Every clear night for the last three weeks, Bob Stephens has pointed his home telescope at the same two stars in hopes of witnessing one of the most violent events in the universe — a nova explosion a hundred thousand times brighter than the sun.

The eruption, which scientists say could happen any day now, has excited the interest of major observatories worldwide, and it promises to advance our understanding of turbulent binary star systems.

Yet for all the high-tech observational power that NASA and other scientific institutions can muster, astrophysicists are relying on countless amateur astronomers like Stephens to spot the explosion first.

The reason? It’s just too costly to keep their equipment focused on the same subject for months at a time.

“I think everyone will look at it while it happens, but sitting there just looking at it isn’t going to make it happen,” said Tom Meneghini, the director of telescope operations and executive director emeritus at the Mt. Wilson Observatory. “It’s like a watched pot,” he joked.

The star is so far away that it takes 3,000 years for its light to reach the Earth, meaning the explosion occurred before the last of the Egyptian pyramids were built. It will appear about as bright as the North Star for just a few days before fading into the darkness.

Once it’s spotted, some of the most advanced observatories on Earth and in space will join in watching, including NASA’s James Webb Space Telescope.

“A lot of people are eagerly waiting to spot the new jewel in the crown,” said Mansi Kasliwal, the Caltech astronomy professor who is planning to use the Palomar Observatory in northeast San Diego County to observe the event. The nova will erupt in the Corona Borealis, or Northern Crown, constellation.

T Coronae Borealis, also called the Blaze Star, is actually two stars — a hot, dense white dwarf, and a cooler red giant.

The dwarf star, which ran out of fuel long ago and collapsed to roughly the size of Earth, has been siphoning hydrogen gas from its larger neighbor for about a human lifetime.

This stolen gas has accumulated in a disk around the dwarf like a hot, messy version of Saturn’s rings. Soon, the disk will grow so heavy that it will become violent and unwieldy, and inevitably, explode like a thermonuclear bomb.

Neither star is destroyed however, and the process repeats itself roughly every 80 years.

Stephens has data from T Coronae Borealis going back years. The oscillations in the data represent the two stars orbiting around each other.

(Robert Gauthier/Los Angeles Times)

This time around, there’s an army of enthusiasts like Stephens ready to sound the alarm when the star goes nova.

Far from mere hobbyists, a number of these amateur observers have published their own scientific research. Stephens even built his own observatory as an addition to his house in Rancho Cucamonga.

“The city thinks it’s a sunroom,” Stephens said. After the inspector stopped by, he removed the screws securing the roof, allowing him to roll it off to reveal the clear sky to his telescope.

Every night, he turns on the telescope and spends more than an hour taking data, which he later posts to an online community of amateur astronomers who monitor the star almost nonstop.

Major observatories simply cannot keep such constant watch. Hundreds of scientists compete for time to look at a wide range of astronomical targets every night. For them, keeping these telescopes glued to the Blaze Star is a waste of valuable observation time.

Estimates on when the nova will occur vary, but most astrophysicists agree it will happen before the end of the year, and likely by the end of August.

Once it blows, there are a few alert systems set up to notify amateurs and professionals. Some observatories have even programmed their telescopes to autonomously ditch their current observation plan and look at the star when the notification comes in, Stephens said.

Major observatories also face another complication. Many of their telescopes are designed to look at the faintest and dimmest targets, but the Blaze Star nova will be anything but faint. Pointing these telescopes at the nova would overwhelm sensors, resulting in a washed-out, overexposed picture.

That’s why Palomar Observatory, Caltech’s research station in north San Diego County, isn’t using its iconic 16-foot-wide Hale telescope under its massive white dome. Instead, it’s using a much smaller telescope, called Gattini-IR, located in a small brick building about a quarter mile down the road.

Once the nova happens, Gattini-IR will go from observing the Blaze Star every couple nights to every couple hours.

Steve Flanders enters the small building on the Palomar Observatory grounds where the Gattini-IR telescope is set up. The Gattini-IR telescope is monitoring the Blaze Star, which is expected to go nova.

(Hayne Palmour IV/For The Times)

Scientists say they still have a lot to learn about novas. For example, physicists are still unsure why some erupt every decade while others likely don’t for millennia.

Some researchers suspect that novas like the Blaze Star could be precursors to supernovas. These explosions — billions of times brighter than the sun — destroy the star, often leaving behind a black hole. Supernovas are also a useful tool for astronomers to measure distance.

Studying similar events has already led to discoveries, however.

Recently, scientists determined that novas tend to fling material into space at faster speeds than what would be predicted based on the intensity of the explosion.

“We want to understand the physics of novae, so having a nova that’s as close as T Coronae Borelias, which will hopefully be very well studied by all telescopes … we can get a very full picture,” said Caltech professor Kasliwal.

Some of that understanding will be due in part to amateur astronomers.

Thanks to the rapid development of telescopes, amateurs are working with technology that professionals didn’t have just 20 years ago, let alone 80, said Forrest Sims, an amateur astronomer from Apache Junction, Ariz., who is also observing the star every clear night.

And the amateurs can achieve better coverage than the big telescopes because “we typically have complete control over when and where we can point [our telescopes],” said Sims. “A professional may have to write a grant to get a half hour or two hours time on a big telescope.”

That allows them to collect a lot of data. And with hundreds in the community observing from around the world, they can achieve almost continuous coverage of the Blaze Star. Many, including Sims and Stephens, post their data to the American Assn. of Variable Star Observers website, allowing everyone to use the data.

Stephens remembers reading a journal article from a professional who managed to observe five asteroids over two years. “I thought, I could do that in a month,” Stephens said. He went on to publish a paper with 10 observations.

In his at-home observatory, Bob Stephens is using a Borg 101 telescope. “Resistance is futile!” Stephens said when introducing the telescope, a reference to the phrase uttered by “the Borg” in “Star Trek.”

(Robert Gauthier/Los Angeles Times)

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One professor was so shocked by the number Stephens was able to see that she reached out and agreed to fly to Puerto Rico for an asteroid conference just to meet him. They ended up working together — Stephens had the telescopes; she had the connections in the field.

Today, amateur astronomers’ work is getting so sophisticated, many in the field have a hard time calling them amateurs.

“We call ourselves ‘small telescope scientists,’ ” said Sims. “It sounds more fun, and in some respects, professionals — and not even grudgingly — will admit that the work we’re doing is often professional caliber.”

In early July, as Hurricane Beryl churned through the Caribbean, a top European weather agency predicted a range of final landfalls, warning that that Mexico was most likely. The alert was based on global observations by planes, buoys and spacecraft, which room-size supercomputers then turned into forecasts.

That same day, experts running artificial intelligence software on a much smaller computer predicted landfall in Texas. The forecast drew on nothing more than what the machine had previously learned about the planet’s atmosphere.

Four days later, on July 8, Hurricane Beryl slammed into Texas with deadly force, flooding roads, killing at least 36 people and knocking out power for millions of residents. In Houston, the violent winds sent trees slamming into homes, crushing at least two of the victims to death.

The Texas prediction offers a glimpse into the emerging world of A.I. weather forecasting, in which a growing number of smart machines are anticipating future global weather patterns with new speed and accuracy. In this case, the experimental program was GraphCast, created in London by DeepMind, a Google company. It does in minutes and seconds what once took hours.

“This is a really exciting step,” said Matthew Chantry, an A.I. specialist at the European Center for Medium-Range Weather Forecasts, the agency that got upstaged on its Beryl forecast. On average, he added, GraphCast and its smart cousins can outperform his agency in predicting hurricane paths.

In general, superfast A.I. can shine at spotting dangers to come, said Christopher S. Bretherton, an emeritus professor of atmospheric sciences at the University of Washington. For treacherous heats, winds and downpours, he said, the usual warnings will be “more up-to-date than right now,” saving untold lives.

Rapid A.I. weather forecasts will also aid scientific discovery, said Amy McGovern, a professor of meteorology and computer science at the University of Oklahoma who directs an A.I. weather institute. She said weather sleuths now use A.I. to create thousands of subtle forecast variations that let them find unexpected factors that can drive such extreme events as tornadoes.

“It’s letting us look for fundamental processes,” Dr. McGovern said. “It’s a valuable tool to discover new things.”

Importantly, the A.I. models can run on desktop computers, making the technology much easier to adopt than the room-size supercomputers that now rule the world of global forecasting.

“It’s a turning point,” said Maria Molina, a research meteorologist at the University of Maryland who studies A.I. programs for extreme-event prediction. “You don’t need a supercomputer to generate a forecast. You can do it on your laptop, which makes the science more accessible.”

People depend on accurate weather forecasts to make decisions about such things as how to dress, where to travel and whether to flee a violent storm.

Even so, reliable weather forecasts turn out to be extraordinarily hard to achieve. The trouble is complexity. Astronomers can predict the paths of the solar system’s planets for centuries to come because a single factor dominates their movements — the sun and its immense gravitational pull.

In contrast, the weather patterns on Earth arise from a riot of factors. The tilts, the spins, the wobbles and the day-night cycles of the planet turn the atmosphere into turbulent whorls of winds, rains, clouds, temperatures and air pressures. Worse, the atmosphere is inherently chaotic. On its own, with no external stimulus, a particular zone can go quickly from stable to capricious.

As a result, weather forecasts can fail after a few days, and sometimes after a few hours. The errors grow in step with the length of the prediction — which today can extend for 10 days, up from three days a few decades ago. The slow improvements stem from upgrades to the global observations as well as the supercomputers that make the predictions.

Not that supercomputing work has grown easy. The preparations take skill and toil. Modelers build a virtual planet crisscrossed by millions of data voids and fill the empty spaces with current weather observations.

Dr. Bretherton of the University of Washington called these inputs crucial and somewhat improvisational. “You have to blend data from many sources into a guess at what the atmosphere is doing right now,” he said.

The knotty equations of fluid mechanics then turn the blended observations into predictions. Despite the enormous power of supercomputers, the number crunching can take an hour or more. And of course, as the weather changes, the forecasts must be updated.

The A.I. approach is radically different. Instead of relying on current readings and millions of calculations, an A.I. agent draws on what it has learned about the cause-and-effect relationships that govern the planet’s weather.

In general, the advance derives from the ongoing revolution in machine learning — the branch of A.I. that mimics how humans learn. The method works with great success because A.I. excels at pattern recognition. It can rapidly sort through mountains of information and spot intricacies that humans cannot discern. Doing so has led to breakthroughs in speech recognition, drug discovery, computer vision and cancer detection.

In weather forecasting, A.I. learns about atmospheric forces by scanning repositories of real-world observations. It then identifies the subtle patterns and uses that knowledge to predict the weather, doing so with remarkable speed and accuracy.

Recently, the DeepMind team that built GraphCast won Britain’s top engineering prize, presented by the Royal Academy of Engineering. Sir Richard Friend, a physicist at Cambridge University who led the judging panel, praised the team for what he called “a revolutionary advance.”

In an interview, Rémi Lam, GraphCast’s lead scientist, said his team had trained the A.I. program on four decades of global weather observations compiled by the European forecasting center. “It learns directly from historical data,” he said. In seconds, he added, GraphCast can produce a 10-day forecast that would take a supercomputer more than an hour.

Dr. Lam said GraphCast ran best and fastest on computers designed for A.I., but could also work on desktops and even laptops, though more slowly.

In a series of tests, Dr. Lam reported, GraphCast outperformed the best forecasting model of the European Center for Medium-Range Weather Forecasts more than 90 percent of the time. “If you know where a cyclone is going, that’s quite important,” he added. “It’s important for saving lives.”

Replying to a question, Dr. Lam said he and his team were computer scientists, not cyclone experts, and had not evaluated how GraphCast’s predictions for Hurricane Beryl compared to other forecasts in precision.

But DeepMind, he added, did conduct a study of Hurricane Lee, an Atlantic storm that in September was seen as possibly threatening New England or, farther east, Canada. Dr. Lam said the study found that GraphCast locked in on landfall in Nova Scotia three days before the supercomputers reached the same conclusion.

Impressed by such accomplishments, the European center recently embraced GraphCast as well as A.I. forecasting programs made by Nvidia, Huawei and Fudan University in China. On its website, it now displays global maps of its A.I. testing, including the range of path forecasts that the smart machines made for Hurricane Beryl on July 4.

The track predicted by DeepMind’s GraphCast, labeled DMGC on the July 4 map, shows Beryl making landfall in the region of Corpus Christi, Texas, not far from where the hurricane actually hit.

Dr. Chantry of the European center said the institution saw the experimental technology as becoming a regular part of global weather forecasting, including for cyclones. A new team, he added, is now building on “the great work” of the experimentalists to create an operational A.I. system for the agency.

Its adoption, Dr. Chantry said, could happen soon. He added, however, that the A.I. technology as a regular tool might coexist with the center’s legacy forecasting system.

Dr. Bretherton, now a team leader at the Allen Institute for A.I. (established by Paul G. Allen, one of the founders of Microsoft), said the European center was considered the world’s top weather agency because comparative tests have regularly shown its forecasts to exceed all others in accuracy. As a result, he added, its interest in A.I. has the world of meteorologists “looking at this and saying, ‘Hey, we’ve got to match this.’”

Weather experts say the A.I. systems are likely to complement the supercomputer approach because each method has its own particular strengths.

“All models are wrong to some extent,” Dr. Molina of the University of Maryland said. The A.I. machines, she added, “might get the hurricane track right but what about rain, maximum winds and storm surge? There’re so many diverse impacts” that need to be forecast reliably and assessed carefully.

Even so, Dr. Molina noted that A.I. scientists were rushing to post papers that demonstrate new forecasting skills. “The revolution is continuing,” she said. “It’s wild.”

Jamie Rhome, deputy director of the National Hurricane Center in Miami, agreed on the need for multiple tools. He called A.I. “evolutionary rather than revolutionary” and predicted that humans and supercomputers would continue to play major roles.

“Having a human at the table to apply situational awareness is one of the reasons we have such good accuracy,” he said.

Mr. Rhome added that the hurricane center had used aspects of artificial intelligence in its forecasts for more than a decade, and that the agency would evaluate and possibly draw on the brainy new programs.

“With A.I. coming on so quickly, many people see the human role as diminishing,” Mr. Rhome added. “But our forecasters are making big contributions. There’s still very much a strong human role.”

Astronomers around the world are preparing for one of the most anticipated cosmic firework shows of the year — but you don’t need a fancy telescope to join in on the festivities.

The hydrogen that a small, dense star has spent the past 80 years siphoning off of its nearby neighbor is about to explode like a thermonuclear bomb a hundred thousand times the brightness of the sun.

From Earth, it’ll be about as bright as the North Star, making it visible to the naked eye — even with Los Angeles’ light pollution.

Countless amateur astronomers and observatories around the world — and in space — are planning to watch the explosion, called a nova. Here’s everything you need to know to join in on the fun:

To get the word when the star goes nova, you can follow NASA Universe on X, formerly known as Twitter. For hardcore enthusiasts that want to know as soon as the astronomers do, you can sign up for novae instant email notices from the Astronomer’s Telegram.

Scientists expect it to happen any time between now and the end of the year, likely before the end of August. (The nova technically occurred some 3,000 years ago, but the light is just now reaching Earth.)

Once the star, nicknamed the “Blaze star,” goes nova, you have just two or three days in Los Angeles — or about a week out in the desert — to hope for clear weather and try to spot it. The star will be at its brightest the very first night after it explodes.

To spot the star the old-school way, first locate the Big Dipper. Then, follow the direction its handle points (before it curves down) until you find a group of stars in a tight “U” shape. This is Corona Borealis, the constellation the Blaze star is located in. The nova will be just outside the “U” on the bottom left.

Or, you can use websites and apps like Stellarium to spot it in the sky. Just input your location, and select the Blaze star. (It’ll likely be listed under its formal name T Coronae Borealis, or T CrB for short).

If you want to make a night out of it, Griffith Observatory hopes to give the public a view — they just need it to get dark early enough that the stars come out before they close at 10 p.m.

If the nova holds out for a while longer, they’ll bring out their lawn telescopes in addition to the 12-inch Zeiss telescope on the roof of the observatory that’s open to the public. Both options are free, and lines close for the telescopes at 9:30 p.m. Griffith staff will be at the ready to help visitors spot it.

One last thing you can do to prepare: practice now. Look at maps showing where the Blaze star is in relation to the Corona Borealis constellation, and try spotting the constellation in the night sky before the big day. It’ll not only help you spot the star faster, but give you an appreciation for how the nova changes the night sky.