If we compare ΛCDM to most other scientific theories it doesn't look so bad in terms of discrepancies. Certainly there are many unexplained effects in solid state physics, there isn't even an accepted explanation for why rubbing a balloon on your head makes it stick to a wall and that's an experiment you probably did as a child.
You mean dielectric moments and static electricity? Electromagnetism is the one thing we know the most about. It's that spooky gravity junk that makes us scratch our heads. It never seems to behave quite right and doesn't mesh with all the other forces.
You're confusing what with why. My understanding is that everyone knows it has something to do with electrons collecting on the balloon; but nobody quite knows why rubbing rubber against hair causes the electrons to do that.
Yup! It's like understanding the why of weather and people. They are messy and have so many factors you can't account for. It's like saying, why are the clouds shaped like that. You can why your way down, but it's turtles all the way!
When it comes to non-linear junk, the why becomes mixed up because the causes are so numerous. There are so many tiny interactions you can't really say there is one individual cause. Often times you have phenomena that occur at specific energy levels that aren't really caused by any one thing. Even something as simple as a double pendulum is unpredictable.
One thing that is kind of mind blowing is strange attractors. Systems that are so random you cannot predict them even a few moments later can exhibit seemingly ordered patterns. They seem to have a cause, but they are literally just statistical mechanics. A slightly more likely outcome out of un-countable numbers of other outcomes.
First you would need a world-wide cloud layer reflecting insolation back without conversion to IR. As the temperature drops, ice forms. When the clouds dissipate, the ice takes over reflecting sunlight out.
Often the gap between what and why is enormous. Humanity began curing meats to protect against microorganisms around 3000BC. The effect of what was going on was immediately observable, but it wasn't until 4500 years or so later that we discovered the why of microorganisms.
But the accepted explanation is "static electricity", no?
Or do you mean we don't "really" know when asking a couple of follow-up "why?" questions further?
> The triboelectric effect is very unpredictable, and only broad generalizations can be made.
> The mechanisms of triboelectrification (or contact-electrification) have been debated for many years, with possible mechanisms including electron transfer, ion transfer or the material's species transfer.
> Recent studies in 2018 using Kelvin probe microscopy and triboelectric nanogenerators revealed that electron transfer is the dominant mechanism for triboelectrification between solid and solid.
> For a general case, since triboelectrification occurs for any material, a generic model has been proposed by Wang, in which the electron transfer is caused by a strong electron cloud overlap between two atoms for the lowered interatomic potential barrier by shortening the bonding length.
So, still very much misunderstood. There is an experiment showing the dominant mechanism (so still only explaining a part!) between solid-solid and a generic model proposed that can be used to explain other interactions (solid-liquid, liquid-liquid, etc).
Unless there's a tested model with predictable results, I'd say we're not really understanding it properly.
This seems like a very large part, no?
I mean, we know it works, we get the majority of it, and it doesn’t seem super necessary to spend a lot of dollars and brain power to satisfy an internet debate on a theory of rubbing a balloon on one’s head.
I get your point. However, this is worked on by researchers who get paid to work on unsolved problems. This is one of them. It's a surprising one, since it looks like such a simple and obvious effect governed by physics we've (seemingly) understood for centuries. Gauss's Laws are from 1773 and much of the work on static electricity is from that era.
So, it's not just an internet debate. Knowing how things work _exactly_ is what scientists do. Getting the majority is not good enough.
And yes, that will often surpass the scale of "Is what we're doing useful?". However, won't know until we find out. Most likely understanding this effect will not bring any revolutionary insight but we should understand it nonetheless. Maybe our understanding will help someone else solve a problem, that solves another problem, that solved another problem, that gives someone a brilliant idea.
Seeming to demand these problems are resolved is a road to cynicism, in my opinion.
Everyone need one.
Also, we'd have to eliminate the practitioners for clearly being witches. We've had that period and history, but it seems some modern day people are content to bring that very time period back.
[1] https://www.lesswrong.com/posts/L22jhyY9ocXQNLqyE/science-as...
[2] https://www.lesswrong.com/posts/NMoLJuDJEms7Ku9XS/guessing-t...
And from the alt-text:
"Friction-driven static electrification is familiar and fundamental in daily life, industry, and technology, but its basics have long been unknown and have continually perplexed scientists from ancient Greece to the high-tech era. [...] To date, no single theory can satisfactorily explain this mysterious but fundamental phenomenon." --Eui-Cheol Shin et. al. (2022)
"Of these four forces, there's one we don't really understand." "Is it the weak force or the strong--" "It's gravity."
Wait for it… Why ice is slippery?
Usual explanation is completely incorrect. Actual semi-conclusive research just recently happened.
That would be my reasoning, but it likely seems to be wrong, well why?
That said, as anyone who has been in icy conditions can attest, it is clear that ice at ~0° C is vastly more slippery than at, say, -20°C.
Maybe the same happens with ice and water.
There is nothing more slippery in my experience, than rain on the street, that just turned frozen. But ice at -20°C is usually older and has not such a smooth surface anymore, so hard to compare in non lab settings.
You mean, its slipperiness?
Spoiler: According to this research, ice is slippery because of a thin layer of water. (As we expected, no?) But the water layer is 1) thinner than expected, 2) more viscous than expected, and 3) contains bits of ice which help make it extra slippery.
> "Usual explanation is completely incorrect."
Only for an unusual definition of "completely" IMO. Again, IANAP.
[1] https://phys.org/news/2019-11-ice-slippery.html
[2] https://journals.aps.org/prx/abstract/10.1103/PhysRevX.9.041...
I can imagine ice on an iceskate wanting to be solid, but because that takes up too much space it becomes a liquid instead.
Wait, why would bits of ice make it extra slippery if it's the water that makes ice slippery?
Agreed. While the "usual explanation" may lack the details that actual testing provided, deduction and logic in this case were pretty much harmonious with the findings. The water layer being thinner or more viscous than expected doesn't invalidate the basic assumption, and that's where all science starts, right? Some basic, yet to be disproved* assumption.
Biologists are almost unique among scientists in being happy to say how little they still know about their subject. Up until last year nobody had thought to see whether anything eats viruses! Turns out some do.
Citation needed.
> Up until last year nobody had thought to see whether anything eats viruses! Turns out some do.
Nah, lots of things eat viruses. It's nothing unusual at all. You eat viruses, I eat viruses. They are everywhere, after all.
The novel finding was a critter that lives / can live solely on viruses.
> Nah, lots of things eat viruses. It's nothing unusual at all. You
> eat viruses, I eat viruses. They are everywhere, after all.
>Moreover, our foraging trials demonstrated robust growth in the Halteria population with only chloroviruses as food (rint = 0.66 ± 0.26 [SD], black lines, Fig. 1A), with minimal to no growth in the controls (with chloroviruses filtered out; rint = 0.22 ± 0.12 [SD], blue lines, Fig. 1C). The abundance of the larger Paramecium did not increase in treatment or control trials (Fig. 1D), indicating that not all ciliates can grow on chloroviruses in these conditions, even when they consume them.
>> Up until last year nobody had thought to see whether anything eats viruses! Turns out some do.
> Nah, lots of things eat viruses. It's nothing unusual at all. You eat viruses, I eat viruses. They are everywhere, after all.
> The novel finding was a critter that lives / can live solely on viruses.
Eg creatures that eat plastic are still news, even if plastic is not their sole diet.
How could you possible find a citation for that? It’s not even pretending to be a scientific or totally objective claim. Asking for a citation for this type of statement is no way to have a discussion. Do you not see why?
Most any scientist will happily babble all about the stuff they don't know yet in their discipline, because that's exactly where the excitement lies for them.
Much of Wikipedia is "curated" by retired professors carefully scrubbing mention of anything new that makes their thesis look wrong.
What makes you think so? What evidence do you have?
The point should be to learn and appreciate the method or process of scientific investigation of uncertain and mysterious or hard to understand phenomena.
Instead we get dogma as a proxy of measuring intelligence with little regard for what the fundamental tools are of being a scientist.
I’ve gone all the way through to Grad School and came out astounded at just how little commitment to or a sense of the essence of scientific investigation and what’s expected of the investigator there is in the system. They don’t prepare you for it because they themselves weren’t prepared. You can try to leverage some meta understanding of the “process” in conversation or debate, but so often the conversation falls flat because few are prepared or accustomed to it. Research is often done, IMO, in philosophical poverty by people eking out a living in the gutters of novelty and paradigmatic safety, averting their gazes from the sky (flourishes aside, you get my point).
Putting aside the health of actual research. If the general public is to benefit from education and pass that benefit into their society (that’s the point right), it needs to be more than soon to be forgotten and often useless fallacies.
> If the general public is to benefit from education and pass that benefit into their society (that’s the point right), it needs to be more than soon to be forgotten and often useless fallacies.
I realize this is hyperbole, but still I think it's obvious that there is more than soon to be forgotten and often useless fallacies.
I do generally agree though that current models/paradigms are usually presented more as "the final word" vs "a useful mental model".
Esp. when paradigms are challenged by, or conflict with untestable traditional explanations, ppl tend to get irritated and overstate the confidence of their own understanding
Nonetheless, while I agree with your pushback, I do wonder how much utility there is in the “dogma” approach. There’s a lot of “facts” being thrown around in education, from what I’ve seen, that are often forgotten or become vague memories. How much better would it be to focus on skills and practice and concepts? Especially in the digital age where a fact is easily discoverable, provided one has the appropriate research skills.
Beware; deep rabbit hole. [1]https://plato.stanford.edu/entries/qm-manyworlds/#:~:text=Th....
Astrophysicists, as a rule, hate to be obliged to consider phenomena that involve plasma fluid dynamics, even what can be shoehorned into MHD. Such phenomena are thus orphaned. The exception, of course, is solar physics, where nothing can be done at all without fully general plasma fluid dynamics. Solar physicists have the largest gonads in science, on par with rocket propellant chemists.
Are there other phenomena they see but don't like to talk about? Maybe?
"Effects which are essentially kinetic and not captured by fluid models include double layers, Landau damping, a wide range of instabilities, chemical separation in space plasmas and electron runaway."
That electrons are 1836 times less massive than the lightest positive charge carrier is neglected. Accelerated, they strike positive and neutral particles and knock loose more electrons.
Can you provide a reference, please?
https://en.wikipedia.org/wiki/Mpemba_effect
> the actual occurrence of the Mpemba effect is a matter of controversy
> In 2016, Burridge and Linden defined the criterion as the time to reach 0 °C (32 °F; 273 K), carried out experiments, and reviewed published work to date. They noted that the large difference originally claimed had not been replicated, and that studies showing a small effect could be influenced by variations in the positioning of thermometers: "We conclude, somewhat sadly, that there is no evidence to support meaningful observations of the Mpemba effect."
> In controlled experiments the effect can entirely be explained by undercooling [water may cool below the freezing point without actually solidifying] and the time of freezing was determined by what container was used.
Looks like there is plenty of opportunity for newly minted physicists to make their names and careers!
Lambda-CDM Model [0], for the ones like me who haven't heard it before.
The number of question marks piling up in cosmology does feel similar. It will help to shape new theories that reconcile all this experimental evidence.
Funnily enough, that's what the science community of the ending 19. century thought about physics, before they started to look deeper.
Max Planck was advised against a career in physics, because:
"In this field, almost everything is already discovered, and all that remains is to fill a few holes."
He rather found some more holes.
People dunk on cosmology because cosmologists have consistently, over decades, insisted, in public, that they knew more than they did, and are continually obliged to abandon what they insisted they knew. If they were more forthright about how much they don't know, they would get less criticism. They have much to learn from the biologists, who know they know practically nothing (even though massively more than you), and are happy to say so.
The health of a branch of science may be read from how eager its researchers are for you to know about what they have no clue about.
Exactly, and each time the theories are proven wrong, it's explained as a never-ending series of "oddities", yet the theories are never altered in any meaningful way other than ad-hoc additions to explain each "oddity".
At some point there needs to be a reckoning that, for instance, the current theories of star formation are essentially completely wrong.
So the solution? There was some very specific period of acceleration, faster than light acceleration to some very specific degree, at some specific point right after the big bang which then ended at some other very specific point, at which point everything returns back to normal. What's the logic for it? Well if we do this, then what we see matches what we expect to see. It's an absolute retrofitting of numbers to make a model fit reality. And not only does that constitute good science in cosmology, it was sufficient to win a Nobel Prize.
It is literally unexplained magic being taken as a fundamental concept of science. And the worst part of it all is that it's completely unfalsifiable. We only have one universe to observe. So if it turns out that the discrepancy is actually being caused by many smaller effects we stand near 0 chance of ever discovering because each one of those small effects will have a million flaws, while the perfectly retrofitted inflation theory has "none." At worst they'll even get absorbed into the inflation theory model magic. Just add more epicycles!
That's just called science. What else do you propose? Give up because you didn't get it right the first time?
I think there are several other scientific areas where we know less than we ought.
1. The sub-atomic level
2. The cellular level
3. Ocean biology
4. Geology, particularly effects of earthquakes and volcanic activity
5. Weather patterns over time
Forest fires were probably in the model, but they seem to be intensifying due to (mis)management and droughts. The Amazon rainforest probably has a significant impact on weather and weather models, but under Bolsenaro a lot of it was cut down and burned. And it goes on.
Global Warming is happening, that is not just a realm of modelling but is directly observable today. The models on a broad scale look to be working very well, specific locations and reactions not so much.
It is possible to make broad engines that work but also get the finer details wrong. Signal : Noise ratio and all of that.
Precise predictions are hard, but the general direction of travel cannot be seriously disputed without arguing against the above simple facts.
Btw, CO2 does 'magically' disappear. Into the oceans. Alas, from what I've read it'll take about 2,000 years to do so.
> [...], but the general direction of travel cannot be seriously disputed without arguing against the above simple facts.
I don't want to argue against global warming, but I want to argue that can't argue against global warming without arguing against your 'simple facts'.
Your 'simple fact' about CO2 could be true, but global warming could still be a myth. (I don't think it is; but your argument is far from sufficient. It's a complex system. Eg from time to time volcanic eruptions produce a lot of CO2, but they are typically associated with a cooling of the climate, because of other factors.
Similarly, burning coal releases a lot of CO2, but it also used to release a lot of SO2. Locally, SO2 is pretty bad (ever heard of acid rain?), but SO2 converts to sulfuric acid aerosols that can block solar radiation. These days most coal fired power plants have measure to avoid spewing so much SO2.
It's conceivable someone could find a coal so 'dirty' with sulphur, that burning it would decrease temperatures. I don't think it's very likely, but it's conceivable. So you need more empirical observations, than just your simple facts to make your argument.)
There are lots more effects. When lots of volcanoes erupt, we also see more CO2, but we see the climate cool down.
That's because the effect of the CO2 is outweighed by other factors. But exactly that there are lots of factors is my point.
To add, the predictions re: global warming seem to have been too optimistic, and they were already gloom and doomsaying enough decades ago. I scoffed when I read a headline saying something about a specific glacier being gone in 100 years - I'm sure it'll be much sooner than that.
Could we train a GPT3 like model with the entire corpus of astronomical research and try to answer some questions that way?
ChatGPT-4: How many roads must a man walk down?
GPT3 can regurgitate, and, in my opinion, even use knowledge, but I don't think it can synthesize knowledge.
But what it definitely cannot do is seek new abstractions. It can't be curious about an inconsistency and probe its own knowledge for possible resolutions, or design an experiment that might shed further light in an unknown area. It can't even play a board game after ingesting the rules to it, much less identify contradictions or problems in such a ruleset. And a board game is a tiny microcosm compared with the laws of physics.
It's conceivable that one or more scientists could work in conjunction with an AI to help augment their own abilities, co-pilot style, but I don't think we have a picture yet of what exactly that kind of thing would look like.
Thinking of mathematics, an abstraction is only as valuable as what it can tell us about the underlying system— a laplace transformation into the frequency domain isn't particularly interesting unless we either a) happen to care about some frequency domain property of the function, or b) we can manipulate the transformed function and then un-transform it afterward, yielding a novel insight in the original time domain.
My layman's assessment is that the current state of the art for machine cognition is about on the level of identifying that such a transformation might be possible, but not actually applying it or doing anything about it, much less unapplying it afterward.
Maybe we disagree about whether that last point means it can meaningfully “do abstraction” or not.
But the beauty of science (and the human mind driving it) that important progress happens with creative jumps that invent completely new things (e.g., new mathematics) and frequently bear little resemblance to the past
Things like, what happens if I shoot two bullet at c/2 in opposite directions on a train going at c/2? Now suppose, I'm an outside observer. And then trying to introduce quantum gravity.
My thought was that perhaps it could 'reason through'. Unfortunately, it was unable to. Eventually, it said that this is an unsolved problem. In other words, it 'recognized' the thought experiments. Perhaps if you use a phrasing that's not in the literature.
EDIT: Actually, just checked again, and chatgpt can't reason through relativity anymore:
Me: Imagine I'm on a train traveling at half the speed of light. I'm in the middle of a car and I fire bullets going at half the speed of light towards the front and back of the car. Do the bullets arrive at the front and back of the car at the same time?
ChatGPT: No, the bullet fired towards the front of the car will arrive at the front of the car first, while the bullet fired towards the back of the car will arrive at the back of the car later. This is because the front bullet is moving in the same direction as the train and the back bullet is moving in the opposite direction of the train. The relative velocity of the bullet and train will determine the time it takes for the bullet to reach the front or back of the car.
There's a depth to explaining things that GPT still can't do. It's still astonishing, and has completely changed my idea on what AI can do, like write plays with very incredible context (better than most humans!) but there are still major limits.
The hell are you talking about? I've been doing this literally any time I need something fixed and it does just fine.
From the external point of view, the goalposts moved, but from within the GP's poorly expressed mental model, they haven't moved. But, that's just a guess.
That said, I can imagine a chatbot can help as a rubber duck, bring up things that weren't considered yet, or be so wrong as to kickstart the human into a breakthrough.
[1] Or whatever circumlocution you prefer to express the same general concept.
Only when things are working properly and there isn't too much cosmic radiation, interference, strange patterns accessing memory, someone turning on a light…
On a very broad level (and I'll get loads of people disagreeing with this, because both mathematics and computer science divide further into different specialities), mathematics is primarily about proving logical truths, whereas computer science is about managing complexity. That's a massive cognitive difference, even if many of the problems the two fields tackle are the same.
What I find so fascinating is that the observations are still quite precise. How do you know the outer rims are rotating too fast? Couldn't this be some gravitational lensing and stars are actually much closer to the core than they appear?
How do you even begin to estimate the mass of a galaxy? How do you weight the behavior of a disc and combine it with keplers law to even see that something is wrong here? As a layman I would be perfectly happy with how galaxy are rotating... I find it fascinating that much is so precisely determined that we have to miss something.
Depending what generation tech we're running on in the parent reality, JWST may be causing a noticeable jump in system load.
Plus cosmology has the problem that you can't really conduct reproducible experiments.
If you have the resources to spare, you can do much better than replicating James Webb style telescopes. See eg https://en.wikipedia.org/wiki/Solar_gravitational_lens
I'm reading the whole JWST project is estimated to cost $10 billion. That's about 4.4 overpriced Twitters, 77 US Department of Defense budgets (just for 2023), and 11.7 Facebook annual revenues.
We have the technology and the means, what's lacking now is the will.
F R A C T A L H A T C H E R Y
It the pattern of previous science revolutions repeats, there could come a point where reinterpreting the large existing body of knowledge using a different paradigm would explain an number of "oddities" in a more economical way.
I don't know if this generation of telescopes will get us there but it feels that this is a plausible outcome over the next 1-2 decades. Which would be very exciting :-)