New Algorithm Enhances Ground-Based Telescope Images Dramatically
A groundbreaking algorithm developed by a team at Johns Hopkins University has the potential to significantly enhance images captured by ground-based telescopes. This innovative technology, named Image MM, effectively removes atmospheric distortions, enabling telescopes like the Subaru Telescope in Hawaii to produce clearer and more detailed images. Following successful tests on the Subaru Telescope, the algorithm is set to be applied to the upcoming images from the Vera C. Rubin Observatory in Chile, which will begin its science operations later this year.
The Image MM algorithm was created by mathematician Yashil Sukurdeep, who explained that the name is derived from the Majorization–Minimization (MM) method. This mathematical technique has been adapted for astronomical use, allowing it to tackle the challenges posed by the Earth’s atmosphere. Ground-based telescopes have traditionally faced limitations due to the distortion of light as it passes through atmospheric layers, which can cause stars to twinkle and obscure celestial details.
Astronomers have long sought to improve the quality of images from ground-based telescopes, striving to reach the theoretical maximum resolution known as the Dawes limit. Techniques such as adaptive optics, which involve creating artificial guide stars for calibration, have been used, but they do not fully eliminate noise or blur. Sukurdeep noted, “Our framework can recover a near-perfect image from a series of imperfect observations.”
The Image MM algorithm models how light from celestial objects travels through distorted atmospheric conditions. By applying this model, it reconstructs the original, sharp images obscured by atmospheric effects. Sukurdeep likened the atmosphere to “a restless sheer curtain” that constantly shifts, making it challenging to capture clear images of the night sky.
Initial tests on the Subaru Telescope have shown that Image MM can produce images that are sharper and more detailed than previously possible. The next phase involves utilizing this algorithm on images from the Vera C. Rubin Observatory, which aims to explore dark matter distribution in the universe. One of its primary scientific objectives includes measuring how dark matter subtly warps space, causing galaxies to appear slightly deformed due to weak gravitational lensing.
The effect of weak gravitational lensing is subtle, necessitating precise observations. The application of Image MM will enhance the accuracy of these measurements. Tamás Budavári, an expert from Johns Hopkins University, remarked, “Gaining even just a small degree of depth and quality improvement from these observations can be huge.”
While space telescopes like the Hubble and the James Webb Space Telescopes produce superior images overall, they have narrower fields of view. In contrast, the Vera C. Rubin Observatory boasts a wide field of view measuring 3.5 degrees, equivalent to the angular diameter of seven full moons. The implementation of Image MM will offer significant advantages in capturing broader celestial phenomena.
Sukurdeep concluded, “We’ll never have ground truth, but we think this is as close as it currently gets to perfect for ground-based telescopes.” A detailed paper discussing Image MM and its test results was published on September 29, 2023, in The Astronomical Journal, marking a significant advancement in astronomical imaging technology.
