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qm4.eng.srt
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Stanford University
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Okay, let's, let's go on
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Let's forget for the moment, the spin system
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We will come back to it, probably tonight, definitely tonight
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But let's remind ourselves of,
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I think I wrote down four principles of quantum mechanics last time
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And I wanna write them down again
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And then move on to a fifth principle
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In fact they are not all independent
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It's easier for me to explain them one at a time
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To deprive from the minimal, absolute minimal number of them
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I don't think there is any particular advantage in doing that
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So I just write down... all the principles that I wrote down
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The first one is the observable, the observables are the things you measure
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It could be called measurable, if I have, if it's up to me, I would call it measurable
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But they are called observables
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Observables are represented... I will just use the equal sign to indicate that
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Observables are represented by Hermitian operators
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I use the symbol L for the moment for the Hermitian operator
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Not all operators, not all linear operators are Hermitian
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And it will not always be the case that
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the symbol L will stand for Hermitian operator
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But right now, L stand for Hermitian operator, any Hermitian operator
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Every observable is identified with a Hermitian operator
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Then the question is whether every Hermitian operator
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is a thing which can be measured, is a generally hard question,
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you know, what can or can't be measured
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depends on what the materials you have available, all kind of things
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Generally, the abstract rule, or the full rule, let's call it,
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Is it any Hermitian operator is identified with a observable and
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Some day somebody will figure out how to measure it
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Okay, but the other way that any observable
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is identified with a Hermitian operator, that's for sure
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The eigenvalue of a Hermitian operator, let's call them lambdas
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Lambda is the eigenvalue of L
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The eigenvalues represent the possible numerical values
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that L can exhibit when it's measured
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Okay so eigenvalues, eigenvalues of L which equal lambda
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Now they represent the possible observe...
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or the possible outcome of an experiment
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Possible outcome of an experiment to measure L of L measurement
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Okay I think we have a third one along the line here
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Physically distinguishable state,
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Now let's just see what physically distinguishable state means
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Certainly up and down are physically distinguishable
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And the meaning of saying two states are physically distinguishable
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is that there exist a measurement of some kind that you can do
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that can tell you the difference between a up state and a down state
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Another words, somebody hands you a spin from out of their pocket
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And they say I created the spin,
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I prepared it in a state which is either up or down
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Can you do an experiment to unambiguously tell me which one it is?
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Yes you tilt your apparatus until it's pointing along the z axis
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And you make the measurement
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If the state was up you will get plus one
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If the state was down you will get minus one
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No ambiguity
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The same is true for left and right
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Different measurement, different thing that you will measure
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You will measure the x component,
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then you will tilt your apparatus along the x axis
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but, same deal,
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on the other hand, supposing somebody, that same person came along and said here
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I'm gonna give you a spin, here it is, and that spin either prepared up
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or I prepared it right
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I'm not gonna tell you which way I prepared it
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I'm not gonna tell you in which way I tilted the apparatus
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when I did the preparation
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I'm just tell you it's either left... I'm sorry it's either up or right
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Can you do a experiment which will uniquely tell you the difference?
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The answer is no, for example supposing you decide to measure the spin along the z axis
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Well if it's up you will get plus one, if it's right,
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with fifty percent probability you will get plus one
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So you can't be sure whether you are up or right
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>> forty five degrees
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still you will have a probability for
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Ya, ya, it would not be unambiguous, right, okay?
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So the next postulate
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>> excuse me, if in that statement you were assuming it was prepared along the z axis
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>> If it have been prepared along the x axis
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>> Then if you measure the x axis first, you get ...
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If you measure the x axis first you will find something else
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But you could have found out exactly the same answer if it was along the z axis
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Either case, there was some probability
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of getting the same answer whether it was up or right
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There is no experiment you can do
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which unambiguously will determine which it was
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That leads to the notion, I am not going to give you a more precise definition of it
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That leads to the notion of physically distinguishable states
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by which it's meant that
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their exist an experiment or a set of experiments
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that can unambiguously determine which of the two states you are talking about
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The next postulate is that physically distinct or physically distinguishable states
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are represented by orthogonal vectors
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Okay, so physically distinct, distinct, distinguishable, same thing
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It's easier to write distinct
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This physically distinct states imply orthogonality
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I said that observables are Hermitian operators
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I could have just said linear operators,
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let's leave with linear operator for the moment
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But let's add a postulate that the result of every experiments
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Every simple primitive experiment it's a real number
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If it's a real number... if it's a complex number
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It really means that, two independent things are measured
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The actual result come out of your apparatus, come out of, you know
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The needle on your apparatus ,the real numbers
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So I will let that as a postulate, the result of experiments are always real numbers
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And therefore the eigenvalues of observables are real numbers
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Now that does not prove that the operators are Hermitian, not enough
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The other added thing is the various eigen vector with different eigen value
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is physically distinguishable states, or orthogonal
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Okay that's the third postulate
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And that tells you the observables are Hermitian operators
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It's the Hermitian operator whose eigen values are always real
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And whose eigen vectors are orthogonal
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That's necessary and sufficient
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And this one like I said, they are not all completely independent to each other
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One, two, three, and let's write number four now
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I forgot what fourth is, oh,
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Well, what was fourth? Ya
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Ah, the probability, the probability principle, okay
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The probability principle, it's also called Born's rule, that Max Born
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But it's a rule for probabilities
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So far, none of these have much content, the added content
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You know, it has content, but the real bite here is for the prediction of the probability
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for various experiments
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And the Born rule is the rule for how to calculate the probabilities
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The Born rule says, if your system has been prepared in state |A>
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System in |A>
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And you measure L, the observable L
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Now I'm using interchangeably the physical idea
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with observables with the operator which represent it
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I'm not going to make a special language where
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operator will always be called operator
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And the observable of L, same thing
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They come in pairs
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Alright, if you, if the system has been prepared in state |A>
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And you measure L, you measure L
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The outcome is going to be one of the eigenvalues
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So the only question you can ask is
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what is the probability that you get the answer lambda
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One of the specific eigenvalues
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The answer is, the probability
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The probability that you get result lambda
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That's the probability you get out of the various eigenvalue you get lambda
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Is equal to the square of inner product of the state vector
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That the system was in
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With the eigen vector corresponding the normalized eigenvector
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or vector normalized now
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The inner product of A with lambda squared
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A with lambda, sometimes incidentally the inner product is called the overlap
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It's a measure, if we say that orthogonality is complete distinguishability
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Or unique in the complete distinguishability
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Then a lack of orthogonality represent to some extend the inability
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to make the clear distinction between two states
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Ya, alright, so this is, question?
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>> I'm surprised to see lambda is represented as a vector
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>> because it's a value
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No, no, alright the notation is every eigen value is associated with a eigen vector
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I will just write E vector
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The notation is the vector labeled by lambda
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is the eigen vector associated with the eigen value lambda
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That's a good point, you know, the problem we are trying to be a pure about notation
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is that the notation get very complicated
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It get so complicated, it get difficult to read,
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too many indices, too many different letters you have to use
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So, ya, sometimes we use slightly excuse the word bastardize notation
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Or where we conflate a symbol for a vector, with the symbol in this case for a eigen value
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Okay, so that's the probability principle or Born's rule
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And just look at it for a minute
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You ask why the square of the absolute value?
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Well in general, this overlap is neither positive nor even real in general
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Overlaps between two vectors are not necessarily real, in fact
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They are generally not, we are talking about a complex vector space
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And if the component of a vector is complex
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In general in a product that would not even be real, let alone positive
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On the other hand, the square of the absolute value of the square,
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Square of the absolute value of the inner product, that is real
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It's not only real, it's also positive
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So this has a chance to be a candidate for the probability
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Whereas the inner product itself doesn't
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The inner product itself is called the probability amplitude
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The probability amplitude is a thing that you square
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in the sense of absolute value to compute a probability
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Needless to say, the justification for this principle in the end
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is experiment
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On the other hand, you could ask how much can I bent them
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And still make physical sense out of prediction
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The answer is nobody has ever found a way
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to change the rule of quantum mechanics
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and still preserve a reasonably logical structure
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So you eventually get familiar with these principles
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>> Which of these principles took you from several possible outcomes
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>> to one actual outcome?
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Well, okay, if <A| is an eigenvector of L, if it is
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If the state, starting state of a system happens to be an eigenvector of L
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Then it would only have an inner product of one of the eigenvectors
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Right, so that's again, it's a good question so
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>> If you say that L lambda can't equal to...(inaudible)
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Ya, ya, that's right
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>> Excuse me, what if lambda is an eigenvalue for multiple eigenvectors?
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Ya, still the rule is the same, but right
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I will give you two answers
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The first answer is don't worry about the case
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with the eigenvalue maybe the same
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Because it's very special, but that's not good enough, let me...
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Let me say what the right answer is
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The right answer is if you want the probability for a given value of lambda
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and there's more than one eigenvector with the same value of lambda
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Then you add them, you simply add the sum of the square
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of the probability addition
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The question, they are really good
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>> What about the case <A| has overlap...
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Yeah, yeah, then you take the sum of the square of them
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You take the sum of the square of them
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If there're several different eigenvectors all with the same eigenvalues
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First of all you make them perpendicular to each other
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You can always make them perpendicular to each other
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No no, even if they are the with the same eigenvalues
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The theorem, let's go back to the theorem
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The theorem says that the eigenvectors with different eigenvalues
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are orthogonal
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It doesn't tell you anything about the eigenvectors to the same eigenvalue
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That's supposing you have two eigenvectors with the same eigenvalue
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Then it's also true that any linear combination of those two vectors
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is also a eigenvector with the same eigenvalue
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For example, let's suppose lambda, lambda 1 and lambda 2,
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Now these are not two different values of lambda
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These are the same value of lambda but two different eigenvector
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Maybe we should write it like this
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Lambda 1 and lambda 2, two different eigenvectors
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Both exhibiting the same eigenvalue
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Then you can take any... what that means is
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L on lambda 1 equals lambda times lambda 1
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L on lambda 2 equals lambda lambda 2
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Multiply this by any complex number alpha
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This one by any complex number beta
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And add the two equations
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What you find is that L on the linear combination
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The linear sum of alpha lambda 1 plus beta lambda 2
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is equal... on this side now you have lambda
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times the same thing as in the bracket here
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Another word if you have two eigenvectors with the same eigenvalues
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You can add them with arbitrary coefficients and they remain eigenvectors
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Now given two distinct vectors, given two distinct vectors
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and all the possible linear combination of them
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You can always find perpendicular combination
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If you got this one, you got this one, now you can always add them
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Or subtract them with coefficient to make them perpendicular
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So the rest of the theorem is that if the two eigenvalues are the same