by Robert Cousin
translated by Edward Gauvin
2023
The Phantom Scientist is a French graphic novel set at a mysterious, isolated institute, where scientists from a variety of fields are invited to advance their research. The institute itself is a kind of experimental project. The idea is that incidental interactions with peers from other fields will produce novel, serendipitous discoveries ... but it also produces a rising tide of chaos that will eventually force the institute's current director (a sociologist!) to call in the army to evacuate everyone for their own safety. This is the fourth iteration of the institute, and when it inevitably collapses, it'll be restarted with new researchers and a new director.
Our viewpoint character is professor Stephane Douasy, a physicist who studies fractals and spirals, who is interested in applying those ideas to understand plant growth. Based on the acknowledgments, it seems he's closely based on a real person, Stephane Douady, so I suspect that the discovery he eventually makes about leaf shapes is a real finding from the actual Dr Douady's research. The fictional Stephane is the last of the 24 scientists to arrive at the institute. A new one comes at regular intervals to dampen the chaos. Now that Stephane has arrived, the institute should function at maximum capacity for the final 6 months of its 7-year cycle before collapsing. But there's a problem - there's already way too much chaos, and it doesn't seem to calm, so the institute may not survive its full span...
Stephane is an outgoing fellow, and he quickly befriends two other scientists in his building - Louise, a linguist who was working on teaching computers speech but has given up since the appearance of chat-bots, and Villhelm, who's written a computer program that accurately predicts his own future actions, but that works so slowly that they always arrive late. (Ominously, each set of predictions includes his percent chance of death.) Their building also has the office of the never-seen Dr Paniany, the 'phantom scientist' of the title.
Stephane is basically doing what the institute is supposed to - he gets his introverted colleagues to leave their labs and talk to each other for the first time in forever, he insists on checking inside Paniany's office (the other two had been assuming he'd either never or arrived or left before they got there), and gaining new insights from seeing his research. Vilhelm figures out how to make his program run faster, and Louise gets reinvigorated out of her torpor, and decides to find where inside the institute Paniany is camped out.
Dr Paniany was researching the P vs NP problem. In math and computing, some problems just don't have a single right answer. Among those that do, there are problems that are 'easy to solve' called P, and problems that are hard to solve but 'easy to check' called NP. Easy to solve here means you have a set of instructions, an algorithm, you can follow that lets you find a solution without needing to guess or use trial-and-error. Easy to check means you can tell that a right answer is right. The NP example author Robin Cousin gives is a jigsaw puzzle - hard to solve, but very easy to tell if it's put together correctly or not. (Complex as they look, Rubik's cubes are P. If you know the steps, you can solve one, from any starting arrangement, in seconds.) There's a longstanding debate about whether or not P = NP, if every problem we can easily check has some algorithm that would let us solve it easily too, even if we haven't found it yet, or if there are some problems that can only be solved by trial-and-error.
In reality, we don't have an answer either way. In the comic, Paniany has proved that P = NP, and written an algorithm using his proof that helps every other researcher who encounters it do their own research much better and faster. He, and his proof, are the source of the rising chaos that overtakes the institute during the second half of the comic.
Cousin's art style reminds me a bit of Jason Shiga. His figures are cartoony, with relatively little detail, fairly thick outlines, and bright colors.
It's pretty rare to see a sociologist show up in contemporary scifi! The other example I can think of is Connie Willis's Bellwether, which was also about how the 'chaos' of interactions between people who might not otherwise meet can produce unexpected creativity or start trends and fads. This is, in fact, a real sociological finding, although both Cousin and Willis play it up for effect, in the same way scifi authors have been doing with ideas from physics forever. But one of the earliest findings in the sociology of networks is about how you can get more new information from acquaintances rather than close friends and family, a phenomenon called 'the strength of weak ties.' That name comes from Mark Granovetter, although if you've heard the idea before, it's probably because of Malcolm Gladwell, who's done the most to popularize it. It's too bad the seismograph-style Organizational Chaos Index the institute director keeps consulting isn't a real measure; it'd be awfully useful!
Our viewpoint character is professor Stephane Douasy, a physicist who studies fractals and spirals, who is interested in applying those ideas to understand plant growth. Based on the acknowledgments, it seems he's closely based on a real person, Stephane Douady, so I suspect that the discovery he eventually makes about leaf shapes is a real finding from the actual Dr Douady's research. The fictional Stephane is the last of the 24 scientists to arrive at the institute. A new one comes at regular intervals to dampen the chaos. Now that Stephane has arrived, the institute should function at maximum capacity for the final 6 months of its 7-year cycle before collapsing. But there's a problem - there's already way too much chaos, and it doesn't seem to calm, so the institute may not survive its full span...
Stephane is an outgoing fellow, and he quickly befriends two other scientists in his building - Louise, a linguist who was working on teaching computers speech but has given up since the appearance of chat-bots, and Villhelm, who's written a computer program that accurately predicts his own future actions, but that works so slowly that they always arrive late. (Ominously, each set of predictions includes his percent chance of death.) Their building also has the office of the never-seen Dr Paniany, the 'phantom scientist' of the title.
Stephane is basically doing what the institute is supposed to - he gets his introverted colleagues to leave their labs and talk to each other for the first time in forever, he insists on checking inside Paniany's office (the other two had been assuming he'd either never or arrived or left before they got there), and gaining new insights from seeing his research. Vilhelm figures out how to make his program run faster, and Louise gets reinvigorated out of her torpor, and decides to find where inside the institute Paniany is camped out.
Dr Paniany was researching the P vs NP problem. In math and computing, some problems just don't have a single right answer. Among those that do, there are problems that are 'easy to solve' called P, and problems that are hard to solve but 'easy to check' called NP. Easy to solve here means you have a set of instructions, an algorithm, you can follow that lets you find a solution without needing to guess or use trial-and-error. Easy to check means you can tell that a right answer is right. The NP example author Robin Cousin gives is a jigsaw puzzle - hard to solve, but very easy to tell if it's put together correctly or not. (Complex as they look, Rubik's cubes are P. If you know the steps, you can solve one, from any starting arrangement, in seconds.) There's a longstanding debate about whether or not P = NP, if every problem we can easily check has some algorithm that would let us solve it easily too, even if we haven't found it yet, or if there are some problems that can only be solved by trial-and-error.
In reality, we don't have an answer either way. In the comic, Paniany has proved that P = NP, and written an algorithm using his proof that helps every other researcher who encounters it do their own research much better and faster. He, and his proof, are the source of the rising chaos that overtakes the institute during the second half of the comic.
Cousin's art style reminds me a bit of Jason Shiga. His figures are cartoony, with relatively little detail, fairly thick outlines, and bright colors.
It's pretty rare to see a sociologist show up in contemporary scifi! The other example I can think of is Connie Willis's Bellwether, which was also about how the 'chaos' of interactions between people who might not otherwise meet can produce unexpected creativity or start trends and fads. This is, in fact, a real sociological finding, although both Cousin and Willis play it up for effect, in the same way scifi authors have been doing with ideas from physics forever. But one of the earliest findings in the sociology of networks is about how you can get more new information from acquaintances rather than close friends and family, a phenomenon called 'the strength of weak ties.' That name comes from Mark Granovetter, although if you've heard the idea before, it's probably because of Malcolm Gladwell, who's done the most to popularize it. It's too bad the seismograph-style Organizational Chaos Index the institute director keeps consulting isn't a real measure; it'd be awfully useful!
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