#also quanta magazine

[hiranospiercing]

i legit survived the worst physics class and the moment i came home i saw that fic about kagi dying that my mutuals have been reblogging and i clearly deserve to be hugged by the gods rn

[typhlonectes]

Insects and Other Animals Have Consciousness, Experts Declare

A group of prominent biologists and philosophers announced a new consensus: There’s “a realistic possibility” that insects, octopuses, crustaceans, fish and other overlooked animals experience consciousness.

In 2022, researchers at the Bee Sensory and Behavioral Ecology Lab at Queen Mary University of London observed bumblebees doing something remarkable: The diminutive, fuzzy creatures were engaging in activity that could only be described as play. Given small wooden balls, the bees pushed them around and rotated them. The behavior had no obvious connection to mating or survival, nor was it rewarded by the scientists. It was, apparently, just for fun. The study on playful bees is part of a body of research that a group of prominent scholars of animal minds cited today, buttressing a new declaration that extends scientific support for consciousness to a wider suite of animals than has been formally acknowledged before. For decades, there’s been a broad agreement among scientists that animals similar to us — the great apes, for example —  have conscious experience, even if their consciousness differs from our own. In recent years, however, researchers have begun to acknowledge that consciousness may also be widespread among animals that are very different from us, including invertebrates with completely different and far simpler nervous systems...

Read more: https://www.quantamagazine.org/insects-and-other-animals-have-consciousness-experts-declare-20240419

[soracities]

where do you find articles or personal essays to read? and also do you have any favorite sources for news? i want to read more but i’m having a difficult time finding sources 🤍

I've answered this just recently but here's a more complete list for essays from places I visit most often (favourites are marked **)

LitHub**

Electric Literature**

Guernica Magazine**

Hazlitt**

Longreads**

Pangyrus

The Dial**

Bloodknife**

Aeon **

The Marginalian**

Asymptote Journal

N+1

Nautilus**

Quanta Magazine**

The Believer

Ordinary Plots**

The Point Magazine

The Baffler

Paris Review (Redux newsletter is good for things usu behind the paywall)

The New Yorker

The Artifice

The Collector

The Rumpus

Catapult

Tin House Archives (the online section is no longer running but past publications are still available)

Additionally, highly recommend switching to Mozilla Firefox and trying the "Pocket" feature on their homepage: it collects links to articles across the web on topics that are either trending or based on the Pocket suggestions you usually click on. I'm on private browser 99% of the time but there's still 2 or 3 articles at least that I'm always interested in and I love it!

Some other places I read things: Poets&Writers, Atlas Obscura, The Guardian, The Independent, New Scientist, Al Jazeera, The Atlantic, BBC, National Geographic, Wired, NY Times, GQ, NPR, The Irish Times / Independent, etc., I don't have favourite news sources as a rule since I usually read 2 or 3 articles on the same topic from different places depending on what it is (I don't like relying on single sources). But on the whole this covers most of what cross my orbit unless I'm looking for something specifically 💗

[noosphe-re]

In 1931, the Austrian logician Kurt Gödel pulled off arguably one of the most stunning intellectual achievements in history. Mathematicians of the era sought a solid foundation for mathematics: a set of basic mathematical facts, or axioms, that was both consistent — never leading to contradictions — and complete, serving as the building blocks of all mathematical truths. But Gödel’s shocking incompleteness theorems, published when he was just 25, crushed that dream. He proved that any set of axioms you could posit as a possible foundation for math will inevitably be incomplete; there will always be true facts about numbers that cannot be proved by those axioms. He also showed that no candidate set of axioms can ever prove its own consistency. His incompleteness theorems meant there can be no mathematical theory of everything, no unification of what’s provable and what’s true. What mathematicians can prove depends on their starting assumptions, not on any fundamental ground truth from which all answers spring.

Natalie Wolchover, How Gödel’s Proof Works, Quanta Magazine, July 14, 2020

[friendlymathematician]

Hello! Sorry if this seems off topic, but literally how do I get better at math and find it enjoyable?

practise, and finding something you enjoy practising.

more concretely, most maths education before university level is shit. you learn to apply algorithms in strictly controlled contexts, and very little to nothing about why things work the way they do, which is what's actually fun. exactly what you might find fun varies, but one thing where you get to think a lot about the "why" is discrete mathematics.

disclaimer: i don't necessarily come up with these from the perspective of someone who is bad at maths. also, regrettably, there's very little popsci maths written/created by women. depending on what you want to do, and what level you're currently at, a few things that might be fun to look at are:

khanacademy (basic school-style practise, with good explanations that tend to be a bit more intuitive than most teachers)

the book "how to think like a mathematician" (introduction to thinking mathematically and discrete maths, intended as a preparation for university level maths)

the book "proofs and refutations" (philosophy, a socratic dialogue discussing how to prove statements in mathematics and what it means to prove something)

the article series "how euler did it" (a bunch of 3-5 page explanations, heavy on the intuition, of some of the most fun proofs of leonard euler)

quanta magazine (excellent science journalism which includes mathematics, where they try to explain what mathematicians actually do)

project euler (if you like/want to learn basic programming, the first few can be brute forced but then you have to start trying to learn combinatorics/number theory)

popsci maths books: the joy of x, fermat's last theorem, the code book, e: the story of a number

[maaarine]

How Loneliness Reshapes the Brain (Marta Zaraska, Quanta Magazine, Feb 28 2023)

"Neuroscience suggests that loneliness doesn’t necessarily result from a lack of opportunity to meet others or a fear of social interactions.

Instead, circuits in our brain and changes in our behavior can trap us in a catch-22 situation: While we desire connection with others, we view them as unreliable, judgmental and unfriendly.

Consequently, we keep our distance, consciously or unconsciously spurning potential opportunities for connections. (…)

However, a study that the team published in 2022 revealed that although threatening social situations trigger more amygdala activity in people suffering from social anxiety, they do not have that effect on lonely people.

Similarly, people with social anxiety have diminished activity in the reward sections of their brain, and that does not appear to be true for lonely people.

“The core features of social anxiety were not evident in loneliness,” Lieberz said.

Those results suggest, she said, that treating loneliness simply by telling lonely people to go out and socialize more (the way you can treat a phobia of snakes with exposure) will often not work because it fails to address the root cause of the loneliness.

In fact, a recent meta-analysis confirmed that simply providing lonely people with easier access to potential friends has no effect on subjective loneliness.

The problem with loneliness seems to be that it biases our thinking.

In behavioral studies, lonely people picked up on negative social signals, such as images of rejection, within 120 milliseconds — twice as quickly as people with satisfying relationships and in less than half the time it takes to blink.

Lonely people also preferred to stand farther away from strangers, trusted others less and disliked physical touch.

This may be why the emotional well-being of lonely individuals often follows “a downward spiral,” said Danilo Bzdok, an interdisciplinary researcher at McGill University with a background in neuroscience and machine learning. (…)

Bzdok and his team showed that some regions of the default network are not only larger in chronically lonely people but also more strongly connected to other parts of the brain.

Moreover, the default network seems to be involved in many of the distinctive abilities that have evolved in humans — such as language, anticipating the future and causal reasoning.

More generally, the default network activates when we think about other people, including when we interpret their intentions.

The findings on default network connectivity provided neuroimaging evidence to support previous discoveries by psychologists that lonely people tend to daydream about social interactions, get easily nostalgic about past social events, and even anthropomorphize their pets, talking to their cats as if they were human, for example.

“It would require the default network to do that too,” Bzdok said.

While loneliness can lead to a rich imaginary social life, it can make real-life social encounters less rewarding.

A reason why may have been identified in a 2021 study by Bzdok and his colleagues that was also based on the voluminous UK Biobank data.

They looked separately at socially isolated people and at people with low social support, as measured by a lack of someone to confide in on a daily or almost daily basis.

The researchers found that in all such individuals, the orbitofrontal cortex — a part of the brain linked to processing rewards — was smaller.

Last year, a large brain-imaging study based on data from more than 1,300 Japanese volunteers revealed that greater loneliness is associated with stronger functional connections in the brain area that handles visual attention.

This finding supports previous reports from eye-tracking studies that lonely people tend to focus excessively on unpleasant social cues, such as being ignored by others. (…)

While interventions such as cognitive behavioral therapy, promoting trust and synchrony, or even ingesting magic mushrooms could help treat chronic loneliness, transient feelings of solitude will most likely always remain part of the human experience.

And there is nothing wrong with that, Tomova said.

She compares loneliness to stress: It’s unpleasant but not necessarily negative.

“It provides energy to the body, and then we can deal with challenges,” she said.

“It becomes problematic when it’s chronic because our bodies are not meant to be in this constant state. That’s when our adaptive mechanisms ultimately break down.”"

[rayssyscourse]

subjective reality anon - I'd love to see those articles :)

absolutely!!!! there was one other person in the reblogs who asked for them too, if I can find them again I'll tag them lol

Quantum superposition - https://scienceexchange.caltech.edu/topics/quantum-science-explained/quantum-superposition

Qbism - https://www.quantamagazine.org/quantum-bayesianism-explained-by-its-founder-20150604/

Perception based on prior assumptions - https://www.quantamagazine.org/brains-speed-up-perception-by-guessing-whats-next-20190502/

https://www.quantamagazine.org/to-be-energy-efficient-brains-predict-their-perceptions-20211115/

Double-slit experiment (famous experiment proving quantum superposition and the decoherence of it) -

https://plus.maths.org/content/physics-minute-double-slit-experiment-0

Observer interference - https://www.researchgate.net/publication/326795653_The_Observer_Effect

https://bigthink.com/starts-with-a-bang/measuring-reality-affect-observe/#:~:text=That%20pattern%20persists%20even%20if,really%20does%20affect%20the%20outcome.

you'll notice this in the links, but one site I really like is called Quanta Magazine--they report on other branches of science too, but their quantum physics stuff is particularly good, and I find it to be really digestible considering how complex the topics are, lol. Enjoy!!

also--a couple things I don't have on hand but might be useful to look up are the Heisenberg uncertainty principle and quantum entanglement :)

[gorey]

@anicemyth you're about to make us soooo autistic about this you don't even know bless you

so group theory: this is a very rudimentary explanation but in mathematics a group describes all the ways a structure can be symmetric aka every operation or transformation that can be done on a structure while still it remains unchanged. for example a symmetry of an equilateral triangle would be mirror flipping it on its axis or rotating it 120 or 240 degrees. the untransformed state of the structure (e.g. rotating said triangle by 0 or 360 degrees) is also counted as one of the total symmetries within the group. There's a lot of detail in the defining of this regarding the arithmetical and algebraic behavior of groups that the resources I'm going to add at the end will surely do a better job of than I could.

A group of these symmetries can be broken up into "building blocks" similarly to how an integer can be broken down into its prime factors. These building blocks of groups are known as simple groups. putting aside the fact that there are infinite simple groups bc let's not even go there - the monster group is one of the finite simple groups.

through an incredible mathematical undertaking it has been proven that we have discovered all the possible finite simple groups that can exist. they fall into categories based on their properties and this categorization is depicted in something that looks a lot like a periodic table of elements:

in the colored columns are the 18 assorted categories of group - cyclic, alternating, etc, but at the bottom the 2 rows in light green show the sporadic groups which are 26 groups that do not fall in any of the above categories. at the bottom right is the monster group.

the reason why this is crazy - the numbers listed at the bottom of each box there are the total number of symmetries contained within the group. for an equilateral triangle like I mentioned above you get 6 symmetries including both rotational and reflectional symmetries and including the baseline state of the triangle without any transformation having been done on it.

The monster group? Contains about. 8 x 10^53 symmetries. That is

808,017,424,794,512,875,886,459,904,961,710,757,005,754,368,000,000,000

symmetries. what the fuck. both massive and specific. if that triangle with 6 symmetries is 2 dimensional - with this many symmetries how big must this monstrous object be?

196,883 dimensions.

in addition to that the monster group actually contains (including itself) 20 of those 26 sporadic groups. (Fun fact those groups contained within the monster have been dubbed the Happy Family with the 6 outliers being named the Pariahs lmao). it's notable also bc it is very difficult to represent it concisely compared to other finite simple groups including the rest of the sporadics.

so it's just this.... thing. that is out there. we know what it is, we know its incredibly specific parameters, but of course we don't know WHY it's there or WHY those are the numbers you arrive at (if thats even a reasonable question to ask), it looks very arbitrary but it is ultimately a fundamental mathematical entity regardless of how inelegant it may seem, the universe is an interesting place

this weird abstract yet very specific structure has connections to other fields of mathematics - it has a connection to modular functions as described by the monstrous moonshine conjecture. yes it's actually called that and it is waaay above my paygrade but this somehow connects to a 24-dimensional variant of string theory (note I absolutely hate string theory for unrelated reasons but the mathematics of it is very interesting) in some way.

in short there exists an incredibly high dimensional object with an obscene number of symmetries that can can be used in tandem with something from a seemingly totally unrelated area of mathematics (the modular j-function) to describe a physics theory. ?????????? they called it moonshine bc they thought it was an absolutely batshit thing to even consider but apparently it works

that is my best attempt at explaining this so here are some resources I really recommend:

additionally I'd like to just plug John Conway as a whole here he's in the first video linked talking about his work regarding the monster group and the moonshine conjecture. you can find him on the channel speaking on other topics including the game of life which is an unrelated but very interesting cellular automaton that is available free online to be played with. his group theory work is what stands out to me though, he sadly passed of covid a few years back at an old age but he is one of my favorite mathematicians of all time not only because of his work but also because he just seems like a chill fucking guy

my fanciful conclusion is like. this Thing evokes in my mind images of angels or eldritch horrors or what have you. vast and incomprehensible it dwells in a space so complex it defies any human understanding beyond the mathematics used to describe it. it is beautiful and unthinkable and perhaps i want to kiss it. the end

(If anyone with a better mathematical background than us which is not at all a high bar to set wishes to add to this please do!)

[abigailspinach]

“It could be the case that we’re all actually experiencing the exact same apple, we’re just describing it differently,” said Rebecca Keogh, a research fellow in cognitive neuroscience at Macquarie University in Sydney, Australia. In 2015, when Zeman coined “aphantasia,” Keogh was finishing her doctorate under Joel Pearson, a professor of cognitive neuroscience at the University of New South Wales. They were intrigued. The group designed a few tests — one probing the mind’s ability to hold a visual image, and another measuring sweat and pupil responses to mental pictures — to confirm aphantasia’s existence. Their results showed that “it’s not just that they’re reporting a difference,” Keogh said. “There seems to be some sort of difference in their experience.”

To Cornelia McCormick, a memory researcher at the University of Bonn in Germany, the idea that some people don’t have mental images was hard to accept. But then she became curious. Knowing that mental images are intimately tied to memory, she thought, “How on Earth do those people remember their own lives?” To test this, she and her team scanned the brains of people with and without aphantasia while they recalled personal memories.

A growing number of papers have also found that aphantasics have activity in their visual cortex as they imagine something. Maybe they “have access to the visual information,” said Paolo Bartolomeo, a neurologist at the Paris Brain Institute, “but somehow they cannot integrate this information in a subjective experience.” This hypothesis meshes with the fact that people with aphantasia can recognize objects and faces, and most can see images as they drift off to sleep and in their dreams.

“They know what imagery is like from their dreams,” Zeman said. But for some reason they have trouble accessing this visual information voluntarily. He wondered what was happening in their brains.

A few years ago, Zeman scanned the brains of volunteers as they rested in an fMRI machine. The scans suggested that, at rest, people with aphantasia have weaker connections between the brain’s higher-level control centers (the prefrontal cortex) and its lower-level perception centers (the visual cortex) compared to those with hyperphantasia.

Taken together, the findings suggest that in people with aphantasia, the connections between vision centers and other integrative brain regions differ from those in people without aphantasia. “This is a good claim for some subset of aphantasia,” said Bence Nanay, a professor of philosophical psychology at the University of Antwerp who researches mental imagery. But chances are, he said, there are other neural explanations as well. That would mean that there’s more than one type of aphantasia — and indeed a whole spectrum of internal visualization across different people.

There’s No Normal

People with aphantasia report a variety of experiences. Some can “hear” in their minds, while others can’t imagine either vision or hearing. Some have excellent autobiographical memory, while many do not. Some have involuntary flashes of mental imagery. Most dream in images, but some cannot. Most are born with aphantasia, although a small minority acquire it after injury. “Aphantasia is not a monolithic phenomenon,” Nanay said.

There’s a subset of people with extremely vivid imaginations who are known as maladaptive daydreamers. Some choose to live in their imagination, rather than in real life, Dijkstra said. “They sit down on the couch, they don’t leave their house, they don’t go to school, they don’t see friends, they don’t go to their work. They just imagine their whole life just the way they want it. Because for them, it feels as real as reality.”

No matter how nascent the research is into these imaging extremes, the scientists all agree on one thing: Aphantasia and hyperphantasia are not disorders. People at either extreme of the spectrum don’t have problems navigating the world. Aphantasics are often fine at describing things, Bartolomeo said. When he’s asked them how they can visually describe objects or people from their memories when they lack mental images, they respond: “I just know,” he said.

“It’s just a variant of the normal brain,” he added. “There are variants in everything human.”

[jackdaw-sprite]

May I ask about the Spider Brains and/or Adoption wips? (Tbh all of your wips seem super interesting!!)

Certainly! Anon is asking about this ask game.

These are both actually two of my very oldest WIPs, or fragments of them. Spider brains has a few completed, unposted things, and a few other WIPs in other programs. Adoption is similar-ish--it has a few outlines in other programs.

For Spider Brains, the idea of the AU is derived from this Quanta Magazine article I'd seen a few weeks before. Specifically, ghosts in this AU work along the lines of:

Ghost cores are little bundles of unstable energy (think eddies in a stream) that are mostly instinctual and can sustain themselves through obsessive concentration on a single topic, but this isn't effective long term. This isn't a death sentence, though, because

Ghost cores can also slowly build lairs. These lairs can help (and eventually completely manage) to reinforce the ghost core itself, and their structure also supports the development of more complex powers, higher level, thinking, etc.

So while a ghost's existence is tied to their core, their personality, abilities, etc. are tied to their lair.

Halfas can get away with using their human physical structure for many of the same purposes.

But get away with isn't really healthy.

There's more to it! I spent a while just rapidly rotating the mechanics of the world obsessively, but that's a decent enough summary of the idea.

Adoption is actually another AU that's heavy on alternate ghost mechanics! It's derived from asking myself 'so if ghosts don't have cores, how does that work?' It ends up involving ghost hunger, of a few different flavors. But instead of getting into that, I'd actually like to talk about the setup!

It's a Livin' Large AU! No, no, don't run away yet, I promise I'm going somewhere with this.

In the previous episode, Undergrowth managed to cause what looks like literal billions of dollars of infrastructure damage to the area, not to mention some kind of plant zombie apocalypse thing that got averted by one of the local ghosts (Danny) managing to scrape together a victory against him.

It doesn't seem like the US government would be best pleased about that.

In fact, it seems pretty reasonable they'd do whatever it took to try and get a lid on the ghost problem for once and for all...

including forcing the Fentons to sell Fentonworks and everything in it, to get sole access to the portal that seems like the source of all these problems. (no, they aren't gung ho about selling their lives' work here)

And it works! Whatever the GIW do in Fentonworks, ghosts stop showing up outside it.

The Fentons are left to scrape together a new lab with the money they got from being effectively eminent domain'ed out of their house

And Danny is left to face building worry about just what the GIW are up to in the increasingly hostile husk of Fentonworks, and increasingly unstable emotions and irrational urges...

[natureintheory]

Encased in a gyroscopic armillary sphere, a supermassive black hole powers the gears that drive a galaxy — or is it the other way around?

Black Hole Armillary Sphere • Editorial Science Illustration • Quanta Magazine • 2022

Credit: Olena Shmahalo for Quanta Magazine

Editorial science illustration for Quanta Magazine: “What Drives Galaxies? The Milky Way’s Black Hole May Be the Key” → https://tinyurl.com/QM-SMBH-22

Thanks to editor Natalie Wolchover!

I art-directed this article and got to fly with the concept. Happy with the result.

Concept sketches: the ingredients that make a galaxy work vs black holes as galactic “ engines ”

Alt. I like this one also, but didn’t end up choosing it because the lines flatten the scene.

[mariacallous]

The original version of this story appeared in Quanta Magazine.

Is this the real life? Is this just fantasy?

Those aren’t just lyrics from the Queen song “Bohemian Rhapsody.” They’re also the questions that the brain must constantly answer while processing streams of visual signals from the eyes and purely mental pictures bubbling out of the imagination. Brain scan studies have repeatedly found that seeing something and imagining it evoke highly similar patterns of neural activity. Yet for most of us, the subjective experiences they produce are very different.

“I can look outside my window right now, and if I want to, I can imagine a unicorn walking down the street,” said Thomas Naselaris, an associate professor at the University of Minnesota. The street would seem real and the unicorn would not. “It’s very clear to me,” he said. The knowledge that unicorns are mythical barely plays into that: A simple imaginary white horse would seem just as unreal.

So “why are we not constantly hallucinating?” asked Nadine Dijkstra, a postdoctoral fellow at University College London. A study she led, recently published in Nature Communications, provides an intriguing answer: The brain evaluates the images it is processing against a “reality threshold.” If the signal passes the threshold, the brain thinks it’s real; if it doesn’t, the brain thinks it’s imagined.

Such a system works well most of the time because imagined signals are typically weak. But if an imagined signal is strong enough to cross the threshold, the brain takes it for reality.

Although the brain is very competent at assessing the images in our minds, it appears that “this kind of reality checking is a serious struggle,” said Lars Muckli, a professor of visual and cognitive neurosciences at the University of Glasgow. The new findings raise questions about whether variations or alterations in this system could lead to hallucinations, invasive thoughts, or even dreaming.

“They’ve done a great job, in my opinion, of taking an issue that philosophers have been debating about for centuries and defining models with predictable outcomes and testing them,” Naselaris said.

When Perceptions and Imagination Mix

Dijkstra’s study of imagined images was born in the early days of the Covid-19 pandemic, when quarantines and lockdowns interrupted her scheduled work. Bored, she started going through the scientific literature on imagination—and then spent hours combing papers for historical accounts of how scientists tested such an abstract concept. That’s how she came upon a 1910 study conducted by the psychologist Mary Cheves West Perky.

Perky asked participants to picture fruits while staring at a blank wall. As they did so, she secretly projected extremely faint images of those fruits—so faint as to be barely visible—on the wall and asked the participants if they saw anything. None of them thought they saw anything real, although they commented on how vivid their imagined image seemed. “If I hadn’t known I was imagining, I would have thought it real,” one participant said.

A 1910 study by the psychologist Mary Cheves West Perky found that when our perceptions match what we are imagining, we assume that their inputs are imaginary.Photograph: DOI/Quanta Magazine

Perky’s conclusion was that when our perception of something matches what we know we are imagining, we will assume it is imaginary. It eventually came to be known in psychology as the Perky effect. “It’s a huge classic,” said Bence Nanay, a professor of philosophical psychology at the University of Antwerp. It became kind of a “compulsory thing when you write about imagery to say your two cents about the Perky experiment.”

In the 1970s, the psychology researcher Sydney Joelson Segal revived interest in Perky’s work by updating and modifying the experiment. In one follow-up study, Segal asked participants to imagine something, such as the New York City skyline, while he projected something else faintly onto the wall—such as a tomato. What the participants saw was a mix of the imagined image and the real one, such as the New York City skyline at sunset. Segal’s findings suggested that perception and imagination can sometimes “quite literally mix,” Nanay said.

Not all studies that aimed to replicate Perky’s findings succeeded. Some of them involved repeated trials for the participants, which muddied the results: Once people know what you’re trying to test, they tend to change their answers to what they think is correct, Naselaris said.

So Dijkstra, under the direction of Steve Fleming, a metacognition expert at University College London, set up a modern version of the experiment that avoided the problem. In their study, participants never had a chance to edit their answers because they were tested only once. The work modeled and examined the Perky effect and two other competing hypotheses for how the brain tells reality and imagination apart.

Evaluation Networks

One of those alternative hypotheses says that the brain uses the same networks for reality and imagination, but that functional magnetic resonance imaging (fMRI) brain scans don’t have high enough resolution for neuroscientists to discern the differences in how the networks are used. One of Muckli’s studies, for example, suggests that in the brain’s visual cortex, which processes images, imaginary experiences are coded in a more superficial layer than real experiences are.

With functional brain imaging, “we’re squinting our eyes,” Muckli said. Within each equivalent of a pixel in a brain scan, there are about 1,000 neurons, and we can’t see what each one is doing.

The other hypothesis, suggested by studies led by Joel Pearson at the University of New South Wales, is that the same pathways in the brain code for both imagination and perception, but imagination is just a weaker form of perception.

During the pandemic lockdown, Dijkstra and Fleming recruited for an online study. Four hundred participants were told to look at a series of static-filled images and imagine diagonal lines tilting through them to the right or left. Between each trial, they were asked to rate how vivid the imagery was on a scale of 1 to 5. What the participants did not know was that in the last trial, the researchers slowly raised the intensity of a faint projected image of diagonal lines—tilted either in the direction the participants were told to imagine or in the opposite direction. The researchers then asked the participants if what they saw was real or imagined.

Dijkstra expected that she would find the Perky effect—that when the imagined image matched the projected one, the participants would see the projection as the product of their imagination. Instead, the participants were much more likely to think the image was really there.

Yet there was at least an echo of the Perky effect in those results: Participants who thought the image was there saw it more vividly than the participants who thought it was all their imagination.

In a second experiment, Dijkstra and her team didn’t present an image during the last trial. But the result was the same: The people who rated what they were seeing as more vivid were also more likely to rate it as real.

The observations suggest that imagery in our mind’s eye and real perceived images in the world do get mixed together, Dijkstra said. “When this mixed signal is strong or vivid enough, we think it reflects reality.” It’s likely that there’s some threshold above which visual signals feel real to the brain and below which they feel imagined, she thinks. But there could also be a more gradual continuum.

To learn what’s happening within a brain trying to distinguish reality from imagination, the researchers reanalyzed brain scans from a previous study in which 35 participants vividly imagined and perceived various images, from watering cans to roosters.

In keeping with other studies, they found that the activity patterns in the visual cortex in the two scenarios were very similar. “Vivid imagery is more like perception, but whether faint perception is more like imagery is less clear,” Dijkstra said. There were hints that looking at a faint image could produce a pattern similar to that of imagination, but the differences weren’t significant and need to be examined further.

Scans of brain function show that imagined and perceived images trigger similar patterns of activity, but the signals are weaker for the imagined ones (at left).Courtesy of Nadine Dijkstra/Quanta Magazine

What is clear is that the brain must be able to accurately regulate how strong a mental image is to avoid confusion between fantasy and reality. “The brain has this really careful balancing act that it has to perform,” Naselaris said. “In some sense it is going to interpret mental imagery as literally as it does visual imagery.”

They found that the strength of the signal might be read or regulated in the frontal cortex, which analyzes emotions and memories (among its other duties). But it’s not yet clear what determines the vividness of a mental image or the difference between the strength of the imagery signal and the reality threshold. It could be a neurotransmitter, changes to neuronal connections or something totally different, Naselaris said.

It could even be a different, unidentified subset of neurons that sets the reality threshold and dictates whether a signal should be diverted into a pathway for imagined images or a pathway for genuinely perceived ones—a finding that would tie the first and third hypotheses together neatly, Muckli said.

Even though the findings are different from his own results, which support the first hypothesis, Muckli likes their line of reasoning. It’s an “exciting paper,” he said. It’s an “intriguing conclusion.”

But imagination is a process that involves much more than just looking at a few lines on a noisy background, said Peter Tse, a professor of cognitive neuroscience at Dartmouth College. Imagination, he said, is the capacity to look at what’s in your cupboard and decide what to make for dinner, or (if you’re the Wright brothers) to take a propeller, stick it on a wing and imagine it flying.

The differences between Perky’s findings and Dijkstra’s could be entirely due to differences in their procedures. But they also hint at another possibility: that we could be perceiving the world differently than our ancestors did.

Her study didn’t focus on belief in an image’s reality but was more about the “feeling” of reality, Dijkstra said. The authors speculate that because projected images, video, and other representations of reality are commonplace in the 21st century, our brains may have learned to evaluate reality slightly differently than people did just a century ago.

Even though participants in this experiment “were not expecting to see something, it’s still more expected than if you’re in 1910 and you’ve never seen a projector in your life,” Dijkstra said. The reality threshold today is therefore likely much lower than in the past, so it may take an imagined image that’s much more vivid to pass the threshold and confuse the brain.

A Basis for Hallucinations

The findings open up questions about whether the mechanism could be relevant to a wide range of conditions in which the distinction between imagination and perception dissolves. Dijkstra speculates, for example, that when people start to drift off to sleep and reality begins blending with the dream world, their reality threshold might be dipping. In conditions like schizophrenia, where there is a “general breakdown of reality,” there could be a calibration issue, Dijkstra said.

“In psychosis, it could be either that their imagery is so good that it just hits that threshold, or it could be that their threshold is off,” said Karolina Lempert, an assistant professor of psychology at Adelphi University who was not involved in the study. Some studies have found that in people who hallucinate, there’s a sort of sensory hyperactivity, which suggests that the image signal is increased. But more research is needed to establish the mechanism by which hallucinations emerge, she added. “After all, most people who experience vivid imagery do not hallucinate.”

Nanay thinks it would be interesting to study the reality thresholds of people who have hyperphantasia, an extremely vivid imagination that they often confuse with reality. Similarly, there are situations in which people suffer from very strong imagined experiences that they know are not real, as when hallucinating on drugs or in lucid dreams. In conditions such as post-traumatic stress disorder, people often “start seeing things that they didn’t want to,” and it feels more real than it should, Dijkstra said.

Some of these problems may involve failures in brain mechanisms that normally help make these distinctions. Dijkstra thinks it might be fruitful to look at the reality thresholds of people who have aphantasia, the inability to consciously imagine mental images.

The mechanisms by which the brain distinguishes what’s real from what’s imaginary could also be related to how it distinguishes between real and fake (inauthentic) images. In a world where simulations are getting closer to reality, distinguishing between real and fake images is going to get increasingly challenging, Lempert said. “I think that maybe it’s a more important question than ever.”

Dijkstra and her team are now working to adapt their experiment to work in a brain scanner. “Now that lockdown is over, I want to look at brains again,” she said.

She eventually hopes to figure out if they can manipulate this system to make imagination feel more real. For example, virtual reality and neural implants are now being investigated for medical treatments, such as to help blind people see again. The ability to make experiences feel more or less real, she said, could be really important for such applications.

It’s not outlandish, given that reality is a construct of the brain.

“Underneath our skull, everything is made up,” Muckli said. “We entirely construct the world, in its richness and detail and color and sound and content and excitement. … It is created by our neurons.”

That means one person’s reality is going to be different from another person’s, Dijkstra said: “The line between imagination and reality is just not so solid.”

[art-of-mathematics]

Wei Ho Is Drawn to Algebra, Geometry and the Human Side of Math | Quanta Magazine

https://www.quantamagazine.org/wei-ho-is-drawn-to-algebra-geometry-and-the-human-side-of-math-20221122/

Wei Ho, the first director of the Women and Mathematics program at the Institute for Advanced Study, combines algebra and geometry in her work on an ancient class of curves.

---

Introduction

Like many people who would go on to become mathematicians, Wei Ho grew up competing in math contests. In eighth grade, she won the Mathcounts state competition in Wisconsin, and her team took third place at nationals.

Unlike many future mathematicians, she wasn’t sure she ever wanted to become one.

“I wanted to do everything, all the time,” Ho said. “I took ballet very seriously until early high school. I edited the literary magazine. I did debate and forensics. I played tennis and soccer and piano and violin.” By contrast, many successful mathematicians appeared to be obsessed with math to the exclusion of everything else. How could she, a person with numerous passions, compete with that level of focus?

Ultimately, Ho was drawn to the rigor of mathematics. She still enjoys ballet, reading novels and doing cryptic crossword puzzles, even as she helps to reinvent the mathematical machinery that underpins fundamental mathematical objects, such as polynomial equations, which have long-standing and perplexing open questions associated with them.

Ho studies familiar geometric objects, but she reformulates the questions to situate them in the realm of the rational numbers — numbers that can be written as fractions. “Then number theory starts to get mixed into all of this,” she said.

She is especially interested in elliptic curves, which are defined by a particular kind of polynomial equation that has applications in different branches of mathematics. Elliptic curves appear in analysis — broadly speaking, the study of continuous things, like the real numbers — and in algebra, which is about finding and defining precise mathematical structures. (Though their focus is different, analysis and algebra are divided more by sensibility than by a strict boundary, as there is plenty of overlap between them.)

Introduction

In a barrier-breaking preprint released in 2018, Ho and her collaborator Levent Alpöge of Harvard University discovered a new upper bound for the number of integer solutions to polynomials that define elliptic curves. Their technique draws upon the decades-old work of Louis Mordell, an American mathematician who emigrated to Britain in 1906. In their paper, Ho and Alpöge were able to glean new information about the distribution of these integer solutions that had evaded other teams studying similar problems.

Ho is spending the year (on leave from her faculty position at the University of Michigan) as a visiting professor at the Institute for Advanced Study, where she was recently named the first director of the IAS’s Women and Mathematics program. She is also a 2023 fellow of the American Mathematical Society and a research scholar at Princeton University.

She’s hopeful that directing the Women and Mathematics program will “at least help the community more, help more people, instead of just me being in my office doing math research by myself or with collaborators,” she said. “I can prove theorems, and maybe someday I can prove a theorem that in 100 years will matter. Maybe, maybe not. But I felt like I wasn’t making enough impact on the world or on people around me.”

Quanta spoke with Ho in a series of videoconferences. The interviews have been condensed and edited for clarity.

How would you describe the way you do mathematics?

Sometimes mathematicians divide ourselves into algebraic and analytic people. The math I do touches both sides, but at heart, I am an algebraist, though I’m geometric in the way I think. I often tend to view algebra and geometry as essentially the same.

That’s not quite accurate, but basically since the work of Descartes and especially in the last century, the two subjects have become really close. There is a rather precise dictionary that can, in some situations, help translate a geometric picture to algebraic consequences.

In my own case, the geometric picture often helps formulate statements and conjectures and give intuition, but then we translate them to algebra when writing. It’s easier to detect mistakes as algebra is typically more rigorous. It can also be easier to use algebra when geometry gets too hard to visualize.

[soracities]

i HAVE to ask, as an essay reading enthusiast, WHERE do you find essays to read?

going through the 'essay' tag on your blog was a time well spend

lit magazines babes!!! Lithub, Electric Lit, Guernica, N+1, Devin Kelly's Ordinary Plots, Longreads, Quanta Magazine, Aeon (my beloved!!), The Marginalian (formerly Brain Pickings), Nautilus, Poetry Foundation, Paris Review's redux archives!!! i also tend to look up essays / authors mentioned IN the essays I'm reading which also introduces me to new work! hope this helps and happy essay reading anon 🤍

[kamari2038]

A theory developed by Sanjeev Arora of Princeton University and Anirudh Goyal, a research scientist at Google DeepMind, suggests that the largest of today’s LLMs are not stochastic parrots. The authors argue that as these models get bigger and are trained on more data, they improve on individual language-related abilities and also develop new ones by combining skills in a manner that hints at understanding — combinations that were unlikely to exist in the training data.

As for the theory, it’s true that it makes a few assumptions, Bubeck said, but “these assumptions are not crazy by any means.” He was also impressed by the experiments. “What [the team] proves theoretically, and also confirms empirically, is that there is compositional generalization, meaning [LLMs] are able to put building blocks together that have never been put together,” he said. 

Hinton thinks the work lays to rest the question of whether LLMs are stochastic parrots. “It is the most rigorous method I have seen for showing that GPT-4 is much more than a mere stochastic parrot,” he said. “They demonstrate convincingly that GPT-4 can generate text that combines skills and topics in ways that almost certainly did not occur in the training data.”

[xtruss]

A New Map of the Universe, Painted With Cosmic Neutrinos

Physicists finally know where at least some of these high-energy particles come from, which helps make the neutrinos useful for exploring fundamental physics.

— Thomas Lewton, Contributing Writer | June 29th, 2023

Since 2012, the IceCube Neutrino Observatory at the South Pole has detected a dozen or so cosmic neutrinos each year. Kristina Armitage/Quanta Magazine; images courtesy of IceCube Collaboration

Of the 100 trillion neutrinos that pass through you every second, most come from the sun or Earth’s atmosphere. But a smattering of the particles — those moving much faster than the rest — traveled here from powerful sources farther away. For decades, astrophysicists have sought the origin of these “cosmic” neutrinos. Now, the IceCube Neutrino Observatory has finally collected enough of them to reveal telltale patterns in where they’re coming from.

In a paper published today in Science, the team revealed the first map of the Milky Way in neutrinos. (Usually our galaxy is mapped out with photons, particles of light.) The new map shows a diffuse haze of cosmic neutrinos emanating from throughout the Milky Way, but strangely, no individual sources stand out. “It’s a mystery,” said Francis Halzen, who leads IceCube.

The results follow an IceCube study from last fall, also in Science, that was the first to connect cosmic neutrinos to an individual source. It showed that a large chunk of the cosmic neutrinos detected so far by the observatory have come from the heart of an “active” galaxy called NGC 1068. In the galaxy’s glowing core, matter spirals into a central supermassive black hole, somehow making cosmic neutrinos in the process.

“It’s really gratifying,” said Kate Scholberg, a neutrino physicist at Duke University who wasn’t involved in the research. “They’ve actually identified a galaxy. This is the kind of thing the entire neutrino astronomy community has been trying to do for forever.”

Pinpointing cosmic neutrino sources opens up the possibility of using the particles as a new probe of fundamental physics. Researchers have shown that the neutrinos can be used to open cracks in the reigning Standard Model of particle physics and even test quantum descriptions of gravity.

Yet identifying the origin of at least some cosmic neutrinos is only a first step. Little is known about how the activity around some supermassive black holes generates these particles, and so far the evidence points to multiple processes or circumstances.

Merrill Sherman/Quanta Magazine; images courtesy of IceCube Collaboration

Long-Sought Origin

Abundant as they are, neutrinos usually zip through Earth without leaving a trace; a magnificently huge detector had to be built to detect enough of them to perceive patterns in the directions they arrive from. IceCube, built 12 years ago, consists of kilometer-long strings of detectors bored deep into the Antarctic ice. Each year, IceCube detects a dozen or so cosmic neutrinos with such high energy that they clearly stand out against a haze of atmospheric and solar neutrinos. More sophisticated analyses can tease out additional candidate cosmic neutrinos from the rest of the data.

Astrophysicists know that such energetic neutrinos could only arise when fast-moving atomic nuclei, known as cosmic rays, collide with material somewhere in space. And very few places in the universe have magnetic fields strong enough to whip cosmic rays up to sufficient energies. Gamma-ray bursts, ultrabright flashes of light that occur when some stars go supernova or when neutron stars spiral into each other, were long thought one of the most plausible options. The only real alternative was active galactic nuclei, or AGNs —galaxies whose central supermassive black holes spew out particles and radiation as matter falls in.

The gamma-ray-burst theory lost ground in 2012, when astrophysicists realized that if these bright bursts were responsible, we would expect to see many more cosmic neutrinos than we do. Still, the dispute was far from settled.

Then, in 2016, IceCube began sending out alerts every time they detected a cosmic neutrino, prompting other astronomers to train telescopes in the direction it came from. The following September, they tentatively matched up a cosmic neutrino with an active galaxy called TXS 0506+056, or TXS for short, that was emitting flares of X-rays and gamma rays at the same time. “That certainly sparked a lot of interest,” said Marcos Santander, an IceCube collaborator at the University of Alabama.

More and more cosmic neutrinos were collected, and another patch of sky began to stand out against the background of atmospheric neutrinos. In the middle of this patch is the nearby active galaxy NGC 1068. IceCube’s recent analysis shows that this correlation almost certainly equals causation. As part of the analysis, IceCube scientists recalibrated their telescope and used artificial intelligence to better understand its sensitivity to different patches of sky. They found that there’s less than a 1-in-100,000 chance that the abundance of neutrinos coming from the direction of NGC 1068 is a random fluctuation.

Statistical certainty that TXS is a cosmic neutrino source isn’t far behind, and in September, IceCube recorded a neutrino probably from the vicinity of TXS that hasn’t been analyzed yet.

“We were partially blind; it’s like we’ve turned the focus on,” said Halzen. “The race was between gamma-ray bursts and active galaxies. That race has been decided.”

An illustration of IceCube’s interior during a detection. When a neutrino interacts with molecules in the Antarctic ice, it produces secondary particles that leave a trace of blue light as they travel through the detector. Nicolle R. Fuller/NSF/IceCube

The Physical Mechanism

These two AGNs appear to be the brightest neutrino sources in the sky, yet, puzzlingly, they’re very different. TXS is a type of AGN known as a blazar: It shoots a jet of high-energy radiation directly toward Earth. Yet we see no such jet pointing our way from NGC 1068. This suggests that different mechanisms in the heart of active galaxies could give rise to cosmic neutrinos. “The sources seem to be more diverse,” said Julia Tjus, a theoretical astrophysicist at Ruhr University Bochum in Germany and a member of IceCube.

Halzen suspects there is some material surrounding the active core in NGC 1068 that blocks the emission of gamma rays as neutrinos are produced. But the precise mechanism is anyone’s guess. “We know very little about the cores of active galaxies because they are too complicated,” he said.

The cosmic neutrinos originating in the Milky Way muddle things further. There are no obvious sources of such high-energy particles in our galaxy — in particular, no active galactic nucleus. Our galaxy’s core hasn’t been bustling for millions of years.

Halzen speculates that these neutrinos come from cosmic rays produced in an earlier, active phase of our galaxy. “We always forget that we are looking at one moment in time,” he said. “The accelerators that made these cosmic rays may have made them millions of years ago.”

What stands out in the new image of the sky is the intense brightness of sources like NGC 1068 and TXS. The Milky Way, filled with nearby stars and hot gas, outshines all other galaxies when astronomers look with photons. But when it’s viewed in neutrinos, “the amazing thing is we can barely see our galaxy,” said Halzen. “The sky is dominated by extragalactic sources.”

Setting the Milky Way mystery aside, astrophysicists want to use the farther, brighter sources to study dark matter, quantum gravity and new theories of neutrino behavior.

IceCube has detected dozens of neutrinos coming from NGC 1068, also known as Messier 77 — an active galaxy located 47 million light-years away. The well-studied galaxy, imaged here by the Hubble Space Telescope, is visible with large binoculars. NASA/ESA/A. van der Hoeven

Probing Fundamental Physics

Neutrinos offer rare clues that a more complete theory of particles must supersede the 50-year-old set of equations known as the Standard Model. This model describes elementary particles and forces with near-perfect precision, but it errs when it comes to neutrinos: It predicts that the neutral particles are massless, but they aren’t — not quite.

Physicists discovered in 1998 that neutrinos can shape-shift between their three different types; an electron neutrino emitted by the sun can turn into a muon neutrino by the time it reaches Earth, for example. And in order to shape-shift, neutrinos must have mass — the oscillations only make sense if each neutrino species is a quantum mixture of three different (all very tiny) masses.

Dozens of experiments have allowed particle physicists to gradually build up a picture of the oscillation patterns of various neutrinos — solar, atmospheric, laboratory-made. But cosmic neutrinos originating from AGNs offer a look at the particles’ oscillatory behavior across vastly bigger distances and energies. This makes them “a very sensitive probe to physics that is beyond the Standard Model,” said Carlos Argüelles–Delgado, a neutrino physicist at Harvard University who is also part of the sprawling IceCube collaboration.

Cosmic neutrino sources are so far away that the neutrino oscillations should get blurred out — wherever astrophysicists look, they expect to see a constant fraction of each of the three neutrino types. Any fluctuation in these fractions would indicate that neutrino oscillation models need rethinking.

Another possibility is that cosmic neutrinos interact with dark matter as they travel, as predicted by many dark-sector models. These models propose that the universe’s invisible matter consists of multiple types of nonluminous particles. Interactions with these dark matter particles would scatter neutrinos with specific energies and create a gap in the spectrum of cosmic neutrinos that we see.

Or the quantum structure of space-time itself can drag on the neutrinos, slowing them down. A group based in Italy recently argued in Nature Astronomy that IceCube data shows hints of this happening, but other physicists have been skeptical of these claims.

Effects such as these would be minute, but intergalactic distances could magnify them to detectable levels. “That’s definitely something that’s worth exploring,” said Scholberg.

Already, Argüelles–Delgado and collaborators have used the diffuse background of cosmic neutrinos — rather than specific sources like NGC 1068 — to look for evidence of the quantum structure of space-time. As they reported in Nature Physics in October, they didn’t find anything, but their search was hampered by the difficulty of distinguishing the third variety of neutrino — tau — from an electron neutrino in the IceCube detector. What’s needed is “better particle identification,” said co-author Teppei Katori of King’s College London. Research is underway to disentangle the two types.

Katori says knowing specific locations and mechanisms of cosmic neutrino sources would offer a “big jump” in the sensitivity of these searches for new physics. The exact fraction of each neutrino type depends on the source model, and the most popular models, by chance, predict that equal numbers of the three neutrino species will arrive on Earth. But cosmic neutrinos are still so poorly understood that any observed imbalance in the fractions of the three types could be misinterpreted. The result could be a consequence of quantum gravity, dark matter or a broken neutrino oscillation model — or just the still-blurry physics of cosmic neutrino production. (However, some ratios would be a “smoking gun” signature of new physics, said Argüelles–Delgado.)

Ultimately, we need to detect many more cosmic neutrinos, Katori said. And it looks as though we will. IceCube is being upgraded and expanded to 10 cubic kilometers over the next few years, and in October, a neutrino detector under Lake Baikal in Siberia posted its first observation of cosmic neutrinos from TXS.

And deep in the Mediterranean, dozens of strings of neutrino detectors collectively called KM3NeT are being fastened on the seafloor by a robot submersible to offer a complementary view of the cosmic-neutrino sky. “The pressures are enormous; the sea is very unforgiving,” said Paschal Coyle, a director of research at the Marseille Particle Physics Center and the experiment’s spokesperson. But “we need more telescopes scrutinizing the sky and more shared observations, which is coming now.”