# Quantum-mechanical operators

We climbed a mountain—step by step, post by post. 🙂 We have reached the top now, and the view is gorgeous. We understand Schrödinger’s equation, which describes how amplitudes propagate through space-time. It’s the quintessential quantum-mechanical expression. Let’s enjoy now, and deepen our understanding by introducing the concept of (quantum-mechanical) operators.

#### The operator concept

We’ll introduce the operator concept using Schrödinger’s equation itself and, in the process, deepen our understanding of Schrödinger’s equation a bit. You’ll remember we wrote it as:

However, you’ve probably seen it like it’s written on his bust, or on his grave, or wherever, which is as follows:

It’s the same thing, of course. The ‘over-dot’ is Newton’s notation for the time derivative. In fact, if you click on the picture above (and zoom in a bit), then you’ll see that the craftsman who made the stone grave marker, mistakenly, also carved a dot above the psi (ψ) on the right-hand side of the equation—but then someone pointed out his mistake and so the dot on the right-hand side isn’t painted. 🙂 The thing I want to talk about here, however, is the H in that expression above, which is, obviously, the following operator:

That’s a pretty monstrous operator, isn’t it? It is what it is, however: an algebraic operator (it operates on a number—albeit a complex number—unlike a matrix operator, which operates on a vector or another matrix). As you can see, it actually consists of two other (algebraic) operators:

1. The ∇operator, which you know: it’s a differential operator. To be specific, it’s the Laplace operator, which is the divergence (·) of the gradient () of a function: ∇= · = (∂/∂x, ∂/∂y , ∂/∂z)·(∂/∂x, ∂/∂y , ∂/∂z) = ∂2/∂x2  + ∂2/∂y+ ∂2/∂z2. This too operates on our complex-valued function wavefunction ψ, and yields some other complex-valued function, which we then multiply by −ħ2/2m to get the first term.
2. The V(x, y, z) ‘operator’, which—in this particular context—just means: “multiply with V”. Needless to say, V is the potential here, and so it captures the presence of external force fields. Also note that V is a real number, just like −ħ2/2m.

Let me say something about the dimensions here. On the left-hand side of Schrödinger’s equation, we have the product of ħ and a time derivative (is just the imaginary unit, so that’s just a (complex) number). Hence, the dimension there is [J·s]/[s] (the dimension of a time derivative is something expressed per second). So the dimension of the left-hand side is joule. On the right-hand side, we’ve got two terms. The dimension of that second-order derivative (∇2ψ) is something expressed per square meter, but then we multiply it with −ħ2/2m, whose dimension is [J2·s2]/[J/(m2/s2)]. [Remember: m = E/c2.] So that reduces to [J·m2]. Hence, the dimension of (−ħ2/2m)∇2ψ is joule. And the dimension of V is joule too, of course. So it all works out. In fact, now that we’re here, it may or may not be useful to remind you of that heat diffusion equation we discussed when introducing the basic concepts involved in vector analysis:

That equation illustrated the physical significance of the Laplacian. We were talking about the flow of heat in, say, a block of metal, as illustrated below. The in the equation above is the heat per unit volume, and the h in the illustration below was the heat flow vector (so it’s got nothing to do with Planck’s constant), which depended on the material, and which we wrote as = –κT, with T the temperature, and κ (kappa) the thermal conductivity. In any case, the point is the following: the equation below illustrates the physical significance of the Laplacian. We let it operate on the temperature (i.e. a scalar function) and its product with some constant (just think of replacing κ by −ħ2/2m gives us the time derivative of q, i.e. the heat per unit volume.

In fact, we know that is proportional to T, so if we’d choose an appropriate temperature scale – i.e. choose the zero point such that T (your physics teacher in high school would refer to as the (volume) specific heat capacity) – then we could simple write:

∂T/∂t = (κ/k)∇2T

From a mathematical point of view, that equation is just the same as ∂ψ/∂t = –(i·ħ/2m)·∇2ψ, which is Schrödinger’s equation for V = 0. In other words, you can – and actually should – also think of Schrödinger’s equation as describing the flow of… Well… What?

Well… Not sure. I am tempted to think of something like a probability density in space, but ψ represents a (complex-valued) amplitude. Having said that, you get the idea—I hope! 🙂 If not, let me paraphrase Feynman on this:

“We can think of Schrödinger’s equation as describing the diffusion of a probability amplitude from one point to another. In fact, the equation looks something like the diffusion equation we introduced when discussing heat flow, or the spreading of a gas. But there is one main difference: the imaginary coefficient in front of the time derivative makes the behavior completely different from the ordinary diffusion such as you would have for a gas spreading out. Ordinary diffusion gives rise to real exponential solutions, whereas the solutions of Schrödinger’s equation are complex waves.”

That says it all, right? 🙂 In fact, Schrödinger’s equation – as discussed here – was actually being derived when describing the motion of an electron along a line of atoms, i.e. for motion in one direction only, but you can visualize what it represents in three-dimensional space. The real exponential functions Feynman refer to exponential decay function: as the energy is spread over an ever-increasing volume, the amplitude of the wave becomes smaller and smaller. That may be the case for complex-valued exponentials as well. The key difference between a real- and complex-valued exponential decay function is that a complex exponential is a cyclical function. Now, I quickly googled to see how we could visualize that, and I like the following illustration:

The dimensional analysis of Schrödinger’s equation is also quite interesting because… Well… Think of it: that heat diffusion equation incorporates the same dimensions: temperature is a measure of the average energy of the molecules. That’s really something to think about. These differential equations are not only structurally similar but, in addition, they all seem to describe some flow of energy. That’s pretty deep stuff: it relates amplitudes to energies, so we should think in terms of Poynting vectors and all that. But… Well… I need to move on, and so I will move on—so you can re-visit this later. 🙂

Now that we’ve introduced the concept of an operator, let me say something about notations, because that’s quite confusing.

#### Some remarks on notation

Because it’s an operator, we should actually use the hat symbol—in line with what we did when we were discussing matrix operators: we’d distinguish the matrix (e.g. A) from its use as an operator (Â). You may or may not remember we do the same in statistics: the hat symbol is supposed to distinguish the estimator (â) – i.e. some function we use to estimate a parameter (which we usually denoted by some Greek symbol, like α) – from a specific estimate of the parameter, i.e. the value (a) we get when applying â to a specific sample or observation. However, if you remember the difference, you’ll also remember that hat symbol was quickly forgotten, because the context made it clear what was what, and so we’d just write a(x) instead of â(x). So… Well… I’ll be sloppy as well here, if only because the WordPress editor only offers very few symbols with a hat! 🙂

In any case, this discussion on the use (or not) of that hat is irrelevant. In contrast, what is relevant is to realize this algebraic operator H here is very different from that other quantum-mechanical Hamiltonian operator we discussed when dealing with a finite set of base states: that H was the Hamiltonian matrix, but used in an ‘operation’ on some state. So we have the matrix operator H, and the algebraic operator H.

Confusing?

Yes and no. First, we’ve got the context again, and so you always know whether you’re looking at continuous or discrete stuff:

1. If your ‘space’ is continuous (i.e. if states are to defined with reference to an infinite set of base states), then it’s the algebraic operator.
2. If, on the other hand, your states are defined by some finite set of discrete base states, then it’s the Hamiltonian matrix.

There’s another, more fundamental, reason why there should be no confusion. In fact, it’s the reason why physicists use the same symbol H in the first place: despite the fact that they look so different, these two operators (i.e. H the algebraic operator and H the matrix operator) are actually equivalent. Their interpretation is similar, as evidenced from the fact that both are being referred to as the energy operator in quantum physics. The only difference is that one operates on a (state) vector, while the other operates on a continuous function. It’s just the difference between matrix mechanics as opposed to wave mechanics really.

But… Well… I am sure I’ve confused you by now—and probably very much so—and so let’s start from the start. 🙂

#### Matrix mechanics

Let’s start with the easy thing indeed: matrix mechanics. The matrix-mechanical approach is summarized in that set of Hamiltonian equations which, by now, you know so well:

If we have base states, then we have equations like this: one for each = 1, 2,… n. As for the introduction of the Hamiltonian, and the other subscript (j), just think of the description of a state:

So… Well… Because we had used already, we had to introduce j. 🙂

Let’s think about |ψ〉. It is the state of a system, like the ground state of a hydrogen atom, or one of its many excited states. But… Well… It’s a bit of a weird term, really. It all depends on what you want to measure: when we’re thinking of the ground state, or an excited state, we’re thinking energy. That’s something else than thinking its position in space, for example. Always remember: a state is defined by a set of base states, and so those base states come with a certain perspective: when talking states, we’re only looking at some aspect of reality, really. Let’s continue with our example of energy states, however.

You know that the lifetime of a system in an excited state is usually short: some spontaneous or induced emission of a quantum of energy (i.e. a photon) will ensure that the system quickly returns to a less excited state, or to the ground state itself. However, you shouldn’t think of that here: we’re looking at stable systems here. To be clear: we’re looking at systems that have some definite energy—or so we think: it’s just because of the quantum-mechanical uncertainty that we’ll always measure some other different value. Does that make sense?

If it doesn’t… Well… Stop reading, because it’s only going to get even more confusing. Not my fault, however!

#### Psi-chology

The ubiquity of that ψ symbol (i.e. the Greek letter psi) is really something psi-chological 🙂 and, hence, very confusing, really. In matrix mechanics, our ψ would just denote a state of a system, like the energy of an electron (or, when there’s only one electron, our hydrogen atom). If it’s an electron, then we’d describe it by its orbital. In this regard, I found the following illustration from Wikipedia particularly helpful: the green orbitals show excitations of copper (Cu) orbitals on a CuOplane. [The two big arrows just illustrate the principle of X-ray spectroscopy, so it’s an X-ray probing the structure of the material.]

So… Well… We’d write ψ as |ψ〉 just to remind ourselves we’re talking of some state of the system indeed. However, quantum physicists always want to confuse you, and so they will also use the psi symbol to denote something else: they’ll use it to denote a very particular Ci amplitude (or coefficient) in that |ψ〉 = ∑|iCi formula above. To be specific, they’d replace the base states |i〉 by the continuous position variable x, and they would write the following:

Ci = ψ(i = x) = ψ(x) = Cψ(x) = C(x) = 〈x|ψ〉

In fact, that’s just like writing:

φ(p) = 〈 mom p | ψ 〉 = 〈p|ψ〉 = Cφ(p) = C(p)

What they’re doing here, is (1) reduce the ‘system‘ to a ‘particle‘ once more (which is OK, as long as you know what you’re doing) and (2) they basically state the following:

If a particle is in some state |ψ〉, then we can associate some wavefunction ψ(x) or φ(p)—with it, and that wavefunction will represent the amplitude for the system (i.e. our particle) to be at x, or to have a momentum that’s equal to p.

So what’s wrong with that? Well… Nothing. It’s just that… Well… Why don’t they use χ(x) instead of ψ(x)? That would avoid a lot of confusion, I feel: one should not use the same symbol (psi) for the |ψ〉 state and the ψ(x) wavefunction.

Huh? Yes. Think about it. The point is: the position or the momentum, or even the energy, are properties of the system, so to speak and, therefore, it’s really confusing to use the same symbol psi (ψ) to describe (1) the state of the system, in general, versus (2) the position wavefunction, which describes… Well… Some very particular aspect (or ‘state’, if you want) of the same system (in this case: its position). There’s no such problem with φ(p), so… Well… Why don’t they use χ(x) instead of ψ(x) indeed? I have only one answer: psi-chology. 🙂

In any case, there’s nothing we can do about it and… Well… In fact, that’s what this post is about: it’s about how to describe certain properties of the system. Of course, we’re talking quantum mechanics here and, hence, uncertainty, and, therefore, we’re going to talk about the average position, energy, momentum, etcetera that’s associated with a particular state of a system, or—as we’ll keep things very simple—the properties of a ‘particle’, really. Think of an electron in some orbital, indeed! 🙂

So let’s now look at that set of Hamiltonian equations once again:

Looking at it carefully – so just look at it once again! 🙂 – and thinking about what we did when going from the discrete to the continuous setting, we can now understand we should write the following for the continuous case:

Of course, combining Schrödinger’s equation with the expression above implies the following:

Now how can we relate that integral to the expression on the right-hand side? I’ll have to disappoint you here, as it requires a lot of math to transform that integral. It requires writing H(x, x’) in terms of rather complicated functions, including – you guessed it, didn’t you? – Dirac’s delta function. Hence, I assume you’ll believe me if I say that the matrix- and wave-mechanical approaches are actually equivalent. In any case, if you’d want to check it, you can always read Feynman yourself. 🙂

Now, I wrote this post to talk about quantum-mechanical operators, so let me do that now.

#### Quantum-mechanical operators

You know the concept of an operator. As mentioned above, we should put a little hat (^) on top of our Hamiltonian operator, so as to distinguish it from the matrix itself. However, as mentioned above, the difference is usually quite clear from the context. Our operators were all matrices so far, and we’d write the matrix elements of, say, some operator A, as:

Aij ≡ 〈 i | A | j 〉

The whole matrix itself, however, would usually not act on a base state but… Well… Just on some more general state ψ, to produce some new state φ, and so we’d write:

| φ 〉 = A | ψ 〉

Of course, we’d have to describe | φ 〉 in terms of the (same) set of base states and, therefore, we’d expand this expression into something like this:

You get the idea. I should just add one more thing. You know this important property of amplitudes: the 〈 ψ | φ 〉 amplitude is the complex conjugate of the 〈 φ | ψ 〉 amplitude. It’s got to do with time reversibility, because the complex conjugate of eiθ = ei(ω·t−k·x) is equal to eiθ = ei(ω·t−k·x), so we’re just reversing the x- and tdirection. We write:

〈 ψ | φ 〉 = 〈 φ | ψ 〉*

Now what happens if we want to take the complex conjugate when we insert a matrix, so when writing 〈 φ | A | ψ 〉 instead of 〈 φ | ψ 〉, this rules becomes:

〈 φ | A | ψ 〉* = 〈 ψ | A† | φ 〉

The dagger symbol denotes the conjugate transpose, so A† is an operator whose matrix elements are equal to Aij† = Aji*. Now, it may or may not happen that the A† matrix is actually equal to the original A matrix. In that case – and only in that case – we can write:

〈 ψ | A | φ 〉 = 〈 φ | A | ψ 〉*

We then say that A is a ‘self-adjoint’ or ‘Hermitian’ operator. That’s just a definition of a property, which the operator may or may not have—but many quantum-mechanical operators are actually Hermitian. In any case, we’re well armed now to discuss some actual operators, and we’ll start with that energy operator.

#### The energy operator (H)

We know the state of a system is described in terms of a set of base states. Now, our analysis of N-state systems showed we can always describe it in terms of a special set of base states, which are referred to as the states of definite energy because… Well… Because they’re associated with some definite energy. In that post, we referred to these energy levels as En (n = I, II,… N). We used boldface for the subscript n (so we wrote n instead of n) because of these Roman numerals. With each energy level, we could associate a base state, of definite energy indeed, that we wrote as |n〉. To make a long story short, we summarized our results as follows:

1. The energies EI, EII,…, En,…, EN are the eigenvalues of the Hamiltonian matrix H.
2. The state vectors |n〉 that are associated with each energy En, i.e. the set of vectors |n〉, are the corresponding eigenstates.

We’ll be working with some more subscripts in what follows, and these Roman numerals and the boldface notation are somewhat confusing (if only because I don’t want you to think of these subscripts as vectors), we’ll just denote EI, EII,…, En,…, EN as E1, E2,…, Ei,…, EN, and we’ll number the states of definite energy accordingly, also using some Greek letter so as to clearly distinguish them from all our Latin letter symbols: we’ll write these states as: |η1〉, |η1〉,… |ηN〉. [If I say, ‘we’, I mean Feynman of course. You may wonder why he doesn’t write |Ei〉, or |εi〉. The answer is: writing |En〉 would cause confusion, because this state will appear in expressions like: |Ei〉Ei, so that’s the ‘product’ of a state (|Ei〉) and the associated scalar (Ei). Too confusing. As for using η (eta) instead of ε (epsilon) to denote something that’s got to do with energy… Well… I guess he wanted to keep the resemblance with the n, and then the Ancient Greek apparently did use this η letter  for a sound like ‘e‘ so… Well… Why not? Let’s get back to the lesson.]

Using these base states of definite energy, we can write the state of the system as:

|ψ〉 = ∑ |ηi〉 C = ∑ |ηi〉〈ηi|ψ〉    over all (i = 1, 2,… , N)

Now, we didn’t talk all that much about what these base states actually mean in terms of measuring something but you’ll believe if I say that, when measuring the energy of the system, we’ll always measure one or the other E1, E2,…, Ei,…, EN value. We’ll never measure something in-between: it’s eitheror. Now, as you know, measuring something in quantum physics is supposed to be destructive but… Well… Let us imagine we could make a thousand measurements to try to determine the average energy of the system. We’d do so by counting the number of times we measure E1 (and of course we’d denote that number as N1), E2E3, etcetera. You’ll agree that we’d measure the average energy as:

However, measurement is destructive, and we actually know what the expected value of this ‘average’ energy will be, because we know the probabilities of finding the system in a particular base state. That probability is equal to the absolute square of that Ccoefficient above, so we can use the P= |Ci|2 formula to write:

Eav〉 = ∑ Pi Ei over all (i = 1, 2,… , N)

Note that this is a rather general formula. It’s got nothing to do with quantum mechanics: if Ai represents the possible values of some quantity A, and Pi is the probability of getting that value, then (the expected value of) the average A will also be equal to 〈Aav〉 = ∑ Pi Ai. No rocket science here! 🙂 But let’s now apply our quantum-mechanical formulas to that 〈Eav〉 = ∑ Pi Ei formula. [Oh—and I apologize for using the same angle brackets 〈 and 〉 to denote an expected value here—sorry for that! But it’s what Feynman does—and other physicists! You see: they don’t really want you to understand stuff, and so they often use very confusing symbols.] Remembering that the absolute square of a complex number equals the product of that number and its complex conjugate, we can re-write the 〈Eav〉 = ∑ Pi Ei formula as:

Eav〉 = ∑ Pi Ei = ∑ |Ci|Ei = ∑ Ci*CEi = ∑ C*CEi = ∑ 〈ψ|ηi〉〈ηi|ψ〉E= ∑ 〈ψ|ηiEi〈ηi|ψ〉 over all i

Now, you know that Dirac’s bra-ket notation allows numerous manipulations. For example, what we could do is take out that ‘common factor’ 〈ψ|, and so we may re-write that monster above as:

Eav〉 = 〈ψ| ∑ ηiEi〈ηi|ψ〉 = 〈ψ|φ〉, with |φ〉 = ∑ |ηiEi〈ηi|ψ〉 over all i

Huh? Yes. Note the difference between |ψ〉 = ∑ |ηi〉 C = ∑ |ηi〉〈ηi|ψ〉 and |φ〉 = ∑ |ηiEi〈ηi|ψ〉. As Feynman puts it: φ is just some ‘cooked-up‘ state which you get by taking each of the base states |ηi〉 in the amount Ei〈ηi|ψ〉 (as opposed to the 〈ηi|ψ〉 amounts we took for ψ).

I know: you’re getting tired and you wonder why we need all this stuff. Just hang in there. We’re almost done. I just need to do a few more unpleasant things, one of which is to remind you that this business of the energy states being eigenstates (and the energy levels being eigenvalues) of our Hamiltonian matrix (see my post on N-state systems) comes with a number of interesting properties, including this one:

H |ηi〉 = Eii〉 = |ηiEi

Just think about what’s written here: on the left-hand side, we’re multiplying a matrix with a (base) state vector, and on the left-hand side we’re multiplying it with a scalar. So our |φ〉 = ∑ |ηiEi〈ηi|ψ〉 sum now becomes:

|φ〉 = ∑ H |ηi〉〈ηi|ψ〉 over all (i = 1, 2,… , N)

Now we can manipulate that expression some more so as to get the following:

|φ〉 = H ∑|ηi〉〈ηi|ψ〉 = H|ψ〉

Finally, we can re-combine this now with the 〈Eav〉 = 〈ψ|φ〉 equation above, and so we get the fantastic result we wanted:

Eav〉 = 〈 ψ | φ 〉 = 〈 ψ | H ψ 〉

Huh? Yes! To get the average energy, you operate on |ψ with H, and then you multiply the result with ψ|. It’s a beautiful formula. On top of that, the new formula for the average energy is not only pretty but also useful, because now we don’t need to say anything about any particular set of base states. We don’t even have to know all of the possible energy levels. When we have to calculate the average energy of some system, we only need to be able to describe the state of that system in terms of some set of base states, and we also need to know the Hamiltonian matrix for that set, of course. But if we know that, we can calculate its average energy.

You’ll say that’s not a big deal because… Well… If you know the Hamiltonian, you know everything, so… Well… Yes. You’re right: it’s less of a big deal than it seems. Having said that, the whole development above is very interesting because of something else: we can easily generalize it for other physical measurements. I call it the ‘average value’ operator idea, but you won’t find that term in any textbook. 🙂 Let me explain the idea.

#### The average value operator (A)

The development above illustrates how we can relate a physical observable, like the (average) energy (E), to a quantum-mechanical operator (H). Now, the development above can easily be generalized to any observable that would be proportional to the energy. It’s perfectly reasonable, for example, to assume the angular momentum – as measured in some direction, of course, which we usually refer to as the z-direction – would be proportional to the energy, and so then it would be easy to define a new operator Lz, which we’d define as the operator of the z-component of the angular momentum L. [I know… That’s a bit of a long name but… Well… You get the idea.] So we can write:

Lzav = 〈 ψ | Lψ 〉

In fact, further generalization yields the following grand result:

If a physical observable A is related to a suitable quantum-mechanical operator Â, then the average value of A for the state | ψ 〉 is given by:

Aav = 〈 ψ | Â ψ 〉 = 〈 ψ | φ 〉 with | φ 〉 = Â ψ 〉

At this point, you may have second thoughts, and wonder: what state | ψ 〉? The answer is: it doesn’t matter. It can be any state, as long as we’re able to describe in terms of a chosen set of base states. 🙂

OK. So far, so good. The next step is to look at how this works for the continuity case.

#### The energy operator for wavefunctions (H)

We can start thinking about the continuous equivalent of the 〈Eav〉 = 〈ψ|H|ψ〉 expression by first expanding it. We write:

You know the continuous equivalent of a sum like this is an integral, i.e. an infinite sum. Now, because we’ve got two subscripts here (i and j), we get the following double integral:

Now, I did take my time to walk you through Feynman’s derivation of the energy operator for the discrete case, i.e. the operator when we’re dealing with matrix mechanics, but I think I can simplify my life here by just copying Feynman’s succinct development:

Done! Given a wavefunction ψ(x), we get the average energy by doing that integral above. Now, the quantity in the braces of that integral can be written as that operator we introduced when we started this post:

So now we can write that integral much more elegantly. It becomes:

Eav = ∫ ψ*(xH ψ(x) dx

You’ll say that doesn’t look like 〈Eav〉 = 〈 ψ | H ψ 〉! It does. Remember that 〈 ψ | = ψ 〉*. 🙂 Done!

I should add one qualifier though: the formula above assumes our wavefunction has been normalized, so all probabilities add up to one. But that’s a minor thing. The only thing left to do now is to generalize to three dimensions. That’s easy enough. Our expression becomes a volume integral:

Eav = ∫ ψ*(rH ψ(r) dV

Of course, dV stands for dVolume here, not for any potential energy, and, of course, once again we assume all probabilities over the volume add up to 1, so all is normalized. Done! 🙂

We’re almost done with this post. What’s left is the position and momentum operator. You may think this is going to another lengthy development but… Well… It turns out the analysis is remarkably simple. Just stay with me a few more minutes and you’ll have earned your degree. 🙂

#### The position operator (x)

The thing we need to solve here is really easy. Look at the illustration below as representing the probability density of some particle being at x. Think about it: what’s the average position?

Well? What? The (expected value of the) average position is just this simple integral: 〈xav = ∫ P(x) dx, over all the whole range of possible values for x. 🙂 That’s all. Of course, because P(x) = |ψ(x)|2 =ψ*(x)·ψ(x), this integral now becomes:

xav = ∫ ψ*(x) x ψ(x) dx

That looks exactly the same as 〈Eav = ∫ ψ*(xH ψ(x) dx, and so we can look at as an operator too!

Huh? Yes. It’s an extremely simple operator: it just means “multiply by x“. 🙂

I know you’re shaking your head now: is it that easy? It is. Moreover, the ‘matrix-mechanical equivalent’ is equally simple but, as it’s getting late here, I’ll refer you to Feynman for that. 🙂

#### The momentum operator (px)

Now we want to calculate the average momentum of, say, some electron. What integral would you use for that? […] Well… What? […] It’s easy: it’s the same thing as for x. We can just substitute replace for in that 〈xav = ∫ P(x) dformula, so we get:

pav = ∫ P(p) dp, over all the whole range of possible values for p

Now, you might think the rest is equally simple, and… Well… It actually is simple but there’s one additional thing in regard to the need to normalize stuff here. You’ll remember we defined a momentum wavefunction (see my post on the Uncertainty Principle), which we wrote as:

φ(p) = 〈 mom p | ψ 〉

Now, in the mentioned post, we related this momentum wavefunction to the particle’s ψ(x) = 〈x|ψ〉 wavefunction—which we should actually refer to as the position wavefunction, but everyone just calls it the particle’s wavefunction, which is a bit of a misnomer, as you can see now: a wavefunction describes some property of the system, and so we can associate several wavefunctions with the same system, really! In any case, we noted the following there:

• The two probability density functions, φ(p) and ψ(x), look pretty much the same, but the half-width (or standard deviation) of one was inversely proportional to the half-width of the other. To be precise, we found that the constant of proportionality was equal to ħ/2, and wrote that relation as follows: σp = (ħ/2)/σx.
• We also found that, when using a regular normal distribution function for ψ(x), we’d have to normalize the probability density function by inserting a (2πσx2)−1/2 in front of the exponential.

Now, it’s a bit of a complicated argument, but the upshot is that we cannot just write what we usually write, i.e. Pi = |Ci|2 or P(x) = |ψ(x)|2. No. We need to put a normalization factor in front, which combines the two factors I mentioned above. To be precise, we have to write:

P(p) = |〈p|ψ〉|2/(2πħ)

So… Well… Our 〈pav = ∫ P(p) dp integral can now be written as:

pav = ∫ 〈ψ|ppp|ψ〉 dp/(2πħ)

So that integral is totally like what we found for 〈xav and so… We could just leave it at that, and say we’ve solved the problem. In that sense, it is easy. However, having said that, it’s obvious we’d want some solution that’s written in terms of ψ(x), rather than in terms of φ(p), and that requires some more manipulation. I’ll refer you, once more, to Feynman for that, and I’ll just give you the result:

So… Well… I turns out that the momentum operator – which I tentatively denoted as px above – is not so simple as our position operator (x). Still… It’s not hugely complicated either, as we can write it as:

px ≡ (ħ/i)·(∂/∂x)

Of course, the purists amongst you will, once again, say that I should be more careful and put a hat wherever I’d need to put one so… Well… You’re right. I’ll wrap this all up by copying Feynman’s overview of the operators we just explained, and so he does use the fancy symbols. 🙂

Well, folks—that’s it! Off we go! You know all about quantum physics now! We just need to work ourselves through the exercises that come with Feynman’s Lectures, and then you’re ready to go and bag a degree in physics somewhere. So… Yes… That’s what I want to do now, so I’ll be silent for quite a while now. Have fun! 🙂

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# Quantum math revisited

It’s probably good to review the concepts we’ve learned so far. Let’s start with the foundation of all of our math, i.e. the concept of the state, or the state vector. [The difference between the two concepts is subtle but real. I’ll come back to it.]

#### State vectors and base states

We used Dirac’s bra-ket notation to denote a state vector, in general, as | ψ 〉. The obvious question is: what is this thing? We called it a vector because we use it like a vector: we multiply it with some number, and then add it to some other vector. So that’s just what you did in high school, when you learned about real vector spaces. In this regard, it is good to remind you of the definition of a vector space. To put it simply, it is is a collection of objects called vectors, which may be added together, and multiplied by numbers. So we have two things here: the ‘objects’, and the ‘numbers’. That’s why we’d say that we have some vector space over a field of numbers. [The term ‘field’ just refers to an algebraic structure, so we can add and multiply and what have you.] Of course, what it means to ‘add’ two ‘objects’, and what it means to ‘multiply’ an object with a number, depends on the type of objects and, unsurprisingly, the type of numbers.

Huh? The type of number?! A number is a number, no?

No, hombre, no! We’ve got natural numbers, rational numbers, real numbers, complex numbers—and you’ve probably heard of quaternions too – and, hence, ‘multiplying’ a ‘number’ with ‘something else’ can mean very different things. At the same time, the general idea is the general idea, so that’s the same, indeed. 🙂 When using real numbers and the kind of vectors you are used to (i.e. Euclidean vectors), then the multiplication amounts to a re-scaling of the vector, and so that’s why a real number is often referred to as a scalar. At the same time, anything that can be used to multiply a vector is often referred to as a scalar in math so… Well… Terminology is often quite confusing. In fact, I’ll give you some more examples of confusing terminology in a moment. But let’s first look at our ‘objects’ here, i.e. our ‘vectors’.

I did a post on Euclidean and non-Euclidean vector spaces two years ago, when I started this blog, but state vectors are obviously very different ‘objects’. They don’t resemble the vectors we’re used to. We’re used to so-called polar vectors, aka as real vectors, like the position vector (x or r), or the momentum vector (p = m·v), or the electric field vector (E). We are also familiar with the so-called pseudo-vectors, aka as axial vectors, like angular momentum (L = r×p), or the magnetic dipole moment. [Unlike what you might think, not all vector cross products yield a pseudo-vector. For example, the cross-product of a polar and an axial vector yields a polar vector.] But here we are talking some very different ‘object’. In math, we say that state vectors are elements in a Hilbert space. So a Hilbert space is a vector space but… Well… With special vectors. 🙂

The key to understanding why we’d refer to states as state vectors is the fact that, just like Euclidean vectors, we can uniquely specify any element in a Hilbert space with respect to a set of base states. So it’s really like using Cartesian coordinates in a two- or three-dimensional Euclidean space. The analogy is complete because, even in the absence of a geometrical interpretation, we’ll require those base states to be orthonormal. Let me be explicit on that by reminding you of your high-school classes on vector analysis: you’d choose a set of orthonormal base vectors e1e2, and e3, and you’d write any vector A as:

A = (Ax, Ay, Az) = Ax·e1 + Ay·e2 + Az·e3 with ei·ej = 1 if i = j, and ei·ej = 0 if i ≠ j

The ei·ej = 1 if i = j and ei·ej = 0 if i ≠ j condition expresses the orthonormality condition: the base vectors need to be orthogonal unit vectors. We wrote it as ei·ej = δij using the Kronecker delta ij = 1 if i = j and 0 if i ≠ j). Now, base states in quantum mechanics do not necessarily have a geometrical interpretation. Indeed, although one often can actually associate them with some position or direction in space, the condition of orthonormality applies in the mathematical sense of the word only. Denoting the base states by i = 1, 2,… – or by Roman numerals, like I and II – so as to distinguish them from the Greek ψ or φ symbols we use to denote state vectors in general, we write the orthonormality condition as follows:

〈 i | j 〉 = δij, with δij = δji is equal to 1 if i = j, and zero if i ≠ j

Now, you may grumble and say: that 〈 i | j 〉 bra-ket does not resemble the ei·ej product. Well… It does and it doesn’t. I’ll show why in a moment. First note how we uniquely specify state vectors in general in terms of a set of base states. For example, if we have two possible base states only, we’ll write:

| φ 〉 = | 1 〉 C1 + | 2 〉 C2

Or, if we chose some other set of base states | I 〉 and | II 〉, we’ll write:

| φ 〉 = | I 〉 CI + | II 〉 CII

You should note that the | 1 〉 C1 term in the | φ 〉 = | 1 〉 C1 + | 2 〉 C2 sum is really like the Ax·e1 product in the A = Ax·e1 + Ay·e2 + Az·e3 expression. In fact, you may actually write it as C1·| 1 〉, or just reverse the order and write C1| 1 〉. However, that’s not common practice and so I won’t do that, except occasionally. So you should look at | 1 〉 C1 as a product indeed: it’s the product of a base state and a complex number, so it’s really like m·v, or whatever other product of some scalar and some vector, except that we’ve got a complex scalar here. […] Yes, I know the term ‘complex scalar’ doesn’t make sense, but I hope you know what I mean. 🙂

More generally, we write:

Writing our state vector | ψ 〉, | φ 〉 or | χ 〉 like this also defines these coefficients or coordinates Ci. Unlike our state vectors, or our base states, Cis an actual number. It has to be, of course: it’s the complex number that makes sense of the whole expression. To be precise, Cis an amplitude, or a wavefunction, i.e. a function depending on both space and time. In our previous posts, we limited the analysis to amplitudes varying in time only, and we’ll continue to do so for a while. However, at some point, you’ll get the full picture.

Now, what about the supposed similarity between the 〈 i | j〉 bra-ket and the ei·ej product? Let me invoke what Feynman, tongue-in-cheek as usual, refers to as the Great Law of Quantum Mechanics:

You get this by taking | ψ 〉 out of the | ψ 〉 = ∑| i 〉〈 i | ψ 〉 expression. And, no, don’t say: what nonsense! Because… Well… Dirac’s notation really is that simple and powerful! You just have to read it from right to left. There’s an order to the symbols, unlike what you’re used to in math, because you’re used to operations that are commutative. But I need to move on. The upshot is that we can specify our base states in terms of the base states too. For example, if we have only two base states, let’s say I and II, then we can write:

| I 〉 = ∑| i 〉〈 i | 1 〉 = 1·| I 〉 + 0·| II 〉 and | II 〉 = ∑| i 〉〈 i | II 〉 = 0·| 1 〉 + 0·| II 〉

We can write this using a matrix notation:

Now that is silly, you’ll say. What’s the use of this? It doesn’t tell us anything new, and it also does not show us why we should think of the 〈 i | j 〉 bra-ket and the ei·ej product as being similar! Well… Yes and no. Let me show you something else. Let’s assume we’ve got some state χ and φ, which we specify in terms of our chosen set of base states as | χ 〉 = ∑ | i 〉 Di and | φ 〉 = ∑ | i 〉 Ci respectively. Now, from our post on quantum math, you’ll remember that 〈 χ | i 〉 and 〈 i | χ 〉 are each other’s complex conjugates, so we know that 〈 χ | i 〉 = 〈 i | χ 〉* = Di*. So if we have all Ci = 〈 i | φ 〉 and all Di = 〈 i | χ 〉, i.e. the ‘components’ of both states in terms of our base states, then we can calculate 〈 χ | φ 〉 – i.e. the amplitude to go from some state φ to some state χ as:

〈 χ | φ 〉 = ∑〈 χ | i 〉〈 i | φ 〉 =∑ Di*C= ∑ Di*〈 i | φ 〉

We can now scrap | φ 〉 in this expression – yes, it’s the power of Dirac’s notation once more! – so we get:

Now, we can re-write this using a matrix notation:

[I assumed that we have three base states now, so as to make the example somewhat less obvious. Please note we can never leave one of the base states out when specifying a state vector, so it’s not like the previous example was not complete. I’ll switch from two-state to three-state systems and back again all the time, so as to show the analysis is pretty general. To visualize things, think of the ammonia molecule as an example of a two-state system versus the spin of a proton or an electron as a three-state system, respectively. OK. Let’s get back to the lesson.]

You’ll say: so what? Well… Look at this:

I just combined the notations for 〈 I | and | III 〉. Can you now see the similarity between the the 〈 i | j〉 bra-ket and the ei·ej product? It really is the same: you just need to respect the subtleties in regard to writing the 〈 i | and | j 〉 vector, or the eand ej vectors, as a row vector or a column vector respectively.

It doesn’t stop here, of course. When learning about vectors in high school, we also learned that we could go from one set of base vectors to another by a transformation, such as, for example, a rotation, or a translation. We showed how a rotation worked in one of our post on two-state systems, where we wrote:

So we’ve got that transformation matrix, which, of course, isn’t random. To be precise, we got the matrix equation above (note that we’re back to two states only, so as to simplify) because we defined the Cand CII coefficients in the | φ 〉 = | I 〉 CI + | II 〉 CII = | 1 〉 C1 + | 2 〉 C2 expression as follows:

• C= 〈 I | ψ 〉 = (1/√2)·(C1 − C2)
• CII = 〈 II | ψ 〉 = (1/√2)·(C1 + C2)

The (1/√2) factor is there because of the normalization condition, and the two-by-two matrix equals the transformation matrix for a rotation of a state filtering apparatus about the y-axis, over an angle equal to (minus) 90 degrees, which we wrote as:

I promised I’d say something more about confusing terminology so let me do that here. We call a set of base states a ‘representation‘, and writing a state vector in terms of a set of base states is often referred to as a ‘projection‘ of that state into the base set. Again, we can see it’s sort of a mathematical projection, rather than a geometrical one. But it makes sense. In any case, that’s enough on state vectors and base states.

Let me wrap it up by inserting one more matrix equation, which you should be able to reconstruct yourself:

The only thing we’re doing here is to substitute 〈 χ | and | φ 〉 for ∑ Dj*〈 j | and ∑ | i 〉 Ci respectively. All the rest follows. Finally, I promised I’d tell you the difference between a state and a state vector. It’s subtle and, in practice, the two concepts refer to the same. However, we write a state as a state, like ψ or, if it’s a base state, like I, or ‘up’, or whatever. When we say a state vector, then we think of a set of numbers. It may be a row vector, like the 〈 χ | row vector with the Di* coefficients, or a column vector, like the | φ 〉 column vector with the Di* coefficients. But so if we say vector, then we think of a one-dimensional array of numbers, while the state itself is… Well… The state. So that’s some reality in physics. So you might define the state vector as the set of numbers that describes the state. While the difference is subtle, it’s important. It’s also important to note that the 〈 χ | and | χ 〉 state vectors are different too. The former appears as the final state in an amplitude, while the latter describes the starting condition. The former is referred to as a bra in the 〈 χ | φ 〉 bra-ket, while the latter is a ket in the 〈 φ | χ 〉 = 〈 χ | φ 〉* amplitude. 〈 χ | is a row vector equal to ∑ Di*〈 i |, while | χ 〉 = ∑ D| χ 〉. So it’s quite different. More in general, we’d define bras and kets as row and column vectors respectively, so we write:

That makes it clear that a bra next to a ket is to be understood as a matrix multiplication. From what I wrote, it is also obvious that the conjugate transpose (which is also known as the Hermitian conjugate) of a bra is the corresponding ket and vice versa, so we write:

Let me formally define the conjugate or Hermitian transpose here: the conjugate transpose of an m-by-n matrix A with complex elements is the n-by-m matrix A† obtained from A by taking the transpose (so we write the rows as columns and vice versa) and then taking the complex conjugate of each element (i.e. we switch the sign of the imaginary part of the complex number). A† is read as ‘A dagger’, but mathematicians will usually denote it by A*. In fact, there are a lot of equivalent notations, as we can write:

OK. That’s it on this.

One more thing, perhaps. We’ll often have states, or base states, that make sense, in a physical sense, that is. But it’s not always the case: we’ll sometimes use base states that may not represent some situation we’re likely to encounter, but that make sense mathematically. We gave the example of the ‘mathematical’ | I 〉 and | II 〉 base states, versus the ‘physical’ | 1 〉 and | 2 〉 base states, in our post on the ammonia molecule, so I won’t say more about this here. Do keep it in mind though. Sometimes it may feel like nothing makes sense, physically, but it usually does mathematically and, therefore, all usually comes out alright in the end. 🙂 To be precise, what we did there, was to choose base states with a unambiguous, i.e. a definite, energy level. That made our calculations much easier, and the end result was the same, indeed!

So… Well… I’ll let this sink in, and move on to the next topic.

The Hamiltonian operator

In my post on the post on the Hamiltonian, I explained that those Ci and Di coefficients are usually a function of time, and how they can be determined. To be precise, they’re determined by a set of differential equations (i.e. equations involving a function and the derivative of that function) which we wrote as:

If we have two base states only, then this set of equations can be written as:

Two equations and two functions – C= C1(t) and C= C2(t) – so we should be able to solve this thing, right? Well… No. We don’t know those Hij coefficients. As I explained in that post, they also evolve in time, so we should write them as Hij(t) instead of Hij tout court, and so it messes the whole thing up. We have two equations and six functions really. Of course, there’s always a way out, but I won’t dwell on that here—not now at least. What I want to do here is look at the Hamiltonian as an operator.

We introduced operators – but not very rigorously – when explaining the Hamiltonian. We did so by ‘expanding’ our 〈 χ | φ 〉 amplitude as follows. We’d say the amplitude to find a ‘thing’ – like a particle, for example, or some system, of particles or other things – in some state χ at the time t = t2, when it was in some state φ state at the time t = t1 was equal to:

Now, a formula like this only makes sense because we’re ‘abstracting away’ from the base states, which we need to describe any state. Hence, to actually describe what’s going on, we have to choose some representation and expand this expression as follows:

That looks pretty monstrous, so we should write it all out. Using the matrix notation I introduced above, we can do that – let’s take a practical example with three base states once again – as follows:

Now, this still looks pretty monstrous, but just think of it. We’re just applying that ‘Great Law of Quantum Physics’ here, i.e. | = ∑ | i 〉〈 i | over all base states i. To be precise, we apply it to an 〈 χ | A | φ 〉 expression, and we do so twice, so we get:

Nothing more, nothing less. 🙂 Now, the idea of an operator is the result of being creative: we just drop the 〈 χ | state from the expression above to write:

Yes. I know. That’s a lot to swallow, but you’ll see it makes sense because of the Great Law of Quantum Mechanics:

Just think about it and continue reading when you’re ready. 🙂 The upshot is: we now think of the particle entering some ‘apparatus’ A in the state ϕ and coming out of A in some state ψ or, looking at A as an operator, we can generalize this. As Feynman puts it:

“The symbol A is neither an amplitude, nor a vector; it is a new kind of thing called an operator. It is something which “operates on” a state to produce a new state.”

Back to our Hamiltonian. Let’s go through the same process of ‘abstraction’. Let’s first re-write that ‘Hamiltonian equation’ as follows:

The Hij(t) are amplitudes indeed, and we can represent them in a 〈 i | Hij(t) | j 〉 matrix indeed! Now let’s take the first step in our ‘abstraction process’: let’s scrap the 〈 i | bit. We get:

We can, of course, also abstract away from the | j 〉 bit, so we get:

Look at this! The right-hand side of this expression is exactly the same as that A | χ 〉 format we presented when introducing the concept of an operator. [In fact, when I say you should ‘abstract away’ from the | j 〉 bit, then you should think of the ‘Great Law’ and that matrix notation above.] So H is an operator and, therefore, it’s something which operates on a state to produce a new state.

OK. Clear enough. But what’s that ‘state’ on the left-hand side? I’ll just paraphrase Feynman here, who says we should think of it as follows: “The time derivative of the state vector |ψ〉 times i is equal to what you get by (1) operating with the Hamiltonian operator H on each base state, (2) multiplying by the amplitude that ψ is in the state j (i.e. 〈j|ψ〉), and (1) summing over all j.” Alternatively, you can also say: “The time derivative, times iħ, of a state |ψ〉 is equal to what you get if you operate on it with the Hamiltonian.” Of course, that’s true for any state, so we can ‘abstract away’ the |ψ〉 bit too and, putting a little hat (^) over the operator to remind ourselves that it’s an operator (rather than just any matrix), we get the Hamiltonian operator equation:

Now, that’s all nice and great, but the key question, of course, is: what can you do with this? Well… It turns out his Hamiltonian operators is useful to calculate lots of stuff. In the first place, of course, it’s a useful operator in the context of those differential equations describing the dynamics of a quantum-mechanical system. When everything is said and done, those equations are the equivalent, in quantum physics, of the law of motion in classical physics. [And I am not joking here.]

In addition, the Hamiltonian operator also has other uses. The one I should really mention here is that you can calculate the average or expected value (EV[X]) of the energy  of a state ψ (i.e. any state, really) by first operating on | ψ 〉 with the Hamiltonian, and then multiplying 〈 ψ | with the result. That sounds a bit complicated, but you’ll understand it when seeing the mathematical expression, which we can write as:

The formula is pretty straightforward. [If you don’t think so, then just write it all out using the matrix notation.] But you may wonder how it works exactly… Well… Sorry. I don’t want to copy all of Feynman here, so I’ll refer you to him on this. In fact, the proof of this formula is actually very straightforward, and so you should be able to get through it with the math you got here. You may even understand Feynman’s illustration of it for the ‘special case’ when base states are, indeed, those mathematically convenient base states with definite energy levels.

Have fun with it! 🙂

Post scriptum on Hilbert spaces:

As mentioned above, our state vectors are actually functions. To be specific, they are wavefunctions, i.e. periodic functions, evolving in space and time, so we usually write them as ψ = ψ(x, t). Our ‘Hilbert space’, i.e. our collection of state vectors, is, therefore, often referred to as a function space. So it’s a set of functions. At the same time, it is a vector space too, because we have those addition and multiplication operations, so our function space has the algebraic structure of a vector space. As you can imagine, there are some mathematical conditions for a space or a set of objects to ‘qualify’ as a Hilbert space, and the epithet itself comes with a lot of interesting properties. One of them is completeness, which is a property that allows us to jot down those differential equations that describe the dynamics of a quantum-mechanical system. However, as you can find whatever you’d need or want to know about those mathematical properties on the Web, I won’t get into it. The important thing here is to understand the concept of a Hilbert space intuitively. I hope this post has helped you in that regard, at least. 🙂

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