University of São Paulo: Astronomers discover star that challenges current models of evolution of the Universe

UIn a study published this month by The Astrophysical Journal Letters(ApJL) reveals the discovery of a star belonging to the very select group of ultra-heavy metal stars. The star, known as SPLUS J2104-0049, was selected to be observed by medium and high resolution spectroscopy in two of the main telescopes in the world, Gemini Sul and Magellan Clay, both located in Chile. An important characteristic of the star SPLUS J2104-0049 is that it has the lowest carbon abundance ever measured in a star of this type, which challenges the models that currently describe the evolution of the first stars. The discovery was made based on data obtained by researchers from the international project S-PLUS, which brings together more than 100 scientists among researchers and students, based at USP’s Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG).

For astronomers, metals are all chemicals that are heavier than helium. “In the field of stellar archeology, it is believed that ultra-metal-heavy stars were born from clouds of gas enriched by the first generation of stars to form in the Universe. Currently, only 35 such stars are known ”, explains Vinicius Placco, associate scientist at NOIRLab, based in Tucson, Arizona, United States, who led the research. A special feature of the SPLUS J2104-0049 star is that it has the lowest carbon abundance ever measured for an ultra-super star in metals. “This challenges current models about the evolution of the first stars”, completes the researcher.

Set of colored panels with images of the star SPLUS 2104-0049, seen through the 12 filters of the S-PLUS; the lines that are indicated with H (hydrogen), Ca (calcium), CH (carbon), Mg (magnesium) are called “absorption lines”, which give an idea of the amount of each chemical element in the star’s atmosphere – Photo: Placco et al.

The DR-2 represents the addition of data and images from an area of 950 square degrees, tripling the area studied until then available in the previous catalog. The images were taken between 2016 and 2020 and include brightness measurements in the 12 photometric bands of more than 21 million new objects. The database has several tools for its exploration. “Interested parties can obtain images of the regions of interest through a simple and friendly interface, being able to assemble color images at the same time”, says Gustavo Schwarz, a Computer Science student at Universidade Presbiteriana Mackenzie and an undergraduate student at IAG, who developed the system. “In addition, we provide a package that also allows you to directly download the project data.”
For a correct interpretation of the data, it was necessary to develop a special calibration technique for the S-PLUS, taking advantage of calibration measures from other projects. “Calibrations of similar projects are transformed to the 12 filter system used by S-PLUS through the use of synthetic stellar models. This type of procedure allows you to optimize the telescope time available for scientific observations, reducing the time needed to complete the project by around 15% ”, explains astrophysicist Felipe de Almeida Fernandes. Fernandes, who is a postdoctoral fellow in the Astronomy Department at IAG, worked on the calibration efforts and leads the article submitted to the Monthly Notices of the Royal Astronomical Society (MNRAS) that describes the launch of the DR-2 of S-PLUS.

Felipe de Almeida Fernandes – Photo: Personal archive

The new calibrations of the DR-2 made it possible to estimate important physical parameters, such as temperature and chemical composition, in particular the amount of carbon, for more than 700,000 stars in the Milky Way. This gigantic effort also required calculation tools based on artificial neural networks that had to be “taught” before. With the volume of data obtained each night by S-PLUS, it would be impossible for a human being to analyze and interpret all information for a lifetime. To solve this type of problem, the analysis of images and processed data includes Artificial Intelligence algorithms.

Separating stars and galaxies
An example is the routine for separating stars, galaxies and quasars that was developed to make an adequate classification without human intervention. For this, the program underwent a “training” and learned to differentiate each type of object. “In addition to including the brightness values in the 5 wide bands of the filter system, as is usually done, the S-PLUS program also included morphological characteristics obtained by the project itself, as well as data from the WISE satellite, which observed the entire sky in the infrared, ”explains Lilianne Nakazono, a doctoral student in the Astronomy Department at IAG, who is part of the group that makes the classification of objects. According to Lilianne, the success rate of the algorithm exceeds 97%, that is, for every thousand classified objects, only 22 have an incorrect classification.

Clécio De Bom, a researcher at the Brazilian Center for Physical Research (CBPF), also uses Artificial Intelligence to analyze the massive S-PLUS data set, leading a project that applies models of deep neural networks to automatically identify the shape of galaxies: spiral and elliptical. The work allows to evaluate the use of the 12 colors of the S-PLUS for this type of classification. “Due to the large amount of data available, this type of visual analysis is becoming increasingly difficult to be done by human specialists”, he evaluates. “In addition, several models of deep learning have been shown to be more efficient than human in certain visual analyzes. The number and proportion of different forms of galaxies are associated with the history of their formation and the structures in the Universe,

Clécio R. De Bom – Photo: Personal archive

Another example of the use of Artificial Intelligence refers to machine learning to obtain distances to objects that are beyond our galaxy. This technique allows to determine the distance to the object through a statistical analysis of its brightness in the filters used by the project. “For the training of the algorithm, photometric databases were used, such as S-PLUS, GALEX, a satellite intended to observe in the ultraviolet, 2MASS and unWISE, which are projects for mapping the entire sky in the infrared”, explains Erik Vinícius de Lima, PhD student at IAG who participates in the study.

The S-PLUS project is an international project with the participation of researchers from countries such as Brazil, Argentina, Chile, USA and Spain, bringing together more than 100 scientists among researchers and students. The S-PLUS is based at IAG, in São Paulo, and has as main researcher Cláudia Mendes de Oliveira, professor at USP. Roderik Overzier, a senior researcher at the National Observatory, is a project scientist.

The S-PLUS was founded by USP, National Observatory, Federal University of Santa Catarina (UFSC), Federal University of Sergipe (UFS) and Universidad de La Serena (Chile), with important contributions from the National Institute for Space Research (INPE) and Centro de Estudios de Física del Cosmos de Aragón (CEFCA), and funding from the São Paulo State Research Support Foundation (Fapesp), National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel ( Capes), Research Support Foundation of the State of Rio de Janeiro (Faperj) and Financier of Studies and Projects (Finep).

Participation as a member of the S-PLUS project ( ) is open to all scientists from Brazilian institutions. Several Brazilian researchers are also part of the collaborations J-PLUS ( ) and J-PAS ( ), these in the Northern Hemisphere, whose data, together with S-PLUS, will cover almost half of the entire celestial sphere.

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