#Katie Bouman

[higherentity]

[queenofthedarkhorizons]

I love Black Holes!

[importantwomensbirthdays]

Katie Bouman

Katie Bouman was born in 1989 in West Lafayette, Indiana. Bouman worked on the Event Horizon Telescope project, which constructed the first ever photograph of a black hole. In 2019, she joined the faculty of the California Institute of Technology as an assistant professor of computing and mathematical sciences. Her research at Caltech focuses on computational imaging.

Image: National Science Foundation

[bearterritory]

REDWOOD CITY – The No. 4 California women's rowing team dominated the duel against No. 7 Washington sweeping all five races Saturday morning at the Redwood Shores in Redwood City. With the Bears' win in the V8+ race, the Simpson Cup, which goes to the winner of the varsity eight race, comes back to Cal for the first time since 2019. Cal's 2V8+, 3V8+, 4V8+ and V4+ also notched wins in the duel. This marks the second time this season the V8+, 3V8+ and V4+ defeated Washington as the two faced off at the San Diego Crew Classic earlier this month.   "Washington brought out the best in us today," Cal head coach Al Acosta said. "We've done quite a bit of racing and travel over the last three weeks, so I was a little concerned about how much juice we'd have for this one, but the team did an amazing job of going stroke for stroke with the Huskies early and then extending the margin later in the race. Four years ago, when our seniors were freshmen, we got swept by UW, so it's very gratifying to see the seniors get this one. Now that we're halfway through the season I think we're in a good spot, but we have some big races coming up and it's not going to get any easier so we will need to continue to get faster."   In the V8+ race, both boats were even through the first 20 strokes before Cal took a two-seat lead in the first 500 meters. As the boats approached the 1,000-meter mark, the Bears were ahead by a half boat. Cal kept the pressure on over the third 500 meters and extended its lead to a seat of open water. The Bears maintained that margin to take the victory in a time of 6:08.8 and bring home the Simpson Cup.

In the matchup of the 2V8+, it was fairly even off the start with Cal taking just a one-seat lead over the first 20 strokes. As the boats hit the halfway mark, the Bears kept their lead and went ahead by two seats. Cal kept the pressure on over the third 500 meters and went ahead by a half boat before extending its lead to almost a full boat over the closing 500 meters to take the win in 6:20.2.   In the 3V8+ race, it was tight over the first 500 meters until Cal took a four-seat lead at the 1,000-meter mark. The Bears were able to extend their lead to open water over the third 500 meters and held that lead to finish first in a time of 6:33.2.   In the 4V8+ duel, the first 500 meters were close before the Bears took a three-seat lead by the halfway mark. Cal was able to extend its lead over the third 500 meters and went ahead by a bit of open water to take the win in a time of 6:46.9.   In the V4+ race, Cal got off to a good start and went ahead by two seats within the first 20 strokes. The Huskies were able to walk back a seat and pulled nearly even over the first 500 meters. By the time Cal hit the halfway mark, it was ahead by almost a boat length. The Bears continued to press and built an open-water lead over the second half of the race to get the win in a time of 6:46.9.    The Bears will have next weekend off before competing in the Big Row against No. 1 Stanford on May 4 at the Redwood Shores.   Results   V8+ 1. Cal – 6:08.8 2. Washington – 6:12.6   2V8+ 1. Cal – 6:20.2 2. Washington – 6:23.2

3V8+ 1. Cal – 6:33.2 2. Washington – 6:40.8   4V8+ 1. Cal – 6:46.9 2. Washington – 6:50.6   V4+ 1. Cal – 6:46.9 2. Washington – 6:50.6   Lineups V8+ Coxswain - Piper Melnick Stroke: Fien van Westreenen 7: Lotta van Westreenen 6: Minou Bouman 5: Antonia Galland 4: Julia Hunt-Davis 3: Ella Wheeler 2: Star Miller Bow: Amy Furlonger

2V8+ Coxswain: Lily Wieland Stroke: Della Luke 7: Sophie Ward 6: Ella Berger 5: Tabo Stekelenburg 4: Shannon Kearney 3: Izzy Campbell 2: Sammie Henriksen Bow: Katie McDermott   V4+ Coxswain: Charley Griffiths 4: Megan Culbert 3: Lola Crampin 2: Julia Irmler 1: Miya Meskis   3V8+ Coxswain: Emily Nowak Stroke: Lily Pember 7: Zoe McKernan 6: Francesca Hammerer 5: Lily Rausser 4: Nicole Weber 3: Gwyneth Fagg 2: Sophie Fussell Bow: Ella Lewerenz

4V8+ Coxswain: Julia Fullington Stroke: Claire Banks 7: Eve Barrancotto 6: Tyra Hjemdal 5: Molly Gold 4: Annie Brown 3: Sydney Koutrouba 2: Sidney Curven Bow: Kate Nixon   STAY POSTED For further coverage of Cal women's rowing, follow the Bears on Instagram (@calwrowing) and Facebook (Cal Crew).

[lizzybeth1986]

Noot Noot

Book: Perfect Match

Pairing: Sloane Washington & Hazel Park (f!black MC) (platonic), Sloane Washington & Iris Young (f!Asian Hayden) (platonic).

Rating: G

Summary: While recovering from a nasty flu, Sloane revisits a childhood favourite TV show with her friends.

Word count: 1,183 words

A/N: I kinda HC Sloane as growing up on Pingu, a British-Swedish stop motion animated classic. It was a fave of mine as a kid, and I later found out that many autistic kids - esp those who use more nonverbal communication - are fond of it.

Tagging @choicesficwriterscreations for Fic of the Week and @choices-february2023 for their February prompt as well as @sloanewashingtonappreciationweek

Using @choices-february2023 prompt for Day 4: Harmony | Homemade Soup | So What (P!nk)

"You two should go home now," Sloane grumbles, her voice almost muffled underneath her Milky Way Galaxy blanket. "I'm fine, really."

And she isn't lying. She hasn't suffered a fever in four days now, and though her throat still feels sore, the sandpaper sensation of using her voice doesn't burn as ferociously as it did a week ago.

Residual throatache and general tiredness. That's all that's left of this awful flu.

Iris ignores her. "Hazel, honey, put on some Pingu," she calls out, frowning over a pot of steaming chicken soup. "'Pingu the Chef' is her favourite."

Hazel's head is buried inside her cupboard of old keepsakes from her mom's home. "Coming!" She yells back to Iris, holding a well-worn penguin in her hand.

She tosses it playfully in the direction of Sloane's bed. "What did you finally name this one?"

Sloane has only enough energy to offer a weak smile. "Katie Bouman." She doesn't remember what she'd named it when Mom gave it to her. "To keep you company at your first ever Space Camp," she'd said, brushing a soft kiss over her forehead. They'd both been so nervous then. Little Trudy had never stayed overnight away from home, away from Mom.

It was one of the few things Sloane took back with her when she'd visited Mom a few years ago, just before Khaan and the group set in motion their plans to defeat Eros. Sloane shivers as she remembers her sense of dread that day, wondering if this would be the last time she'd ever visit this room. How she swallowed the lump in her throat when she saw the worry in Mom's eyes, the questions Sloane couldn't bring herself to answer.

Hazel frowns at Sloane's involuntary shudder, enfolding her in her thick blanket and tucking Katie into her weak arms.

The two settle back on the bed, backs against the bedstand, as the titular little penguin throws corn kernels into a hot pan. His baby sister watches, jumping up and down when the yellow seeds puff up and turn white.

"What?" Hazel mouths when she sees Sloane silently giggling. She covers her mouth, already anticipating one of her favourite parts in the episode; Pingu's sister fooling her brother into looking away before stealing his share of kernels.

Pingu stares for a second at the empty pan, then glares after his baby sister, his beak already stretching to form the shape of a trumpet horn.

"Noot noot!"

Hazel guffaws, slapping her thigh. "He looks so cute when he does that."

Sloane's laughter is significantly fainter, yet carries the same note of joy and amusement. "Mom says when I first started watching Pingu, I wouldn't stop saying 'noot noot' for a whole month."

Iris comes out of the kitchen as she says this, bowl of soup in hand. Sloane breathes in the scent of roasted garlic emanating from it with a sigh of pleasure. On Sloane's laptop screen, Pingu takes out an obscenely large amount of corn kernels and throws them in a far larger pot.

"It's a very versatile word," Hazel says, grinning, "You could say it when you're excessively happy... excessively distressed..."

"... excessively pissed off at annoying younger siblings who steal your food from right under your nose..." Iris adds, winking in Sloane's direction. Hazel is surprisingly quiet in the middle of all the teasing.

Sloane has enough energy to half-heartedly elbow Iris in the ribs. "You damn well deserved a few noot noots for nicking my Ben&Jerry tub on your first day here."

Iris looks all injured innocence. "I didn't do that, Dipper did."

"Very nice, very 'the dog ate my homework', Iris," Hazel mocks gently, rolling her eyes at her girlfriend before looking at Sloane. "Did you always do that?"

"Do what?" Sloane takes slow, lingering sips of her soup, savoring its warmth. Pingu and his sister are now panicking over a mile-long trail of popcorn strewn over their kitchen floor.

"Repeat phrases no matter the context? In some of the childhood stories you've told me so far, you'd done that with other words."

Echolalia, the first therapist they'd met had told Mom. She likes repeating the words, but is yet to grasp their meaning. That last thought is more imagination than memory; all she can truly recall from that visit were the tiny farm animals she had sorted in a row on a playmat, by order of height.

"Yeah," Sloane whispers, her smile a tiny bit wider as she watches Pingu take boxes of freshly made popcorn on his sled, going from house to house, using his overzealous mistake to feed an entire polar neighborhood. "I always thought of words in terms of sounds first. The more I liked the sound of something, the more I'd use it whether I knew the meaning or not. You had to show me a visual, over and over again until I connected the two, if you wanted me to understand what a word meant. It took Mom a little time to realize that."

Sloane smiles at the sight the three of them must make right now, watching a childhood favourite on a bed surrounded by all the interests and all the achievements of her adulthood. The first time she'd watching this show, Mom had been curious. She'd never shown much interest in watching anything for more than a couple minutes, making going to the cinema almost an impossibility.

But this show, with its adorable clay penguin figures who spoke a language she didn't need to understand and who forced her to read their body language instead...this show was different. This show grabbed her attention and wouldn't let go. This show stayed with her long after she stopped binge-watching it, growing into a lifelong interest in real-life penguins.

She looks up at her best friends, both so different in their body language yet so familiar. Hazel's limbs are sprawled over her bed in a sort of casual grace, as if she is owning the space. Iris rests her chin on her right knee, her head tilted as she often does when she's thinking deeply about the media she's watching. Sloane feels a frisson of familiarity as she watches her - in so many ways they're so similar; sometimes Sloane wonders how much of herself she's incorporated into Iris. There are moments when looking at her is like looking at a mirror - the same responses on a drastically different face.

Even now, if Sloane tries hard enough, she knows that some of the ways she reads people's reactions can be vaguely traced to that stressful - yet indescribably exciting - exercise of trying to understand what Pingu was doing, what Pingu was saying, what Pingu was feeling.

"Mm," Iris says, grinning as Sloane finishes off her soup. She's been showing better appetite today than she has the whole week. "looks like they managed to clear out all that excess popcorn, eh?"

Sloane smiles back. Pingu drives his sled through the snow from house to house, his beak morphing into the shape of a trumpet horn as he announces his arrival. In a sound that is no longer annoyance, or anger - but excitement.

Noot noot!

--

* Katie Bouman is a post-doctoral fellow at Harvard who helped develop the code to find the black hole needle in the haystack of data collected from the effort.

** You can watch the episode of Pingu mentioned here.

*** Echolalia is one of the things that some autistic kids grow up with. Some are nonverbal in their communication, and some may not always engage in meaningful communication although they do attempt speech. Echolalia involves a tendency to repeat words or phrases while not understanding the meaning, eg. A child repeating someone's question instead of answering it. I HC Sloane as having speech delays as a child, that initially didn't go noticed because she was echoing words she heard.

[sjerzgirl]

There's a lot of news going on about the "black hole girl" right now, and how she's being given too much credit for her role in the historic first image of a black hole. Because this is too important, I want to set the record straight.Remember the kmi

Once Katie Bouman became the "face" of the black hole photo, and articles began to call her "the woman behind the black hole photo", an assortment of people that I'm strongly inclined to call incels but won't decided to figure out just how much of a role she had in it. Why? You'd have to ask them. Something about her attractiveness, youthfulness, and femaleness disturbed them to the point where they had to go digging.

And after digging, they found Andrew Chael, who wrote an algorithm, and put his algorithm online. Andrew Chael worked on the black hole photo as well. And because people kept saying that Katie Bouman wrote "the algorithm", these people decided that "the algorithm" in question must be Chael's.

So they looked at Chael's GitHub repository and checked the history. The history showed that Andrew Chael's commits totaled more than 850,000 lines, while Katie Bouman contributed only 2,400.

"Oh my god!" they all said. "He did almost all of the work on the algorithm and yet she's the one getting all of the credit!"

They dug a little deeper - but not much - and discovered that the algorithm that "ultimately" generated the world-famous photo was created a different man, named Mareki Honma.

"She's taken the credit from two men!" they gasped. "Feminism and the PC media is destroying everything!"

There were, of course, those who tried to be kind. "She's always said that this was a team effort," they said. "We don't blame her, we blame the media. She didn't ask to become the poster girl of a team project she barely contributed to."

Meanwhile, Andrew Chael - a gay man - tweeted in defense of her. He thanked people for congratulating him on the work he'd spent years on but clarified that if they were doing so as a part of a sexist attack on Katie Bouman, they should go away and reconsider their lives. He said that his work couldn't have happened without Katie.

And it turns out that he was the one who took the viral photo of Bouman, specifically because he didn't want her contributions to be lost to history

So I decided to find out for myself what Katie Bouman's actual contributions were. As a programmer, I'm well aware that the number of GitHub commits means nothing without context. And Chael himself clarified that the lines being counted in the commits were from automatic commits of large data files. The actual software was made up of 68,000 lines, and though he didn't count how many he did personally (having said he doesn't actually care how much of it he personally authored), someone else assessed that he wrote about 24,000 of those.

Whether 68,000 or 24,000-- it's more than 2,400 right? Why call it "her" algorithm, then?

Because there's more than one algorithm being referenced here. These people just don't realize it.

I'll work my way backward because it's easier to explain that way.

The photo that everyone is looking at, the world famous black hole photo? It's actually a composite photo. It was generated by an algorithm credited to Mareki Honma. Honma's algorithm, based on MRI technology, is used to "stitch together" photos and fill in the missing pixels by analyzing the surrounding pixels.

But where did the photos come from that are composited into this photo?

The photos making up the composite were generated by 4 separate teams, led by Katie Bouman and Andrew Chael, Kazu Akiyama and Sara Issaoun, Shoko Koyama, Jose L. Gomez, and Michael Johnson. Each team was given a copy of the black hole data and isolated from each other. Between the four of them, they used two techniques - an older, traditional one called CLEAN, and a newer one called RML - to generate an image.

The purpose of this division and isolation of teams was deliberately done to test the accuracy of the black hole data they were all using. If four isolated teams using different algorithms all got similar results, that would indicate that the data itself was accurate.

And lo, that's exactly what happened. The data wasn't just good, it's the most accurate of its kind. 5 petabytes (millions of billions of bytes) worth of accurate black hole data.

But where did the data come from?

Eight radio telescopes around the world trained their attention on the night sky in the direction of this black hole. The black hole is some ungodly distance away, a relative speck amidst billions of celestial bodies. And what the telescopes caught was not only the data of the black hole but the data of everything else as well.

Data that would need to be sorted.

Clearly, it's not the sort of thing you can sort by hand. To separate the wheat (one specific black hole's data) from the chaff (literally everything else around and between here and there) required an algorithm that could identify and single it out, calculations that were crunched across 800 CPUs on a 40Gbit/s network. And given that the resulting black hole-specific data was 5 petabytes (hundreds of pounds worth of hard drives!) you can imagine that the original data set was many times larger.

The algorithm that accomplished this feat was called CHIRP, short for "Continuous High-resolution Image Reconstruction using Patch priors".

CHIRP was created by Katie Bouman.

At the age of 23, she knew nothing about black holes. Her field is computer science and artificial intelligence, topics she'd been involved in since high school. She had a theory about the shadows of black holes, and her algorithm was designed to find those shadows. Katie Bouman used a variety of what MIT called "clever algebraic solutions" to overcome the obstacles involved in creating the CHIRP algorithm. And though she had a team working to help her, her name comes first on the peer-reviewed documentation.

It's called the CHIRP algorithm because that's what she named it. It's the only reason these images could be created, and it's responsible for creating some of the images that were incorporated into the final image. It's the algorithm that made the effort of collecting all that data worth it. Any data analyst can tell you that you can't analyze or visualize data until it's been prepared first. Cleaned up. Narrowed down to the important information.

That's what Katie Bouman did, and after working as a data analyst for two years with a focus on this exact thing - data transformation - I can tell you it's not easy. It's not easy on the small data sets I worked with, where I could wind up spending a week looking for the patterns in a 68K Excel spreadsheet containing only one month's worth of programming for a single TV station!

Katie Bouman's 2,400 line contribution to Andrew Chael's work is on top of all of her other work. She spent five years developing and refining the CHIRP algorithm before leading four teams in testing the data created. The data collection phase of this took 10 days in April 2017, when the eight telescopes simultaneously trained their gazes towards the black hole.

This photo was ultimately created as a way to test Katie Bouman's algorithm for accuracy. MIT says that it's frequently more accurate than similar predecessors. And it is the algorithm that gave us our first direct image of a black hole.

Around the internet, there are people who have the misperception that Katie Bouman is just the pretty face, a minor contributor to a project where men like Andrew Chael and Mareki Honma deserve the credit. There are people pushing memes and narratives that she's only being given such acclaim because of feminism. And because Katie Bouman refuses to say that this was anything other than a team effort, even the most flattering comments about her still place her contributions to the photo at less-than-equal contribution to others.

But I'm writing to set the story straight:

When it is written that Katie Bouman is the woman "behind the black hole photo", it is objectively true. She wasn't the only woman, but her work was crucial to making all of this happen.

When Andrew Chael says that his software could not have worked without her, he isn't just being a stand-up guy, he's being literal. And there are those who could just as easily say the same about his contribution, or the contributions of many others.

And while it's true that every one of the 200+ people involved played an important role, Katie Bouman deserves every ounce of superstardom she receives.

If there must be a face to this project - and there usually is - then why shouldn't it be her, her fingers twined across her lips, her gleeful eyes luminous and wide with awe and joy?

Edited:

Thinking on it a little further, I felt I should clarify that I'm not actually trying to downplay Andrew Chael. His imaging algorithm is actually the result of years of effort, a labor of love. Each image that could be composited into the final photo brought with it a unique take on the data, without which the final photo wouldn't have been complete.

So let's take a moment to celebrate the fact that two of the most integral contributors to the first direct photo of a black hole

were a woman

and a gay man.

===============================================

2nd Update (LONG!)

I went to bed at 19 shares on a post I wrote to vent to my FB friends, and now it's over 2K. I guess it's gone viral. That means I have some work to do.

I'm going to provide a list of the various articles I read to piece this together. When I wrote this, I wasn't trying to write an essay so I didn't put sources in and I didn't ensure that every detail is 100% accurate. So I'm doing that now.

Any edits I make are mentioned below (apart from spelling/grammar fixes). The resources that led me to write this are listed below. And because I value accuracy, I welcome people to point out mistakes of any kind. I'll make corrections and credit them here.

Edit: I incorrectly wrote that Bouman worked on the algorithm for 6 years and spent 2 years refining it. This was an accidental mush of facts: She's been working on this project for a total of 6 years (ages 23 to 29). She spent 3 years building CHIRP and 2 years refining it. I've corrected that and included that she led the four teams, as two separate articles mention it.

Edit: One of the leads for the 4 team project was a man named Jose L Gomez. I added that to the above, after being sent a twitter thread from Xu S. Han. Thank you! Twitter thread here:

https://twitter.com/saraissaoun/status/1116304522660519936?s=21

Edit: Thanks to Zoë Barraclough and someone who would prefer not to be named, for messaging me with another couple of edits. As confirmed on Kazu Akiyama's twitter, there were more than four leaders for the four imaging teams. As I find out the names of these co-leaders, I'll incorporate them into the post.

NEWEST LINK:

A very astute commenter left a note that included this link:

Caltech colloquium, Friday, April, 12th — “Imaging a Black Hole [Shadow] with the Event Horizon Telescope”: https://m.youtube.com/watch?v=UGL_OL3OrCE

This hour-long presentation is of Katie Bouman describing in more detail. If you have some time, watch it! It does get technical but she keeps it engaging.

SOURCES:

http://news.mit.edu/2016/method-image-black-holes-0606

This is a 2016 MIT article announcing CHIRP. It gives a pretty excellent idea about the magnitude of Bouman's contribution.

https://www.extremetech.com/extreme/229675-mit-researcher-develops-new-algorithm-for-imaging-black-holes

This goes into detail about Katie Bouman's algorithm. It describes how her algorithm differs from normal/traditional interferometric algorithms. This article explains the difficulty she faced in how trying to capture a black hole is like trying to photograph "a grapefruit on the moon." This also explains how Bouman's algorithm made all of this work-- it combines all of the data from the participating telescopes into, in essence, one massive telescope.

https://youtu.be/BIvezCVcsYs

This is a 2016 TEDx talk from Bouman where she describes her work. Note: though I am intentionally focusing on her contributions specifically to defend the attention she's getting, she makes it clear that this was a team effort. She always gives credit to her teammates who work with her. She is full of humility and wonder.

http://people.csail.mit.edu/klbouman/pw/papers_and_presentations/cvpr2016_bouman.pdf

This is the paper based on Bouman's work, where she's listed as first author. The position of her name is important. While the meaning of being first author can differ in certain fields, I'm basing the 'primary contributor' interpretation on the fact that multiple other articles say she was lead, MIT refers to the algorithm as hers, as well as the fact that she named CHIRP.

https://github.com/achael/eht-imaging

This is Andrew Chael's imaging library available on GitHub. It's where our original "sleuths" discovered that Bouman had contributed very little and assumed that she was stealing the glory from others. NOTE: Andrew Chael didn't make these claims or ask for this sort of attention!

https://arxiv.org/abs/1605.06156

This is a paper describing Chael's work, which is impressive. Bouman is in the position of last author. Again, the relevance of the author order can differ, but the common significance of 'last author' is either the supervisor or the relative least contribution. In Bouman's paper, the position of last author seemed to indicate supervisor(s) based on the organization hierarchy on the EHT website. In this instance, I interpret Bouman's name being last as her being a minor contributor to Chael's specific work.

https://eventhorizontelescope.org/

This is the official EHT telescope website. I can't remember what I looked at here, it's in my history. I think I was trying to find out who Bouman's project lead was.

https://twitter.com/thisgreyspirit/status/1116518544961830918

This is the twitter thread where Chael defends Katie. He explains that he didn't write 850K lines, defends Katie and says that his algorithm couldn't have worked without her, mentions his LGBTQ status, and more. He seems like a great guy.

https://physicstoday.scitation.org/do/10.1063/PT.6.1.20190411a/full/

This article speaks to some of the other people involved, including the project leader Sheperd Doeleman. This describes the process they went through in creating the black hole image and is where I got the information about how they split the teams into 4, and how the final image is a composite.

https://phys.org/news/2019-04-scientist-superstar-katie-bouman-algorithm.html

This is the article that talks about CHIRP sorting through a "true mountain" of data, and how that data was passed out to four teams to check for accuracy.

https://www.theguardian.com/science/2019/apr/10/black-hole-picture-captured-for-first-time-in-space-breakthrough

This article talks about Bouman coming up with a new algorithm to "stitch data across the EHT network" of telescopes, and how she led an elaborate series of tests (splitting the data up across four teams, etc) to verify that the output wasn't the result of a glitch or fluke.

http://www.asahi.com/ajw/articles/AJ201904110037.html

This article explains Honma's significant role. It describes what Honma's algorithm does and how it was used in this project.

https://www.nao.ac.jp/en/news/science/2019/20190410-eht.html

Here is another article that goes into more detail about Honma and team. He does a great job of explaining how all of the algorithms in question were, in fact, capable of producing accurate images of the black hole, and a part of the task of his algorithm was to verify the accuracy of those generated photos.

The final link is the document by all 200+ participants. This document is important because it gives such a clear idea of the work that went into this, the fabric of which Bouman is an integral part. While I'm intentionally highlighting her contributions in defense of her, it should be understood that, like with most scientific breakthroughs, there were many unsung heroes:

https://iopscience.iop.org/article/10.3847/2041-8213/ab0ec7

=============================================

Final Update:

As the furor begins to die down, I'm glad to see that more and more information is coming out about the people involved in this. I'm going to stop editing this post now, as it's been an exhilerating and exhausting process. But on a final note, I want to answer a few common questions.

FAQ:

Q: Why did you write this?

A: To counter the viral narrative that Katie Bouman contributed nothing to this years-long endeavor.

Q: Why didn't you call her Dr. Bouman? She has a title.

A: Without being certain of everyone's title, I decided to leave all titles off. This was an intentional decision to avoid the appearance of slighting other contributors.

Q: Are you trying to give her full credit for the project?

A: No. I don't believe that highlighting one person's contributions to something is the same as giving them full credit. When someone does a 'profile in courage' of a war veteran, they're not saying that one person won the entire war on their own, just that they played a vital part.

Q: What is your background? Are you a scientist?

A: I'm not a scientist and I don't have a college degree. I attended college briefly, first as a vocal major and later as a web development major. My knowledge of programming and data is self-taught and developed through work environments. My work experiences began with an internship for Independence Blue Cross and turned into a number of opportunities in multimedia, graphic and web design, programming, and most recently data analysis and data transformation with TiVo. Data remains my current field. Astrophysics is just a passion I've had since childhood.

Q: What do you think of the Occupy Democrats meme that she did everything 'single-handedly'?

A: I feel that's categorically false and I wish they hadn't done that. While I think that there' a legitimate purpose to celebrating women's roles in STEM, it's important at all times to be objective and accurate in all accounts.

Q: Do you think everyone who questioned her contributions are incels?

A: No. I'm one of those people who ultimately questioned her contributions as well, and I'm not an incel. Wanting to know the truth is legitimate. What isn't legitimate are the sexist and misogynist attacks she endured.

That's all, folks. Love and light to you all.There's a lot of news going on about the "black hole girl" right now, and how she's being given too much credit for her role in the historic first image of a black hole. Because this is too important, I want to set the record straight.

Once Katie Bouman became the "face" of the black hole photo, and articles began to call her "the woman behind the black hole photo", an assortment of people that I'm strongly inclined to call incels but won't decided to figure out just how much of a role she had in it. Why? You'd have to ask them. Something about her attractiveness, youthfulness, and femaleness disturbed them to the point where they had to go digging.

And after digging, they found Andrew Chael, who wrote an algorithm, and put his algorithm online. Andrew Chael worked on the black hole photo as well. And because people kept saying that Katie Bouman wrote "the algorithm", these people decided that "the algorithm" in question must be Chael's.

So they looked at Chael's GitHub repository and checked the history. The history showed that Andrew Chael's commits totaled more than 850,000 lines, while Katie Bouman contributed only 2,400.

"Oh my god!" they all said. "He did almost all of the work on the algorithm and yet she's the one getting all of the credit!"

They dug a little deeper - but not much - and discovered that the algorithm that "ultimately" generated the world-famous photo was created a different man, named Mareki Honma.

"She's taken the credit from two men!" they gasped. "Feminism and the PC media is destroying everything!"

There were, of course, those who tried to be kind. "She's always said that this was a team effort," they said. "We don't blame her, we blame the media. She didn't ask to become the poster girl of a team project she barely contributed to."

Meanwhile, Andrew Chael - a gay man - tweeted in defense of her. He thanked people for congratulating him on the work he'd spent years on but clarified that if they were doing so as a part of a sexist attack on Katie Bouman, they should go away and reconsider their lives. He said that his work couldn't have happened without Katie.

And it turns out that he was the one who took the viral photo of Bouman, specifically because he didn't want her contributions to be lost to history

So I decided to find out for myself what Katie Bouman's actual contributions were. As a programmer, I'm well aware that the number of GitHub commits means nothing without context. And Chael himself clarified that the lines being counted in the commits were from automatic commits of large data files. The actual software was made up of 68,000 lines, and though he didn't count how many he did personally (having said he doesn't actually care how much of it he personally authored), someone else assessed that he wrote about 24,000 of those.

Whether 68,000 or 24,000-- it's more than 2,400 right? Why call it "her" algorithm, then?

Because there's more than one algorithm being referenced here. These people just don't realize it.

I'll work my way backward because it's easier to explain that way.

The photo that everyone is looking at, the world famous black hole photo? It's actually a composite photo. It was generated by an algorithm credited to Mareki Honma. Honma's algorithm, based on MRI technology, is used to "stitch together" photos and fill in the missing pixels by analyzing the surrounding pixels.

But where did the photos come from that are composited into this photo?

The photos making up the composite were generated by 4 separate teams, led by Katie Bouman and Andrew Chael, Kazu Akiyama and Sara Issaoun, Shoko Koyama, Jose L. Gomez, and Michael Johnson. Each team was given a copy of the black hole data and isolated from each other. Between the four of them, they used two techniques - an older, traditional one called CLEAN, and a newer one called RML - to generate an image.

The purpose of this division and isolation of teams was deliberately done to test the accuracy of the black hole data they were all using. If four isolated teams using different algorithms all got similar results, that would indicate that the data itself was accurate.

And lo, that's exactly what happened. The data wasn't just good, it's the most accurate of its kind. 5 petabytes (millions of billions of bytes) worth of accurate black hole data.

But where did the data come from?

Eight radio telescopes around the world trained their attention on the night sky in the direction of this black hole. The black hole is some ungodly distance away, a relative speck amidst billions of celestial bodies. And what the telescopes caught was not only the data of the black hole but the data of everything else as well.

Data that would need to be sorted.

Clearly, it's not the sort of thing you can sort by hand. To separate the wheat (one specific black hole's data) from the chaff (literally everything else around and between here and there) required an algorithm that could identify and single it out, calculations that were crunched across 800 CPUs on a 40Gbit/s network. And given that the resulting black hole-specific data was 5 petabytes (hundreds of pounds worth of hard drives!) you can imagine that the original data set was many times larger.

The algorithm that accomplished this feat was called CHIRP, short for "Continuous High-resolution Image Reconstruction using Patch priors".

CHIRP was created by Katie Bouman.

At the age of 23, she knew nothing about black holes. Her field is computer science and artificial intelligence, topics she'd been involved in since high school. She had a theory about the shadows of black holes, and her algorithm was designed to find those shadows. Katie Bouman used a variety of what MIT called "clever algebraic solutions" to overcome the obstacles involved in creating the CHIRP algorithm. And though she had a team working to help her, her name comes first on the peer-reviewed documentation.

It's called the CHIRP algorithm because that's what she named it. It's the only reason these images could be created, and it's responsible for creating some of the images that were incorporated into the final image. It's the algorithm that made the effort of collecting all that data worth it. Any data analyst can tell you that you can't analyze or visualize data until it's been prepared first. Cleaned up. Narrowed down to the important information.

That's what Katie Bouman did, and after working as a data analyst for two years with a focus on this exact thing - data transformation - I can tell you it's not easy. It's not easy on the small data sets I worked with, where I could wind up spending a week looking for the patterns in a 68K Excel spreadsheet containing only one month's worth of programming for a single TV station!

Katie Bouman's 2,400 line contribution to Andrew Chael's work is on top of all of her other work. She spent five years developing and refining the CHIRP algorithm before leading four teams in testing the data created. The data collection phase of this took 10 days in April 2017, when the eight telescopes simultaneously trained their gazes towards the black hole.

This photo was ultimately created as a way to test Katie Bouman's algorithm for accuracy. MIT says that it's frequently more accurate than similar predecessors. And it is the algorithm that gave us our first direct image of a black hole.

Around the internet, there are people who have the misperception that Katie Bouman is just the pretty face, a minor contributor to a project where men like Andrew Chael and Mareki Honma deserve the credit. There are people pushing memes and narratives that she's only being given such acclaim because of feminism. And because Katie Bouman refuses to say that this was anything other than a team effort, even the most flattering comments about her still place her contributions to the photo at less-than-equal contribution to others.

But I'm writing to set the story straight:

When it is written that Katie Bouman is the woman "behind the black hole photo", it is objectively true. She wasn't the only woman, but her work was crucial to making all of this happen.

When Andrew Chael says that his software could not have worked without her, he isn't just being a stand-up guy, he's being literal. And there are those who could just as easily say the same about his contribution, or the contributions of many others.

And while it's true that every one of the 200+ people involved played an important role, Katie Bouman deserves every ounce of superstardom she receives.

If there must be a face to this project - and there usually is - then why shouldn't it be her, her fingers twined across her lips, her gleeful eyes luminous and wide with awe and joy?

Edited:

Thinking on it a little further, I felt I should clarify that I'm not actually trying to downplay Andrew Chael. His imaging algorithm is actually the result of years of effort, a labor of love. Each image that could be composited into the final photo brought with it a unique take on the data, without which the final photo wouldn't have been complete.

So let's take a moment to celebrate the fact that two of the most integral contributors to the first direct photo of a black hole

were a woman

and a gay man.

===============================================

2nd Update (LONG!)

I went to bed at 19 shares on a post I wrote to vent to my FB friends, and now it's over 2K. I guess it's gone viral. That means I have some work to do.

I'm going to provide a list of the various articles I read to piece this together. When I wrote this, I wasn't trying to write an essay so I didn't put sources in and I didn't ensure that every detail is 100% accurate. So I'm doing that now.

Any edits I make are mentioned below (apart from spelling/grammar fixes). The resources that led me to write this are listed below. And because I value accuracy, I welcome people to point out mistakes of any kind. I'll make corrections and credit them here.

Edit: I incorrectly wrote that Bouman worked on the algorithm for 6 years and spent 2 years refining it. This was an accidental mush of facts: She's been working on this project for a total of 6 years (ages 23 to 29). She spent 3 years building CHIRP and 2 years refining it. I've corrected that and included that she led the four teams, as two separate articles mention it.

Edit: One of the leads for the 4 team project was a man named Jose L Gomez. I added that to the above, after being sent a twitter thread from Xu S. Han. Thank you! Twitter thread here:

https://twitter.com/saraissaoun/status/1116304522660519936?s=21

Edit: Thanks to Zoë Barraclough and someone who would prefer not to be named, for messaging me with another couple of edits. As confirmed on Kazu Akiyama's twitter, there were more than four leaders for the four imaging teams. As I find out the names of these co-leaders, I'll incorporate them into the post.

NEWEST LINK:

A very astute commenter left a note that included this link:

Caltech colloquium, Friday, April, 12th — “Imaging a Black Hole [Shadow] with the Event Horizon Telescope”: https://m.youtube.com/watch?v=UGL_OL3OrCE

This hour-long presentation is of Katie Bouman describing in more detail. If you have some time, watch it! It does get technical but she keeps it engaging.

SOURCES:

http://news.mit.edu/2016/method-image-black-holes-0606

This is a 2016 MIT article announcing CHIRP. It gives a pretty excellent idea about the magnitude of Bouman's contribution.

https://www.extremetech.com/extreme/229675-mit-researcher-develops-new-algorithm-for-imaging-black-holes

This goes into detail about Katie Bouman's algorithm. It describes how her algorithm differs from normal/traditional interferometric algorithms. This article explains the difficulty she faced in how trying to capture a black hole is like trying to photograph "a grapefruit on the moon." This also explains how Bouman's algorithm made all of this work-- it combines all of the data from the participating telescopes into, in essence, one massive telescope.

https://youtu.be/BIvezCVcsYs

This is a 2016 TEDx talk from Bouman where she describes her work. Note: though I am intentionally focusing on her contributions specifically to defend the attention she's getting, she makes it clear that this was a team effort. She always gives credit to her teammates who work with her. She is full of humility and wonder.

http://people.csail.mit.edu/klbouman/pw/papers_and_presentations/cvpr2016_bouman.pdf

This is the paper based on Bouman's work, where she's listed as first author. The position of her name is important. While the meaning of being first author can differ in certain fields, I'm basing the 'primary contributor' interpretation on the fact that multiple other articles say she was lead, MIT refers to the algorithm as hers, as well as the fact that she named CHIRP.

https://github.com/achael/eht-imaging

This is Andrew Chael's imaging library available on GitHub. It's where our original "sleuths" discovered that Bouman had contributed very little and assumed that she was stealing the glory from others. NOTE: Andrew Chael didn't make these claims or ask for this sort of attention!

https://arxiv.org/abs/1605.06156

This is a paper describing Chael's work, which is impressive. Bouman is in the position of last author. Again, the relevance of the author order can differ, but the common significance of 'last author' is either the supervisor or the relative least contribution. In Bouman's paper, the position of last author seemed to indicate supervisor(s) based on the organization hierarchy on the EHT website. In this instance, I interpret Bouman's name being last as her being a minor contributor to Chael's specific work.

https://eventhorizontelescope.org/

This is the official EHT telescope website. I can't remember what I looked at here, it's in my history. I think I was trying to find out who Bouman's project lead was.

https://twitter.com/thisgreyspirit/status/1116518544961830918

This is the twitter thread where Chael defends Katie. He explains that he didn't write 850K lines, defends Katie and says that his algorithm couldn't have worked without her, mentions his LGBTQ status, and more. He seems like a great guy.

https://physicstoday.scitation.org/do/10.1063/PT.6.1.20190411a/full/

This article speaks to some of the other people involved, including the project leader Sheperd Doeleman. This describes the process they went through in creating the black hole image and is where I got the information about how they split the teams into 4, and how the final image is a composite.

https://phys.org/news/2019-04-scientist-superstar-katie-bouman-algorithm.html

This is the article that talks about CHIRP sorting through a "true mountain" of data, and how that data was passed out to four teams to check for accuracy.

https://www.theguardian.com/science/2019/apr/10/black-hole-picture-captured-for-first-time-in-space-breakthrough

This article talks about Bouman coming up with a new algorithm to "stitch data across the EHT network" of telescopes, and how she led an elaborate series of tests (splitting the data up across four teams, etc) to verify that the output wasn't the result of a glitch or fluke.

http://www.asahi.com/ajw/articles/AJ201904110037.html

This article explains Honma's significant role. It describes what Honma's algorithm does and how it was used in this project.

https://www.nao.ac.jp/en/news/science/2019/20190410-eht.html

Here is another article that goes into more detail about Honma and team. He does a great job of explaining how all of the algorithms in question were, in fact, capable of producing accurate images of the black hole, and a part of the task of his algorithm was to verify the accuracy of those generated photos.

The final link is the document by all 200+ participants. This document is important because it gives such a clear idea of the work that went into this, the fabric of which Bouman is an integral part. While I'm intentionally highlighting her contributions in defense of her, it should be understood that, like with most scientific breakthroughs, there were many unsung heroes:

https://iopscience.iop.org/article/10.3847/2041-8213/ab0ec7

=============================================

Final Update:

As the furor begins to die down, I'm glad to see that more and more information is coming out about the people involved in this. I'm going to stop editing this post now, as it's been an exhilerating and exhausting process. But on a final note, I want to answer a few common questions.

FAQ:

Q: Why did you write this?

A: To counter the viral narrative that Katie Bouman contributed nothing to this years-long endeavor.

Q: Why didn't you call her Dr. Bouman? She has a title.

A: Without being certain of everyone's title, I decided to leave all titles off. This was an intentional decision to avoid the appearance of slighting other contributors.

Q: Are you trying to give her full credit for the project?

A: No. I don't believe that highlighting one person's contributions to something is the same as giving them full credit. When someone does a 'profile in courage' of a war veteran, they're not saying that one person won the entire war on their own, just that they played a vital part.

Q: What is your background? Are you a scientist?

A: I'm not a scientist and I don't have a college degree. I attended college briefly, first as a vocal major and later as a web development major. My knowledge of programming and data is self-taught and developed through work environments. My work experiences began with an internship for Independence Blue Cross and turned into a number of opportunities in multimedia, graphic and web design, programming, and most recently data analysis and data transformation with TiVo. Data remains my current field. Astrophysics is just a passion I've had since childhood.

Q: What do you think of the Occupy Democrats meme that she did everything 'single-handedly'?

A: I feel that's categorically false and I wish they hadn't done that. While I think that there' a legitimate purpose to celebrating women's roles in STEM, it's important at all times to be objective and accurate in all accounts.

Q: Do you think everyone who questioned her contributions are incels?

A: No. I'm one of those people who ultimately questioned her contributions as well, and I'm not an incel. Wanting to know the truth is legitimate. What isn't legitimate are the sexist and misogynist attacks she endured.

That's all, folks. Love and light to you all.

[jcmarchi]

New Data, Same Great Appearance for M87* - Technology Org

New Post has been published on https://thedigitalinsider.com/new-data-same-great-appearance-for-m87-technology-org/

New Data, Same Great Appearance for M87* - Technology Org

Nearly five years ago, a globe-spanning team of astronomers gave the world its first-ever glimpse of a black hole. Now the team has validated both their original findings and our understanding of black holes with a new image of the supermassive black hole M87*.

This supermassive black hole, 6.5 billion times the mass of our Sun, resides at the center of the Messier 87 (M87) galaxy in the Virgo galaxy cluster, located 55 million light-years from Earth.

The new image, like the old one, was captured by the Event Horizon Telescope (EHT), an array of radio telescopes stretching across the planet. These new data, however, were gathered a year later, in 2018, and benefitted from enhancements in the telescope array, notably with the inclusion of a telescope in Greenland.

EHT’s original image of M87* was important not just because it represented the first time humans had imaged a black hole, but also because the object looked the way it was supposed to look. Notably, the image showed what is known as a black-hole shadow—a dark region at the center of a glowing disk of hot matter circling the black hole.

A black-hole shadow isn’t a shadow in the same sense as the one you cast when you walk outside on a sunny day. Instead, the dark region is created by the black hole’s immense gravitational field, which is so strong that light cannot escape it. Since no light leaves a black hole, it appears dark.

Additionally, that strong gravity bends light that passes near the black hole without falling into it, effectively acting like a lens. This is known as gravitational lensing, and it creates a ring of light that can be seen no matter which angle the black hole is viewed from. These effects were both predicted from Albert Einstein’s theory of general relativity. Because M87*’s image shows these effects, it is strong evidence that general relativity and our understanding of the physics of black holes is correct.

This new M87* image was produced with key contributions from an imaging team at Caltech, including Professor Katherine (Katie) L. Bouman, assistant professor of computing and mathematical sciences, electrical engineering, and astronomy; former Caltech PhD student Nitika Yadlapalli Yurk (PhD ’23); and current Caltech postdoctoral research associate in computing and mathematical sciences Aviad Levis.

Bouman is a coordinator of the EHT Imaging Working Group and was a postdoctoral fellow at the Harvard Smithsonian Center for Astrophysics and co-lead of the EHT imaging team when the original image was published in 2019. In that role, she helped develop the algorithms that assembled the trove of data collected by the EHT’s multiple radio telescopes into a single, cohesive image. Since joining the Caltech faculty, Bouman, who is also a Rosenberg Scholar and Heritage Medical Research Institute Investigator, has continued her work with EHT. She also co-led the imaging of the Milky Way’s supermassive black hole published in 2022.

Yurk joined the EHT Collaboration in 2020 and played an active role in the imaging team for the latest M87* image. Her main contributions included developing synthetic datasets to be used in the training and validation of the imaging algorithms. Yurk also wrote software that was used in the exploration of image candidates. She was recently recognized by the EHT for her efforts with a PhD Thesis Award for the advances she brought to the imaging and validation of the most recent M87* image. She is currently a NASA Postdoctoral Program fellow at JPL, which Caltech manages for NASA.

Imaging an object like M87* with the EHT is very different than imaging a planet like Saturn with a conventional telescope. Instead of seeing light, the EHT observes the radio waves emitted by objects and must computationally combine the information to form a picture.

“The raw data that comes out of these telescopes are basically just voltage values,” Yurk says. “I like to describe radio telescopes as the world’s most sensitive volt meters, and they collect voltages really accurately from different parts of the sky.”

Turning those voltage values into an image is tricky, Bouman says, because the information the researchers are working with is incomplete, and there is nothing to compare the image against since no one has seen M87* with their own eyes.

“We don’t want to plug in our expectations of what the black hole should look like when we’re computationally forming the image,” Bouman says. “Otherwise, it might lead us to an image that we expect rather than one that captures reality.”

To avoid that problem, the researchers test their image processing algorithms with what is known as synthetic data, a suite of simulated images with simple geometric shapes. Those data are run through the algorithms to produce an image. If the output image is true to the input image, they know the algorithm is working correctly and would be able to accurately see surprising structures around the black hole.

Bouman says that process, which was co-led by Yurk, involved exploring hundreds of thousands of parameters to gauge the effectiveness of the algorithms in reconstructing different image structures. The team found that with the addition of the Greenland telescope to the EHT, the methods more robustly recovered features in the images.

The process produced an image of M87* that is only slightly different than the first. The most obvious difference is that the brightest portion of the glowing ring surrounding M87* has shifted about 30 degrees counterclockwise. According to the EHT, that movement is likely the result of the turbulent flow of matter around a black hole. Importantly, the ring has remained the same size, which was also predicted by general relativity.

Bouman adds that the team’s ability to produce another image of M87* with new data that agrees so closely with the previous image is exciting.

“I think that people are going to ask, ‘Why is this important? You already showed a picture of M87*.’ Other groups have reproduced the M87* picture with data that were taken in 2017. But it’s a totally different thing to have a new dataset taken a different year and to come to the same conclusions. Reproducibility with independent data is a big deal, too.”

Written by Emily Velasco

Source: Caltech

You can offer your link to a page which is relevant to the topic of this post.

[warriors-last-words]

I´ve never been angrier than finding out that this thing

was the cropped version made by the news.

The actual photo of the black hole looks like this:

[akirakirxaa-ooc]

Don't forget Katie Bouman, the computer scientist who was responsible for the first ever photo of a black hole.

“I always remember having this fight with a random dude who claimed that ‘straight white men’ were the only true innovators. His prime example for this was the computer… the computer… THE COMPUTER!!! THE COM-PU-TER!!!

Alan Turing - Gay man and ‘father of computing’ Wren operating Bombe - The code cracking computers of the 2nd world war were entirely run by women Katherine Johnson - African American NASA mathematician and ‘Human computer’ Ada Lovelace - arguably the 1st computer programmer”

- Sacha Coward

Also Margaret Hamilton - NASA computer scientist who put the first man on the moon - an as-yet-unmatched feet of software engineering, here pictured beside the full source of that computer programme. #myhero

Grace Hopper - the woman that coined the term “bug”  

- @robinlayfield

[theoppositeofadults]

“our work should equip the next generation of women to outdo us in every field this is the legacy we’ll leave.”

- rupi kaur

[music-thestrongestformofmagic]

Incels and other sexist men can't see a woman doing something incredible without fuming and trying to discredit her. They're now dissing on Katie Bouman, who helped write one of the algorithms that got us the black hole picture, saying she was just an assistant (they don't know what assistant professor is), and using Andrew Chael, her colleague in the Event Horizon Telescope team who helped write one of the codes, as ~the true person behind the codes who is being erased by this anti-men society~ or whatever. They're even saying crap like "lmao women really don't do shit". Andrew took to Twitter himself to call bullshit on that.

If y'all can spread this thread to counter such narrative it'd be great.

(x)

[edgeworth-s]

okay guys but do you know who led the team that made it possible for us to see the picture of the black hole?

so her name is dr Katie Bouman, a 29-year-old who has created the algorhitm during grad school at MIT

the first picture shows dr Bouman when the data was being reconstructed, the second one is her with STACKS of hard drives of black hole data

(by the way, doesnt it remind you of this photo of Margaret Hamilton with her code that let us fly to the moon?)

anyway, i want for you guys to remember dr Katie Bouman because what she did is INCREDIBLE and its a huge step for us all so i REALLY hope youre gonna remember her and share this bc she DESERVES IT

(also for those of you who complain that the image is blurry; fuck off)

[mcgonnagals]

[milkysagittariusway]

“A black hole and its shadow have been captured in an image for the first time, a historic feat by an international network of radio telescopes called the Event Horizon Telescope (EHT).

A black hole is an extremely dense object from which no light can escape. Anything that comes within a black hole’s “event horizon,” its point of no return, will be consumed, never to re-emerge, because of the black hole’s unimaginably strong gravity. By its very nature, a black hole cannot be seen, but the hot disk of material that encircles it shines bright. Against a bright backdrop, such as this disk, a black hole appears to cast a shadow.   

The stunning new image shows the shadow of the supermassive black hole in the center of Messier 87 (M87), an elliptical galaxy some 55 million light-years from Earth. This black hole is 6.5 billion times the mass of the Sun. Catching its shadow involved eight ground-based radio telescopes around the globe, operating together as if they were one telescope the size of our entire planet.”

Credit- nasa.gov

[computersciencegothic]

This is an excellent but VERY LONG post, so I’m putting in a read more:

[lawofcollage]

Remember how I said there was art coming of the black hole? Props to Katie Bouman!

Redbubble