The windmill you are fighting has nothing to do with the orthodox formulation of QM, which is perfectly compatible with decoherence.
What is the orthodox formulation of QM? Link?
I wouldn't call it “orthodox”, but see this:
...In addition to these formal axioms one needs a rudimentary interpretation relating the formal part to experiments. The following minimal interpretation seems to be universally accepted.
MI. Upon measuring at times t_l (l=1,...,n) a vector X of observables with commuting components, for a large collection of independent identical (particular) systems closed for times t<t_l, all in the same state rho_0 = lim_{t to t_l from below} rho(t) (one calls such systems identically prepared), the measurement res
In response to falenas108's "Ask an X" thread. I have a PhD in experimental particle physics; I'm currently working as a postdoc at the University of Cincinnati. Ask me anything, as the saying goes.
This is an experiment. There's nothing I like better than talking about what I do; but I usually find that even quite well-informed people don't know enough to ask questions sufficiently specific that I can answer any better than the next guy. What goes through most people's heads when they hear "particle physics" is, judging by experience, string theory. Well, I dunno nuffin' about string theory - at least not any more than the average layman who has read Brian Greene's book. (Admittedly, neither do string theorists.) I'm equally ignorant about quantum gravity, dark energy, quantum computing, and the Higgs boson - in other words, the big theory stuff that shows up in popular-science articles. For that sort of thing you want a theorist, and not just any theorist at that, but one who works specifically on that problem. On the other hand I'm reasonably well informed about production, decay, and mixing of the charm quark and charmed mesons, but who has heard of that? (Well, now you have.) I know a little about CP violation, a bit about detectors, something about reconstructing and simulating events, a fair amount about how we extract signal from background, and quite a lot about fitting distributions in multiple dimensions.