Without imputing any actual intention to the author, I agree with your points on tone. It feels focused on optics, not outcomes.
It's one thing to say that you want to get things done. It's another to say you want to be _seen_ as someone who gets things done.
Again, I don't intend to mind read here, and I think the author actually has some really good data gathering ideas. But the language definitely smacks of political motivation, which some folks (myself included) find off-putting.
hey hn, I'm the lead engineer on this project. This was a super fun feature to build, and was incredibly challenging at a technical level.
Lots of fun stuff to figure out, from wrangling structured data, working around limited context sizes, and figuring out how to even write down sensible metrics to determine how well the models are doing.
> Until now no neutrino produced at a particle collider has ever been directly detected. Colliders
copiously produce both neutrinos and anti-neutrinos of all flavors, and they do so in a range of
very high energies where neutrino interactions have not yet been observed. Nevertheless, collider
neutrinos have escaped detection, because they interact extremely weakly, and the highest energy
neutrinos, which have the largest probability of interacting, are predominantly produced in the
forward region, parallel to the beam line. In 2021, the FASER collaboration identified the
first collider neutrino candidates 13 using a 29 kg pilot detector, highlighting the potential of
discovering collider neutrinos in LHC collisions.
> Until now no neutrino produced at a particle collider has ever been directly detected.
Is this considered different from e.g. the OPERA experiment because in that they dump the proton beam from the SPS into a target? So what you're observing here are neutrinos from the actual beam crossing? And is this interesting because you could conceivably start to correlate the actual collision that creates the neutrino with its eventual detection?
What collides here exactly? I always thought collider do throw a particule A in the direction of particule B while B travels in the direction of A, with measure instruments all around but not blocking one of the particule path. The photographie 0 make me wonder if they also crash particules directly into their instruments?
Well, you sort of have to have the particle collide with something in order to detect it. When a photon collides with your retina, you see a flash of light (it causes a protein to twist, which generates an electrical signal, which is sent to your brain). The problem is the neutrinos tend to pass right through without getting absorbed by anything. No absorption, no change, no detection.
So the neutrino has to collide with something to get detected. Given that previous neutrino detections require a large vat of heavy water underground, while the current results are from a little box, the salient question is what did they do differently (and is it applicable elsewhere). The article completely ignores this.
The experiment is described in this[1] article. Relevant quote:
The detector is positioned on the beam collision axis line-of-sight (LOS) 480 m from the ATLAS collision point (interaction point 1, IP1) in an unused service tunnel, TI12. [...] A huge number of neutrinos are produced in LHC collisions via hadron decays, and their flux is collimated along the beam collision axis.
So what they did differently is to place the detector in a spot which has much higher neutrino flux than your average spot on earth. Thus the small detector volume is compensated for by having more neutrinos pass through it in a given time.
Neutrinos pass through the entire planet from space, so hopefully they will be able to see the background neutrinos as well as the neutrinos from their collisions.
If this was a brimstone and fire depiction for those with a religion vent, neutrinos would be likened to ash, the other particles would be various sizes of burning embers, some large but glowing gently (beta), others small and burning brightly (alpha).
Its all contained in a giant underground magnetic donut that would have Homer Simpson salivating which accelerates the particles, like a rail gun or steam catapult on an navy aircraft carrier or a catapult launcher for roller coasters, and it keeps accelerating these particles, like a child with ADHD on sodium benzoate can accelerate a fidget spinner, until the particles collide, like the crescendo of a fantastic firework display at a country's official New Years eve display watched through computer screens that's somewhat reminiscent of the 1979 Atari Inc Asteroids computer game when an asteroid explodes.
The electrical demand for the magnets is great but short term like the Death Star blowing up Alderaan, so whilst its CO2 footprint could be likened to a large Cruise Liner over the year, it generates this footprint over extremely small periods of time when running these experiments like something out of Weird Science when Kelly LeBrock comes to life!
So the electrical infrastructure is highly capable.
The electrical companies need advance knowledge to make sure they have ordered in enough coal and gas, and topped up the hydroelectric dams, when they run their experiments, otherwise the neighbourhood experiences something of blackout like in the movie Batteries Not Included.
I haven't read the full article yet but the abstract has some hints: I think what they're doing is leveraging the fact that they know where and when the neutrinos were created to narrow down the search in the actual neutrino detector itself.
Because they can see the associated muon, they know when to look for a correlated neutrino signal.
Between that and the extremely hot source, they can get away with a relatively small active detector volume.
Again that's just based on my reading of the abstract, I need to see the full article to validate that guess.
hey, I'm the lead engineer on this project! I love that you did this :)
our experience thus far is that GPT4 definitely needs help when it comes to datasheet-like data. it's great at broad "functional" strokes, but details and particularly numerical details are not its forte.
I think the real solution is to manually convert component datasheets to spice models (I think there are already commercial databases of these), simulate the circuit, and then get a language model like GPT-4 propose changes to the circuit to make it perform better.
The real question becomes how to interface the spice model and the language model - do you for example let it connect a virtual oscilloscope to any node, and give the language model the results back as plain numbers?
It's one thing to say that you want to get things done. It's another to say you want to be _seen_ as someone who gets things done.
Again, I don't intend to mind read here, and I think the author actually has some really good data gathering ideas. But the language definitely smacks of political motivation, which some folks (myself included) find off-putting.