A great question.
As a condensed matter physics grad student (doing scanning tunneling microscopy), I should start my reply by saying that going to grad school in physics is something that fewer people should be doing. If you want to do research in the field it is basically irreplaceable, but you have to be aware that there are many fewer spaces for postgraduate researchers, especially faculty, than there are grad students. If you are accepted at a top university, or get to work in a prestigious lab (good publications in Nature, PRL, Nature Physics, etc.), then you at least have a shot, but even then there's not enough space and too many hopefuls. Don't depend on everything going right, and if you have other plans, consider them. If you don't have any other plans that are even mildly appealing, this is a warning sign that you need to spend some more time planning. A little time on plans can save you a lot of trouble.
That said, doing a PhD can force you to improve yourself. You'll become better at doing research. It can be a lot of fun. And sometimes not so much fun, but hey, that's why they pay you and not vice versa. Just keep in mind that if you do it, you should do it because you enjoy it, because the odds are against you being a researcher in the field in 15 years.
Okay, with the important but slightly tangential stuff out of the way, let's talk about Moore's law.
Why do you consider an end to Moore's law to be bad? If you're an unreflective computerphile, your answer might be "computers are great, and faster, cheaper computer are greater," but I call this unreflective because it values computers based only on themselves, rather than mentioning the impact that computers have on people. If you're a transhumanist, your answer might be "there's people suffering and dying out there, and the faster we get to post-scarcity the better for everyone." Or if you think AI will have a huge impact on the future, replace 'post-scarcity' with 'a positive singularity.'
Around here, the typical response goes like this: the thing holding us back from a positive singularity, or a post-scarcity society where robots do the work, is not really that we don't have good enough computers. It's that we lack understanding. We need understanding of how to get AI to learn concepts and make plans in a complicated world, and how to train AI with complicated goal systems that capture what humans care about. If we don't have that understanding, giving us better computers won't help, and might be harmful if we build AIs that have a big impact but don't care about what humans care about.
Which is all to say, I think you should not work on quantum computing if your sole motivation is the long-term impact of better computers. But I think it's a fine thing to do if you enjoy the technical elements of research.
P.S. Have you seen this talk by John Martinis?
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A physics research team has members who can (and occasionally do) in secret insert false signals into the experiment the team is running. The goal is practice resistance to false positives. A very interesting approach, first time I've heard about physicists using it.
Bias combat in action :-)
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This is really fascinating, I wonder what other existing big science efforts 'blind injection' would benefit.