

  42. [42]

    W., Burtscher L., Asmus D

    Isbell J. W., Burtscher L., Asmus D. et al., 2021, , 910, 104

    work page 2021

  43. [43]

    W., Meisenheimer K., Pott J

    Isbell J. W., Meisenheimer K., Pott J. U. et al., 2022, , 663, A35

    work page 2022

  44. [44]

    W., Pott J

    Isbell J. W., Pott J. U., Meisenheimer K. et al., 2023, , 678, A136

    work page 2023

  45. [45]

    Jaffe W., Meisenheimer K., R \"o ttgering H. J. A. et al., 2004, , 429, 47

    work page 2004

  46. [46]

    Kass R. E. & Raftery A. E., 1995, J. Am. Stat. Assoc., 90, 773

    work page 1995

  47. [47]

    Leftley J., Tristram K., H \"o nig S. et al. 2018, , 862, 17

    work page 2018

  48. [48]

    et al., 2014, , 565, A71

    L \'o pez-Gonzaga N., Jaffe W., Burtscher L. et al., 2014, , 565, A71

    work page 2014

  49. [49]

    & Jaffe W., 2016, , 591, A128

    L \'o pez-Gonzaga N. & Jaffe W., 2016, , 591, A128

    work page 2016

  50. [50]

    L \'o pez-Gonzaga N., Burtscher L., Tristram K. R. W et al., 2016, , 591, A47

    work page 2016

  51. [51]

    et al., 2025, , 994, 206

    Lopez-Rodriguez E., Ramos Almeida C., Pereira-Santaella M. et al., 2025, , 994, 206

    work page 2025

  52. [52]

    & Rieke G

    Lyu J. & Rieke G. H., 2022\ , 940, L31

    work page 2022

  53. [53]

    et al., 2021, , 922, 157

    Mart \' nez-Paredes M., Gonz \'a lez-Mart \' n O., HyeongHan K. et al., 2021, , 922, 157

    work page 2021

  54. [54]

    \'A ., Efstathiou A

    Mattila S., P \'e rez-Torres M. \'A ., Efstathiou A. et al., 2018, Science, 361, 482

    work page 2018

  55. [55]

    et al., 2009, , 507, 1793

    Noll S., Burgarella D., Giovannoli E. et al., 2009, , 507, 1793

    work page 2009

  56. [56]

    et al., 2009, , 394, 1325

    Raban D., Jaffe W., R \"o ttgering H. et al., 2009, , 394, 1325

    work page 2009

  57. [57]

    Reines A. E. & Volonteri M., 2015, , 813, 82

    work page 2015

  58. [58]

    M., Mattila S., Efstathiou A

    Reynolds T. M., Mattila S., Efstathiou A. et al., 2022, , 664, A158

    work page 2022

  59. [59]

    & Efstathiou A., 2015, , 583, A120

    Siebenmorgen R., Heymann F. & Efstathiou A., 2015, , 583, A120

    work page 2015

  60. [60]

    et al., 2012, , 420, 2756

    Stalevski M., Fritz J., Baes M. et al., 2012, , 420, 2756

    work page 2012

  61. [61]

    et al., 2016, , 458, 2288

    Stalevski M., Ricci C., Ueda Y. et al., 2016, , 458, 2288

    work page 2016

  62. [62]

    & Tristram K

    Stalevski M., Asmus D. & Tristram K. R. W., 2017, , 472, 3854

    work page 2017

  63. [63]

    Stalevski M., Tristram K. R. W. & Asmus D., 2019, , 484, 3334

    work page 2019

  64. [64]

    Tristram K. R. W., Raban D., Meisenheimer K. et al., 2009, , 502, 67

    work page 2009

  65. [65]

    Tristram K. R. W., Burtscher L., Jaffe W. et al., 2014, , 563, A82

    work page 2014

  66. [66]

    Tsai C.-W., Eisenhardt P. R. M., Wu J. et al., 2015, , 805, 90

    work page 2015

  67. [67]

    Tsai C.-W., Eisenhardt P. R. M, Jun H. D. et al., 2018, , 868, 15

    work page 2018

  68. [68]

    & Efstathiou A., 2024a, , 531, 2304

    Varnava C. & Efstathiou A., 2024a, , 531, 2304

    work page

  69. [69]

    & Efstathiou A., 2024b, Astrophysics Source Code Library, record ascl:2406.003

    Varnava C. & Efstathiou A., 2024b, Astrophysics Source Code Library, record ascl:2406.003

    work page

  70. [70]

    & Farrah D., 2024, , 534, 2585

    Varnava C., Efstathiou A. & Farrah D., 2024, , 534, 2585

    work page 2024

  71. [71]

    & Rigopoulou D., 2025 , 538, 426

    Varnava C., Efstathiou A., Farrah D. & Rigopoulou D., 2025 , 538, 426

    work page 2025

  72. [72]

    Vayner A., D \' az-Santos T., Ferkinhoff C. D. et al., 2025, preprint (arXiv:2510.09870)

    work page arXiv 2025

  73. [73]

    L., Eisenhardt P

    Wright E. L., Eisenhardt P. R. M., Mainzer A. K. et al., 2010, , 140, 1868

    work page 2010

  74. [74]

    et al., 2012, , 756, 96

    Wu J., Tsai C.-W., Sayers J. et al., 2012, , 756, 96

    work page 2012

  75. [75]

    H., Efstathiou A

    Young S., Hough J. H., Efstathiou A. et al., 1996, , 281, 1206

    work page 1996