Math and statistics help explain the FBI’s ‘missing scientists’ cases
Statistical principles show you don’t need a nefarious plot to explain clusters of missing scientists and lab workers
J. Edgar Hoover FBI wall emblem on the side of the FBI Building.
In April a writer friend e-mailed me a story from the U.K.-based tabloid Daily Mail—“Mystery surrounds death of NINTH scientist tied to US secrets as disturbing pattern grows”—with the comment, “and they’re just starting to notice?” But I didn’t see the pattern, even after reading it twice.
Now the FBI has launched an investigation, and the list has grown to 11 or maybe 12 people seemingly linked through their “mysterious” deaths or disappearances. Yet some simple statistical principles suggest any connection is likely an illusion.
One idea that comes in handy in cases like this is statistician David Hand’s “improbability principle.” Random numbers, words or distributions of events, he says, can appear to clump and cluster in patterns if you make the numbers big enough. And the missing scientist situation, he says, “is a case for the improbability principle.”
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The principle is rooted in what Hand and others have called the law of truly large numbers. In a series of trillions of random numbers, for example, a string of seven 7’s would be almost certain to show up. In a world of more than eight billion busy people, a few will bump into a neighbor traveling in a distant country, for example. The world has so many moving parts that extraordinary and even unheard-of things happen all the time.
It’s not even particularly improbable that of the thousands of Americans who disappear or are murdered every year, a few would include prominent scientists or people who’ve worked at large laboratories.
Hand says that a couple of errors that can make randomly occurring patterns look deceptively connected. One is the “near-enough” effect. This often shows up in surprising stories about repeat lottery winners when the definition of “win” is expanded to include people who won second or third prizes of relatively small value. Suddenly a double win doesn’t seem astronomically improbable at all.
In the missing scientist investigation, it helps to consider how the allegedly disturbing pattern was first identified. CNN ran a helpful story tracing the index case to the late Massachusetts Institute of Technology physicist Nuno Loureiro. He died on December 16 after being shot by the same person who had opened fire on a group of students at Brown University days earlier, killing two people. The shooter was soon identified as a former physics classmate thought to have been jealous of Loureiro’s success.
Elsewhere, however, people speculated that Loureiro was targeted because of his work in nuclear fusion. Fusion—uniting small atomic nuclei into larger ones—promises more abundant, cleaner energy once scientists perfect it. Some fusion research is connected to weapons, but Loureiro was part of a large network of scientists working on big experimental reactors and sharing ideas at meetings and in papers. If a breakthrough had motivated his murder, his colleagues should have known about it.
Were other fusion scientists being murdered? A writer named Jessica Reed Kraus noted that another scientist, Carl Grillmair, was shot at his home north of Los Angeles in February. Grillmair, however, was an astrophysicist who worked on observations of exoplanets—planets orbiting other stars in the galaxy.
Kraus wrote that both murdered scientists were “versed in planetary catastrophes.” What fusion and exoplanets have to do with planetary catastrophes is unclear, but for some, it’s near enough.
The victim list grew to a “NINTH” person, as the Daily Mail would have it, through another improbability principle error called the “look-elsewhere” effect, which was named by particle physicists to explain a hazard of attempting to interpret the debris they capture by smashing particles together in collider experiments. Particle physicists don’t observe new particles directly but look for a cluster or “peak” of debris with some predicted properties. If they don’t see what they expected, they are sometimes tempted to look elsewhere in the data and say something like, “Hey, what about this smaller peak over here—maybe that’s a new particle that will revolutionize physics!”
But as some have learned the hard way, that tendency of random things to appear to form patterns means that the other peak might be just noise. In the missing scientist case, would-be sleuths looked elsewhere and found a cluster of four people in New Mexico who went missing within the past year and have not been found. One was a retired Air Force general, two others were not scientists but had worked at Los Alamos National Laboratory, and another had a security clearance but worked elsewhere.
Another alleged cluster turned up among people with ties to the Jet Propulsion Laboratory in California, but only one had disappeared—a materials engineer who is thought to have become lost on a hike in June 2025. The other two had worked as scientists at the lab and died at age 59 in 2023 and age 61 in 2024, respectively, and their families didn’t disclose the causes. The near-enough effect comes back into play in the weaving together of these clusters found elsewhere and adding a few other sporadic deaths.
If about 200,000 adults go missing every year in the U.S., Hand says, and about 70,000 people work in areas associated with nuclear energy, you’d expect roughly 50 people involved in that work to annually go missing. But given the way this mystery has sprawled across professions and forms of tragedy, it’s impossible to find statistics on the expected number of scientists and science-related people who were shot or disappeared or been lost hiking or died in a way the family chose not to disclose within a given time period in the U.S.
“I don’t really think there’s a mystery or, indeed, anything suspicious that needs to be explained,” he says.
Still, these pitfalls are easy to find alarming. Celebrity physicist Michio Kaku recently spoke to Fox News about the case: “This is unheard of,” he said. “This has never happened before.” He’s not wrong, but according to Hand’s improbability principle, unheard-of combinations of things that never happened before happen every day—even to scientists.