Artificial Intelligence Archives

August 31, 2024August 31, 2024 by Mark Thompson

Estimating the Basic Settings of the Universe

This snapshot compares the distribution of galaxies in a simulated universe used to train SimBIG (right) to the galaxy distribution seen in the real universe (left). Bruno Régaldo-Saint Blancard/SimBIG collaboration

The Standard Model describes how the Universe has evolved at large scale. There are six numbers that define the model and a team of researchers have used them to build simulations of the Universe. The results of these simulations were then fed to a machine learning algorithm to train it before it was set the task of estimating five of the cosmological constants, a task which it completed with incredible precision.

May 2, 2024May 2, 2024 by Matt Williams

What Can AI Learn About the Universe?

Will AI become indispensable in an age of "big data" astronomy? Credit: DALL-E

Artificial intelligence and machine learning have become ubiquitous, with applications ranging from data analysis, cybersecurity, pharmaceutical development, music composition, and artistic renderings. In recent years, large language models (LLMs) have also emerged, adding human interaction and writing to the long list of applications. This includes ChatGPT, an LLM that has had a profound impact since it was introduced less than two years ago. This application has sparked considerable debate (and controversy) about AI’s potential uses and implications.

Astronomy has also benefitted immensely, where machine learning is used to sort through massive volumes of data to look for signs of planetary transits, correct for atmospheric interference, and find patterns in the noise. According to an international team of astrophysicists, this may just be the beginning of what AI could do for astronomy. In a recent study, the team fine-tuned a Generative Pre-trained Transformer (GPT) model using observations of astronomical objects. In the process, they successfully demonstrated that GPT models can effectively assist with scientific research.

April 6, 2024April 6, 2024 by Evan Gough

Roman Will Learn the Ages of Hundreds of Thousands of Stars

By carefully observing star spots, the Nancy Grace Roman Space Telescope will determine stellar ages. It needs some help from AI though. Image Credit: NASA and STScI

Astronomers routinely provide the ages of the stars they study. But the methods of measuring ages aren’t 100% accurate. Measuring the ages of distant stars is a difficult task.

The Nancy Grace Roman Space Telescope should make some progress.

January 22, 2024January 22, 2024 by Evan Gough

Vera Rubin Will Help Us Find the Weird and Wonderful Things Happening in the Solar System

The Vera Rubin Observatory at twilight on April 2021. It's been a long wait, but the observatory should see first light later this year. Image Credit: Rubin Obs/NSF/AURA

The Vera Rubin Observatory (VRO) is something special among telescopes. It’s not built for better angular resolution and increased resolving power like the European Extremely Large Telescope or the Giant Magellan Telescope. It’s built around a massive digital camera and will repeatedly capture broad, deep views of the entire sky rather than focus on any individual objects.

By repeatedly surveying the sky, the VRO will spot any changes or astronomical transients. Astronomers call this type of observation Time Domain Astronomy.

November 28, 2023November 28, 2023 by Matt Williams

Why Don't We See Robotic Civilizations Rapidly Expanding Across the Universe?

The central region of the Milky Way, also known as the Zone of Avoidance. Credit: ESO/S. Brunier

In 1950, while sitting down to lunch with colleagues at the Los Alamos Laboratory, famed physicist and nuclear scientist Enrico Fermi asked his famous question: “Where is Everybody?” In short, Fermi was addressing the all-important question that has plagued human minds since they first realized planet Earth was merely a speck in an infinite Universe. Given the size and age of the Universe and the way the ingredients for life are seemingly everywhere in abundance, why haven’t we found any evidence of intelligent life beyond Earth?

This question has spawned countless proposed resolutions since Fermi’s time, including the infamous Hart-Tipler Conjecture (i.e., they don’t exist). Other interpretations emphasize how space travel is hard and extremely time and energy-consuming, which is why species are likely to settle in clusters (rather than a galactic empire) and how we are more likely to find examples of their technology (probes and AI) rather than a species itself. In a recent study, mathematician Daniel Vallstrom examined how artificial intelligence might be similarly motivated to avoid spreading across the galaxy, thus explaining why we haven’t seen them either!

September 29, 2023September 29, 2023 by Laurence Tognetti

Since Aliens Obey the Laws of Physics, Can We Guess What They Look Like?

Since time immemorial, humans have gazed up at the stars and wondered if we’re alone in the universe. We have asked if there are other intelligent beings out there in the vastness of the cosmos, also known as extraterrestrial intelligence (ET). Yet, despite our best efforts, we have yet to confirm the existence of ET outside of the Earth. While the search continues, it’s fair to speculate if they might look “human” or humanoid in appearance, or if they could look like something else entirely. Here, we present a general examination and discussion with astrobiologists pertaining to what ET might look like and what environmental parameters (e.g., gravity, atmospheric makeup, stellar activity) might cause them to evolve differently than humans.

August 18, 2023August 22, 2023 by Matt Williams

Want to Find UFOs? That's a Job for Machine Learning

UFO encounter video — Cockpit video shows an anomalous aerial encounter in 2015. Credit: U.S Navy Video

In 2017, humanity got its first glimpse of an interstellar object (ISO), known as 1I/’Oumuamua, which buzzed our planet on its way out of the Solar System. Speculation abound as to what this object could be because, based on the limited data collected, it was clear that it was like nothing astronomers had ever seen. A controversial suggestion was that it might have been an extraterrestrial probe (or a piece of a derelict spacecraft) passing through our system. Public fascination with the possibility of “alien visitors” was also bolstered in 2021 with the release of the UFO Report by the ODNI.

This move effectively made the study of Unidentified Aerial Phenomena (UAP) a scientific pursuit rather than a clandestine affair overseen by government agencies. With one eye on the skies and the other on orbital objects, scientists are proposing how recent advances in computing, AI, and instrumentation can be used to assist in the detection of possible “visitors.” This includes a recent study by a team from the University of Strathclyde that proposes how hyperspectral imaging paired with machine learning could lead to an advanced data pipeline for characterizing UAP.

April 14, 2023April 14, 2023 by Alan Boyle

Artificial Intelligence Produces a Sharper Image of M87’s Big Black Hole

The new PRIMO reconstruction of the black hole in M87. This is based on a newly "cleaned-up" image from the Event Horizon Telescope. (Credit: Lia Medeiros et al. / ApJL, 2023)

Astronomers have used machine learning to sharpen up the Event Horizon Telescope’s first picture of a black hole — an exercise that demonstrates the value of artificial intelligence for fine-tuning cosmic observations.

The image should guide scientists as they test their hypotheses about the behavior of black holes, and about the gravitational rules of the road under extreme conditions.

February 10, 2023February 10, 2023 by Matt Williams

Machine Learning is a Powerful Tool When Searching for Exoplanets

Three young planets in orbit around an infant star known as HD 163296 Credit: NRAO/AUI/NSF; S. Dagnello

Astronomy has entered the era of big data, where astronomers find themselves inundated with information thanks to cutting-edge instruments and data-sharing techniques. Facilities like the Vera Rubin Observatory (VRO) are collecting about 20 terabytes (TB) of data on a daily basis. Others, like the Thirty-Meter Telescope (TMT), are expected to gather up to 90 TB once operational. As a result, astronomers are dealing with 100 to 200 Petabytes of data every year, and astronomy is expected to reach the “exabyte era” before long.

In response, observatories have been crowdsourcing solutions and making their data open-access so citizen scientists can assist with the time-consuming analysis process. In addition, astronomers have been increasingly turning to machine learning algorithms to help them identify objects of interest (OI) in the Universe. In a recent study, a team led by the University of Georgia revealed how artificial intelligence could distinguish between false positives and exoplanet candidates simultaneously, making the job of exoplanet hunters that much easier.

December 7, 2022December 7, 2022 by Paul M. Sutter

How Artificial Intelligence Can Find the Source of Gamma-Ray Bursts

Gamma-ray bursts (GRBs) are powerful flashes of energetic gamma-rays lasting from less than a second to several minutes. They release a tremendous amount of energy in this short time making them the most powerful events in the Universe. They are thought to be mostly associated with the explosion of stars that collapse into black holes. In the explosion, two jets of very fast-moving material are ejected, as depicted in this artist’s illustration. If a jet happens to be aimed at Earth, we see a brief but powerful gamma-ray burst. Credit: ESO/A. Roquette

Gamma-ray bursts come in two main flavors, short and long. While astronomers believe that they understand what causes these two kinds of bursts, there is still significant overlap between them. A team of researchers have proposed a new way to classify gamma-ray bursts using the aid of machine learning algorithms. This new classification scheme will help astronomers better understand these enigmatic explosions.