Abstract
We explore novel methods of recovering the original spectral line profiles from data obtained by instruments that sample those profiles with an extended or multipeaked spectral transmission profile. The techniques are tested on data obtained at high spatial resolution from the Fast Imaging Solar Spectrograph (FISS) grating spectrograph at the Big Bear Solar Observatory and from the Interferometric Bidimensional Spectrometer (IBIS) instrument at the Dunn Solar Telescope. The method robustly deconvolves wide spectral transmission profiles for fields of view sampling a variety of solar structures (granulation, plage and pores) with a photometrical precision of less than 1%. The results and fidelity of the method are tested on data from IBIS obtained using several different spectral resolution modes. The method, based on convolutional neural networks (CNN), is extremely fast, performing about $10^5$ deconvolutions per second on a CPU and $10^6$ deconvolutions per second on NVIDIA TITAN RTX GPU for a spectrum with 40 wavelength samples. This approach is applicable for deconvolving large amounts of data from instruments with wide spectral transmission profiles, such as the Visible Tunable Filter (VTF) on the DKI Solar Telescope (DKIST). We also investigate its application to future instruments by recovering spectral line profiles obtained with a theoretical multi-peaked spectral transmission profile. We further discuss the limitations of this deconvolutional approach through the analysis of the dimensionality of the original and multiplexed data.
Highlights
The finite spectral resolution of real instruments affects the inferred signal by blending the intensities at different wavelengths
The concept of exploiting this multiplexing to recover spectral information was originally developed by Caccin and Roberti (1979) and later Baranyi and Ludmány (1983) in order to reconstruct spectral profiles sampled by the relatively broad (0.15–0.5 Å FWHM) spectral pointspread function (sPSF) of the tunable Universal Birefringent Filter (UBF) (Beckers et al, 1975)
The method developed, which relied on analytical descriptions of the sPSF, was employed by Caccin et al (1983) and Baranyi (1986) to reconstruct H-alpha and Na D line profiles recorded through a UBF
Summary
The finite spectral resolution of real instruments affects the inferred signal by blending the intensities at different wavelengths. Given the typical shape of an absorption line, the convolution with a broad sPSF raises the intensity around the line core and broadens the wings of the profile This smearing tends to increase the similarity among different spectral profiles, reducing the spatial contrast and the ability to identify small scale structures in images of the solar atmosphere. We discuss the limitations on the precision of the recovered profiles based on the dimensionality of the data derived from maximum-likelihood intrinsic-dimensionality estimate (Levina and Bickel, 2004)
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