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So if I understood correctly, Schrodinger's Cat is a thought experiment that puts a cat inside a box, and there's a mechanism that kills the cat with 50% probability based on a quantum process. The argument is that the cat now must be in a superposition of dead and alive. But, is the cat really in a superposition?

This is my argument against superposition. Say someone drew a line and said to measure it. When you look at the line, you don't know how long the line is until you measure it. The line can't be different lengths, it already has a defined length. So if you don't know the spin of a particle until you measure it, it's like not knowing the length of the line right? My question is, is a particle really in a superposition before we observe it? The spin may be unknown, but it's still has a defined spin right?

Don Dix
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Schrödinger's cat is a pathologically flawed example, because a living being is an utterly intractably complicated system - far more complicated than physics ever deals with or will deal with for the foreseeable future - and moreover one would need to define an observable (a quantum measurement) that would define whether the cat were dead or alive. Since not even biology can agree on a rigorous definition of "alive", we don't seem to have any foreseeable hope of a definition that could be encoded into such a thing.

We believe in principle complicated isolated systems do have a unitarily-evolving pure quantum state, but the dimensionality of a cat and the world it interacts with would be stupendously big. This is a very different situation from simple, one-particle systems and queries by simple observables such as the measurement of spin up / down in a Stern-Gerlach apparatus for an electron.

Lone particles with a measurement modelled by a one simple Hermitian operators bear little likeness to the mind boggling complexity of something like a cat. One really cannot argue against the validity of the quantum conception of the world simply because quantum behaviors we see in simple systems don't seem to model behaviors of more everyday, but vastly more complicated, objects.