I'd take anything coming from them with a grain of salt.
I'd take anything coming from them with a grain of salt.
I have my doubts...
Not sure what the key paper is, but "Graph isomorphism in quasipolynomial time" is at leas relevant:
https://dl.acm.org/doi/10.1145/2897518.2897542
or perhaps, this arxiv paper:
https://arxiv.org/abs/1512.03547
No idea about a quantum algorithm for GI
How does anyone launch satellites? You pay someone to do it. Are you under the impression you need to have a rocket company to do this? One of the mandates of SpaceX (and others) is to lower the cost of these things.
1. You were making an argument about analog computers. There is big difference between a digital computer and an analog simulator. See this comics https://www.smbc-comics.com/comic/2013-07-19 -- We have went through this with classical computers over the last 100 years. The first computers were analog simulators that were just rescaled physical experiments: instead of measuring the flow of a river you made a scale model; instead of measuring the trajectory of a bomb you made an analog electronic model. These computers were great time-savers, but they were single-purpose and not "scalable" (i.e. the precision of their results was very limited due to fundamental physical reasons). When digital computers become sophisticated enough, we stopped using analog computers: a digital fluid model of the river is better than an analog scale model because by "just" increasing the mesh resolution you get more precise results, infeasible in the analog case; the digital bomb trajectory simulator is better because by "just" adding a new term and changing a data type you get more realistic results. Basically, digital computers are (a) scalable and (b) reprogrammable. Analog computers are not -- they are just rescaled physical experiments. Much of quantum computation today is just that: an analog experiment too far from the digital regime.
2. The point that OP was making is that Boson sampling, while it can be considered "digital" and "programmable" is too "boring". It shows a computation that can not be done by a classical computer efficiently, but the computation itself is just some silly sampling problem from a probability distribution that we would probably never care about. However, to me at least, it is a very big deal that we can reprogram (change the parameters) on the fly the probability distribution. And it is an even bigger deal that this is a scalable computation: a simple analog computer just starts giving chaotic results when you add too many degrees of freedom, unlike here where you start sampling from even more complicated distributions.