The Characteristic Dimension of Lyman-α Forest Clouds toward Q0957+561

Details The Characteristic Dimension of Lyman-α Forest Clouds toward Q0957+561 The Characteristic Dimension of Lyman-α Forest Clouds toward Q0957+561

May 2000

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000aas...196.1603d&link_type=abstract

American Astronomical Society, 196th AAS Meeting, #16.03; Bulletin of the American Astronomical Society, Vol. 32, p.694

Astronomy and Astrophysics

Astronomy

Scientific paper

Far-ultraviolet spectra of the gravitational lens components Q0957+561 A and B were obtained with the Hubble Space Telescope Faint Object Spectrograph to investigate the characteristic dimension of Ly-α forest clouds in the direction of the quasar. If one makes the usual assumption that the absorbing structures are spherical clouds with a single radius, that radius can be found analytically from the ratio of the number of Ly-α wavelengths in only one line of sight to the number in both. A simple power series approximation to this solution, accurate everywhere to better than 1%, will be presented. Absorption lines in Q0957+561 having equivalent width > 0.3 Angstroms in the observer's frame not previously identified by Michalitsianos et al. (1997) as interstellar lines, metal lines, or higher order Lyman lines were taken to be Ly-α forest lines. The existence of each line in this consistently selected set was then verified by its presence in two archival FOS spectra with ~1.5 times higher signal to noise than our spectra. Ly-α forest lines appear at 41 distinct wavelengths in the spectra of the two images. One absorption line in the spectrum of image A has no counterpart in the spectrum of image B, and one line in image B has no counterpart in image A. Based on the separation of the lines of sight over the redshift range searched for Ly-α forest lines, the density of the absorbing clouds in the direction of Q0957+561 must change significantly over a radius R = 160 (+120, -70) h50-1 kpc (H0 = 50 h50 km s-1 Mpc-1, q0 = 1/2). The 95% confidence interval on R extends from (50 - 950) h50-1 kpc. QN acknowledges support from NSF grant AST-9417035.

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