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SPLUS: Science Hunters

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Results

Results and Data Releases

So, here's the deal: Imagine you're trying to measure how bright the objects in the sky are. You'd think that it would be pretty straightforward, but it's not that simple. The brightness you see depends of many factors, like on how far away the stars are, the dusty between us, how big they are, and how hot they are.

Now, let's talk about how we go about doing this in large scale. We use something called a "Photometric survey" to collect the light coming from these stars. The survey is like a big data-gathering project. For each observation, we decide how long to look, what kind of light to use, and which filters to put in place. These decisions depend on what we're trying to learn.

In the case of the SPLUS survey, we picked our filters carefully. They're designed to capture specific types of light that tell us a lot about galaxies and stars. We're not just randomly looking at stars; we're trying to get the most useful information.

So, we collect all this data, and what do we do with it? Well, it's like putting together a giant puzzle. We use the data to figure out things like what the stars are made of, their shapes, and how they're all arranged in space. On the flip side, when it comes to galaxies, we're on a mission to understand everything about them – their shapes, sizes, the mysterious dark matter they hide, and the intricate structures they form. It's like trying to unlock the cosmic secrets hidden in the depths of the universe.

And we don't just keep all this knowledge to ourselves. We write up our findings in fancy scientific papers and send them to scientific journals. Each paper is like a chapter in the big book of space knowledge.

Here's the cool part: you're a part of this too! We don't hide our data. We share it with our internal team and eventually with the whole world. You can access it, download it, analyze it, and even make your discoveries. Just head over to splus.cloud for more details (https://www.splus.cloud).

But wait, there's more! Below, we've listed some publications that were made using the SPLUS data. They can give you a better idea of how all this works. It's like our way of showing you the roadmap to the secrets of the universe!

Publication List

  1. Observations of the First Electromagnetic Counterpart to a Gravitational-wave Source by the TOROS Collaboration Díaz et al. 2017: AJ, v848, L29
  2. Multi-messenger Observations of a Binary Neutron Star Merger Abbot et al 2017: AJ, 848, L12
  3. The Southern Photometric Local Universe Survey (S-PLUS): improved SEDs, morphologies, and redshifts with 12 optical filters Mendes de Oliveira et al. 2019: MNRAS, 489, 241
  4. The S-PLUS: a star/galaxy classification based on a Machine Learning approach Costa-Duarte et al. 2019: MNRAS, submitted
  5. Assessing the photometric redshift precision of the S-PLUS survey: the Stripe-82 as a test-case Molino et al. 2020: MNRAS, 499, 3884
  6. J-PLUS: Tools to identify compact planetary nebulae in the Javalambre and southern photometric local Universe surveys Gutiérrez-Soto et al. 2020: A&A, 633, 123
  7. One Hundred SMUDGes in S-PLUS: Ultra-diffuse Galaxies Flourish in the Field Barbosa et al. 2020: ApJS, 247, 46
  8. On the discovery of stars, quasars, and galaxies in the Southern Hemisphere with S-PLUS DR2 Nakazono et al. 2021: MNRAS, 507, 5847
  9. Searching for active low-mass stars in CMa star-forming region: multi-band photometry with T80S Jane Gregorio-Hetem et al. 2021: AJ, 161, 133
  10. SPLUS J210428.01-004934.2: An Ultra Metal-poor Star Identified from Narrowband Photometry Placco et al. 2021: ApJL, 912, 32
  11. The Photometric Metallicity and Carbon Distributions of the Milky Way's Halo and Solar Neighborhood from S-PLUS Observations of SDSS Stripe 82 Whitten et al. 2021: ApJ, 912, 147
  12. Deep Learning assessment of galaxy morphology in S-PLUS Data Release 1 Bom et al. 2021: MNRAS, 507, 1937
  13. A new method to detect globular clusters with the S-PLUS survey Buzzo et al. 2021: MNRAS, 510, 1383
  14. Photometric redshifts for the S-PLUS Survey: Is machine learning up to the task? Lima et al. 2022: Astronomy & Computing, 38, 100510
  15. Data Release 2 of S-PLUS: accurate template-fitting based photometry covering ∼∼1000 square degrees in 12 optical filters Almeida-Fernandes et al. 2022: MNRAS, 511, 4590
  16. S-PLUS: Exploring wide field properties of multiple populations in galactic globular clusters at different metallicities Hartmann et al. 2022: MNRAS, 515, 4191
  17. Mining S-PLUS for Metal-poor Stars in the Milky Way Placco et al. 2022: AJ, 262, 8
  18. S-PLUS DR1 galaxy clusters and groups catalogue using PzWav Werner et al. 2023: MNRAS, 519, 2630
  19. CALSAGOS: Clustering ALgorithmS Applied to Galaxies in Overdense Systems Olave-Rojas et al. 2023: MNRAS, 519, 4171
  20. Chemodynamical properties and ages of metal-poor stars in S-PLUS Almeida-Fernandes et al. 2023: MNRAS, 523, 2934
  21. An Extended Catalogue of galaxy morphology using Deep Learning in Southern Photometric Local Universe Survey Data Release 3 Bom et al. 2023: arXiv, arXiv:2306.08684
  22. Estimating stellar population and emission-line properties in S-PLUS galaxies Thainá-Batista et al. 2023: MNRAS, 526, 1874
  23. Ages and metallicities of stellar clusters using S-PLUS narrow-band integrated photometry: the Small Magellanic Cloud de Souza et al. 2023: MNRAS, submitted
  24. The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster. Smith Castelli et al. (MNRAS, submitted)

Theses

  1. Luiz Mauricio Azanha, MSc, 13/11/2018: Study of feasibility for the detection of halos of galaxies in Hα using multi-band photometry (IAG/USP, supervisor: Claudia Mendes de Oliveira)
  2. Stephane Vaz Werner de Almeida, MSc, 30/09/2019: SPACE - Galaxy cluster catalog for the S-PLUS DR1 Stripe82 (IAG/USP, supervisor: Claudia Mendes de Oliveira)
  3. Erik-Vinicius Rodrigues de Lima, MSc, 29/10/2019: Photometric redshifts for S-PLUS using machine learning techniques (IAG/USP, supervisor: Laerte Sodré Jr.)
  4. Luis Angel Gutiérrez Soto, PhD, 05/12/2019: Tools to discover planetary and symbiotic nebulae in optical multi-band photometric surveys (OV/UFRJ, supervisor: Denise Rocha Gonçalves)
  5. Richard Camuccio, MSc, 05/2020: Searching for optical counterparts to gravitational waves (The University of Texas Rio Grande Valley, supervisor: Mario C. Diaz)
  6. Maria Luísa Gomes Buzzo, MSc, 23/07/2020: Detailed Studies of Lenticular Galaxies in the Local Universe (IAG/USP, supervisor: Claudia Mendes de Oliveira)
  7. Catalina Francisca Labayru Fernandez, MSc, 13/08/2020: Ciencia análoga a estudios de espectroscopía de campo integral a través del uso de S-PLUS (Universidad de La Serena, supervisor: Sergio Torres-Flores)
  8. Rodrigo Magalhães de Araujo, MSc, 06/04/2021: Identificação e estudo de fontes de rádio no Stripe82 do Southern Photometric Local Universe Survey (Observatório Nacional, supervisor: Roderik Overzier)
  9. Gabriel Fabiano de Souza, MSc, 28/06/2021: Idades e metalicidades de aglomerados estelares na Pequena Nuvem de Magalhães utilizando fotometria integrada do S-PLUS (IAG/USP, supervisor: Claudia Mendes de Oliveira)
  10. Júlia Thainá Da Silva Cunha Batista, MSc, 30/08/2021: Primeiros experimentos com cubos de dados de galáxias do S-PLUS (Universidade Federal de Santa Catarina, supervisor: Roberto Cid Fernandes)
  11. Círia Lima Dias, PhD, 28/12/2021: A panchromatic view of Hydra cluster galaxies with S-PLUS data (ULS, supervisor: Antonela Monachesi e Sergio Torres Flores)
  12. Pedro Ticiani dos Santos, MSc, 30/10/2023: Em busca de estrelas Be utilizando fotometria de múltiplas bandas: Estudo de caso de NGC330 utilizando dados do SOAR e S-PLUS (IAG/USP, supervisor: Alex Cavaliéri Carciofi)