4 ms·

As a complete physics layperson, I can’t comment with any authority on the subject matter. What I do have is a metric fuckton of experience with incentives and

As a complete physics layperson, I can’t comment with any authority on the subject matter. What I do have is a metric fuckton of experience with incentives and mechanism design in technical fields: and mainstream physicists have been talking like people who have bonuses linked to specific outcomes for decades. The moving goalposts around falsifiability, the too-coincidental synergies between supersymmetric-style (and there for string world) stuff and missing mass (dark matter), the growing group of highly-qualified skeptics, the curt public dismissals everything from LQG to constructor stuff to MOND as beneath refutation, the popularizers who go on PBS and don’t even acknowledge a debate. And the alternative explanation, that it takes so long to learn this stuff that your career is over if Dark Matter or String Theory turns out to be hokum? Yeah, that scans.

jollybean 4y ago
This is very cynical but there's some truth to it. I also believe that it's less conscious. Once people accept an idea they're conditioned to think of it as true, and then when jobs and institutions revolved around that it amplifies aberrations. Maybe String Theory is total bupkiss, a lot of people are going to have a hard time with it. But with this subject we're at least working with observable data ...
- cryptonector 4y ago
  Network effects can yield delusion and fraud without the participants consciously trying for it.
ncmncm 4y ago
Not so different from Alzheimer's researchers continuing to give one another federal grants for ways to block production of amyloids decades after it has been shown to be a dead end. One wonders what all those amyloid biochemists can do with themselves once amyloid grants finally go away.
irjustin 4y ago
To me, this is the cost of discovery. Just like a game of chess, you have to spend a lot of energy/cost thinking about lines that will not come to fruition to find the correct path. Poor Alzheimer's research was/is stunted for a few people at the top pushing the wrong path. We'll see if that's the case for DM vs MOND vs something else. Money will always be distributed to the wrong areas, but as long as you believe the human race to exist far into the future, it will eventually work itself out.
find 4y ago
I'm an astrophysicist. I love the idea of shaking up how we do science, but MOND models really aren't that compelling for a practicing scientist (I would love to be wrong). I periodically consider working a modified gravity project, but it never seems that interesting. Maybe I can lay out my personal impressions for you in a software analogy. There are simple situations where physics can be reasonably distinguished from the noise. Think Newton watching an apple fall from a tree -- these are test harnesses with a debugger and careful control of the environment. There are also astrophysical situations where it's very hard to squeeze insight out of the chaos. Instead of looking at an apple to derive Newtonian gravity, imagine instead trying to figure gravity out by looking at a flock of birds. There are tricky things in the way of our understanding, like lift, turbulence, and biomechanics. We hope to understand the bad situations someday, but right now it's tough. Instead of the nice test harness, these situations are like debugging through cryptic, un-reproducible user complaints. What's their OS? Do they have the right drivers installed? Do they have all of their ports blocked for some reason? In astrophysics, one nice system is the Universe at very large scales: echos of the big bang, the clustering of matter, and the formation of structure. We have great data these days about the large scales, and general relativity (GR) + dark matter (DM) is a very predictive model here. To our chagrin, the data always matches the theory. It takes 5 or 6 parameters, but the model has withstood huge improvements in data quality without really changing since the 90s. The other nice situation is the small scales like our own solar system: we can measure things extremely precisely at home, and again GR works remarkably well. There are a few other good situations involving objects like pulsars. Finally there are the hard situations: intermediate scales that involve the messy physics of star and galaxy formation. We don't really know how these processes work, but we can cobble together simple models with DM that sort of match the data. Modified gravities in the literature always seem to act exactly like general relativity + dark matter in the clean, understandable situations, although it takes various contortions (screening) for these models to do this. Modified gravity models seem to only act differently in the bad arenas that are hard to understand, when there trickier issues like galaxy and star formation. That's deeply suspicious, and really weakens the value proposition of these alternatives. It's like introducing a software feature to fix something that never happens on the dev machine, based on mysterious user reports that you can only half decipher.
- 4y ago

jollybean 4y ago

This is very cynical but there's some truth to it. I also believe that it's less conscious. Once people accept an idea they're conditioned to think of it as true, and then when jobs and institutions revolved around that it amplifies aberrations. Maybe String Theory is total bupkiss, a lot of people are going to have a hard time with it. But with this subject we're at least working with observable data ...

cryptonector 4y ago
Network effects can yield delusion and fraud without the participants consciously trying for it.

ncmncm 4y ago

Not so different from Alzheimer's researchers continuing to give one another federal grants for ways to block production of amyloids decades after it has been shown to be a dead end. One wonders what all those amyloid biochemists can do with themselves once amyloid grants finally go away.

irjustin 4y ago

To me, this is the cost of discovery. Just like a game of chess, you have to spend a lot of energy/cost thinking about lines that will not come to fruition to find the correct path. Poor Alzheimer's research was/is stunted for a few people at the top pushing the wrong path. We'll see if that's the case for DM vs MOND vs something else. Money will always be distributed to the wrong areas, but as long as you believe the human race to exist far into the future, it will eventually work itself out.

find 4y ago

I'm an astrophysicist. I love the idea of shaking up how we do science, but MOND models really aren't that compelling for a practicing scientist (I would love to be wrong). I periodically consider working a modified gravity project, but it never seems that interesting. Maybe I can lay out my personal impressions for you in a software analogy. There are simple situations where physics can be reasonably distinguished from the noise. Think Newton watching an apple fall from a tree -- these are test harnesses with a debugger and careful control of the environment. There are also astrophysical situations where it's very hard to squeeze insight out of the chaos. Instead of looking at an apple to derive Newtonian gravity, imagine instead trying to figure gravity out by looking at a flock of birds. There are tricky things in the way of our understanding, like lift, turbulence, and biomechanics. We hope to understand the bad situations someday, but right now it's tough. Instead of the nice test harness, these situations are like debugging through cryptic, un-reproducible user complaints. What's their OS? Do they have the right drivers installed? Do they have all of their ports blocked for some reason? In astrophysics, one nice system is the Universe at very large scales: echos of the big bang, the clustering of matter, and the formation of structure. We have great data these days about the large scales, and general relativity (GR) + dark matter (DM) is a very predictive model here. To our chagrin, the data always matches the theory. It takes 5 or 6 parameters, but the model has withstood huge improvements in data quality without really changing since the 90s. The other nice situation is the small scales like our own solar system: we can measure things extremely precisely at home, and again GR works remarkably well. There are a few other good situations involving objects like pulsars. Finally there are the hard situations: intermediate scales that involve the messy physics of star and galaxy formation. We don't really know how these processes work, but we can cobble together simple models with DM that sort of match the data. Modified gravities in the literature always seem to act exactly like general relativity + dark matter in the clean, understandable situations, although it takes various contortions (screening) for these models to do this. Modified gravity models seem to only act differently in the bad arenas that are hard to understand, when there trickier issues like galaxy and star formation. That's deeply suspicious, and really weakens the value proposition of these alternatives. It's like introducing a software feature to fix something that never happens on the dev machine, based on mysterious user reports that you can only half decipher.

4y ago