[The Epoch Times, February 20, 2023](Epoch Times reporter Linda compiled and reported) A large-scale survey of the galactic plane of the Milky Way has revealed 3.32 billion cosmic objects in stunning detail.
This vast catalog of celestial objects, possibly the largest of its kind, was built using data from the Dark Energy Camera at the Cerro Tololo Inter-American Observatory in Chile, funded by the National Science Foundation (NSF) operations.
“Imagine this group photo of more than 3 billion people, and everyone can recognize it!” Debra Fischer, director of the NSF Division of Astronomical Sciences, released a statement last month.statement“In the coming decades, astronomers will scrutinize the details of the portraits of more than 3 billion stars in the Milky Way,” Zhong said.
Earth’s Milky Way is made up of hundreds of billions of stars, numerous star-forming regions, and huge clouds of gas and dust. Cataloging such objects is a daunting task, but the team behind the new catalog — the second data release of the Dark Energy Camera Plane Survey, called DECaPS2 — took up the challenge.
The researchers used the Dark Energy Camera to observe the galactic plane at optical and near-infrared wavelengths, revealing this region of the Milky Way in unprecedented detail. It took two years to make the catalog, and the Dark Energy Camera generated more than 10 terabytes of data from 21,400 individual exposures of the southern sky, team members said.
“A major reason for the success of DECaPS2 is that we targeted only one region of extremely high star density and carefully identified images that nearly overlapped each other,” said study lead author Andrew Saydjari at NSF on Jan. 18. The new results were announced in the same statement released today.
Saydjari, a researcher at the Harvard-Smithsonian Center for Astrophysics, said: “This allows us to generate the largest such catalog of stars ever produced from a single camera.”
Most of the Milky Way’s stars and dust lie in the galactic plane, seen as a bright band across the center in a newly released Dark Energy Camera image. While the abundance of stars and glowing dust makes for spectacular pictures, it also hinders observation of the galactic plane.
Visible in these images are dark tendrils of gas and dust that absorb starlight and completely obscure faint stars, while light from dense, cold stellar nebulae prevents measurements of the brightness of individual objects. In addition, the large star population means that stars overlap in galactic plane images of the Milky Way, making it difficult to distinguish individual stars from their neighbors.
Although tricky, this problem can be countered by observing the galactic plane in near-infrared light. Because gas clouds don’t absorb these wavelengths of light well, astronomers can see through the gas and dust to see obscured stars.
The Inter-American Observatory team also used an innovative data processing method that allowed it to predict the background of each star. This approach reduces image blurring caused by nebulae and dense star clusters and ensures the accuracy of data processing in the catalog.
The accuracy of the Dark Energy Camera data was then further enhanced by combining the Dark Energy Camera data with observations from other telescopes.
“When combined with images from Pan-STARRS 1, DECaPS2 completes a 360-degree panoramic view of the Milky Way’s disk,” study co-author Edward Schlafly of the Space Telescope Science Institute in Baltimore said in a statement. said the statement. “With this new survey, we can create the most detailed three-dimensional map of the Milky Way’s stars and dust.”
This catalog of about 3.32 billion celestial objectsRaw dataAccessible to astronomers and the public, this new version enables the survey to cover up to 6.5 percent of the night sky, extending 130 degrees, or 13,000 times the angular size of the full Moon.
A paper published on the preprint website ArXiv details the team’s research, which has been accepted for publication in the Astrophysical Journal Supplement. ◇#
Editor in charge: Ye Ziwei
