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Hello, bonjour, sdravo, ia orana,

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welcome to the fifth tutorial of Statistical Mechanics: Algorithms and Computations,

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from the Physics Department of Ecole Normale supérieure.

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In this week's lecture, we made our first move into quantum mechanics

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and quantum statistical mechanics.

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We used two languages. The first language is the one of wavefunctions

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and of quantized energy levels, both solutions of the Schroedinger equation.

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For the harmonic potential, this is what we studied in harmonic_wavefunctions.py.

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Besides this traditional approach to quantum mechanics, we also employed the language of density matrices.

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This lead us directly to matrix squaring

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to the Feynman path integral and to path integral Monte Carlo simulations.

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To make the connection between wavefunctions on the one hand

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and path integrals on the other, we must provide the missing link

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the density matrix at small beta, that holds the path together.

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This is like a spring constant

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of our quantum mechanical elastic object

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We will arrive at this connection between Schroedinger and Feynman in two steps

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First, in what follows

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Michael will actually compute the density matrix for a free particle

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and derive and illustrate a result that was already presented in the lecture.

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He will then extend this simplest of all calculations

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using the path integral representation.

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Then, Alberto will derive and explain

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the Trotter decomposition.

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Remember: among the three properties of the density matrix

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this was the one which allowed to incorporate

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arbitrary interaction at high temperature.

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This simulation knows

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about the free density matrix and the Trotter decomposition

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but not about much else.

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And certainly not about the solutions of the Schroedinger equation.

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So, now in these simulations

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let us spend a moment to speak about the axis.

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In the wavefunction picture, the axis are the position x and the energy level E.

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So things are clear.

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But in the path integral picture, the axes here is again x, the position

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but the y axis refers an "inverse temperature like" variable, tau.

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In quantum statistical mechanics, we call this variable the imaginary time,

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and this mysterious name adds to the fascination of path integrals.

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Vivien, in the last part of this tutorial,

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will tell us about the relationship between temperature and time.

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He will convince us that the Trotter decomposition at high temperature

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can also be used at small times.

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This will allow you to simulate time evolution on the computer,

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and to see some of the amazing effect of quantum physics, like the quantum tunneling effect.

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But now, let us listen to Michael

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explain to us the whence and the whither of the free density matrix

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and how it combines with the language of path integrals.

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As Werner mentioned in this week lecture

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we are able to explicitly write down the density matrix of a particle

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in an arbitrary potential V. We do this by use of the Trotter decomposition formula.

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Unfortunately, though, this approach is limited to the high-temperature regime.

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On the contrary, for a free particle (that is the case V=0)

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we are actually able to calculate an exact result which is valid at any temperature.

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So let us see how this is done.

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As in this week's lecture, we consider the Schroedinger's equation,

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and in the case of the free particle it reduces to the expression shown here.

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This is simply a wave equation

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and you can easily convince yourself that it is satisfied by any sine or cosine wave

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as sine and cosine simply reproduce themselves

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in the second derivative, up to a sign and a scaling factor.

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When we put the particle into a box of size L

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say with periodic boundary conditions

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then we can only use sine or cosine waves

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whose period is equal to the box length L.

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Other waves simply don't fit.

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The complete set of waves that do fit is shown here

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The superscripts denote symmetric and antisymmetric wavefunctions

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with respect to the center of the interval from 0 to L.

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You see one ground-state

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and the symmetric and antisymmetric solutions

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for each excited state, with the energies E_n

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= 2 pi^2 n^2 / L^2.

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In Python, this gives the following program

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it is analogous to the program harmonic_wavefunction.py

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that was introduced by Werner in this week's lecture

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and it computes the density matrix by summing over all states.

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So let us have a look at the density matrix

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by simply plotting the results of our little program.

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The stripe on the diagonal of the matrix

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indicated that the density matrix rho_free(x, x', beta)

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is in fact a function of x-x' only.

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This means that rho_free is translation invariant

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as the individual values of x and x' do not matter.

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only the distance x-x' counts.

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rho_free is largest on the diagonal

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In fact at high temperature (that is small beta)

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it is all concentrated on the diagonal, where x=x'.

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As we lower the temperature, we see that the off-diagonal part

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become larger and larger with increasing beta.

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This is the famous coherence, that is governed by the thermal De Broglie wavelength.

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Now let us do a small calculation

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but for simplicity, we will not use the sines and cosines

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but rather the equivalent complex exponential wavefunctions.

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You can actually check this equivalence by writing a small Python program.

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When you compare the output of this program to the output of the previous program, you will see

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that it arrives exactly at the same results as before.

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However, we promised an exact expression

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for the free density matrix, so let us now calculate it.

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Using the complex exponential wavefunctions

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the density matrix is given by this expression

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where you notice that each term is in fact a complex number.

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At first glance this seems a bit strange as we know that the finite result will be real.

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This is because for each complex number in the sum

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there's a complex conjugate counterpart and together they become real.

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Having the particle in a box of size L

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is no true limitation, as we can let L go to infinity

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and replace the sum over n by an integral.

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This may sound difficult, but it can be easily understood

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when we introduce a dummy parameter delta_n = 1,

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difference between two successive n values.

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We then change the variables from n to lambda

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with lambda = 2 pi n / L

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Thus we have delta_lambda = 2 pi delta_n / L

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This leads to this term by term equivalent sum

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where we use this result

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which follows when we take ctilde = c / sigma^2, from the Gaussian integral.

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This Gaussian integral was already evaluated in Lecture 4, last week's lecture.

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We finally arrive at the free density matrix

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where we have reinserted Planck constant hbar

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and the particle mass m.

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The free density matrix is indeed a function of x-x'

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and see how at large temperatures (that is small beta)

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rho_free becomes infinitely peaked

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at the diagonal x=x', as we noticed earlier.

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Note in particular that the density matrix is positive, not only on the diagonal but everywhere.

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For us Monte Carlo specialists

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this is important as you can interpret the density matrix as a probability.

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Now in this calculation

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we made a transformation from a sum to an integral

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when taking the limit L to infinity.

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But what is the density matrix of a finite box with periodic boundary conditions, that is for finite L?

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The above sum can be evaluated using the famous Poisson's sum rule

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and the result is really simple.

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The parameter w is called the winding number and you will see in a moment where this name comes from.

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The density matrix rho(x,x',beta) is made up

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of all the paths

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(in Feynman's path integral picture) that go from x to x' directly

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plus all the paths that wind around the box

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once, that is they have the winding number w=1

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plus all the paths that wind around the box twice and so on and so on for higher winding numbers.

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Of course, we can also wind a path to the left, corresponding to negative winding numbers.

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This concept of winding number will come in handy two weeks from now.

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It is key to understand Bose-Einstein condensation.

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So we have now obtained the free density matrix at all temperatures and it is a Gaussian of x-x'

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with a normalization 1 / sqrt(2 pi beta)

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and a variance of beta.

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Alberto will determine a general expression

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for all potentials at high temperatures, using the Trotter formula.

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But before you go on, please take a moment or three to download, run and modify the programs discussed in this section.

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On the Coursera website, you will find the program free_periodic_sine_cosine.py and its cousin

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free_periodic_complex_exp.py

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Take these programs apart to understand the inner workings of complex arithmetics

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that lead to a final real-valued and positive result.

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As explained by Michael, for a free particle we can compute exactly the density matrix

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this is of great importance

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as we can compute the general density matrix - so to speak - which grows from this seed, as we will discuss

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For what follows

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you must understand that rho(x,x',beta) is a matrix of two indices

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x and x', but it is also an operator: exp(- beta H)

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The matrix elements of the Hamiltonian H can be written in an arbitrary basis

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and in this basis the matrix elements of rho write like this

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This expression can be familiar to those of you who have studied a little bit of quantum mechanics

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but for all of you, please retain that the density matrix

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is an operator, the exponential of minus beta H

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it is the direct generalization of the Boltzmann distribution

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Let us now consider the density matrix of a system with the following Hamiltonian

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H = Hfree + V

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where Hfree is the Hamiltonian discussed by Michael

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and V is the interaction potential, that for the harmonic oscillator is (1/2) x^2

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Now, the Trotter decomposition corresponds to the following expression.

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To see that this is true, we will expand both terms up to the order beta^2

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but attention, Hfree and V are operators

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the product V Hfree can be different from Hfree V.

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Operators, matrices in general do not commute.

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So, let's start from the second term of this equation

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We can first expand exp( (-beta/2) V(x))

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'a' corresponds to the linear term in beta, and 'b' to the second order term

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Then we expand rho_free

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'c' is the linear term and 'd' is the second order term,

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finally we can also expand exp(-(beta/2) V(x'))

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So let's reorganize these terms order by order in beta.

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At the zero order we have one.

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At the first order in beta, we have a+c+e

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and then we need a little bit of work to write the second order term

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This expression fully agrees with the direct expansion of the full density matrix

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These two equations prove

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that the Trotter expansion is correct up to beta^2.

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Please note that this manipulations

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are valid on operators and wavefunctions

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in a finite box.

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In Python we can implement the Trotter's decomposition using Michael's approach,

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and plot the entire density matrix at high temperature.

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Remember: the free density matrix

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rho_free(x,x',beta)

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is a function of x-x'

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and this gives the nice stripe in this diagram.

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Now let us add the harmonic potential V to the Trotter decomposition.

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You see that for large x and x' the density matrix is suppressed

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and this is what keeps close to the origin the quantum harmonic oscillator.

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In this week's homework, you will use

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both the Trotter decomposition

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and the convolution properties

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to compute the density matrix up to very low temperatures.

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As you must square the matrix many times, the approximation errors will grow

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However, the quality of this approximation (correct up to beta^2) is so high that it will survive

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up to low temperatures.

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The Trotter break-up is completely general:

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it applies to an arbitrary potential

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and (as will be shown by Vivien in a moment)

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it can be even turned around to describe the real time evolution of the system.

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But before understanding why the inverse temperature beta is an imaginary time,

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please take a moment to download, run and modify

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the program harmonic_trotter_movie.py

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which implements the Trotter decomposition and provides a nice graphical output.

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You can check this approximation

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and actually in this week's homework

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you will test this approximation against the output of harmonic_wavefunctions.py

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In this section we examine a complementary problem

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which is the time evolution of a quantum system

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Werner, Michael and Alberto have explained to you

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in the previous sequences

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how to describe a quantum system at finite temperature

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in equilibrium, by the use of the density matrix

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However, in general, systems are described by

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a wavefunction psi(t) which evolves in time.

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So, if we fix this wavefunction psi(t=0)

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to be equal to psi0 at initial time

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it evolves in time according to the Schroedinger equation displayed here

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which is i times dpsi/dt

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= H psi

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and here H is the Hamiltonian of the system

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and we have also fixed the constant hbar to be equal to one.

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To solve this equation, one may be tempted to replace

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the time derivative by a first order approximation

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which is displayed there

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but this is not an option in our case because this would break the conservation of probability.

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A better choice is to consider the operator solution

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of this equation, which writes as follows

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It is psi(t) = exp(-i H t)

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times the initial vector psi(0)

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You may indeed check, by differentiating with respect to t

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that this expression is the solution of the Schroedinger equation

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with initial condition psi(t=0)=psi0.

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Now, let's have a closer look to this formula.

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You note that by formally replacing

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(i t) by beta

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that is to say, by working in imaginary time

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you obtain the very same expression as that of the density matrix

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that we know for a quantum system at equilibrium at inverse temperature beta.

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So this relation provides us a dictionary

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a mathematical dictionary between time evolution and thermal equilibrium.

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It is not only beautiful from the abstract point of view

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but also very useful in practice

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Indeed, you can apply what Alberto has told you

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about the Trotter expansion

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to devise an algorithm which allows you

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to study very efficiently the evolution of quantum systems

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Let us now focus our attention to a particle at position x

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in a potential V(x) in dimension 1

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If we set the mass of the particles to be m=1, its evolution

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is governed by the Schroedinger equation

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of Hamiltonian H = Hfree + V(x)

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The idea is to decompose the full time interval t

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into N time steps of duration delta_t = t / N

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The full operator of evolution is now expressed exactly as a product of N

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infinitesimal operator of evolution, as displayed here.

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Each of these infinitesimal operators of evolution writes exp(-i delta_t H)

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Now to understand the contribution

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of the components Hfree and V(x) of this Hamiltonian

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we can use Alberto's Trotter decomposition, which writes as follows

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You recognize the same formula, where beta has been replaced by (i delta_t)

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This approximation is valid up to order delta_t ^2

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that is to say, the first error term is of order delta_t^3.

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Let us examine each term of this product

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the first and the last term are easy to understand

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they consist in the multiplication by the same factor exp(-(i/2) delta_t V(x))

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The free term is a bit enigmatic

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but the mystery is lifted by transforming the wavefunction to Fourier space

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for the spatial coordinate.

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This consists in going from the real space psi(x,t)

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to the momentum space psi_hat(p,t)

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You will easily convince yourself - for instance by reading the short fact-sheet associated to this tutorial 5 -

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that the action of the free operator

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consists in a multiplication by a factor exp(- (i/2) p^2)

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So, the action of this operator is just the multiplication by a Gaussian factor.

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This provides a possible scheme to devise an algorithm which is the following:

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first, define the initial wavefunction, then

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discretize the time interval t into N time slices of duration delta_t,

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define the Fourier procedure,

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and apply the Trotter formula many times.

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At each time step

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first in real space, multiply by a factor exp(-(i/2) delta_t V(x)),

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make a Fourier transformation,

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multiply by exp(- (i/2) p^2 delta_t),

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and go back to the real space multiplying by the same factor as previously.

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This is the only step, you just have to iterate and it gives the following beautiful algorithm

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quantum_time_evolution.py.

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This method is really powerful.

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To illustrate it, let's consider the fate of a quantum particle confined between two barriers:

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an infinite barrier on its left and a finite barrier on its right.

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The particle starts from some position between the two walls.

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If the particle were classical, it would bounce forever between the two walls.

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You observe that each time the wavefunction bounces on the wall on the right

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a finite but tangible proportion of the wave actually goes through the wall.

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This quantum tunneling effect is a genuine quantum effect and has no classical counterpart.

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We have illustrated how our mathematical dictionary between

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real time and imaginary time

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has allowed us to observe the quantum tunneling effect in a simple one-dimensional situation.

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However, have in mind that the very same effect

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has deep physical consequences

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from for instance the radioactive decay to the construction of the transistor in the CPUs of your computer,

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or in more complex situation to the devise of the scanning tunneling microscope,

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or even to the evaporation of black holes.

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It is now time for you to download, run and modify

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the beautiful program we have seen in this section: quantum_time_evolution.py.

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Check it out.

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See by yourself how a quantum particle can tunnel through a wall

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and program maybe some other exciting potentials

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Take also a look to the fact-sheet which explains to you how the Fourier transform from x

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to p is implemented in practice.

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In this tutorial

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we zoomed in to the density matrix and its three main properties

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the convolution, the free density matrix and the Trotter decomposition

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we already perceive the plot of these three stage characters

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that prepare for a great story and that will lead us to quite complicated situations

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In what Alberto and Michael told us

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the density matrix remains positive and real

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allowing us to interpret it as a probability, and to do quantum Monte Carlo.

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This positivity is preserved for many particles,

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arbitrary interactions, and even for bosons

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It is broken in the case of fermionic particles

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In what Vivien told us

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in the time-evolution all of this was broken also

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the density matrix was complex-valued and it could be negative

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The great algorithm produced only works in one-dimension

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because quantum time evolution is a really hard nut to crack

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So now it is time for you

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to look at how these three characters that we described

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intervene in practice

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and we wish you good luck and a lot of fun with the homework session 5.