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Register a new userMachine Learning Approach to Integral Field Unit Spectroscopy Observations: I. HII Region Kinematics
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SITELLE is a novel integral field unit spectroscopy instrument that has an impressive spatial (11 by 11 arcmin), spectral coverage, and spectral resolution (R=1-20000). SIGNALS is anticipated to obtain deep observations (down to 3.6x10-17ergs s-1cm-2) of 40 galaxies, each needing complex and substantial time to extract spectral information. We present a method that uses Convolution Neural Networks (CNN) for estimating emission line parameters in optical spectra obtained with SITELLE as part of the SIGNALS large program. Our algorithm is trained and tested on synthetic data representing typical emission spectra for HII regions based on Mexican Million Models database(3MdB) BOND simulations. The networks activation map demonstrates its ability to extract the dynamical (broadening and velocity) parameters from a set of 5 emission lines (e.g. H{alpha}, N[II] doublet, and S[II] doublet) in the SN3 (651-685 nm) filter of SITELLE. Once trained, the algorithm was tested on real SITELLE observations in the SIGNALS program of one of the South West fields of M33. The CNN recovers the dynamical parameters with an accuracy better than 5 km s-1 in regions with a signal-to-noise ratio greater than 15 over the H{alpha}line. More importantly, our CNN method reduces calculation time by over an order of magnitude on the spectral cube with native spatial resolution when compared with standard fitting procedures. These results clearly illustrate the power of machine learning algorithms for the use in future IFU-based missions. Subsequent work will explore the applicability of the methodology to other spectral parameters such as the flux of key emission lines.
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In the first paper of this series (Rhea et al. 2020), we demonstrated that neural networks can robustly and efficiently estimate kinematic parameters for optical emission-line spectra taken by SITELLE at the Canada-France-Hawaii Telescope. This paper expands upon this notion by developing an artificial neural network to estimate the line ratios of strong emission-lines present in the SN1, SN2, and SN3 filters of SITELLE. We construct a set of 50,000 synthetic spectra using line ratios taken from the Mexican Million Model database replicating Hii regions. Residual analysis of the network on the test set reveals the networks ability to apply tight constraints to the line ratios. We verified the networks efficacy by constructing an activation map, checking the [N ii] doublet fixed ratio, and applying a standard k-fold cross-correlation. Additionally, we apply the network to SITELLE observation of M33; the residuals between the algorithms estimates and values calculated using standard fitting methods show general agreement. Moreover, the neural network reduces the computational costs by two orders of magnitude. Although standard fitting routines do consistently well depending on the signal-to-noise ratio of the spectral features, the neural network can also excel at predictions in the low signal-to-noise regime within the controlled environment of the training set as well as on observed data when the source spectral properties are well constrained by models. These results reinforce the power of machine learning in spectral analysis.
We present an improved version of FIT3D, a fitting tool for the analysis of the spectroscopic properties of the stellar populations and the ionized gas derived from moderate resolution spectra of galaxies. FIT3D is a tool developed to analyze Integral Field Spectroscopy data and it is the basis of Pipe3D, a pipeline already used in the analysis of datasets like CALIFA, MaNGA, and SAMI. We describe the philosophy behind the fitting procedure, and in detail each of the different steps in the analysis. We present an extensive set of simulations in order to estimate the precision and accuracy of the derived parameters for the stellar populations. In summary, we find that using different stellar population templates we reproduce the mean properties of the stellar population (age, metallicity, and dust attenuation) within ~0.1 dex. A similar approach is adopted for the ionized gas, where a set of simulated emission- line systems was created. Finally, we compare the results of the analysis using FIT3D with those provided by other widely used packages for the analysis of the stellar population (Starlight, Steckmap, and analysis based on stellar indices) using real high S/N data. In general we find that the parameters for the stellar populations derived by FIT3D are fully compatible with those derived using these other tools.
The X-ray Integral Field Unit (X-IFU) is the high resolution X-ray spectrometer of the ESA Athena X-ray observatory. Over a field of view of 5 equivalent diameter, it will deliver X-ray spectra from 0.2 to 12 keV with a spectral resolution of 2.5 eV up to 7 keV on ~5 arcsecond pixels. The X-IFU is based on a large format array of super-conducting molybdenum-gold Transition Edge Sensors cooled at about 90 mK, each coupled with an absorber made of gold and bismuth with a pitch of 249 microns. A cryogenic anti-coincidence detector located underneath the prime TES array enables the non X-ray background to be reduced. A bath temperature of about 50 mK is obtained by a series of mechanical coolers combining 15K Pulse Tubes, 4K and 2K Joule-Thomson coolers which pre-cool a sub Kelvin cooler made of a 3He sorption cooler coupled with an Adiabatic Demagnetization Refrigerator. Frequency domain multiplexing enables to read out 40 pixels in one single channel. A photon interacting with an absorber leads to a current pulse, amplified by the readout electronics and whose shape is reconstructed on board to recover its energy with high accuracy. The defocusing capability offered by the Athena movable mirror assembly enables the X-IFU to observe the brightest X-ray sources of the sky (up to Crab-like intensities) by spreading the telescope point spread function over hundreds of pixels. Thus the X-IFU delivers low pile-up, high throughput (>50%), and typically 10 eV spectral resolution at 1 Crab intensities, i.e. a factor of 10 or more better than Silicon based X-ray detectors. In this paper, the current X-IFU baseline is presented, together with an assessment of its anticipated performance in terms of spectral resolution, background, and count rate capability. The X-IFU baseline configuration will be subject to a preliminary requirement review that is scheduled at the end of 2018.
Direct imaging instruments have the spatial resolution to resolve exoplanets from their host star. This enables direct characterization of the exoplanets atmosphere, but most direct imaging instruments do not have spectrographs with high enough resolving power for detailed atmospheric characterization. We investigate the use of a single-mode diffraction-limited integral-field unit that is compact and easy to integrate into current and future direct imaging instruments for exoplanet characterization. This achieved by making use of recent progress in photonic manufacturing to create a single-mode fiber-fed image reformatter. The fiber-link is created with 3D printed lenses on top of a single-mode multi-core fiber that feeds an ultrafast laser inscribed photonic chip that reformats the fiber into a pseudo-slit. We then couple it to a first-order spectrograph with a triple stacked volume phase holographic grating for a high efficiency over a large bandwidth. The prototype system has had a successful first-light observing run at the 4.2 meter William Herschel Telescope. The measured on-sky resolving power is between 2500 and 3000, depending on the wavelength. With our observations we show that single-mode integral-field spectroscopy is a viable option for current and future exoplanet imaging instruments.
The X-ray Integral Field Unit (X-IFU) on board the Advanced Telescope for High-ENergy Astrophysics (Athena) will provide spatially resolved high-resolution X-ray spectroscopy from 0.2 to 12 keV, with 5 arc second pixels over a field of view of 5 arc minute equivalent diameter and a spectral resolution of 2.5 eV up to 7 keV. In this paper, we first review the core scientific objectives of Athena, driving the main performance parameters of the X-IFU, namely the spectral resolution, the field of view, the effective area, the count rate capabilities, the instrumental background. We also illustrate the breakthrough potential of the X-IFU for some observatory science goals. Then we briefly describe the X-IFU design as defined at the time of the mission consolidation review concluded in May 2016, and report on its predicted performance. Finally, we discuss some options to improve the instrument performance while not increasing its complexity and resource demands (e.g. count rate capability, spectral resolution). The X-IFU will be provided by an international consortium led by France, The Netherlands and Italy, with further ESA member state contributions from Belgium, Finland, Germany, Poland, Spain, Switzerland and two international partners from the United States and Japan.
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