How many photons are received per bit transmitted from Voyager 1? • Hacker News Board

Re: How many photons are received per bit transmitted from Voyager 1?

#201

Post by jessriedel » Thu, Jun 06, 2024, 4:11 AM UTC

empyrrhicist wrote: post #200

jessriedel wrote: post #199

Earlier quoted context omitted.

You said > in general we just can't [describe a system in the limiting regime using the fundamental theory] without hand-waving, period...It's sort of true, but not in a useful way. And I am saying that it in fact can be done, and has been done, in physics and math in a very non-hand-waving way. One can show rigorously when a certain abstractions is accurate.

Well... sure, but I think you're still almost purposely missing the point. Take this example - can we prove that a system of differential equations emerges in a meaningful way from discrete systems? Yes, obviously. That's a far cry from the OP's "if you think about it, all things are quantum", which is where this thread started and what I'm talking about. It also illustrates the actual point pretty well - when you ha…

If you think that fact that levels of abstraction give insight is a rebuttal to the OP, you don't under what he's doing. Understanding how the fundamental theory reduces to the abstraction (1) allows you to precisely know the limits of the abstraction and (2) allows you to port knowledge you have about one side to the other.

Like, this comment of your is a great example of the sort of confusion that arises when you don't understand the non-relativistic limit:

> Lol, so you've got a working theory to bridge the quantum and classical worlds? That is, you've figured out how to make general relativity and quantum mechanics emerge from a more fundamental theory?

https://news.ycombinator.com/item?id=40574789

Re: How many photons are received per bit transmitted from Voyager 1?

#202

Post by kragen » Thu, Jun 06, 2024, 9:59 AM UTC

sunk1st wrote: post #127

nico wrote: post #76

Earlier quoted context omitted.

Maybe I’m mixing Shannon’s limit with the sampling rate imposed by the Nyquist-Shannon Sampling theorem > Around 2004, Emmanuel Candès, Justin Romberg, Terence Tao, and David Donoho proved that given knowledge about a signal's sparsity, the signal may be reconstructed with even fewer samples than the sampling theorem requires.[4][5] This idea is the basis of compressed sensing … > However, if further restrictions are…

In so many words, Shannon gave a proof showing that in general the sample rate of a digital sensor puts an upper bound on the frequency of any signal that sensor is able to detect. Unlike the Nyquist-Shannon theory, compressed sensing is not generally applicable: it requires a sparse signal. As with many other optimization techniques, it’s a trade off between soundness and completeness.

that is not correct. digital sensors detect frequencies above the nyquist limit all the time, which is why they need an analog antialiasing filter in front of them. what they can't do is distinguish them from baseband aliases

you could just as correctly say 'nyquist-shannon theory is not generally applicable; it requires a bandlimited signal' (which is why compressed sensing doesn't violate it)

Re: How many photons are received per bit transmitted from Voyager 1?

#203

Post by nico » Fri, Jun 07, 2024, 5:06 AM UTC

kragen wrote: post #202

sunk1st wrote: post #127

Earlier quoted context omitted.

In so many words, Shannon gave a proof showing that in general the sample rate of a digital sensor puts an upper bound on the frequency of any signal that sensor is able to detect. Unlike the Nyquist-Shannon theory, compressed sensing is not generally applicable: it requires a sparse signal. As with many other optimization techniques, it’s a trade off between soundness and completeness.

that is not correct. digital sensors detect frequencies above the nyquist limit all the time, which is why they need an analog antialiasing filter in front of them. what they can't do is distinguish them from baseband aliases you could just as correctly say 'nyquist-shannon theory is not generally applicable; it requires a bandlimited signal' (which is why compressed sensing doesn't violate it)

Thank you for the clarification, great point about the importance of distinguishing the acts of "detecting" and "making sense of" some signal/data/information

Re: How many photons are received per bit transmitted from Voyager 1?

#204

Post by stracer » Fri, Jun 07, 2024, 5:10 PM UTC

resters wrote: post #111

ganzuul wrote: post #108

Earlier quoted context omitted.

In addition to wavelength EM also has several polarization modes and near/far field characteristics that can carry information.

Can individual photons be measured for polarization and phase or is there a similar limit that requires more than one photon to do so? I suppose both are relative to some previous polarization or phase?

Polarization can be measured using polarization filter and light detector, but it is destructive in the usual sense of quantum theory. That is, if the detector after polarization filter clicks, we know the EM field had non-zero component in the direction of the filter, but we do not find out the other components it had before entering the filter.

Re: How many photons are received per bit transmitted from Voyager 1?

#205

Post by akdom » Sat, Jun 08, 2024, 3:02 PM UTC

imoverclocked wrote: post #185

eru wrote: post #172

Earlier quoted context omitted.

Going off on a bit of a tangent: Some people suggest that digital computing and neural networks are a bit fit, and that would should be using analog devices. That sounds very appealing at first. But we have (at least) two problems: First, our transistors dissipate almost no energy when they are either 'fully open' or 'fully closed'. Because either there's approximately no current, or approximately no resistance. Hold…

I love tangents! I think all of your points are valid. I also think that we have optimized heavily for this state of technology. If we figured out that analog computing was somehow superior in a big way, I bet we would find ways of reducing power etc in analog designs. One way that analog computing would be really neat for neural networks is in speed. The way it might not be so great is in reliability (or repeatabili…

Specifically to the point of the comparatively low reliability / high variation of analog systems: an interesting property of neural nets is that they can be robust relative to noise when trained with the same type of noise witnessed under inference.

Whether or not speed/etc. would be better in the digital vs. analog design-space, it's an interesting thing to consider that neural nets can automatically account for the encoding-medium's variability. This perhaps makes neural solutions a good fit for low power analog media which otherwise aren't useful for classical computing.

See https://arxiv.org/abs/2104.13386 for an exploration of physically encoding neural architectures.