pith. machine review for the scientific record. sign in

arxiv: 2604.14088 · v2 · submitted 2026-04-15 · 🌌 astro-ph.CO · astro-ph.IM

Recognition: unknown

BROOM: a python package for model-independent analysis of microwave astronomical data

Authors on Pith no claims yet

Pith reviewed 2026-05-10 12:28 UTC · model grok-4.3

classification 🌌 astro-ph.CO astro-ph.IM
keywords component separationmicrowave astronomycosmic microwave backgroundinternal linear combinationpython packageforeground removaldata analysis
0
0 comments X

The pith

BROOM package reconstructs CMB and other microwave signals using minimum-variance linear combinations from multi-frequency data.

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

The paper presents BROOM as a Python package that applies blind minimum-variance methods to separate components in microwave astronomical observations. It reconstructs signals with known spectral energy distributions, such as the cosmic microwave background, Sunyaev-Zeldovich effects, and foreground moments, in both temperature and polarization via Internal Linear Combination techniques. The package also enables blind recovery of coherent emission components with unknown properties through a Generalized Internal Linear Combination approach. Users gain additional tools to diagnose foreground complexity, estimate residual contamination across scales, generate realistic simulations, and compute power spectra. A sympathetic reader would care because the software offers an accessible, public way to analyze data from satellite and ground-based experiments while reducing reliance on detailed astrophysical models for contaminants.

Core claim

BROOM implements Internal Linear Combination methods to reconstruct known spectral signals such as the CMB from multi-frequency microwave maps in the presence of astrophysical and instrumental contaminants, and it provides a Generalized ILC framework for blind reconstruction of components with unknown covariance properties, with validation performed on simulations of full-sky satellite missions and ground-based experiments.

What carries the argument

Internal Linear Combination (ILC) and Generalized ILC (GILC) frameworks, which compute minimum-variance weights across frequency channels to isolate a target signal while suppressing contaminants.

Load-bearing premise

The minimum-variance ILC and GILC implementations correctly handle the mixture of astrophysical and instrumental contaminants in real data without introducing significant biases.

What would settle it

Running BROOM on actual satellite or ground-based microwave observations produces reconstructed maps whose measured residual contamination levels differ substantially from the levels obtained in the package's validation simulations.

read the original abstract

We present BROOM, a new python package for the application of blind, minimum-variance component-separation techniques to microwave observations. The package enables the reconstruction of signals with known spectral energy distributions, such as the Cosmic Microwave Background (CMB), Sunyaev--Zeldovich distortions, or foreground moments, in both temperature and polarization through a suite of Internal Linear Combination (ILC) implementations, in the presence of astrophysical and instrumental contaminants. In addition, BROOM supports the blind reconstruction of coherent emission components with unknown covariance properties via a Generalized ILC (GILC) framework. Beyond component separation, the package provides tools to diagnose foreground complexity and to estimate residual contamination leaking into reconstructed maps across angular scales and sky regions. It also includes utilities to generate realistic microwave simulations for arbitrary CMB experiments and to compute angular power spectra of the resulting products. We present a comprehensive description and validation of the implemented pipelines in two representative experimental configurations: a full-sky satellite mission and a ground-based experiment. BROOM is publicly available, fully documented, and easily installable at https://github.com/alecarones/broom

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

1 major / 3 minor

Summary. The manuscript introduces BROOM, a publicly available Python package implementing Internal Linear Combination (ILC) methods for reconstructing signals with known spectral energy distributions (e.g., CMB, Sunyaev-Zeldovich distortions, foreground moments) in temperature and polarization, along with a Generalized ILC (GILC) framework for blind reconstruction of coherent components with unknown covariance. It includes diagnostic tools for foreground complexity and residual contamination, utilities for generating realistic microwave simulations, and angular power spectrum computation. The package is validated through described pipelines on two simulated experimental setups: a full-sky satellite mission and a ground-based experiment.

Significance. If the implementations are correct as described, BROOM provides a documented, open-source tool for model-independent component separation that supports reproducible analyses in CMB and microwave astronomy. Credit is due for the public GitHub availability, full documentation, simulation utilities, and explicit validation on two distinct configurations (full-sky satellite and ground-based). These elements lower barriers for applying ILC/GILC techniques and enable users to assess residuals across scales and regions.

major comments (1)
  1. [Validation section] Validation section: The description of the two experimental setups (full-sky satellite and ground-based) states that validation was performed but does not report quantitative metrics such as residual power spectra, bias levels, or cross-checks against input maps; this weakens the ability to confirm that the minimum-variance ILC and GILC implementations handle mixed astrophysical/instrumental contaminants without significant bias, as asserted in the abstract.
minor comments (3)
  1. [Introduction] The abstract and introduction refer to 'a suite of ILC implementations' without enumerating the specific variants (e.g., standard ILC, constrained ILC) or their distinguishing features in a table or dedicated subsection.
  2. [Methods] Notation for covariance matrices and weight vectors in the GILC framework should be defined explicitly with equations upon first use to aid readers unfamiliar with the extension.
  3. [Figures] Figure captions for any diagnostic plots (e.g., residual contamination vs. angular scale) should include the exact sky region, frequency channels, and simulation parameters used.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their positive assessment of the manuscript and for recommending minor revision. We address the major comment on the validation section below.

read point-by-point responses
  1. Referee: [Validation section] Validation section: The description of the two experimental setups (full-sky satellite and ground-based) states that validation was performed but does not report quantitative metrics such as residual power spectra, bias levels, or cross-checks against input maps; this weakens the ability to confirm that the minimum-variance ILC and GILC implementations handle mixed astrophysical/instrumental contaminants without significant bias, as asserted in the abstract.

    Authors: We agree that the validation section would benefit from explicit quantitative metrics to strengthen the claims regarding the performance of the ILC and GILC methods. In the revised manuscript, we will expand this section to report residual power spectra, bias levels in the reconstructed maps, and direct cross-checks against the input maps for both the full-sky satellite and ground-based setups. These additions will quantify the level of residual contamination across scales and confirm that the implementations recover the target signals without significant bias in the presence of mixed astrophysical and instrumental contaminants. revision: yes

Circularity Check

0 steps flagged

No significant circularity; standard ILC/GILC implementation with separate validation

full rationale

The paper presents BROOM as a software package implementing established Internal Linear Combination (ILC) and Generalized ILC (GILC) techniques for component separation of microwave signals with known or unknown SEDs. No derivation chain is claimed that reduces a prediction or result to its own inputs by construction. The central functionality is described via pipelines, diagnostic tools, simulation utilities, and validation on independent simulated datasets (full-sky satellite and ground-based configurations). No self-definitional equations, fitted parameters renamed as predictions, or load-bearing self-citations that close a loop are present in the provided text. The methods are standard in the field, and the package supplies separate diagnostics rather than deriving results from the same fitted quantities.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The work relies on standard domain assumptions of ILC methods without introducing new free parameters, axioms beyond those in the field, or invented entities.

axioms (1)
  • domain assumption Minimum-variance ILC assumptions including known spectral energy distributions for target signals and uncorrelated contaminants
    Invoked throughout the description of component separation pipelines.

pith-pipeline@v0.9.0 · 5513 in / 1150 out tokens · 26314 ms · 2026-05-10T12:28:16.877681+00:00 · methodology

discussion (0)

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

Reference graph

Works this paper leans on

102 extracted references · 96 canonical work pages · 8 internal anchors

  1. [1]

    Planck 2018 results. VI. Cosmological parameters

    Planck Collaboration, N. Aghanim, Y. Akrami, M. Ashdown, J. Aumont, C. Baccigalupi et al.,Planck 2018 results. VI. Cosmological parameters, A&A641(2020) A6 [1807.06209]

  2. [2]

    The Atacama Cosmology Telescope: DR6 Power Spectra, Likelihoods and $\Lambda$CDM Parameters

    T. Louis, A. La Posta, Z. Atkins, H.T. Jense, I. Abril-Cabezas, G.E. Addison et al.,The Atacama Cosmology Telescope: DR6 Power Spectra, Likelihoods and LCDM Parameters, arXiv e-prints(2025) arXiv:2503.14452 [2503.14452]

  3. [3]

    SPT-3G D1: CMB temperature and polarization power spectra and cosmology from 2019 and 2020 observations of the SPT-3G Main field

    E. Camphuis, W. Quan, L. Balkenhol, A.R. Khalife, F. Ge, F. Guidi et al.,SPT-3G D1: CMB temperature and polarization power spectra and cosmology from 2019 and 2020 observations of the SPT-3G Main field,arXiv e-prints(2025) arXiv:2506.20707 [2506.20707]

  4. [4]

    Kamionkowski, A

    M. Kamionkowski, A. Kosowsky and A. Stebbins,A Probe of Primordial Gravity Waves and Vorticity, Phys.Rev.Lett78(1997) 2058 [astro-ph/9609132]

  5. [5]

    Planck Collaboration, R. Adam, N. Aghanim, M. Ashdown, J. Aumont, C. Baccigalupi et al., Planck intermediate results. XLVII. Planck constraints on reionization history, A&A596 (2016) A108 [1605.03507]

  6. [6]

    Y. Qin, V. Poulin, A. Mesinger, B. Greig, S. Murray and J. Park,Reionization inference from the CMB optical depth and E-mode polarization power spectra, MNRAS499(2020) 550 [2006.16828]

  7. [7]

    Allison, P

    R. Allison, P. Caucal, E. Calabrese, J. Dunkley and T. Louis,Towards a cosmological neutrino mass detection, Phys.Rev.D92(2015) 123535 [1509.07471]

  8. [8]

    Pogosian, M

    L. Pogosian, M. Shimon, M. Mewes and B. Keating,Future CMB constraints on cosmic birefringence and implications for fundamental physics, Phys.Rev.D100(2019) 023507 [1904.07855]

  9. [9]

    Cosmic Birefringence from the Planck Data Release 4,

    P. Diego-Palazuelos, J.R. Eskilt, Y. Minami, M. Tristram, R.M. Sullivan, A.J. Banday et al., Cosmic Birefringence from the Planck Data Release 4, Phys.Rev.Lett128(2022) 091302 [2201.07682]

  10. [10]

    Zaldarriaga and U

    M. Zaldarriaga and U. Seljak,All-sky analysis of polarization in the microwave background, Phys.Rev.D55(1997) 1830 [astro-ph/9609170]

  11. [11]

    Zaldarriaga and U

    M. Zaldarriaga and U. Seljak,Gravitational lensing effect on cosmic microwave background polarization, Phys.Rev.D58(1998) 023003 [astro-ph/9803150]

  12. [12]

    Okamoto and W

    T. Okamoto and W. Hu,Cosmic microwave background lensing reconstruction on the full sky, Phys.Rev.D67(2003) 083002 [astro-ph/0301031]

  13. [13]

    Lewis and A

    A. Lewis and A. Challinor,Weak gravitational lensing of the CMB, Phys.Rep.429(2006) 1 [astro-ph/0601594]. – 70 –

  14. [14]

    P. Ade, J. Aguirre, Z. Ahmed, S. Aiola, A. Ali, D. Alonso et al.,The Simons Observatory: science goals and forecasts, JCAP2019(2019) 056 [1808.07445]

  15. [15]

    Allyset al.(LiteBIRD), PTEP2023, 042F01 (2023), arXiv:2202.02773 [astro-ph.IM]

    LiteBIRD Collaboration, E. Allys, K. Arnold, J. Aumont, R. Aurlien, S. Azzoni et al., Probing cosmic inflation with the LiteBIRD cosmic microwave background polarization survey, Progress of Theoretical and Experimental Physics2023(2023) 042F01 [2202.02773]

  16. [16]

    P.A.R. Ade, Z. Ahmed, M. Amiri, D. Barkats, R.B. Thakur, C.A. Bischoff et al.,Improved Constraints on Primordial Gravitational Waves using Planck, WMAP, and BICEP/Keck Observations through the 2018 Observing Season, Phys.Rev.Lett127(2021) 151301 [2110.00483]

  17. [17]

    Eriksen, J.B

    H.K. Eriksen, J.B. Jewell, C. Dickinson, A.J. Banday, K.M. G´ orski and C.R. Lawrence,Joint Bayesian Component Separation and CMB Power Spectrum Estimation, ApJ676(2008) 10 [0709.1058]

  18. [18]

    Galloway, K.J

    M. Galloway, K.J. Andersen, R. Aurlien, R. Banerji, M. Bersanelli, S. Bertocco et al., BEYONDPLANCK. III. Commander3, A&A675(2023) A3 [2201.03509]

  19. [19]

    Stompor, S

    R. Stompor, S. Leach, F. Stivoli and C. Baccigalupi,Maximum likelihood algorithm for parametric component separation in cosmic microwave background experiments, MNRAS392 (2009) 216 [0804.2645]

  20. [20]

    Azzoni, M.H

    S. Azzoni, M.H. Abitbol, D. Alonso, A. Gough, N. Katayama and T. Matsumura,A minimal power-spectrum-based moment expansion for CMB B-mode searches, JCAP2021(2021) 047 [2011.11575]

  21. [21]

    Vacher, J

    L. Vacher, J. Aumont, L. Montier, S. Azzoni, F. Boulanger and M. Remazeilles,Moment expansion of polarized dust SED: A new path towards capturing the CMB B-modes with LiteBIRD, A&A660(2022) A111 [2111.07742]

  22. [22]

    de la Hoz, P

    E. de la Hoz, P. Vielva, R.B. Barreiro and E. Mart´ ınez-Gonz´ alez,On the detection of CMB B-modes from ground at low frequency, JCAP2020(2020) 006 [2002.12206]

  23. [23]

    Bennett, R.S

    C.L. Bennett, R.S. Hill, G. Hinshaw, M.R. Nolta, N. Odegard, L. Page et al.,First-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Foreground Emission, ApJS 148(2003) 97 [astro-ph/0302208]

  24. [24]

    Delabrouille, J.-F

    J. Delabrouille, J.-F. Cardoso, M. Le Jeune, M. Betoule, G. Fay and F. Guilloux,A full sky, low foreground, high resolution CMB map from WMAP, A&A493(2009) 835 [0807.0773]

  25. [25]

    Delabrouille, J.F

    J. Delabrouille, J.F. Cardoso and G. Patanchon,Multidetector multicomponent spectral matching and applications for cosmic microwave background data analysis, MNRAS346 (2003) 1089 [astro-ph/0211504]

  26. [26]

    Fern´ andez-Cobos, P

    R. Fern´ andez-Cobos, P. Vielva, R.B. Barreiro and E. Mart´ ınez-Gonz´ alez,Multiresolution internal template cleaning: an application to the Wilkinson Microwave Anisotropy Probe 7-yr polarization data, MNRAS420(2012) 2162 [1106.2016]

  27. [27]

    Carones, M

    A. Carones, M. Migliaccio, G. Puglisi, C. Baccigalupi, D. Marinucci, N. Vittorio et al., Multiclustering needlet ILC for CMB B-mode component separation, MNRAS525(2023) 3117 [2212.04456]

  28. [28]

    Delabrouille and J.F

    J. Delabrouille and J.F. Cardoso,Diffuse source separation in CMB observations,arXiv e-prints(2007) astro [astro-ph/0702198]

  29. [29]

    J. Kim, P. Naselsky and P.R. Christensen,CMB polarization map derived from the WMAP 5year data through the harmonic internal linear combination method, Phys.Rev.D79(2009) 023003 [0810.4008]

  30. [30]

    Basak and J

    S. Basak and J. Delabrouille,A needlet internal linear combination analysis of WMAP 7-year data: estimation of CMB temperature map and power spectrum, MNRAS419(2012) 1163 [1106.5383]. – 71 –

  31. [31]

    Akrami et al

    Planck Collaboration, Y. Akrami, M. Ashdown, J. Aumont, C. Baccigalupi, M. Ballardini et al.,Planck 2018 results. IV. Diffuse component separation, A&A641(2020) A4 [1807.06208]

  32. [32]

    Remazeilles, J

    M. Remazeilles, J. Delabrouille and J.-F. Cardoso,Foreground component separation with generalized Internal Linear Combination, MNRAS418(2011) 467 [1103.1166]

  33. [33]

    Aghanim, M

    Planck Collaboration, N. Aghanim, M. Ashdown, J. Aumont, C. Baccigalupi, M. Ballardini et al.,Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies, A&A596(2016) A109 [1605.09387]

  34. [34]

    Fern´ andez-Cobos, A

    R. Fern´ andez-Cobos, A. Marcos-Caballero, P. Vielva, E. Mart´ ınez-Gonz´ alez and R.B. Barreiro,Exploring two-spin internal linear combinations for the recovery of the CMB polarization, MNRAS459(2016) 441 [1601.01515]

  35. [35]

    Adak,A new approach of estimating the galactic thermal dust and synchrotron polarized emission template in the microwave bands, MNRAS507(2021) 4618 [2104.13778]

    D. Adak,A new approach of estimating the galactic thermal dust and synchrotron polarized emission template in the microwave bands, MNRAS507(2021) 4618 [2104.13778]

  36. [36]

    Remazeilles, A

    M. Remazeilles, A. Rotti and J. Chluba,Peeling off foregrounds with the constrained moment ILC method to unveil primordial CMB B modes, MNRAS503(2021) 2478 [2006.08628]

  37. [37]

    Carones and M

    A. Carones and M. Remazeilles,Optimization of foreground moment deprojection for semi-blind CMB polarization reconstruction, JCAP2024(2024) 018 [2402.17579]

  38. [38]

    M., Hivon , E., Banday , A

    K.M. G´ orski, E. Hivon, A.J. Banday, B.D. Wandelt, F.K. Hansen, M. Reinecke et al., HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere, ApJ622(2005) 759 [astro-ph/0409513]

  39. [39]

    Zonca, L

    A. Zonca, L. Singer, D. Lenz, M. Reinecke, C. Rosset, E. Hivon et al.,healpy: equal area pixelization and spherical harmonics transforms for data on the sphere in Python,The Journal of Open Source Software4(2019) 1298

  40. [40]

    Rybicki and A.P

    D.B. Rybicki and A.P. Lightman,Radiative Processes in Astrophysics(1979)

  41. [41]

    Marinucci, D

    D. Marinucci, D. Pietrobon, A. Balbi, P. Baldi, P. Cabella, G. Kerkyacharian et al.,Spherical needlets for cosmic microwave background data analysis, MNRAS383(2008) 539 [0707.0844]

  42. [42]

    Lewis, A

    A. Lewis, A. Challinor and N. Turok,Analysis of CMB polarization on an incomplete sky, Phys.Rev.D65(2001) 023505 [astro-ph/0106536]

  43. [43]

    Carones, M

    A. Carones, M. Migliaccio, D. Marinucci and N. Vittorio,Analysis of Needlet Internal Linear Combination performance on B-mode data from sub-orbital experiments, A&A677(2023) A147 [2208.12059]

  44. [44]

    E.F. Bunn, M. Zaldarriaga, M. Tegmark and A. de Oliveira-Costa,E/B decomposition of finite pixelized CMB maps, Phys.Rev.D67(2003) 023501 [astro-ph/0207338]

  45. [45]

    A unified pseudo-$C_\ell$ framework

    D. Alonso, J. Sanchez, A. Slosar and LSST Dark Energy Science Collaboration,A unified pseudo-Cℓ framework, MNRAS484(2019) 4127 [1809.09603]

  46. [46]

    H. Liu, J. Creswell, S. von Hausegger and P. Naselsky,Methods for pixel domain correction of E B leakage, Phys.Rev.D100(2019) 023538 [1811.04691]

  47. [47]

    Sunyaev and Y.B

    R.A. Sunyaev and Y.B. Zeldovich,The Spectrum of Primordial Radiation, its Distortions and their Significance,Comments on Astrophysics and Space Physics2(1970) 66

  48. [48]

    Sunyaev and Y.B

    R.A. Sunyaev and Y.B. Zeldovich,The Observations of Relic Radiation as a Test of the Nature of X-Ray Radiation from the Clusters of Galaxies,Comments on Astrophysics and Space Physics4(1972) 173

  49. [49]

    Challinor and A

    A. Challinor and A. Lasenby,Relativistic Corrections to the Sunyaev-Zeldovich Effect, ApJ 499(1998) 1 [astro-ph/9711161]

  50. [50]

    Thorne, J

    B. Thorne, J. Dunkley, D. Alonso and S. Næss,The Python Sky Model: software for simulating the Galactic microwave sky, MNRAS469(2017) 2821 [1608.02841]. – 72 –

  51. [51]

    Zonca, B

    A. Zonca, B. Thorne, N. Krachmalnicoff and J. Borrill,The Python Sky Model 3 software, The Journal of Open Source Software6(2021) 3783 [2108.01444]

  52. [52]

    Borrill, S.E

    The Pan-Experiment Galactic Science Group, :, J. Borrill, S.E. Clark, J. Delabrouille, A.V. Frolov et al.,Full-sky Models of Galactic Microwave Emission and Polarization at Sub-arcminute Scales for the Python Sky Model,arXiv e-prints(2025) arXiv:2502.20452 [2502.20452]

  53. [53]

    Krachmalnicoff, E

    N. Krachmalnicoff, E. Carretti, C. Baccigalupi, G. Bernardi, S. Brown, B.M. Gaensler et al., S-PASS view of polarized Galactic synchrotron at 2.3 GHz as a contaminant to CMB observations, A&A618(2018) A166 [1802.01145]

  54. [54]

    Weiland, G.E

    J.L. Weiland, G.E. Addison, C.L. Bennett, M. Halpern and G. Hinshaw,Polarized Synchrotron Foreground Assessment for CMB Experiments, ApJ936(2022) 24 [2203.11445]

  55. [55]

    J., Finkbeiner, D

    D.J. Schlegel, D.P. Finkbeiner and M. Davis,Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds, ApJ 500(1998) 525 [astro-ph/9710327]

  56. [56]

    Dickinson, M

    C. Dickinson, M. Peel and M. Vidal,New constraints on the polarization of anomalous microwave emission in nearby molecular clouds, MNRAS418(2011) L35 [1108.0308]

  57. [57]

    G´ enova-Santos, J.A

    R. G´ enova-Santos, J.A. Rubi˜ no-Mart´ ın, R. Rebolo, A. Pel´ aez-Santos, C.H. L´ opez-Caraballo, S. Harper et al.,QUIJOTE scientific results - I. Measurements of the intensity and polarisation of the anomalous microwave emission in the Perseus molecular complex, MNRAS 452(2015) 4169 [1501.04491]

  58. [58]

    Herman, B

    D. Herman, B. Hensley, K.J. Andersen, R. Aurlien, R. Banerji, M. Bersanelli et al., BEYONDPLANCK. XV. Limits on large-scale polarized anomalous microwave emission from Planck LFI and WMAP, A&A675(2023) A15 [2201.03530]

  59. [59]

    T.M. Dame, D. Hartmann and P. Thaddeus,The Milky Way in Molecular Clouds: A New Complete CO Survey, ApJ547(2001) 792 [astro-ph/0009217]

  60. [60]

    Planck Collaboration, P.A.R. Ade, N. Aghanim, M.I.R. Alves, C. Armitage-Caplan, M. Arnaud et al.,Planck 2013 results. XIII. Galactic CO emission, A&A571(2014) A13 [1303.5073]

  61. [61]

    Spitzer Jr,Physical processes in the interstellar medium, John Wiley & Sons (2008)

    L. Spitzer Jr,Physical processes in the interstellar medium, John Wiley & Sons (2008)

  62. [62]

    Dickinson, R.D

    C. Dickinson, R.D. Davies and R.J. Davis,Towards a free-free template for CMB foregrounds, MNRAS341(2003) 369 [astro-ph/0302024]

  63. [63]

    Hauser and E

    M.G. Hauser and E. Dwek,The Cosmic Infrared Background: Measurements and Implications, ARA&A39(2001) 249 [astro-ph/0105539]

  64. [64]

    Planck Collaboration, P.A.R. Ade, N. Aghanim, C. Armitage-Caplan, M. Arnaud, M. Ashdown et al.,Planck 2013 results. XXX. Cosmic infrared background measurements and implications for star formation, A&A571(2014) A30 [1309.0382]

  65. [65]

    Planck Collaboration, P.A.R. Ade, N. Aghanim, F. Arg¨ ueso, M. Arnaud, M. Ashdown et al., Planck 2015 results. XXVI. The Second Planck Catalogue of Compact Sources, A&A594 (2016) A26 [1507.02058]

  66. [66]

    Puglisi, V

    G. Puglisi, V. Galluzzi, L. Bonavera, J. Gonzalez-Nuevo, A. Lapi, M. Massardi et al., Forecasting the Contribution of Polarized Extragalactic Radio Sources in CMB Observations, ApJ858(2018) 85 [1712.09639]

  67. [67]

    Chluba, J.C

    J. Chluba, J.C. Hill and M.H. Abitbol,Rethinking CMB foregrounds: systematic extension of foreground parametrizations, MNRAS472(2017) 1195 [1701.00274]

  68. [68]

    Jackson and J.V

    C.A. Jackson and J.V. Wall,Radio Galaxy Spectra, inParticles and Fields in Radio Galaxies – 73 – Conference, R.A. Laing and K.M. Blundell, eds., vol. 250 ofAstronomical Society of the Pacific Conference Series, p. 400, Jan., 2001, DOI [astro-ph/0101367]

  69. [69]

    Delabrouille and J.-F

    J. Delabrouille and J.-F. Cardoso,Diffuse Source Separation in CMB Observations, inData Analysis in Cosmology, V.J. Mart´ ınez, E. Saar, E. Mart´ ınez-Gonz´ alez and M.-J. Pons-Border´ ıa, eds., vol. 665 ofLecture Notes in Physics, Berlin Springer Verlag, pp. 159–205, 2009, DOI

  70. [71]

    Remazeilles, J

    M. Remazeilles, J. Delabrouille and J.-F. Cardoso,CMB and SZ effect separation with constrained Internal Linear Combinations, MNRAS410(2011) 2481 [1006.5599]

  71. [72]

    Chandran, M

    J. Chandran, M. Remazeilles and R.B. Barreiro,An improved Compton parameter map of thermal Sunyaev-Zeldovich effect from Planck PR4 data, MNRAS526(2023) 5682 [2305.10193]

  72. [73]

    McCarthy and J

    F. McCarthy and J.C. Hill,Component-separated, CIB-cleaned thermal Sunyaev-Zel’dovich maps from Planck PR4 data with a flexible public needlet ILC pipeline, Phys.Rev.D109 (2024) 023528 [2307.01043]

  73. [74]

    Liu, J.-R

    H. Liu, J.-R. Li and Y.-F. Cai,Evaluation of the Single-component Thermal Dust Emission Model in Cosmic Microwave Background Experiments, ApJS276(2025) 45 [2411.04543]

  74. [75]

    J.-R. Li, P. Yuan, Y.-F. Cai and H. Liu,Do We Have Sufficient Knowledge of the Galactic Foreground Emission in Cosmic Microwave Background Science?, ApJS283(2026) 80 [2603.14287]

  75. [76]

    Carones,Debiasing cosmological parameters from large-scale foreground contamination in Cosmic Microwave Background data,arXiv e-prints(2025) arXiv:2510.20785 [2510.20785]

    A. Carones,Debiasing cosmological parameters from large-scale foreground contamination in Cosmic Microwave Background data,arXiv e-prints(2025) arXiv:2510.20785 [2510.20785]

  76. [77]

    K. Wolz, S. Azzoni, C. Herv´ ıas-Caimapo, J. Errard, N. Krachmalnicoff, D. Alonso et al.,The Simons Observatory: Pipeline comparison and validation for large-scale B-modes, A&A686 (2024) A16 [2302.04276]

  77. [78]

    Baldi, G

    P. Baldi, G. Kerkyacharian, D. Marinucci and D. Picard,Asymptotics for spherical needlets, arXiv Mathematics e-prints(2006) math/0606599 [math/0606599]

  78. [79]

    Pietrobon, A

    D. Pietrobon, A. Balbi and D. Marinucci,Integrated Sachs-Wolfe effect from the cross correlation of WMAP 3year and the NRAO VLA sky survey data: New results and constraints on dark energy, Phys.Rev.D74(2006) 043524 [astro-ph/0606475]

  79. [80]

    Narcowich, P

    F.J. Narcowich, P. Petrushev and J.D. Ward,Localized tight frames on spheres,SIAM Journal on Mathematical Analysis38(2006) 574 [https://doi.org/10.1137/040614359]

  80. [81]

    Scodeller, Ø

    S. Scodeller, Ø. Rudjord, F.K. Hansen, D. Marinucci, D. Geller and A. Mayeli,Introducing Mexican Needlets for CMB Analysis: Issues for Practical Applications and Comparison with Standard Needlets, ApJ733(2011) 121 [1004.5576]

Showing first 80 references.