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Spectroscopy with the JWST Advanced Deep Extragalactic Survey (JADES) - the NIRSpec/NIRCAM GTO galaxy evolution project

Published online by Cambridge University Press:  04 June 2020

Andrew J. Bunker Open the ORCID record for Andrew J. Bunker [Opens in a new window]
Andrew J. Bunker*
Affiliation:
Department of Physics, University of Oxford, Keble Road, OxfordOX13RH, United Kingdom email: andy.bunker@physics.ox.ac.uk
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Abstract

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I present an overview of the JWST Advanced Deep Extragalactic Survey (JADES), a joint program of the JWST/NIRCam and NIRSpec Guaranteed Time Observations (GTO) teams involving 950 hours of observation. We will target two well-studied fields with excellent supporting data (e.g., from HST-CANDELS): GOODS-North and South, including the Ultra Deep Field. The science goal of JADES is to chart galaxy evolution at z > 2, and potentially out to z > 10, using the rest-frame optical and near-IR though observations from ≍ 1–5μm. Multi-colour NIRCam imaging with 9 filters will enable photometric redshifts and the application of the Lyman break technique out to unprecedented distances. NIRSpec spectroscopy (with spectral resolving powers of R = 100, 1000 & 2700) will measure secure spectroscopic redshifts of the photometrically-selected population, as well as stellar continuum slopes in the UV rest-frame, and hence study the role of dust, stellar population age, and other effects. Measuring emission lines can constrain the dust extinction, star formation rates, metallicity, chemical abundances, ionization and excitation mechanism in high redshift galaxies. Coupling NIRCam and NIRSpec observations will determine stellar populations (age, star formation histories, abundances) of galaxies and provide the information to correct their broad-band spectral energy distribution for likely line contamination. Potentially we can search for signatures of Population III stars such as HeII. We can address the contribution of star-forming galaxies at z > 7 to reionization by determining the faint end slope of the luminosity function and investigating the escape fraction of ionizing photons by comparing the UV stellar continuum with the Balmer-line fluxes.

Keywords

instrumentation: spectrographsgalaxies: evolutionformationluminosity function
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 15 , Symposium S352: Uncovering Early Galaxy Evolution in the ALMA and JWST Era , June 2019 , pp. 342 - 346
Copyright
© International Astronomical Union 2020

References

Baldwin, J. A., Phillips, M. M. & Terlevich, R. 1981 PASP, 93, 5CrossRefGoogle Scholar
Bunker, A. J., Stanway, E. R., Ellis, R. S., et al. 2003, MNRAS, 342L, 47CrossRefGoogle Scholar
Bunker, A. J., Stanway, E. R., Ellis, R. S., et al. 2004, MNRAS, 355, 37410.1111/j.1365-2966.2004.08326.xCrossRefGoogle Scholar
Caruana, J., Bunker, A. J., Wilkins, S. M., et al. 2014, MNRAS, 443, 2831CrossRefGoogle Scholar
Chevallard, J., Curtis-Lake, E., Charlot, S.et al. 2019, MNRAS, 483, 262110.1093/mnras/sty2426CrossRefGoogle Scholar
Dijkstra, M., Haiman, Z. & Loeb, A. 2004, ApJ, 601, 66610.1086/380603CrossRefGoogle Scholar
Eldridge, J. J. & Stanway, E. R. 2009, MNRAS, 400, 101910.1111/j.1365-2966.2009.15514.xCrossRefGoogle Scholar
Giallongo, E., Grazian, A., Fiore, F., et al. 2015, A&A, 578, 83Google Scholar
Lorenzoni, S., Bunker, A. J., Wilkins, S. M., et al. 2013, MNRAS, 429, 150CrossRefGoogle Scholar
Oesch, P. A., Brammer, G., van Dokkum, P. G., et al. 2016, ApJ, 819, 12910.3847/0004-637X/819/2/129CrossRefGoogle Scholar
Pagel, B., Edmunds, M. G., Blackwell, D. E., Chun, M. S. & Smith, G. 1979, MNRAS 189, 9510.1093/mnras/189.1.95CrossRefGoogle Scholar
Planck Collaboration 2016, A&A, 596A, 108Google Scholar
Schaerer, D. 2003, A&A, 397, 527Google Scholar
Smit, R., Bouwens, R. J., Carniani, S., et al. 2018, Nature, 553, 178CrossRefGoogle Scholar
Stanway, E. R., McMahon, R. G. & Bunker, A. J. 2005, MNRAS, 359, 1184CrossRefGoogle Scholar
Stark, D. P.et al. 2015, MNRAS, 450, 184610.1093/mnras/stv688CrossRefGoogle Scholar
Stark, D. P., Ellis, R. S., Chiu, K., et al. 2010, MNRAS, 408, 162810.1111/j.1365-2966.2010.17227.xCrossRefGoogle Scholar
Wilkins, S. M.et al. 2011, MNRAS, 417, 71710.1111/j.1365-2966.2011.19315.xCrossRefGoogle Scholar
Zackrisson, E., Inoue, A. K. & Jensen, H. 2013, ApJ, 777, 3910.1088/0004-637X/777/1/39CrossRefGoogle Scholar
Zitrin, A., Labbé, I., Belli, S., et al. 2015, ApJ, 810L, 1210.1088/2041-8205/810/1/L12CrossRefGoogle Scholar