Description of the PRIMASS-L bundle V2.0 ======================================== Bundle Generation Date: 2024-05-20 Peer Review: 2024_Asteroid_Review Discipline node: Small Bodies Node Content description for the PRIMASS-L bundle ============================================ PRIMASS-Library Overview ======================== In 2010, we started the PRIMitive Asteroids Spectroscopic Survey (PRIMASS) to study the surface of primitive asteroids at different locations in the main belt, through visible and near-infrared spectroscopy. Up to 2023, PRIMASS has produced 18 papers in peer-reviewed publications, over 30 presentations at international conferences, and has been part of four Ph.D. dissertations. The study of primitive asteroids is relevant for understanding the origin and nature of volatile and organic material in the early Solar System. Furthermore, it provides a rich source of information about the composition of the pre-biotic environment from which life formed. Spectral data from asteroids belonging to the families that could be the source of the primitive near-Earth asteroids (NEAs) are key for understanding the delivery of volatile material to Earth, and provide context and enhance the scientific outcome of the two current sample-return missions orbiting primitive NEAs (OSIRIS-REx; Lauretta et al. 2010 and Hayabusa2; Tsuda et al. 2013). Meanwhile, the existence of water ice on the surface of two asteroids in primitive families (Campins et al. 2010, Rivkin and Emery 2010, Licandro et al. 2011) in the outer belt, one of them the largest member of a collisional family, adds additional motivation to extend the study to the families and asteroid groups all across the inner Solar System. The PRIMitive Asteroid Spectroscopic Survey Library (PRIMASS-L) contains the collection of all spectra and results of the analysis published in the PRIMASS project. As of October 2023, the dataset contains 438 visible and 264 near-infrared spectra of asteroids while observations are ongoing. For PRIMASS, we use a variety of ground-based observatories. The majority of the visible spectra come from the 10.4m Gran Telescopio Canarias (GTC), located at the El Roque de Los Muchachos Observatory (ORM, La Palma, Spain). Most of the near-infrared spectra come from both, the 3.6m Telescopio Nazionale Galileo (TNG), located also at the ORM, and the 3.0m NASA Infrared Telescope Facility (IRTF) on Mauna Kea (Hawai, USA). We have also used other telescopes, like the 4.1m Southern Astrophysical Research Telescope (SOAR) at Cerro Pachon (Chile), the 3.6m New Technology Telescope (NTT) located at La Silla Observatory, and the 2.54m Issac Newton Telescope (INT) located at the El Roque de los Muchachos Observatory (ORM, La Palma, Spain). The wavelength channels depend on the instrumentation (e.g., IRTF vs TNG), which provides slightly different wavelength ranges, and on the data quality on every different night, which may result in removing a specific region of the spectrum for some specific targets. To analyze these spectra we use the Code for ANalyisis of Asteroids (CANA), a tool created by us for this purpose and introduced in De Prá et al. (2018b). This tool can be used for the analysis of spectra acquired using other telescopes and is publically available at http://github.com/cana-asteroids/cana. This package (PRIMASS-L v2.0) contains near-infrared spectroscopy of the families in the inner- and outer-belt and Hilda dynamical group, as defined in Nesvorny et al. (2015). However, the dynamical definition of the families has censed since and some objects are not considered family members anymore. Note that by Polana family we refer to the low albedo asteroids in the Nysa-Polana region. This includes what was later defined by Walsh et al. (2013) as the Polana and Eulalia families. To separate between Polana and Eulalia membership, refer to Pinilla-Alonso et al. (2016) and de Leon et al. (2016). However, the dynamical definition of the families has changed since and some objects are not considered family members anymore. The primitive background population was taken from the definition in Delbo et al. (2017). This is all reflected in the table containing the physical properties. Additionally, obtaining quality near-infrared spectra of the Svea and Clarissa families from ground-based telescopes is currently not possible as they are very faint in the near-infrared. For comparison, we include NIR spectra of other primitive asteroids obtained by this team that were studied in preparation for this survey in de Leon et al. (2012). All of these bodies had been classified as B-type, based on visible spectroscopy, without any dependence on family membership. - Inner-Belt - Chaldaea: - VIS: 15 spectra - NIR: 15 spectra - Chimaera: - VIS: 20 spectra - Clarissa: - VIS: 33 spectra - Erigone: - VIS: 101 spectra - NIR: 26 spectra - Klio: - VIS: 30 spectra - NIR: 21 spectra - Polana: - VIS: 67 spectra - NIR: 66 spectra - PBF: - NIR: 58 spectra - Sulamitis: - VIS: 64 spectra - NIR: 19 spectra - Svea: - VIS: 16 spectra - Outer-Belt - Hygiea: - VIS: 11 spectra - Lixiaohua: - VIS: 53 spectra - NIR: 17 spectra - Themis: - VIS: 16 spectra - Veritas: - VIS: 9 spectra - Cybele: - VIS: 10 spectra - Hilda: - VIS: 9 spectra - NIR: 20 spectra - B-type: - NIR: 22 spectra PRIMASS-L bundle V1.0 contains spectra of these and other families in the main belt obtained in the visible wavelengths (doi: 10.26033/xnfh-np39) PRIMASS-L bundle V2.0 contains spectra of these and other families in the main belt obtained in the near-infrared wavelengths. The collection of visible spectra, and associated results are the same in V2.0 and V1.0. Note that we include a column describing the directory of where the spectrum file is located for easier access. Description of Files ==================== Data directories ---------------- - primassl_visible_spectral_data_compilation.csv: List of acquired visible spectra, observing conditions, physical parameters, and corresponding PRIMASS publication. - primassl_visible_spectral_parameters.csv: Results of the analysis of each visible spectrum listing taxonomical classification, spectral slope in the visible, characteristics of the aqueous alteration band at 0.7 µm, and the turn-off around 0.5 µm, provided by the CANA package. - primassl_nir_spectral_data_compilation.csv: List of acquired near infrared spectra, observing conditions, physical parameters, and corresponding PRIMASS publication. - primassl_nir_spectral_parameters.csv: Results of the analysis of each near infrared spectrum listing taxonomical classification and spectral gradient - solar_analog_stars_legend.csv: Legend for the solar analogs used in the observations as described in the table primassl_nir_spectral_data_collection.csv - spectra/*: Spectral data files for each asteroid. These files are organized in folders according to the respective main belt region and related publication. The file name is based on the asteroid number (or provisional designation, if not numbered) with a suffix indicating the wavelength range of the spectrum ("_vis" or "_nir"). If the asteroid has multiple observations another suffix is added ("_1", "_2",...) Document directory ------------------------ - primassl_visible_spectral_compilation_plot.pdf: This document consists of one single PDF file that contains individual plots of all visible spectra. The scale is the same for all of them so that the slope and features can be easily compared visually. For those objects that were observed multiple times, the spectra are represented in the same individual panel. For those objects observed with different setups, we append a "_r" or "_b" to the name that indicates if the observation covers the bluer or redder part of the visible spectrum. Note that the edges of the spectra can be affected by a low signal-to-noise ratio because of the lower transmission of the system so, they have to be taken cautiously for analysis purposes. - primassl_visible_spectral_parameters_plot.pdf: This document consists of one single PDF file that contains individual plots of the visible spectrum of each object, including graphical representation of the obtained spectral parameters. Note that the edges of the spectra can be affected by a low signal-to-noise ratio because of the lower transmission of the system and may not have been used for the fits. Check the definition of each parameter for more details. The fits are represented in the wavelength range where they are calculated. - primassl_nir_spectral_compilation_plot.pdf:This document consists of one single PDF file that contains individual plots of all near infrared spectra. The scale is the same for all of them so that the slope and features can be easily compared visually. For those objects that were observed multiple times, the spectra are represented in the same individual panel. Note that the edges of the spectra can be affected by a low signal-to-noise ratio of the lower transmission of the system so, they have to be taken cautiously for analysis purposes. - primassl_nir_spectral_parameters_plot.pdf: This document consists of one single PDF file that contains individual plots of the near infrared spectrum of each object, including graphical representation of the obtained spectral parameters. Note that the edges of the spectra can be affected by a low signal-to-noise ratio because of the lower transmission of the system and may not have been used for the fits. Check the definition of each parameter for more details. The fits are represented in the wavelength range where they are calculated. Spectral Parameters =================== - Spectral Gradient: This is a measure of the color of the spectrum, in a certain wavelength range, calculated following the definition of the Spectral Gradient in Luu & Jewitt (1990) with this formula: Sprim = S[lambda1, lambda2]/R_lambdaN [percent/0.1 µm], where S is the linear fit to the reflectance in the wavelength range limited by 0.5 and 0.87 µm in the visible and by 1.1 and 2.2 µm in the near infrared. The value of R_lambdaN is the value of the fit at the normalization point, 0.5 µm and 1.2 µm for the visible and near infrared, respectively. - Band Center and Band Depth (visible spectra only): These parameters are calculated for an absorption band centered around 0.7 µm that may be indicative of hydrated minerals. The methodology is described Morate et al. (2016). The spectral continuum was estimated fitting a straight line to both the right and left edges of the absorption band, in the 0.55-0.57 and 0.84-0.88 µm intervals. Thereafter, we removed the continuum from the spectrum with a fourth-order spline fit in the 0.55-0.88 µm range. The center of the band is measured at the wavelength of the minimum of the fit. The depth of the band is (1 - Rm), where Rm is the value of the spline fit at the center of the band. If the minimum reflectance of the fit contained in the 0.65-0.75 µm region is at a depth larger than 1% and above 3-sigma of the spectrum noise, we claim the detection of the band. If any of these criteria are not satisfied we reject the band identification and values are not provided in the primassl_visible.spectral_parameters.csv file. - Turn-down, also referred to in the papers as turn-off (visible spectra only): This parameter is calculated for a feature appearing around 0.50 µm and is defined in De Prá et al. (2018a). It measures the position of the point where the spectrum shows a maximum in the curvature in the 0.40-0.65 µm wavelength range. We identified the turn-down if the parameter surpasses a threshold established by visual inspection. The calculation of the errors associated with these parameters is described in De Prá et al. (2020a). The results of the analysis of this parametrization is provided in the primassl_visible.spectral_parameters_plot.pdf in the document directory. Taxonomic Classification ======================== We assign the taxonomical class to the visible collection of spectra using CANA (De Pra et al 2018b). We include there the most probable class and confirm or reassigned it based on visual inspection. Because of the lack of clear absorptions in the near infrared spectra, taxonomical classification can be challenging. Therefore, we used different approaches, CANA (De Pra et al. 2018b) and MIT tool, both implementations use the Bus-DeMeo taxonomy. After that, we proceed with visual inspection following a decision flow chart detailed in Harvison et al. 2024. Acknowledgment ============== Support for this work was provided by NASA grants NNH17ZDA001N-PDART, Planetary Data Archiving, Restoration, and Tools, through the project "PRIMitive Asteroids Spectroscopic Survey (PRIMASS): the past as a puzzle", NNH18ZDA018C-SSERVI (CAN-1 and CAN-3) through the Center for Lunar and Asteroid Surface Science (CLASS), and by the project AYA2017-89090-P of the Spanish MINECO. This library is partially based on observations made with the Gran Telescopio Canarias (GTC), installed at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, in the island of La Palma, at the Southern Astrophysical Research (SOAR) telescope, which is a joint project of the Ministério da Ciência, Tecnologia e Inovações do Brasil (MCTI/LNA), the US National Science Foundation’s NOIRLab, the University of North Carolina at Chapel Hill (UNC), and Michigan State University (MSU), at the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astrofisica), at the Isaac Newton Telescope operated on the island of La Palma by the Isaac Newton Group of Telescopes, the latter two telescopes sited in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, at the Infrared Telescope Facility (IRTF), which is operated by the University of Hawaii under contract 80HQTR19D0030 with the National Aeronautics and Space Administration, and at the European Organization for Astronomical Research in the Southern Hemisphere with the New Technology Telescope (NTT). This research has made use of data and/or services provided by Horizons-JPL system that was developed at the Jet Propulsion Laboratory (Solar System Dynamics Group), California Institute of Technology, under contract with the National Aeronautics and Space Administration. We explicitly want to express our thanks to all the support astronomers and telescope operators for their excellent assistance during the vast number of hours of observations. Also, we are grateful to Beatrice Mueller, our point of contact at the Planetary Data System, whose incredible patience and knowledge made the creation of this library possible. Caveats to the data user ======================== - Refer to Arredondo et al. (2021a), for objects without a specific solar analog association. - The results of the spectral parametrization files are derived using an automatic pipeline contained within the Code for ANalyisis of Asteroids (CANA, De Prá et al. 2018b, 2020a) optimized for PRIMASS. The values in this library might be slightly different from those in the associated papers. In particular, the taxonomy for all the near infrared sample is included in Harvison et al. (2024). We strongly recommend using the values included here for a consistent analysis of the sample. - For objects without a clear taxonomic type, we include the two most probable classes. If an object is labeled as inconclusive (inc), we were unable to determine a reliable class. - The folder for the B-types (de Leon et al. 2012) contains objects selected based on their taxonomical classification and not by the relation with any dynamical family. Nonetheless, some of them are members of families studied in this survey, which can be checked in the file describing the full data collection. To track were to find each spectrum use the full path contained in such file. - Asteroids 1705, 2259, and 5333 were studied as part of the near-infrared B-type, Polana, and Chaldaea papers, respectively, but they were later defined as PBF members. For the aim of clarity, we include them in the folder corresponding to the paper they were firstly studied in. - Spectra of objects that were observed more than once but for different papers are contained in different folders (named after the corresponding publication). Again, use the full path contained in the file describing the full data collection.