New Measurements of the Lyα Forest Continuum and Effective Optical Depth with LyCAN and DESI Y1 Data
W. Turner, Paul Martini, Naim Göksel Karaçaylı, José Edgar Madriz Aguilar, S. P. Ahlen, D. Brooks, T. Claybaugh, Axel de la Macorra, Arjun Dey, P. Doel, K. Fanning, J. E. Forero-Romero, Satya Gontcho A Gontcho, Alma X. González‐Morales, G. Gutierrez, J. Guy, H. K. Herrera-Alcantar, K. Honscheid, S. Juneau, Theodore Kisner, Anthony Kremin, Andrew Lambert, Martin Landriau, L. Le Guillou, Aaron Meisner, R. Miquel, John Moustakas, E. Müeller, A. Muñoz-Gutiérrez, Adam D. Myers, Jundan Nie, Gustavo Niz, Claire Poppett, Francisco Prada, Mehdi Rezaie, G. Rossi, E. Sánchez, Edward F. Schlafly, David J. Schlegel, M. Schubnell, Hee‐Jong Seo, David Sprayberry, G. Tarlé, B. A. Weaver, Hu Zou
Abstract
Abstract We present the Ly α Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040–1600 Å based on the red side of the Ly α emission line (1216–1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ( z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>τ</mml:mi> <mml:msup> <mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:mi>z</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mo>=</mml:mo> <mml:msub> <mml:mrow> <mml:mi>τ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> <mml:mo stretchy="false">(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo> <mml:mi>z</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> <mml:mrow> <mml:mi>γ</mml:mi> </mml:mrow> </mml:msup> </mml:math> to our measurements and find τ 0 = (2.46 ± 0.14) × 10 −3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.