> “This isn’t just a new value of the Hubble constant,” the collaboration notes, “it’s a community-built framework that brings decades of independent distance measurements together, transparently and accessibly.”
Don't love that I can't read sentences like this without wondering if an LLM was involved.
Yeah it's sort of an LLM smell but honestly the models learned that pattern because it's common in the training data. People write that way because it sounds like they're revealing something profound.
LLM inference does not just regurgitate the training corpus; RLHF is almost certainly to blame for this. There’s probably some Google n-gram graph to prove it.
Nobody seriously doubts the "tension" anymore. The analysis is good.
The question is are there systemic errors. Chief among them is whether our ability to infer the distance to objects billions of light years away is truly as good as we think it is.
According to the article “This work effectively rules out explanations of the Hubble tension that rely on a single overlooked error in local distance measurements". So any systemic errors would need to affect multiple measurement types.
We don't just use one single method to infer distances. TA is about that there are multiple methods, and that the framework is open for new ones. What is more likely at fault is the underlying model of how the cosmos developed, which is highly likely to be incomplete or misguided.
Actually is quite the opposite. If the difference in expansion between the early and late universe is real than the reigning cosmological model lambda-CDM will at least have to be revised, or be replaced with a model that made that prediction (there are several of them)
> “This isn’t just a new value of the Hubble constant,” the collaboration notes, “it’s a community-built framework that brings decades of independent distance measurements together, transparently and accessibly.”
Don't love that I can't read sentences like this without wondering if an LLM was involved.
Yeah it's sort of an LLM smell but honestly the models learned that pattern because it's common in the training data. People write that way because it sounds like they're revealing something profound.
LLM inference does not just regurgitate the training corpus; RLHF is almost certainly to blame for this. There’s probably some Google n-gram graph to prove it.
Nobody seriously doubts the "tension" anymore. The analysis is good.
The question is are there systemic errors. Chief among them is whether our ability to infer the distance to objects billions of light years away is truly as good as we think it is.
According to the article “This work effectively rules out explanations of the Hubble tension that rely on a single overlooked error in local distance measurements". So any systemic errors would need to affect multiple measurement types.
Definitely a good first step if their research holds up. Given the huge implications thou, it is unlikely to sway opinions much.
Extraordinary claims require extraordinary evidence
We don't just use one single method to infer distances. TA is about that there are multiple methods, and that the framework is open for new ones. What is more likely at fault is the underlying model of how the cosmos developed, which is highly likely to be incomplete or misguided.
Actually is quite the opposite. If the difference in expansion between the early and late universe is real than the reigning cosmological model lambda-CDM will at least have to be revised, or be replaced with a model that made that prediction (there are several of them)
That stuck out at me too, along with the em-dashes above.
English version: https://noirlab.edu/public/news/noirlab2611/?nocache=true&
Went to Spanish.
If I click EN it goes here:
https://noirlab.edu/public/news/noirlab2611/?nocache=true&la...
That explains why the original link is broken, the language selector on the whole site must be broken!