About this Research Topic
Recent decades have brought an enormous wealth of various asteroid data. This huge amount of data is continuously being gathered in targeted observing campaigns (traditional ground-based observations and survey-like measurements, e.g., PanSTARSS, NEOWISE, Zwicky Transient Facility survey, ATLAS) as well as collected by surveys dedicated to study other astronomical objects, but containing serendipitous asteroid data (Gaia, Transiting Exoplanet Survey Satellite TESS, Sloan Digital Sky Survey SDSS, VISTA survey, Tomo-e Gozen transient survey and many others).
This data allows us to study hundreds of thousands of asteroids simultaneously, giving insight into population characteristics and thus tackling major questions in planetary science. The main challenge of the big data era is in processing datasets which have distinct properties. That is, for example, combining sparse and dense photometric data originating from various sources, having different systematic and random errors, often obtained at different wavelengths or being completely divergent measurement types (e.g., occultations vs. photometry).
The main goal of this Research Topic is to understand individual asteroids and populations from a combination of multiple divergent datasets.
Advances with diverse data sources have already been made. These include modeling asteroid spins and shapes from sparse and dense photometry, inclusion of the occultation chords, adaptive optics and thermal data in complex inversion algorithms such as SAGE or ADAM, determination of asteroid orbits based on variable precision and accuracy astrometry where uncertainties ~1 arcsec from Minor Planet Center are combined with precise Gaia measurements with micro arcsec uncertainties, mineralogical modeling from multi-filter surveys complementary in wavelengths (SDSS, VISTA). On the other hand, some asteroid modeling areas still rely mostly on single datasets (e.g., phase curve modeling performed on single databases such as PTS, PanSTARRS, or ATLAS).
New and planned (e.g., LSST, Gaia DR3, Euclid) observing campaigns and surveys will provide increasing amounts of data, which will also introduce computational and modeling challenges.
This Research Topic aims to address the problem of further development in combining and processing small (relatively small in numbers, but typically accurate and/or dense) and/or large (numerous, but often sparse, sometimes burdened with larger uncertainties) datasets to study individual objects as well as entire populations.
We invite all papers (including Original Research and Data Reports) describing all types of asteroid and asteroid population modeling (photometric, astrometric, spectral, thermal, etc.) with a focus on various datasets. This Research Topic will address:
1. state-of-the-art methods of processing sparse data, as well as approaches to combine multiple datasets
2. modeling of individual objects and/or populations based on targeted observations and/or survey data
3. archives, services, software, and data products containing raw and processed asteroid information
This data allows us to study hundreds of thousands of asteroids simultaneously, giving insight into population characteristics and thus tackling major questions in planetary science. The main challenge of the big data era is in processing datasets which have distinct properties. That is, for example, combining sparse and dense photometric data originating from various sources, having different systematic and random errors, often obtained at different wavelengths or being completely divergent measurement types (e.g., occultations vs. photometry).
The main goal of this Research Topic is to understand individual asteroids and populations from a combination of multiple divergent datasets.
Advances with diverse data sources have already been made. These include modeling asteroid spins and shapes from sparse and dense photometry, inclusion of the occultation chords, adaptive optics and thermal data in complex inversion algorithms such as SAGE or ADAM, determination of asteroid orbits based on variable precision and accuracy astrometry where uncertainties ~1 arcsec from Minor Planet Center are combined with precise Gaia measurements with micro arcsec uncertainties, mineralogical modeling from multi-filter surveys complementary in wavelengths (SDSS, VISTA). On the other hand, some asteroid modeling areas still rely mostly on single datasets (e.g., phase curve modeling performed on single databases such as PTS, PanSTARRS, or ATLAS).
New and planned (e.g., LSST, Gaia DR3, Euclid) observing campaigns and surveys will provide increasing amounts of data, which will also introduce computational and modeling challenges.
This Research Topic aims to address the problem of further development in combining and processing small (relatively small in numbers, but typically accurate and/or dense) and/or large (numerous, but often sparse, sometimes burdened with larger uncertainties) datasets to study individual objects as well as entire populations.
We invite all papers (including Original Research and Data Reports) describing all types of asteroid and asteroid population modeling (photometric, astrometric, spectral, thermal, etc.) with a focus on various datasets. This Research Topic will address:
1. state-of-the-art methods of processing sparse data, as well as approaches to combine multiple datasets
2. modeling of individual objects and/or populations based on targeted observations and/or survey data
3. archives, services, software, and data products containing raw and processed asteroid information
Keywords: asteroids, lightcurves, phase curves, spins, shapes, surveys, observing campaigns, spectra, astrometry, photometry, colors, taxonomy
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
