Trying to "beat" this rule is like trying to beat the Pythagorean theorem. If you want to derive higher frequencies, you'll quite obviously have to make additional assumptions about the measured wave.
This point of view also has some advantages in that if you think about it, you can see how you might play some games to work your way around things, many of which are used in the real world. For instance, if I'm sampling a 20KHz range, you could sample 0-10KHz with one signal, and then have something that downshifts 40-50KHz into the 10-20KHz range, and get a funky sampling of multiple bands of the spectrum. But no matter what silly buggers you play on the analog or the digital side, you can't escape from the pigeonhole principle.
From here we get the additional mathematical resonance that this sounds an awful lot like the proof that there can be no compression algorithm that compresses all inputs. And there is indeed a similarity; if we had a method for taking a digital signal that could have been 500Hz or 50500Hz despite an identical aliased signal, we could use that as a channel for storing bits in above and beyond what the raw digital signal contains; if we figure out it's the 500Hz signal it's an extra 0, or if it's 50500Hz it's a 1. With higher harmonics we could get even more bits. They don't claim something quite so binary, they've got more of a probabilistic claim, but that just means they're getting fractional extra bits instead of entire extra bits; the fundamental problem is the same. It doesn't matter how many bits you pull from nowhere; anything > 0.0000... is not valid.
Of course, one of the things we know from the internet is that there is still a set of people who don't accept the pigeonhole principle, despite it literally being just about the simplest possible mathematical claim I can possibly imagine (in the most degenerate case, "if you have two things and one box, it is not possible to put both of the things in a box without the box having more than one thing in it").
Aliasing is always a factor because no real signal has a highest frequency nor a fixed bandwidth (noise is never zero, and all filters roll off gradually forever)
The reason it's not perfect is because of your example, where a signal is not baseband. The extra leap required to understand that is amplitude modulation and demodulation.
Notice that to reconstruct the original signal of your example, you need to know the samples which are collected following the hypothesis of the sampling theorem, and you ALSO need to know the magic frequency 100MHz so that you can shift up your 2kHz bandwidth. That's the same setting as modulation.
The only concept missing, then, is recognizing that sampling can perform demodulation.
Take a look at Wikipedia: https://en.m.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_samp... it suggests that Shannon himself considered your case an additional point on top of the sampling theorem.
Assuming there's no external source of radiation, I can absolutely guarantee there is no energy propagating at cosmic ray frequencies in a circuit built around an audio op-amp with standard off-the-shelf components.
This isn't just pedanticism, you really can't just sample at 2x the corner frequency of your circuit.
(Unless there's some quantum effect that gives a minimum energy level possible for a signal? But even then it would be probabablistic? Is this what you mean? I didn't pay close enough attention in physics class)