atyy said:
I don't agree. The expectation and the average value are the same by definition in probability. One is the formal term, the other is the informal term.
Nitpicking a bit: Both have formal definitions, and they're different. There are theorems (
"laws of large numbers") that prove that the average converges in at least two different ways to the expectation value.
I was ignoring that there's a formal definition of "average". My point was that regardless of what mathematical terms we define, the physics is in the assumptions that tell us how the math is related to the real world. I consider this a supremely important fact; it's the very foundation of the philosophy of mathematics and science. Because of this, I find it rather odd that pretty much everyone but me (definitely not just you) are going out of their way to avoid mentioning these correspondence rules explicitly. Instead they seem to prefer to connect mathematics to reality simply by using the same term for the real-world thing and the corresponding mathematical thing. This is what people do with "proper time" in the relativity forum. I don't like it because it hides what we're really doing.
Edit: Even though "average" and "expectation value" are essentially the same in pure mathematics (because of the laws of large numbers), there's a difference between these concepts and the
real-world average, i.e. the average of the measurement results in an actual experiment. The assumption that the real-world average is equal to a number given by a mathematical formula, is a fundamental assumption. This
correspondence rule is a hugely important part of the definition of the theory.
atyy said:
I do agree that it is an additional assumption to say that probability is operationally defined as relative frequency.
Probability is typically defined something like this: Let ##X=\{1,2,3,4,5,6\}##. I'll use the notation ##|E|## for the number of elements of ##E##. For each ##E\subseteq X##, define ##P(E)=|E|/|X|##. For each ##E\subseteq X##, the number ##P(E)## is called the probability of E. Note that there's no connection to the real world whatsoever. The probability measure P is just an assignment of numbers in the interval [0,1] to subsets of some set X. Now we can turn this piece of pure mathematics into a falsifiable theory about the real world with a few simple assumptions. Some of them are common to all probability theories. But at least one assumption is part of the definition of the specific probability theory. In our case, that assumption can be that the elements of the set X correspond to the possible results of a roll of a six-sided die.
stevendaryl said:
Well, whatever it is that you want to call the expression \langle \Phi|O|\Phi \rangle, it's an assumption that it's equal to the average value of observable O in the state described by |\Phi\rangle.
atyy said:
But it is not an assumption different from the assumption that it is the expectation value of the observable.
If "average" refers to the average of the results of actual measurements, then I would say that it's definitely a different assumption. Not only that. It's a very different
kind of assumption.
There's a mathematical definition that associates the term "expectation value" with that number. There's a mathematical definition that associates the term "average" with something else. There are theorems that tell us how the average converges to the expectation value. But all of this is pure mathematics. The physics is in the correspondence rules, not in the mathematics, and in this case, the correspondence rule is the assumption that the expectation value is equal to the
real-world average (not just the "formal average", i.e. the number that the laws of large numbers are making claims about).