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Shep Doeleman

Things Shep Says on Podcasts

Where to Find Them

Shep Doeleman has been a guest on StarTalk Radio , Into the Impossible With Brian Keating , Templeton Ideas Podcast and The Joy of Why .

Recently: “How Do You Take a Picture of a Black Hole?” on The Joy of Why (October 2026); “Shep Doeleman (Black Holes)” on Templeton Ideas Podcast (May 2024); “Shep Doeleman: How the Event Horizon Telescope caught the Milky Way’s MONSTER Black Hole! (#229)” on Into the Impossible With Brian Keating (May 2022); “Hunting for Black Holes, with Janna Levin - StarTalk All-Stars” on StarTalk Radio (November 2016).

What They Said

“We split our teams up into four groups. Each group had the data, but they could not talk to each other because we wanted to make sure that we all weren't in the same room thinking, like, I see a ring. Do you see a ring? I see a ring. And it's not a ring, right? … The four teams put up their images, and they were all rings. That was a moment where there was a lot of crying and screaming. And then we spent the next six months trying to make those rings go away.” — Shep Doeleman, The Joy of Why

Doeleman on how the Event Horizon Telescope team guarded against groupthink before releasing the first image of a black hole. Afterwards, they trained their algorithms on everything except rings, and the data kept coming back as a ring.

The Joy of Why · 2026-10-29 Permalink → Listen →
The Joy of Why Around 40:39 into the episode
Shep Doeleman

…a tie. And one of my postdocs is showing me the data for the first time. And there's a picture going, what am I looking at? And I came back to my office that night and I went through the calculations based on where these bounces were. And I realized it's exactly the size it's supposed to be.

Janna Levin

Wow.

Shep Doeleman

Right. So that was the first indication that we had something. And then we started imaging. So we had been perfecting these imaging algorithms on synthetic data. We'd fed these algorithms made-up data. So we would take a black hole image that we might be looking at, we'd corrupt it with noise, and we'd send it through these algorithms. We'd refine these to the point we were pretty confident in these algorithms. But before we set these loose on the data, we also realized that human error or human groupthink could be a really big problem. So we split our teams up into four groups. Each group had the data, but they could not talk to each other because we wanted to make sure that we all weren't in the same room thinking, like, I see a ring. Do You Take a ring? I see a ring. And it's not a ring, right? So we had four different geographically separated groups, and they all used different algorithms. And then we all came together to the building where I am sitting right now, the Black Hole? Initiative at Harvard, in July of 2018. And we were in the basement of this building, and the four teams put up their images, and they were all rings. That was a moment where there was a lot of crying and screaming. And then we all, and then we spent the next six…

Janna Levin

Let's talk about the ring image again. You've alluded to why it looks this way. There's material splattered around the black hole that's orbiting outside of the event horizon, to be clear. But close, really close. You mentioned some observations of things in orbit around the black hole were…

Shep Doeleman

Yeah, the way this works is that when you're so close to the black hole, the paths of light, which normally would travel in a straight line, is forced to travel along the curved space-time. And so it's really tracing the metric of space-time. It's tracing the gravitational well that it finds itself…

Janna Levin

Yeah, there's nothing, there are no ingredients in there that aren't fundamental facts of nature except the mass of the black hole. And that's, I think people don't appreciate how black holes are fundamental in that way. All stars are kind of different, different colors, but black holes are…

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