Earlier quoted context omitted.
Sure they are smart, but you'll find smarter people at any theoretical physics department, if we're talking IQ. Also, I don't think we are talking about rich as in global top 100, what I at least meant more mundane financial success, like earning $1 m a year. At that level, you definitely don't need to be a genius, I'd say if anything a genius is much less likely to make a million a year.
People who don't try to become rich probably won't. That much is clear. When people pursue theoretical physics they knowingly choose a career that cuts off almost all paths to wealth. The question "so, why aren't you rich?" doesn't apply to people who aren't even trying. For success within theoretical physics you see, again, exactly how important raw intelligence is. Charisma and people skills are nice, but top resea…
I actually believed physics has repeated run into the problem where large swaths of research is in fact unverifiable and exists purely on a theoretical basis until technology has caught up with the theory. Wasn't there a large discussion within the past 12 months or so about the many flaws of the field of physics, including the repeating of the same mistakes due to not wanting to stray too far from the existing literature? Doesn't this field also have large swaths of theories with plenty of mathematics behind both that are also mutually exclusive?
If I would think about a field with a long history of verified research, physics would most certainly not be up there. I'd say chemistry has physics beat there for example.
Additionally, epidemiological modeling has to deal with real data from sources whose trustworthiness are largely only somewhat known and somehow project this into the future. This is a garbage in, garbage out situation and I don't know if this should reflect on the field overall. It'd be like judging ML as a field based off of a problem case in which all training data has untrustworthy labels.