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Paper · 1605.04460 · 2016

Detecting Damped Lyman-$α$ Absorbers with Gaussian Processes

arXiv · PDF · Open in the Atlas

Code that ran

We lifted 17 functions out of this paper's own repositories and ran 7 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.

RepositoryRoleRan
rmgarnett/gp_dla_detection canonical 7 of 13
yishayv/lyacorr pwc_unofficial 0 of 4
FunctionStatusWhere it lives
Gaussian Ran rmgarnett/gp_dla_detection/CDDF_analysis/voigt.py
code served (permissive licence) · get_code("a57bc207f6ddcefd")
Lorentzian Ran rmgarnett/gp_dla_detection/CDDF_analysis/voigt.py
code served (permissive licence) · get_code("ea5f29cc0aa083e3")
Voigt Ran rmgarnett/gp_dla_detection/CDDF_analysis/voigt.py
code served (permissive licence) · get_code("8aeede7dbc9a3695")
do_MAP_Garnett_comparison Ran rmgarnett/gp_dla_detection/CDDF_analysis/make_multi_dla_plots.py
code served (permissive licence) · get_code("76072d8283565983")
format_latex_num Ran rmgarnett/gp_dla_detection/CDDF_analysis/make_tables.py
code served (permissive licence) · get_code("ac127482fcea809e")
format_latex_two_num Ran rmgarnett/gp_dla_detection/CDDF_analysis/make_tables.py
code served (permissive licence) · get_code("a4b05b4034087806")
search_index_from_another Ran rmgarnett/gp_dla_detection/CDDF_analysis/qso_loader.py
code served (permissive licence) · get_code("1565258e3ade9752")
downsample_spectrum Not yet run yishayv/lyacorr/calc_mean_transmittance.py
code served (permissive licence) · get_code("51a17680901e801c")
find_pixel_noise Not yet run rmgarnett/gp_dla_detection/CDDF_analysis/calc_cddf.py
code served (permissive licence) · get_code("222bf414dd90e625")
find_pixel_snr Not yet run rmgarnett/gp_dla_detection/CDDF_analysis/calc_cddf.py
code served (permissive licence) · get_code("182da4fc0eea4948")
find_snr Not yet run rmgarnett/gp_dla_detection/CDDF_analysis/calc_cddf.py
code served (permissive licence) · get_code("1c50a1f41e00583e")
fit_function Not yet run yishayv/lyacorr/continuum_goodness_of_fit.py
code served (permissive licence) · get_code("ec69220b26d8f0f7")
generate_qsos Not yet run rmgarnett/gp_dla_detection/CDDF_analysis/make_multi_dla_plots.py
code served (permissive licence) · get_code("a7449f1591071b7d")
generate_qsos_lyseries Not yet run rmgarnett/gp_dla_detection/CDDF_analysis/make_multi_dla_plots.py
code served (permissive licence) · get_code("d30953e8080cd285")
load_table Not yet run rmgarnett/gp_dla_detection/CDDF_analysis/make_tables.py
code served (permissive licence) · get_code("64806c35f9a763ad")
max_delta_f_per_snr Not yet run yishayv/lyacorr/continuum_goodness_of_fit.py
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rescale Not yet run yishayv/lyacorr/delta_transmittance_remove_mean.py
code served (permissive licence) · get_code("8f9d07f118f46224")

Repositories linked to this paper

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Abstract

We develop an automated technique for detecting damped Lyman-$α$ absorbers (DLAs) along spectroscopic lines of sight to quasi-stellar objects (QSOs or quasars). The detection of DLAs in large-scale spectroscopic surveys such as SDSS-III sheds light on galaxy formation at high redshift, showing the nucleation of galaxies from diffuse gas. We use nearly 50 000 QSO spectra to learn a novel tailored Gaussian process model for quasar emission spectra, which we apply to the DLA detection problem via Bayesian model selection. We propose models for identifying an arbitrary number of DLAs along a given line of sight. We demonstrate our method's effectiveness using a large-scale validation experiment, with excellent performance. We also provide a catalog of our results applied to 162 858 spectra from SDSS-III data release 12.

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