Earlier this year a machine learning algorithm identified up to 5,000 potential gravitational lenses that could transform our ability to chart the evolution of galaxies since the Big Bang.

Now astronomer Kim-Vy Tran from ASTRO 3D and UNSW Sydney and colleagues have assessed 77 of the lenses using the Keck Observatory in Hawai’i and the Very Large Telescope in Chile. She and her international team confirmed that 68 out of the 77 are strong gravitational lenses spanning vast cosmic distances. 

This success rate of 88 percent suggests that the algorithm is reliable and that we could have thousands of new gravitational lenses. To date, gravitational lenses have been hard to find, and only about a hundred are routinely used.

Kim-Vy Tran proposes spectroscopic confirmation of strong gravitational lenses previously identified using Convolutional Neural Networks (CNN), developed by data scientist Dr. Colin Jacobs at ASTRO 3D and Swinburne University.

The work is part of the ASTRO 3D Galaxy Evolution with Lenses (AGEL) survey.

“Our spectroscopy allowed us to map a 3D picture of the gravitational lenses to show they are genuine and not merely chance superposition,” says corresponding author Dr. Tran from the ARC Centre of Excellence for All Sky Astrophysics in 3-Dimensions (ASTRO3D) and the University of NSW (UNSW).

“Our goal with AGEL is to spectroscopically confirm around 100 strong gravitational lenses that can be observed from both the Northern and Southern hemispheres throughout the year,” she says.

The paper is the result of a collaboration spanning the globe with researchers from Australia, the United States, the United Kingdom, and Chile.

The work was made possible by the development of the algorithm to look for certain digital signatures.

“With that, we could identify many thousands of lenses compared to just a few handfuls,” says Dr. Tran.

Gravitational lensing was first identified as a phenomenon by Einstein who predicted that light bends around massive objects in space in the same way that light bends going through a lens.

In doing so, it greatly magnifies images of galaxies that we would not otherwise be able to see.

While it has been used by astronomers to observe far away galaxies for a long time, finding these cosmic magnifying glasses in the first place has been hit and miss.

“These lenses are very small so if you have fuzzy images, you're not going to really be able to detect them,” says Dr. Tran.

While these lenses let us see objects that are millions of light years away more clearly, they should also let us ‘see’ invisible dark matter that makes up most of the Universe.

“We know that most of the mass is dark,” says Dr. Tran. “We know that mass is bending light and so if we can measure how much light is bent, we can then infer how much mass must be there.”

Having many more gravitational lenses at various distances will also give us a more complete image of the timeline going back almost to the Big Bang.

“The more magnifying glasses you have, the better chance you can try to survey these more distant objects. Hopefully, we can better measure the demographics of very young galaxies,” says Dr. Tran.

“Then somewhere between those really early first galaxies and us, there's a whole lot of evolution that's happening, with tiny star-forming regions that convert pristine gas into the first stars to the sun, the Milky Way.

“And so with these lenses at different distances, we can look at different points in the cosmic timeline to track essentially how things change over time, between the very first galaxies and now.”

Dr. Tran’s team spanned the globe, with each group providing different expertise.

“Being able to collaborate with people, at different universities, has been so crucial, both for setting the project up in the first place, and now continuing with all of the follow-up observations,” she says.

Professor Stuart Wyithe of the University of Melbourne and Director of the ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (Astro 3D) says each gravitational lens is unique and tells us something new.

“Apart from being beautiful objects, gravitational lenses provide a window to studying how mass is distributed in very distant galaxies that are not observable via other techniques. By introducing ways to use these new large data sets of the sky to search for many new gravitational lenses, the team opens up the opportunity to see how galaxies get their mass,” he says.

Professor Karl Glazebrook of Swinburne University, and Dr. Tran’s Co-Science Lead on the paper, paid tribute to the work that had gone before.

“This algorithm was pioneered by Dr. Colin Jacobs at Swinburne. He sifted through tens of millions of galaxy images to prune the sample down to 5,000. Never did we dream that the success rate would be so high,” he says.

“Now we are getting images of these lenses with the Hubble Space Telescope, they range from jaw-droppingly beautiful to extremely strange images that will take us considerable effort to figure out.”

Associate Professor Tucker Jones of UC Davis, another co-science lead on the paper, described the new sample as “a giant step forward in learning how galaxies form over the history of the Universe”.

“Normally these early galaxies look like small fuzzy blobs, but the lensing magnification allows us to see their structure with much better resolution. They are ideal targets for our most powerful telescopes to give us the best possible view of the early universe,” he says.

“Thanks to the lensing effect we can learn what these primitive galaxies look like, what they are made of, and how they interact with their surroundings.”

Over the last 40 years, a rapid shrinking of Arctic sea ice has been one of the most significant indicators of climate change. The amount of sea ice that survives the Arctic summer has declined 13 percent per decade since the late 1970s and projections show the region could experience its first ice-free summer by 2040. 

This rapid melting is not just disruptive to surrounding coastal cities and small island nations; it also may have a lasting impact on global weather patterns, according to a new study from a University at Albany researcher. 

Researchers have revealed that the magnitude and pattern of Arctic sea-ice loss can directly influence El Niño. Further, as the Arctic becomes seasonally ice-free, the frequency of strong El Niño events increases significantly.

El Niño is a complex weather pattern that occurs when surface water in the central and eastern Pacific Ocean becomes warmer than average and east winds blow weaker than normal. The events, which typically occur every few years, can produce unusual and, sometimes dangerous, weather conditions around the world including droughts, floods, and severe storms. 

Before this study, little was known about whether dwindling Arctic sea ice is capable of influencing strong El Niño events, according to its lead author Jiping Liu, an associate professor in UAlbany’s Department of Atmospheric and Environmental Sciences in the College of Arts and Sciences. 

“El Niño is an important climate phenomenon, recognized as a driver of climate variability responsible for large and diverse societal impacts,” Liu said. “Our study, for the first time, finds that large Arctic sea-ice loss directly influences global climate extremes, including an increase in the frequency of strong El Niño events.” 

{module title="Inside Content Banners"} Modeling Sea Ice 

Liu and colleagues ran a series of time slice model simulations that relied on atmosphere, land, ocean, and sea ice variables to determine the influence of Arctic sea ice loss on El Niño events.

Before running the simulations, they directly fixed Arctic sea ice cover during three time periods —1980-99, 2020-2039, and 2080-99. The simulations were generated using the National Center for Atmospheric Research’s Community Climate System Model, a global climate model that provides state-of-the-art supercomputer simulations of the Earth's past, present, and future climate states. 

By comparing the simulations, the researchers found no significant change in the occurrence of strong El Niño events in response to moderate Arctic sea-ice loss, which is consistent with satellite observations to date. However, as the ice loss continues and the Arctic becomes seasonally ice-free, the frequency of strong El Niño events increases by more than one-third. 

“After decades of research, there is general, albeit not universal, the agreement that the frequency of El Niño events, especially extremely strong El Niño events, will increase under greenhouse warming,” Liu said. “Since Arctic sea ice is projected to continue to decline dramatically, it was important to assess whether the projected increase in strong El Niño can be directly connected.” 

To separate the role of Arctic sea ice loss and greenhouse gas emissions, the researchers conducted an additional experiment in which Arctic sea ice cover was fixed based on the historical simulations, but increased carbon dioxide levels by 1 percent for 100 years starting from its level in the year 2000. They conclude that at least 37-48 percent of the increase of strong El Niño events near the end of the 21st century would be associated specifically with Arctic sea ice loss.  

“It is becoming clearer that climate models need to simulate decreasing Arctic sea ice realistically in order to correctly simulate El Niño variability,” Liu said. 

Climate Change in the Arctic 

Liu’s latest research adds to his substantial contributions to understanding sea ice variability and its role in global climate dynamics. 

In 2016, he published a study in the Journal of Climate that showed how Arctic sea ice melt is an underlying cause of the shrinking of the Greenland ice sheet observed in recent decades. He was also the lead author of a 2019 study that aimed to improve Arctic sea ice prediction, at daily to seasonal time scales, using multivariate data assimilation.    

Along with Liu, collaborators in the new study include Mirong Song and Zhu Zhu of the Chinese Academy of Sciences, Radley Horton of Columbia University, Yongyun Hu of Peking University in China, and Shang-Ping Xie of the University of California San Diego.