Advertisement

Experimental Astronomy

, Volume 48, Issue 1, pp 1–24 | Cite as

An automated approach for photometer and dust mass calculation of the Crab nebula

  • Cyrine NehméEmail author
  • Sarkis Kassounian
  • Marc Sauvage
Original Article
  • 21 Downloads

Abstract

Ample evidence exists regarding supernovae being a major contributor to interstellar dust. In this work, the deepest far-infrared observations of the Crab Nebula are used to revisit the estimation of the dust mass present in this supernova remnant. Images in filters between 70 and 500 μ m taken by the PACS and SPIRE instruments on-board of the Herschel Space Observatory are used. With a novel and automated approach we constructed the spectral energy distribution of the Crab nebula to recover the dust mass. This approach makes use of several image processing techniques (thresholding, morphological processes, contouring, etc..) to objectively separate the nebula from its surrounding background. After subtracting the non-thermal synchrotron component from the integrated fluxes, the spectral energy distribution is found to be best fitted using a single modified blackbody of temperature T = 42.06 ± 1.14 K and a dust mass of Md = 0.056 ± 0.037 M. Our aim in this paper is to highlight the importance of the photometric methods and spectral energy distribution construction on the accuracy of inference for astrophysical parameters.

Keywords

Dust mass Crab Nebula Far-Infrared (FIR) Image processing Herschel Synchrotron 

Notes

References

  1. 1.
    Andersen, A.C.: Why Galaxies Care About AGB Stars: Their Importance as Actors and Probes. In: Kerschbaum, F., Charbonnel, C., Wing, R.F. (eds.) Astronomical Society of the Pacific Conference Series, vol. 378, p 170 (2007)Google Scholar
  2. 2.
    Casey, C.M.: Far-infrared spectral energy distribution fitting for galaxies near and far. MNRAS 425, 3094–3103 (2017)ADSCrossRefGoogle Scholar
  3. 3.
    De Looze, I., Barlow, M.J., Swinyard, B.M., et al.: The dust mass in Cassiopeia A from a spatially resolved Herschel analysis, vol. 465, p 3309 (2017)Google Scholar
  4. 4.
    Dell’Agli, F., García-hernández, D.A., Ventura, P., et al.: AGB stars in the SMC: evolution and dust properties based on Spitzer observations. MNRAS 454, 4235 (2015)ADSCrossRefGoogle Scholar
  5. 5.
    Draine, B.T., Lee, H.M.: Optical properties of interstellar graphite and silicate grains. APJ 285, 89 (1984)ADSCrossRefGoogle Scholar
  6. 6.
    Dwek, E., Cherchneff, I.: The Origin of Dust in the Early Universe: Probing the Star Formation History of Galaxies by Their Dust Content. APJ 727, 63 (2011)ADSCrossRefGoogle Scholar
  7. 7.
    Gaensler, B.M., Slane, P.O.: The evolution and structure of pulsar wind nebulae. ARA&A 44, 17 (2006)ADSCrossRefGoogle Scholar
  8. 8.
    Gail, H.-P., Zhukovska, S.V., Hoppe, P., Trieloff, M.: Stardust from asymptotic giant branch stars. APJ 698, 1136 (2009)ADSCrossRefGoogle Scholar
  9. 9.
    Gomez, H.L., Krause, O., Barlow, M.J., et al.: A cool dust factory in the crab nebula: a HERSCHEL study of the filaments. APJ 760, 96 (2009)ADSCrossRefGoogle Scholar
  10. 10.
    Griffin, M.J., Abergel, A., Abreu, A., et al.: The herschel-SPIRE instrument and its in-flight performance. A & A 518, L3 (2010)ADSCrossRefGoogle Scholar
  11. 11.
    Helling, C., Woitke, P.: Dust in brown dwarfs-V. Growth and evaporation of dirty dust grains. A & A 455, 325 (2006)ADSCrossRefGoogle Scholar
  12. 12.
    Hildebrand, R.H.: The determination of cloud masses and dust characteristics from submillimetre thermal emission. QJRAS 24, 267 (1983)ADSGoogle Scholar
  13. 13.
    Kelly, B.C., Shetty, R., Stutz, A.M., et al.: Dust spectral energy distributions in the era of Herschel and Planck: A hierarchical Bayesian-fitting technique. APJ 752, 55 (2012)ADSCrossRefGoogle Scholar
  14. 14.
    Krafton, K., Clayton, G., Andrews, J., Barlow, M., De Looze, I.: Continuous Dust Formation in SNe 2010jl and 2011ja. Spitzer Proposal (2016)Google Scholar
  15. 15.
    Laor, A., Draine, B.T.: Spectroscopic constraints on the properties of dust in active galactic nuclei. APJ 402, 441 (1993)ADSCrossRefGoogle Scholar
  16. 16.
    Marassi, S., Schneider, R., Limongi, M., et al.: The metal and dust yields of the first massive stars. MNRAS 454, 4250 (2015)ADSCrossRefGoogle Scholar
  17. 17.
    Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Sys., Man. Cyber. 9(1), 6266 (1979)CrossRefGoogle Scholar
  18. 18.
    Ott, S.: Astronomical Data Analysis Software and Systems XIX. In: Mizumoto, Y., Morita, K.-I., Ohishi, M. (eds.) Astronomical Society of the Pacific Conference Series, p 434 139 (2010)Google Scholar
  19. 19.
    Owen, P.J., Barlow, M.J.: The dust and gas content of the Crab Nebula. APJ 801, 141 (2015)ADSCrossRefGoogle Scholar
  20. 20.
    Piazzo, L., Calzoletti, L., Faustini, F., et al.: UNIMAP: A generalized least-squares map maker for Herschel data. MNRAS 447, 1471 (2015)ADSCrossRefGoogle Scholar
  21. 21.
    Pilbratt, G.L., Riedinger, J.R., Passvogel, T., et al.: Herschel Space Observatory-An ESA facility for far-infrared and submillimetre astronomy. A & A 518, L1 (2010)ADSCrossRefGoogle Scholar
  22. 22.
    Poglitsch, A., Waelkens, C., Geis, N., et al.: The photodetector array camera and spectrometer (PACS) on the Herschel space observatory. A & A 518, L2 (2010)ADSCrossRefGoogle Scholar
  23. 23.
    Schneider, R., Valiante, R., Ventura, P., et al.: Dust production rate of asymptotic giant branch stars in the Magellanic Clouds. MNRAS 442, 1440 (2014)ADSCrossRefGoogle Scholar
  24. 24.
    Silvia, D.W., Smith, B.D., Shull, J.M.: Numerical simulations of supernova dust destruction. I. Cloud-crushing and post-processed grain sputtering. APJ 715, 1575 (2010)ADSCrossRefGoogle Scholar
  25. 25.
    Smith, S.: The scientist and engineer’s guide to digital signal processing, pp 436–442. California Technical Pub., San Diego (1997)Google Scholar
  26. 26.
    Temim, T., Dwek, E.: The importance of physical models for deriving dust masses and grain size distributions in supernova ejecta. I. Radiatively heated dust in the Crab Nebula. APJ 774, 8 (2013)ADSCrossRefGoogle Scholar
  27. 27.
    Trimble, V.: The distance to the Crab nebula and NP 0532. PASP 85, 579 (1973)ADSCrossRefGoogle Scholar
  28. 28.
    Trimble, V.: Search for extinction in and near crab nebula. Astrophys. Lett. 18, 145 (1977)ADSGoogle Scholar
  29. 29.
    Weingartner, J.C., Draine, B.T.: Dust grain-size distributions and extinction in the milky way, large magellanic cloud, and small magellanic cloud. APJ 548, 296 (2001)ADSCrossRefGoogle Scholar
  30. 30.
    Zhukovska, S., Gail, H.-P., Trieloff, M.: Evolution of interstellar dust and stardust in the solar neighborhood. A & A 479, 453 (2008)ADSCrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Cyrine Nehmé
    • 1
    • 2
    • 3
    Email author
  • Sarkis Kassounian
    • 1
  • Marc Sauvage
    • 2
    • 3
  1. 1.Department of Physics & AstronomyNotre Dame UniversityLouaizeLebanon
  2. 2.AIM, CEA, CNRS, Université Paris-SaclaySaint-AubinFrance
  3. 3.Université Paris DiderotSorbonne Paris CitéFrance

Personalised recommendations