L. Rustige, J. Kummer, F. Griese, K. Borras, Marcus Brüggen, P. Connor, F. Gaede, G. Kasieczka, Tobias Knopp Peter Schleper
Machine learning techniques that perform morphological classification of astronomical sources often suffer from a scarcity of labelled training data. Here, we focus on the case of supervised deep learning models for the morphological classification of radio galaxies, which is particularly topical for the forthcoming large radio surveys. We demonstrate the use of generative models, specifically Wasserstein Generative Adversarial Networks (wGANs), to generate data for different classes of radio galaxies. Further, we study the impact of augmenting the training data with images from our wGAN on three different classification architectures. We find that this technique makes it possible to improve models for the morphological classification of radio galaxies. A simple Fully Connected Neural Network (FCN) benefits most from including generated images into the training set, with a considerable improvement of its classification accuracy. In addition, we find it is more difficult to improve complex classifiers. The classification performance of a Convolutional Neural Network (CNN) can be improved slightly. However, this is not the case for a Vision Transformer (ViT).
{"title":"Morphological Classification of Radio Galaxies with wGAN-supported Augmentation","authors":"L. Rustige, J. Kummer, F. Griese, K. Borras, Marcus Brüggen, P. Connor, F. Gaede, G. Kasieczka, Tobias Knopp Peter Schleper","doi":"10.1093/rasti/rzad016","DOIUrl":"https://doi.org/10.1093/rasti/rzad016","url":null,"abstract":"\u0000 Machine learning techniques that perform morphological classification of astronomical sources often suffer from a scarcity of labelled training data. Here, we focus on the case of supervised deep learning models for the morphological classification of radio galaxies, which is particularly topical for the forthcoming large radio surveys. We demonstrate the use of generative models, specifically Wasserstein Generative Adversarial Networks (wGANs), to generate data for different classes of radio galaxies. Further, we study the impact of augmenting the training data with images from our wGAN on three different classification architectures. We find that this technique makes it possible to improve models for the morphological classification of radio galaxies. A simple Fully Connected Neural Network (FCN) benefits most from including generated images into the training set, with a considerable improvement of its classification accuracy. In addition, we find it is more difficult to improve complex classifiers. The classification performance of a Convolutional Neural Network (CNN) can be improved slightly. However, this is not the case for a Vision Transformer (ViT).","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"41 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121580267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a novel airborne magnetometer system deployed on an unmanned aerial vehicle (UAV) that is capable of measuring the horizontal gradient of the three components of the magnetic field. The system consists of two three-component fluxgate magnetometers (FGM) that are mounted on a transverse horizontal boom. The sensor attitude is determined with a low-cost inertial measurement unit. The estimation of the magnetic field components as well as its gradient is extremely sensitive to sensor movement and sensor rotation and requires sophisticated data processing and corrections. Here, we present four specific calibration and correction procedures we consider essential to achieve sufficient accuracy. First, we present a new in-flight calibration method for a FGM gradiometer. Second, we introduce a procedure that corrects for rotation-induced noise in the FGMs that has not been described previously in the literature. In a third step, we correct for mechanical vibrations, which induce high frequency noise in the data. Finally, the gradient of each component is mathematically rotated into the geographical coordinate system. The performance of the system is evaluated on a test site where several metal objects of known magnetisation were placed on the ground surface. For the first time, we show the gradients of magnetic field components measured on a UAV. The gradients agree with the results of a forward simulation within a few nT m−1. The accuracy will be sufficient for many practical applications, such as geological mapping, ore exploration, and the search for metallic bodies.
{"title":"A new system to measure the gradient vector of the magnetic field on unmanned aerial vehicles (UAV) - data processing and field experiment","authors":"Christian Kulüke, C. Virgil, J. Stoll, A. Hördt","doi":"10.1093/rasti/rzac008","DOIUrl":"https://doi.org/10.1093/rasti/rzac008","url":null,"abstract":"\u0000 We present a novel airborne magnetometer system deployed on an unmanned aerial vehicle (UAV) that is capable of measuring the horizontal gradient of the three components of the magnetic field. The system consists of two three-component fluxgate magnetometers (FGM) that are mounted on a transverse horizontal boom. The sensor attitude is determined with a low-cost inertial measurement unit. The estimation of the magnetic field components as well as its gradient is extremely sensitive to sensor movement and sensor rotation and requires sophisticated data processing and corrections. Here, we present four specific calibration and correction procedures we consider essential to achieve sufficient accuracy. First, we present a new in-flight calibration method for a FGM gradiometer. Second, we introduce a procedure that corrects for rotation-induced noise in the FGMs that has not been described previously in the literature. In a third step, we correct for mechanical vibrations, which induce high frequency noise in the data. Finally, the gradient of each component is mathematically rotated into the geographical coordinate system. The performance of the system is evaluated on a test site where several metal objects of known magnetisation were placed on the ground surface. For the first time, we show the gradients of magnetic field components measured on a UAV. The gradients agree with the results of a forward simulation within a few nT m−1. The accuracy will be sufficient for many practical applications, such as geological mapping, ore exploration, and the search for metallic bodies.","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125377039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
U. Chowdhury, F. Levy-Bertrand, M. Calvo, J. Goupy, A. Monfardini
Millimetre-wave observations represent an important tool for Cosmology studies. The Line Intensity Mapping (LIM) technique has been proposed to map in three dimensions the specific intensity due to line (e.g. [C ii], CO) emission, for example from the primordial galaxies, as a function of redshift. Hyper-spectral integrated devices have the potential to replace the current Fourier transform, or the planned Fabry-Perot-based instruments operating at millimetre and sub-millimetre wavelengths. The aim is to perform hyper-spectral mapping, with a spectral resolution R = λ/Δλ = 100–1000, over large, i.e. thousands of beams, instantaneous patches of the Sky. The innovative integrated device that we have developed allows avoiding moving parts, complicated and/or dispersive optics or tunable filters to be operated at cryogenic temperatures. The prototype hyper-spectral focal plane is sensitive in the 75-90 GHz range and contains nineteen horns for sixteen spectral-imaging channels, each selecting a frequency band of about 0.1 GHz. For each channel a conical horn antenna, coupled to a planar superconducting resonant absorber made of thin aluminium, collects the radiation. A capacitively coupled titanium-aluminium bilayer Lumped Element Kinetic Inductance Detector (LEKID) is then in charge of dissipating and sensing the super-current established in the resonant absorber. The prototype is fabricated with only two photo-lithography steps over a commercial mono-crystalline sapphire substrate. It exhibits a spectral resolution R = λ/Δλ ≈ 800. The optical noise equivalent power of the best channels is in the observational relevant $4cdot 10^{-17} W/sqrt{Hz}$ range. The average sensitivity of all the channels is around $1cdot 10^{-16} W/sqrt{Hz}$. The device, as expected from 3-D simulations, is polarisation-sensitive, paving the way to spectro-polarimetry measurements over very large instantaneous field-of-views.
{"title":"A millimetre-wave superconducting hyper-spectral device","authors":"U. Chowdhury, F. Levy-Bertrand, M. Calvo, J. Goupy, A. Monfardini","doi":"10.1093/rasti/rzad038","DOIUrl":"https://doi.org/10.1093/rasti/rzad038","url":null,"abstract":"\u0000 Millimetre-wave observations represent an important tool for Cosmology studies. The Line Intensity Mapping (LIM) technique has been proposed to map in three dimensions the specific intensity due to line (e.g. [C ii], CO) emission, for example from the primordial galaxies, as a function of redshift. Hyper-spectral integrated devices have the potential to replace the current Fourier transform, or the planned Fabry-Perot-based instruments operating at millimetre and sub-millimetre wavelengths. The aim is to perform hyper-spectral mapping, with a spectral resolution R = λ/Δλ = 100–1000, over large, i.e. thousands of beams, instantaneous patches of the Sky. The innovative integrated device that we have developed allows avoiding moving parts, complicated and/or dispersive optics or tunable filters to be operated at cryogenic temperatures. The prototype hyper-spectral focal plane is sensitive in the 75-90 GHz range and contains nineteen horns for sixteen spectral-imaging channels, each selecting a frequency band of about 0.1 GHz. For each channel a conical horn antenna, coupled to a planar superconducting resonant absorber made of thin aluminium, collects the radiation. A capacitively coupled titanium-aluminium bilayer Lumped Element Kinetic Inductance Detector (LEKID) is then in charge of dissipating and sensing the super-current established in the resonant absorber. The prototype is fabricated with only two photo-lithography steps over a commercial mono-crystalline sapphire substrate. It exhibits a spectral resolution R = λ/Δλ ≈ 800. The optical noise equivalent power of the best channels is in the observational relevant $4cdot 10^{-17} W/sqrt{Hz}$ range. The average sensitivity of all the channels is around $1cdot 10^{-16} W/sqrt{Hz}$. The device, as expected from 3-D simulations, is polarisation-sensitive, paving the way to spectro-polarimetry measurements over very large instantaneous field-of-views.","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130228996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Hale, W. Chaplin, G. Davies, Y. Elsworth, R. Howe
We describe a new spectrophotometer for the Birmingham Solar Oscillations Network (BiSON), based on a next generation observation platform, BiSON:NG, a significantly miniaturised system making use of inexpensive consumer-grade hardware and off-the-shelf components, where possible. We show through system modelling and simulation, along with a summer observing campaign, that the prototype instrument produces data on the Sun’s low-degree acoustic (p-mode) oscillations that are of equal quality and can be seamlessly integrated into the existing network. Refreshing the existing ageing hardware, and the extended observational network potential of BiSON:NG, will secure our ongoing programme of high-quality synoptic observations of the Sun’s low-degree oscillations (e.g., for seismic monitoring of the solar cycle at a “whole Sun” level).
{"title":"The next generation Birmingham Solar Oscillations Network (BiSON) spectrophotometer: a new miniaturised instrument for helioseismology","authors":"S. Hale, W. Chaplin, G. Davies, Y. Elsworth, R. Howe","doi":"10.1093/rasti/rzac007","DOIUrl":"https://doi.org/10.1093/rasti/rzac007","url":null,"abstract":"\u0000 We describe a new spectrophotometer for the Birmingham Solar Oscillations Network (BiSON), based on a next generation observation platform, BiSON:NG, a significantly miniaturised system making use of inexpensive consumer-grade hardware and off-the-shelf components, where possible. We show through system modelling and simulation, along with a summer observing campaign, that the prototype instrument produces data on the Sun’s low-degree acoustic (p-mode) oscillations that are of equal quality and can be seamlessly integrated into the existing network. Refreshing the existing ageing hardware, and the extended observational network potential of BiSON:NG, will secure our ongoing programme of high-quality synoptic observations of the Sun’s low-degree oscillations (e.g., for seismic monitoring of the solar cycle at a “whole Sun” level).","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122869034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Sunseri, Z. Slepian, S. Portillo, Jiamin Hou, Sule Kahraman, D. Finkbeiner
We present a new python package sarabande for measuring 3 & 4 Point Correlation Functions (3/4 PCFs) in $mathcal {O} (N_{mathrm{g}}log N_{mathrm{g}})$ time using Fast Fourier Transforms (FFTs), with Ng the number of grid points used for the FFT. sarabande can measure both projected and full 3 and 4 PCFs on gridded 2D and 3D datasets. The general technique is to generate suitable angular basis functions on an underlying grid, radially bin these to create kernels, and convolve these kernels with the original gridded data to obtain expansion coefficients about every point simultaneously. These coefficients are then combined to give us the 3/4 PCF as expanded in our basis. We apply sarabande to simulations of the Interstellar Medium (ISM) to show the results and scaling of calculating both the full and projected 3/4 PCFs.
{"title":"SARABANDE: 3/4 Point Correlation Functions with Fast Fourier Transforms","authors":"J. Sunseri, Z. Slepian, S. Portillo, Jiamin Hou, Sule Kahraman, D. Finkbeiner","doi":"10.1093/rasti/rzad003","DOIUrl":"https://doi.org/10.1093/rasti/rzad003","url":null,"abstract":"\u0000 We present a new python package sarabande for measuring 3 & 4 Point Correlation Functions (3/4 PCFs) in $mathcal {O} (N_{mathrm{g}}log N_{mathrm{g}})$ time using Fast Fourier Transforms (FFTs), with Ng the number of grid points used for the FFT. sarabande can measure both projected and full 3 and 4 PCFs on gridded 2D and 3D datasets. The general technique is to generate suitable angular basis functions on an underlying grid, radially bin these to create kernels, and convolve these kernels with the original gridded data to obtain expansion coefficients about every point simultaneously. These coefficients are then combined to give us the 3/4 PCF as expanded in our basis. We apply sarabande to simulations of the Interstellar Medium (ISM) to show the results and scaling of calculating both the full and projected 3/4 PCFs.","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122601557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The inverse problem of extracting the stellar population content of galaxy spectra is analysed here from a basic standpoint based on information theory. By interpreting spectra as probability distribution functions, we find that galaxy spectra have high entropy, thus leading to a rather low effective information content. The highest variation in entropy is unsurprisingly found in regions that have been well studied for decades with the conventional approach. We target a set of six spectral regions that show the highest variation in entropy – the 4000 Å break being the most informative one. As a test case with real data, we measure the entropy of a set of high quality spectra from the Sloan Digital Sky Survey, and contrast entropy-based results with the traditional method based on line strengths. The data are classified into star-forming (SF), quiescent (Q) and AGN galaxies, and show – independently of any physical model – that AGN spectra can be interpreted as a transition between SF and Q galaxies, with SF galaxies featuring a more diverse variation in entropy. The high level of entanglement complicates the determination of population parameters in a robust, unbiased way, and affect traditional methods that compare models with observations, as well as machine learning (especially deep learning) algorithms that rely on the statistical properties of the data to assess the variations among spectra. Entropy provides a new avenue to improve population synthesis models so that they give a more faithful representation of real galaxy spectra.
{"title":"The entropy of galaxy spectra: How much information is encoded?","authors":"I. Ferreras, O. Lahav, R. Somerville, J. Silk","doi":"10.1093/rasti/rzad004","DOIUrl":"https://doi.org/10.1093/rasti/rzad004","url":null,"abstract":"\u0000 The inverse problem of extracting the stellar population content of galaxy spectra is analysed here from a basic standpoint based on information theory. By interpreting spectra as probability distribution functions, we find that galaxy spectra have high entropy, thus leading to a rather low effective information content. The highest variation in entropy is unsurprisingly found in regions that have been well studied for decades with the conventional approach. We target a set of six spectral regions that show the highest variation in entropy – the 4000 Å break being the most informative one. As a test case with real data, we measure the entropy of a set of high quality spectra from the Sloan Digital Sky Survey, and contrast entropy-based results with the traditional method based on line strengths. The data are classified into star-forming (SF), quiescent (Q) and AGN galaxies, and show – independently of any physical model – that AGN spectra can be interpreted as a transition between SF and Q galaxies, with SF galaxies featuring a more diverse variation in entropy. The high level of entanglement complicates the determination of population parameters in a robust, unbiased way, and affect traditional methods that compare models with observations, as well as machine learning (especially deep learning) algorithms that rely on the statistical properties of the data to assess the variations among spectra. Entropy provides a new avenue to improve population synthesis models so that they give a more faithful representation of real galaxy spectra.","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131355588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is a need for line broadening parameters for molecules found in exoplanetary atmospheres for a variety of broadeners and a range of temperatures. The use of an easily handled semi-classical theoretical expression is suggested for the calculation of pressure-broadened linewidths for (vib)rotational transitions over a large temperature range (200–3000 K) starting from a minimal set of input parameters: kinetic molecular properties and the character of the leading term in the intermolecular interaction potential. Applications to NO and OH colliding with rare-gas atoms and non-polar molecules demonstrate good consistency with available measurements over the full indicated temperature range. The procedure therefore can be expected to provide realistic estimates for line broadening of ‘exotic’ molecules and molecular ions present in hot planetary atmospheres.
{"title":"Simple semi-classical model of pressure-broadened infrared/microwave linewidths in the temperature range 200–3000 K","authors":"J. Buldyreva, S. Yurchenko, J. Tennyson","doi":"10.1093/rasti/rzac004","DOIUrl":"https://doi.org/10.1093/rasti/rzac004","url":null,"abstract":"\u0000 There is a need for line broadening parameters for molecules found in exoplanetary atmospheres for a variety of broadeners and a range of temperatures. The use of an easily handled semi-classical theoretical expression is suggested for the calculation of pressure-broadened linewidths for (vib)rotational transitions over a large temperature range (200–3000 K) starting from a minimal set of input parameters: kinetic molecular properties and the character of the leading term in the intermolecular interaction potential. Applications to NO and OH colliding with rare-gas atoms and non-polar molecules demonstrate good consistency with available measurements over the full indicated temperature range. The procedure therefore can be expected to provide realistic estimates for line broadening of ‘exotic’ molecules and molecular ions present in hot planetary atmospheres.","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114615399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This is an exciting era for exo-planetary exploration. The recently launched JWST, and other upcoming space missions such as Ariel, Twinkle and ELTs are set to bring fresh insights to the convoluted processes of planetary formation and evolution and its connections to atmospheric compositions. However, with new opportunities come new challenges. The field of exoplanet atmospheres is already struggling with the incoming volume and quality of data, and machine learning (ML) techniques lands itself as a promising alternative. Developing techniques of this kind is an inter-disciplinary task, one that requires domain knowledge of the field, access to relevant tools and expert insights on the capability and limitations of current ML models. These stringent requirements have so far limited the developments of ML in the field to a few isolated initiatives. In this paper, We present the Atmospheric Big Challenge Database (ABC Database), a carefully designed, organised and publicly available database dedicated to the study of the inverse problem in the context of exoplanetary studies. We have generated 105,887 forward models and 26,109 complementary posterior distributions generated with Nested Sampling algorithm. Alongside with the database, this paper provides a jargon-free introduction to non-field experts interested to dive into the intricacy of atmospheric studies. This database forms the basis for a multitude of research directions, including, but not limited to, developing rapid inference techniques, benchmarking model performance and mitigating data drifts. A successful application of this database is demonstrated in the NeurIPS Ariel ML Data Challenge 2022.
{"title":"ESA-Ariel Data Challenge NeurIPS 2022: Introduction to exo-atmospheric studies and presentation of the Atmospheric Big Challenge (ABC) Database","authors":"Q. Changeat, K. H. Yip","doi":"10.1093/rasti/rzad001","DOIUrl":"https://doi.org/10.1093/rasti/rzad001","url":null,"abstract":"\u0000 This is an exciting era for exo-planetary exploration. The recently launched JWST, and other upcoming space missions such as Ariel, Twinkle and ELTs are set to bring fresh insights to the convoluted processes of planetary formation and evolution and its connections to atmospheric compositions. However, with new opportunities come new challenges. The field of exoplanet atmospheres is already struggling with the incoming volume and quality of data, and machine learning (ML) techniques lands itself as a promising alternative. Developing techniques of this kind is an inter-disciplinary task, one that requires domain knowledge of the field, access to relevant tools and expert insights on the capability and limitations of current ML models. These stringent requirements have so far limited the developments of ML in the field to a few isolated initiatives. In this paper, We present the Atmospheric Big Challenge Database (ABC Database), a carefully designed, organised and publicly available database dedicated to the study of the inverse problem in the context of exoplanetary studies. We have generated 105,887 forward models and 26,109 complementary posterior distributions generated with Nested Sampling algorithm. Alongside with the database, this paper provides a jargon-free introduction to non-field experts interested to dive into the intricacy of atmospheric studies. This database forms the basis for a multitude of research directions, including, but not limited to, developing rapid inference techniques, benchmarking model performance and mitigating data drifts. A successful application of this database is demonstrated in the NeurIPS Ariel ML Data Challenge 2022.","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123739303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
From data collection to photometric fitting and analysis of white dwarfs, to generating a white dwarf luminosity function requires numerous astrophysical, mathematical, and computational domain knowledge. The steep learning curve makes it difficult to enter the field, and often individuals have to reinvent the wheel to perform identical data reduction and analysis tasks. We have gathered a wide range of publicly available white dwarf cooling models and synthetic photometry to provide a toolkit that allows (i) visualization of various models, (ii) photometric fitting of a white dwarf with or without distance and reddening, and (iii) the computing of white dwarf luminosity functions with a choice of initial mass function, main-sequence evolution model, star-formation history, initial–final mass relation, and white dwarf cooling model. We have recomputed and compared the effective temperature of the white dwarfs from the Gaia EDR3 white dwarf catalogue. The two independent works show excellent agreement in the temperature solutions.
{"title":"WDPhotTools – a white dwarf photometric toolkit in Python","authors":"M. Lam, Kee Wang Yuen, W. Li, M. Green","doi":"10.5281/zenodo.6595029","DOIUrl":"https://doi.org/10.5281/zenodo.6595029","url":null,"abstract":"\u0000 From data collection to photometric fitting and analysis of white dwarfs, to generating a white dwarf luminosity function requires numerous astrophysical, mathematical, and computational domain knowledge. The steep learning curve makes it difficult to enter the field, and often individuals have to reinvent the wheel to perform identical data reduction and analysis tasks. We have gathered a wide range of publicly available white dwarf cooling models and synthetic photometry to provide a toolkit that allows (i) visualization of various models, (ii) photometric fitting of a white dwarf with or without distance and reddening, and (iii) the computing of white dwarf luminosity functions with a choice of initial mass function, main-sequence evolution model, star-formation history, initial–final mass relation, and white dwarf cooling model. We have recomputed and compared the effective temperature of the white dwarfs from the Gaia EDR3 white dwarf catalogue. The two independent works show excellent agreement in the temperature solutions.","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124481423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"RAS techniques and instruments","authors":"J. Tennyson, A. Scaife","doi":"10.1093/rasti/rzac002","DOIUrl":"https://doi.org/10.1093/rasti/rzac002","url":null,"abstract":"","PeriodicalId":367327,"journal":{"name":"RAS Techniques and Instruments","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126511995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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