Logistics

  • Book(s)
    • Landau and Lifshitz
    • Kardar
    • Pathria

Thermodynamics

0th Law

  • Thermodynamic equilibrium means that each object in thermal contact with each other have the same temperature
    • Ideal gases, as you cool them down, all converge to a single point, which defines absolute zero. For Kelvin,, the triple point of water defines the size of each step on the scale (273.16 K)

1st Law

  • $dE = \delta W + \delta Q$
    • The change is energy can either come from work, or heat
    • $dE = E_{f}-E_{i}$
      • Energy is a function of state (path independent)
    • $\delta W$ and $\delta Q$ are path dependent
    • Can expand out $\delta W$ into more parts:
      • $dE = -p dV + \delta Q$, where the negative sign comes from the fact that the system does work on the outside environment
        • You don’t need to be restricted to pressure and volume. In general, you can have some “displacements” $\chi_{i}$ (ie. extensive quantities) and their conjugate forces $J_{i}$ (ie. intensive quantities) to get that $dW = \Sigma_{i} J_{i} d\chi_{i}$

Response Functions

  • Response function characterize the macroscopic behavior of a system
  • Heat Capacity:
    • $C_{V} = (\frac{dQ}{dT})_{V}$
    • $C_{P} = (\frac{dQ}{dT})_{P}$
      • This is always large than $C_{V}$ since some of the heat is used up in the work done in changes in volume
  • Force constants
    • the isothermal compressibility of gas : $\kappa_{T} = -(\frac{\partial V}{\partial P})_{T}/V $
    • the susceptibility of a magnet $\chi_{T} = (\frac{\partial M}{\partial B})_{T}/V$
  • Thermal Responses:
    • Things like the expansitivity of a gas, given by $\alpha_{p} = \frac{\partial V}{\partial T}|_{P}/V$

2nd Law

  • Efficiency of an ideal heat engine is defined by $\eta = \frac{W}{Q_{H}} = \frac{Q_{H}-Q_{C}}{Q_{H}} \leq 1$
  • The figure of merit for an ideal refrigerator is $\omega = \frac{Q_{C}}{W} = \frac{Q_{C}}{Q_{H}-Q_{C}}$
  • Kelvin formulation of 2nd Law: No process is possible whose sole result is the complete conversion of heat into work
  • Clausius’s Statement: No process is possible whose sole result is the transfer of heat from a colder to a hotter body
    • The above two are equivalent: Can show that violation of one implies a violation of another via hooking up outputs of an ideal engine to an ideal refrigerator
  • Carnot’s Theorem: You can’t beat the Carnot engine in terms of efficiency
    • A Carnot cycle is defined by two isotherms at $T_{H}$ and $T_{C}$, and two adiabatic curves linking the isotherms
    • The efficiency of a Carnot engine is defined by $\eta = \frac{T_{H}-T_{C}}{T_{H}}$. This can be derived hooking up two different Carnot engines at 3 temperatures. The heat from one gets dumped to the next. The overall efficiency is then the product of the two, which implies that the efficiency is some ratio of temperatures
      • $1-\eta = \frac{Q_{2}}{Q_{1}} = \frac{T_{2}}{T_{1}}$
  • NOTE: When dealing with engines, try to keep all quantities positive (ie. a positive amount of heat leaves the hot reservoir, a positive amount of work leaves the engine, and a positive amount of heat enters the cold reservoir)

Entropy

  • Clausius’s Theorem: For any cyclic transformation (reversible or not) $\oint \frac{dQ}{T} \leq 0$, where $dQ$ is the heat increment supplied to the system at temperature T
    • Imagine dividing the cycle into a series of infinitesimal portions, where the system receives energy from dQ and dW. Imagine that dQ gets funneled into some Carnot engine which is attached to some reservoir at a fixed temperature $T_{0}$
    • Since the sign of dQ is unspecified, the Carnot engine must be able to run in both directions. In order to do this, the engine must extract some heat $dQ_{R}$ from the fixed reservoir
    • This implies that $dQ_{R} = \frac{T_{0}}{T} dQ$
    • The net effect of this process is that some heat $Q_{R} = \oint dQ_{R}$ is extracted from the reservoir and converted to external work W. By the Kelvin formulation of the 2nd law, $Q_{R} = W \leq 0$ which implies $\oint \frac{dQ}{T} \leq 0$
  • For a reversible cycle, we know $\oint \frac{dQ_{rev}}{T} = 0$ This implies that for a reversible cycle, this integral is independent of the path. We can use this to define the entropy S: $S(B)-S(A) = \int_{A}^{B} \frac{dQ_{rev}}{T}$
  • Imagine that you make an irreversible change from A to B, but make a reversible regression from B to A: $\int_{A}^{B} \frac{dQ}{T}+ \int \frac{dQ_{rev}}{T} \leq 0$ which implies $\int_{A}^{B} \frac{dQ}{T} \leq S(B)-S(A)$
    • This is the statement that entropy always increases or stays the same
  • For a reversible (and/or quasi-static) process, we can write $dQ = TdS$, where T and S and conjugate variables
  • Equilibrium exists when entropy is maximized!
  • For a cyclic process, entropy does not change!

3rd Law

  • Entropy of a closed system in thermodynamic equillibrium approaches a constant value as temperature approaches absolute 0 (typically 0)
  • This also implies that heat capacities and thermal expansivities must go to 0 as T approaches 0

Thermodynamic Potentials

  • The energy gets extremized in equillibrium for an adiabatically isolated system
  • If you are in an out of equillibrium system that is not adiabatically isolated and subject to external work, then you can define other thermodynamic potentials which are extremized in equillibrium

Enthalpy

  • If there is no heat exchange, and the system comes to mechanical equilibrium subject to a constant external force, then enthalpy is the appropriate potential
    • Can be though of as minimizing the energy, plut the work from the external agent
  • $H = E- \vec{J}\cdot \vec{x}$
  • $dH = dE -d(J\cdot x)$ (Just the legendre transform w.r.t. J and x)

Helmhotz Free Energy

  • For isothermal transformations in the absence of mechanical work (dW=0)
  • F = E-TS (Legendre transform w.r.t. T and S)

Gibbs Free Energy

  • For isothermal transformations involving mechanical work at constant external force
  • $G = E-TS-J\cdot x$
    • Legendre transform in both T,S and J,x

Grand Potential

  • What if the number of particles in the system changes? we can define the chemical work as $dW = \vec{\mu} \cdot d\vec{N}$, where each species has it’s own chemical potential
  • We can introduce this work by simply adding this work to a potential

Probability

Definitions

  • Random variable x has a set of outcome S (can be continuous or discrete)
  • An event is a subset of outcomes from S, and is assigned a probability
  • Probabilities must obey the following rules
    • They must be greater than or equal to 0
    • They must be additive if the events subsets are disjoint
    • They must be normalizable (ie. probability of S should be 1)
  • a cumulative probability function (CPF) denoted P(x) is the probability of an outcome with any value less than x
    • P(x) must be a monotonically increasing function of x
    • $P(-\infty) = 0$ and $P(\infty) = 1$
  • a probability density function (PDF) is defined by $p(x) = \frac{dP(x)}{dx}$
    • This must satisfy $\int p(x) dx = 1$
  • The expectation value of any function F(x) of the random variable is $<F(x)> = \int_{-\infty}^{\infty} dx p(x) F(x)$
    • Easily extendable to multiple dimensions
  • The moments of a PDF are expectation values for power of the random variable
    • The nth moment is $m_{n} = <x^{n}> = \int dx p(x) x^{n}$
  • The characteristic function is the generator of moments of the distribution. It’s just the Fourier transform of the PDF
    • $\tilde{p}(k) = \int dx p(x) exp(-ikx)$
    • The PDF can be recovered from the characteristic function via the inverse Fourier transform $p(x) = \frac{1}{2\pi} \int dk \tilde{p}(k) exp(ikx)$
    • The moments can be calculated by expanding $\tilde{p}(k)$ in powers of k: $\tilde{p}(k) = \Sigma_{n=0}^{\infty} \frac{(-ik)^{n}}{n!}<x^{n}>$
    • Moments of the PDF around any $x_{0}$ can also be generated by substituting x for $x-x_{0}$ in the moment generation
  • The cumulant generation function is the logarithm of the characteristic function
    • You can generate cumulants of the distribution by expansions in powers of x: $ln \tilde{p}(k) = \Sigma_{n=1}^{\infty} \frac{(-ik)^{n}}{n!}<x^{n}>_{c}$
    • Moments can be related to cumulants by using $\ln(1+\epsilon) = \Sigma_{n=1}^{\infty} (-1)^{\epsilon+1} \frac{\epsilon^{n}}{n}$ to expand out $\ln\tilde{p}(k)$
  • A Joint PDF is the probability density of many variables. If all variables are independent, this is just the product of the individual pdfs
  • Stirling’s approximation for N! holds for very large N. This states that
    • $ln(N!) \approx N ln N - N + \frac{1}{2}ln(2\pi N)$

Important Probability Distributions

  • Gaussian: $p(x) = \frac{1}{\sqrt{2\pi \sigma^{2}}} exp(- \frac{(x-\lambda)^{2}}{2\sigma^{2}})$
    • The characteristic function is $\tilde{p}(k) = exp(-ik\lambda-\frac{k^{2}\sigma^{2}}{2})$
    • Only the first two cumulants are non-zero
    • Multidimensional version is $p(x) = \frac{1}{\sqrt{(2\pi)^{N}det(C)}}exp(\frac{-1}{2}\Sigma_{mn}C_{mn}^{-1}(x_m-\lambda_{m})(x_{n}-\lambda_{n}))$
      • C is the a positive definite symmetric matrix
  • Binomial: $p_{N}(N_{A}) = \binom{N}{N_{A}} p_{A}^{N}p_{B}^{N-N_{A}}$
    • Characteristic function is $\tilde{p}(k) = (p_{A}e^{-ik}+p_{B})^{N}$
  • Poisson Distribution
    • This is the limit of the binomial distribution. We want to find the probability of observing N decays in time interval T. Subdivide the interval into $N = \frac{T}{dt} » 1$
      • In each interval, the chance of an event occuring os $p_{A} = \alpha dt$ and the chance of no event in the interval is $p_{B} = 1-\alpha dt$
      • This implies the characteristic function is $\tilde{p}(k) = (p_{A}exp(-ik)+p_{B})^{N} = lim_{dt\rightarrow 0}(1+\alpha dt (e^{-ik}-1))^{\frac{T}{dt}} = exp(\alpha(e^{-ik}-1)T)$
      • Taking the inverse Fourier transform yields the Poisson PDF: $p(x) = \int_{-\infty}^{\infty} \frac{dk}{2\pi} e^{ikx} \Sigma_{M=0}^{\infty} \frac{(\alpha T)^{M}}{M!}e^{-ikM}$ (using power series for the exponential)
      • Using the identity $\int_{-\infty}^{\infty} \frac{dk}{2\pi} exp(ik(x-M)) = \delta(x-M)$, which implies $p_{\alpha,T}(M) = e^{-\alpha T}\frac{(\alpha T)^{M}}{M!}$

Kinetic Theory of Gases

  • We want to be able to connect macroscopic properties of systems to the microscopic picture of particles
  • Imagine a 6N dimensional phase space, where time evolution of each particle is governed by Hamilton’s equations
    • $\dot{q_{i}} = \frac{\partial H}{\partial p_{i}}$
    • $-\dot{p_{i}} = \frac{\partial H}{\partial q_{i}}$
  • We can consider some probability density $\rho(p,q,t)$ which describes the density of particles in that region of phase space
  • We can compute macroscopic values for functions $O(p,q)$ via $<O> = \int \Gamma \rho(p,q,t) O(p,q)$

Liouville’s Theorem

  • Concisely, Liouville’s Theorem states that $\rho$ behaves like an incompressible fluid
  • The proof is as follows:
    • Imagine that you Taylor expand out all the q and p’s as a function of time
    • The volume of phase space before is simply $\Pi_{i} dq_{i}dp_{i}$
    • The volume of phase space after is then the dot product of the Taylor expanded momenta and position. You can use Hamilton’s equations to eliminate the time dependent portion of the expansion, which implies that the phase space volume is unchanged
  • A consequence of this is that $\frac{d\rho}{dt} = \frac{\partial \rho}{\partial t}+\Sigma_{\alpha=1}^{3N} (\frac{\partial \rho}{\partial p_{\alpha}}\frac{dp_{\alpha}}{dt}+\frac{\partial \rho}{\partial q_{\alpha}}\frac{dq_{\alpha}}{dt}) = 0$
    • Alternatively: $\frac{\partial \rho }{\partial t} = -\{\rho, H\}$, where $\{\}$ is the Poisson bracket
  • Another consequence of this is that $\frac{d<O>}{dt} = <\{O,H\}>$
    • straightforward to prove (integration by parts, and using Hamilton equations gives it)
  • If a density has reached equillibrium, this implies that it’s independent of time. This implies that $\{\rho_{eq},H\}= 0$
    • If $\rho_{eq}$ is a function of the Hamiltonian, then this equation holds
    • This implies that $\rho$ is constant of surfaces of constant energy in phase space
      • This is the basic assumption of statistical mechanics! You have equal probabilities at constant energies

Bogoliubov-Born-Green-Kirkwood-Yvon Hierarchy (BBGKY)

  • For multiple particle, you can generate the s-particle density via $f_{s}(p_{1}…q_{s},t) = \frac{N!}{(N-s)!}\int \Pi_{i=s+1}^{N} dV_{i} \rho(p,q,t) = \frac{N!}{(N-s)!}\rho_{s}(p_{1},…,q_{s},t)$
    • For the one particle case, this can be interpreted as the probability that any one of the N particles has the specified p and q values (easily generalized to s particles)
    • The normalization is $\frac{N!}{(N-s)!}$ (comes from permutations of s particles amongst N indistinguishable particles) and $p_{s}$ is the unconditional PDF for the coordinates of s particles
  • Can imagine a Hamiltonian which is $H = \Sigma_{i=1}^{N} (\frac{p_{i}^{2}}{2m}+U(q_{i}))+\frac{1}{2}\Sigma_{i,j=1}^{N} V(q_{i}-q_{j})$ where U is some external potential and V is a two-body interaction
  • Imagine splitting this hamiltonian into 3 parts
    • $H_{s} = \Sigma_{n=1}^{s}(\frac{p_{n}^{2}}{2m}+U(q_{n}))+\frac{1}{2}\Sigma_{n,m=1}^{N} V(q_{n}-q_{m})$
    • $H_{N-s} = \Sigma_{i=s+1}^{N}(\frac{p_{i}^{2}}{2m}+U(q_{i}))+\frac{1}{2}\Sigma_{i,j=s+1}^{N} V(q_{i}-q_{j})$
    • $H^{’} = \Sigma_{n=1}^{s}\Sigma_{i=s+1}^{N} V(q_{n}-q_{i})$
  • You can write the time evolution of $\rho_{s}$ as $\frac{\partial \rho_{s}}{\partial t} = -\int \Pi_{i=s+1}^{N} dV_{i} \{\rho, H_{s}+H_{N-s}+H^{’}\}$
    • If you take the Poisson bracket of each term, you find that $\frac{\partial f_{s}}{\partial t} = -\{H_{s}, f_{s}\} = \Sigma_{n=1}^{s} \int dV_{s+1} \frac{\partial V(q_{n}-q_{s+1})}{\partial q_{n}}\frac{\partial f_{s+1}}{\partial p_{n}}$
      • Note the hierarchy here: $\frac{\partial f_{s}}{\partial t}$ depends on $\frac{\partial f_{s+1}}{\partial t}$
  • To terminate the hierarchy, we need to be able to neglect some terms. Since all terms have units of inverse time, we can seperate terms according to time scale.
    • $\frac{1}{\tau_{U}}\approx \frac{\partial U}{\partial q}\frac{\partial}{\partial p}$ is some extrinsic time scale, which can be made arbitrarily small by increasing the system size. On the order of 1E-5 sec for length scales of 1E-3 m ($\tau \approx \frac{d}{v}$)
    • $\frac{1}{\tau_{c}}\approx \frac{\partial V}{\partial q}\frac{\partial }{\partial p}$ has some collision time, on the order of 1E-12 sec
      • Longe range interactions are harder to get a collision time
    • There are also collision terms which depend on $f_{s+1}$
      • $\frac{1}{\tau_{x}} \approx \int dV \frac{\partial V}{\partial q}\frac{\partial}{\partial p}\frac{f_{s+1}}{f_{s}}$ where $\tau_{x}$ is the mean free time
      • $\tau_{x} \approx \frac{\tau_{c}}{nd^{3}}$

Boltzmann Equation

  • The Boltzmann equation assumes that the density is much smaller than 1. This allows us to drop the mean free time terms from the equation.
  • The first two equations in the BBGKY hierarchy are
    • $(\frac{\partial}{\partial t} - \frac{\partial U}{\partial q} \frac{\partial}{\partial p }+\frac{p_{1}}{m}\frac{\partial}{\partial q}) f_{1} = \int dV_{2} \frac{\partial V}{\partial q_{1}}\frac{\partial f_{2}}{\partial p_{1}}$
    • $(\frac{\partial}{\partial t}-\frac{\partial U}{\partial q_{1}}\frac{\partial }{\partial p_{1}}-\frac{\partial U}{\partial q_{2}}\frac{\partial}{\partial p_{2}}+\frac{p_{1}}{m}\frac{\partial}{\partial q_{1}}+\frac{p_{2}}{m}\frac{\partial}{\partial q_{2}}-\frac{\partial V(q_{1}-q_{2})}{\partial q_{1}}(\frac{\partial}{\partial p_{1}}-\frac{\partial}{\partial p_{2}}))f_{2} = \int dV_{3} (\frac{\partial V(q_{1}-q_{3})}{\partial q_{1}}\frac{\partial}{\partial p_{1}}+\frac{\partial V(q_{2}-q_{3})}{\partial q_{2}}\frac{\partial}{\partial p_{2}}) f_{3}$
  • With the dilute gas approximation, you can truncate the BBGKY hierarchy by setting the RHS of the 2nd equation to 0
  • It’s also reasonable to expect that at very large distances, the particles become independent (ie. $f_{2}(p_{1},q_{1},p_{2},q_{2},t) \rightarrow f_{1}(p_{1},q_{1},t)f_{1}(p_{2},q_{2},t)$)
  • The final closed form of Boltzmann’s equation is $\frac{\partial f_{1}}{\partial t}-\{H,f_{1}\} = \int d \Gamma_{2} d\Omega \frac{|p_{2}-p_{1}|}{m} \frac{d\sigma}{d\Omega}[f_{1}(\Gamma_{1},t)f_{1}(\Gamma_{2},t)-f_{1}(\Gamma_{1},t)f_{1}(\Gamma_{2},t)]$

H-Theorem

  • The Theorem: If $f_{1}(\vec{p},\vec{q},t)$ satisfies the Boltzmann equation, then $\frac{dH}{dt} \leq 0$, where $H(t) = \int d^{3}\vec{p}d^{3}\vec{q} f_{1} ln f_{1}$
    • H is very closely related to the information content of a one particle PDF
  • The proof is straight forward
    • Take the time derivative of H, and use approximation $\ln (f_{1})+1 \approx \ln f_{1}$
    • Use Boltzmann equation
    • Use some integration by parts to eliminate the streaming terms (ie. $\ln f_{1}(\frac{\partial U}{\partial \vec{q_{1}}}\cdot\frac{\partial f_{1}}{\partial p_{1}}-\frac{\vec{p_{1}}}{m}\cdot \frac{\partial f_{1}}{\partial \vec{q_{1}}})$)
    • Observe that the equation must hold if you swap particle 1 for particle 2. Do the swap, then average the two expressions
    • Make the change of integration variables from the initiators of the collision $(p_{1},p_{2},b)$ to the products of the collision $(p_{1}’,p_{2}’,b’)$
      • We know that the Jacobian is unitary from time symmetry
    • We realize that we can swap the initiators and the products. Do this swap, then average the two equations again
  • The final results is something like $\frac{dH}{dt} = -\frac{1}{4}\int d\Gamma x$ where x is some strictly positive integrand. Hence $\frac{dH}{dt}\leq 0$
  • This is a big deal, since it gives a microscopic explanation to how entropy arises. Make the definition $S = -k_{b} H(T)$, or equivalently, on a microscopic scale: $\sigma(\Gamma,t) = -k_{b} \ln f_{1}(\Gamma,t)$

Classical Statistical Mechanics

Microcanonical Ensemble

  • The microstates are defined by points in phase space, and their time evolution is governed by the Hamiltonian. Since the Hamiltonian is energy conserving, all micro-states are confined to a constant energy surface in phase space
    • This implies that all points on the surface are mutually accessible, which gives the central postulate of stat mech $p(E,x) (\mu) = \frac{1}{\Omega(E,x)}* \delta(H(\mu)-E)$ where $\mu$ enumerate the microstates
      • ie. on the surface, all microstates are equally likely. If you are off the surface, you can’t access it
      • The normalization $\Omega$ is the area of the surface of the constant energy E in phase space. Typically, we define $E-\Delta \leq H(\mu) \leq E+\Delta$, where $\Delta$ is uncertainty in the energy. This allows us to have the normalization be a spherical shell
      • The entropy of this uniform probability distribution is $S = k_{b} \ln \Omega$
        • The overall allowed phase space is the product of individual ones (assuming independent systems)
    • Another consequence of this is that in the microcanonical ensemble, $dE=0$ since we are prescribing a fixed energy

Two State System Example

  • Consider N impurity atoms trapped in a solid matrix. Each impurity can either have energy 0 or $\epsilon$
  • $H = \epsilon\Sigma_{i=1}^{N} n_{i} = \epsilon N_{1}$ where $N_{1}$ is the total number of excited impurities
  • $p(n_{i}) = \frac{1}{\Omega}\delta_{\epsilon,\Sigma_{i}n_{e}E}$
  • $\Omega$ is the number of ways of choosing $N_{1}$ excited levels among the available N atoms. This is just ${N}\choose{N_{1}}$
  • Entropy is just $S = k_{b} \ln \frac{N!}{(N-N_{1})!N_{1}!}$
  • You can use Stirling’s formula to approximate $\ln N! \approx N \ln N -N$
  • You can then get the temperature from $\frac{\partial S}{\partial E} = \frac{1}{T}$, and invert this to get the erngy as a function of temperature
  • You can figure out the occupancy of a particular level by imagining a a small subsystem that is decreased by the energy of that state, with particle number that is one less (ie. $p_{n_{1}} = \frac{\Omega(E-n_{1}\epsilon, N-1)}{\Omega(E,N)}$)

0th Law

  • $\frac{\partial S}{\partial E} = \frac{1}{T}$
    • Think of this as a statement of thermal equilibrium

1st Law

  • $dE = T dS + \vec{J}\cdot d\vec{x}$
    • Alternatively, you can write $\frac{\partial S}{\partial x_{i}} = - \frac{J_{i}}{T}$

2nd Law

  • $\delta S = (\frac{1}{T_{1}}-\frac{1}{T_{2}})\delta E_{1} \geq 0$
  • This is only stable if $\frac{\partial^{2}S_{1}}{\partial E_{1}^{2}}+\frac{\partial^{2}S_{2}}{\partial E_{2}^{2}} \leq 0$

Ideal Gas

  • The Hamiltonian of this system is $H = \Sigma_{i=1}^{N} \frac{p_{i}^{2}}{2m}+U(q_{i})$ where U is some external potential. For now, assume that U=0
  • Assuming some fixed E, $\Omega$ is just
    • the spatial components ($V^{N}$, since each particle can be anywhere in the volume)
    • times momentum components (this is just the surface of a hypersphere of dimension 3N and radius $\Sigma_{i=1}^{N} p_{i}^{2} = \sqrt{2mE}$)
      • The area of a hypersphere is given by $A_{d} = S_{d}R^{d-1}$
      • Can calculate $S_{d}$ via $I_{d} =( \int_{\infty}^{\infty} dx e^{-x^{2}})^{d}$
        • This equals $ \pi^{\frac{d}{2}}$
        • This integral is the product of d one-dimensional gaussians. This is spherically symmetric. Making that change in variable ($dV_{d} = S_{d}R^{d-1}dR$), then make another change of variable $y=R^{2}$, then use the integral form of the Gamma function $\int_{0}^{\infty} dy y^{\frac{d}{2}-1}e^{-y} = (\frac{d}{2}-1)!$
        • This implies that $S_{d} = \frac{2\pi^{\frac{d}{2}}}{(\frac{d}{2}-1)!}$
      • Hence $\Omega = V^{N} \frac{2\pi^{\frac{d}{2}}}{(\frac{d}{2}-1)!} (2mE)^{\frac{3N-1}{2}}\Delta R$ where $\delta R$ is the thickness of the hypersphere
  • The entropy (after Sterling approximation) is then $S = Nk_{b} \ln (V (\frac{4\pi e m E}{3N})^{\frac{3}{2}})$
    • $\frac{1}{T} = \frac{3}{2}\frac{Nk_{b}}{E}$
    • Can recover ideal gas law from $\frac{P}{V} = \frac{\partial S}{\partial V}$
  • Can calculate the probability of finding a particle of momentum $\vec{p_{1}}$ via $p(\vec{p_{1}}) = \frac{V \Omega(E-\frac{p_{1}^{2}}{2m},V,N-1)}{\Omega(E,V,C)}$
    • After some algebra and Sterling’s approximation, you get the normalized Maxwell-Boltzmann distribution
      • $p(p_{1}) = (\frac{3N}{4\pi m E})^{\frac{3}{2}}exp(\frac{-3N}{2}\frac{p_{1}^{2}}{2mE})$, where $E = \frac{3Nk_{b}T}{2}$

Mixing Entropy

  • The problem with the above ideal gas entropy is that it’s not extensive! (ie. $S(\lambda E, \lambda V, \lambda N) = \lambda S $)
  • What happens if you mix two gases together?
    • Initially, $S_{i} = N_{1}k_{b} \ln(V_{1})+N_{2}k_{b} \ln(V_{2})$
    • After mixing $S_{f} = N_{1}k_{b} \ln(V_{1}+V_{2})+N_{2}k_{b} \ln(V_{1}+V_{2})$
    • Which means the change in entropy is $\Delta S = -N k_{b} (\frac{N_{1}}{N}\ln\frac{V_{1}}{V}+\frac{N_{2}}{N}\ln\frac{V_{2}}{V})$
  • One problem with this is that if you are “mixing” two gases. Imagine that you have a partition separating the gas. Removing the partition shouldn’t change the entropy, but the above argument shows that you have some entropy change
    • The resolution to this is that with indistinguishable particles, you are over counting the number of states by a factor of N!. The above entropy works for for distinguishable particles

The Canonical Ensemble

  • Instead of fixing the energy E and varying the temperature T, you fix the temperature T and vary the energy E
  • Consider two systems: one which is the system you care about (S) and another which is sufficiently large such that its temperature is not changed by interactions with S (call this system R)
    • From a microcanonical ensemble POV, the joint probability of micro-states ($\mu_{S}\otimes \mu_{R}$) satisfied $p(\mu_{S}\otimes \mu_{R}) = \frac{1}{\Omega} \delta_{E,E_{tot}}$ where $E=H_{s}(\mu_{s})+H_{R}(\mu_{R})$
    • The unconditional probability for S just marginalizes over all of the energies of R
    • If $\mu_{s}$ is specified, we can view S as some microcanonical ensemble of the reservoir with energy $E_{tot}-H_{S}$
      • All of the above implies $p(\mu_{s}) = \frac{\Omega_{R}(E_{tot}-H_{S}(\mu_{s}))}{\Omega_{S\otimes R}(E_{tot})}$
      • Since we assume that the energy of S is much smaller than the energy of R: $S_{R}(E_{tot} -H_{s}) \approx S_{R}(E_{tot}) -H_{s}\frac{\partial S_{R}}{\partial E_{R}} = S_{R}(E_{tot})-\frac{H_{S}}{T}$
  • The above yields that $P(\mu,T) = \frac{e^{-\beta H(\mu)}}{Z}$ where Z is the normalization $Z = \Sigma_{\mu} e^{-\beta H(\mu)}$
    • This Z is called the partition function
  • We can make the association $F = -k_{b}T \ln Z(T,x)$
    • Suppose that Z is a function of $\beta$ (ie. T) and position (x)
    • $d(\ln Z) = \frac{\partial \ln Z}{\partial \beta}d \beta +\frac{\partial \ln Z}{\partial x} dx = -U d\beta + \beta X dx$ where $X = \frac{1}{\beta} \frac{\partial \ln Z}{\partial x}$
    • We can solve for dU, which we can rearrange to be dF
  • You can write the n’th cumulant of H as $<H^{n}> = (-1)^{n} \frac{\partial^{n} ln Z}{\partial \beta^{n}}$
    • This includes things like the average and the variance…
  • $C_{V} = -T \frac{\partial^{2} F}{\partial T^{2}}$

Grand Canonical Ensemble

  • We now allow chemical work on the system. In an analogous manner to deriving the canonical ensemble, we can give the probabilities of being in a particular energy
    • $p(E) = \frac{exp(\beta \mu N - \beta H(E))}{Q}$ where $Q=\Sigma_{E}exp(\beta \mu N(E)-\beta H(E))$
    • You can get the average number of particles via $\frac{\partial}{\partial (\beta \mu)}\ln Q$ and the variance ($\frac{\partial^{2}}{\partial (\beta\mu)^{2}}\ln Q$)
  • You can define a grand canonical potential $\mathbb{G }(T,\mu, x) = E-TS-\mu N = -k_{b}T \ln Q$ in an analogous way to the canonical ensemble
Conserved Ensemble Notes
  • For each thermodynamical potential, there is an associated ensemble where that potential is constant
    • For microcanonical, dE = 0
    • For canonical, dF = 0
  • There are similar ensembles for H and G. In any case, you can define $X = -\beta \ln Z$ where X is the conserved potential. Simply add on $\mu N$ to the exponential to recover the associate grand potentials

Interacting Particles

Cumulant Expansion

  • Imagine a general Hamiltonian $H = \Sigma_{i=1}^{N} \frac{p_{i}^{2}}{2m}+U(q_1,… q_N)$
  • We can write the total partition function as $Z(T,V,N) = \frac{1}{N!} \int \Pi_{i=1}^{N} (\frac{d^{3}p_{i}d^{3}q_{i}}{h^{3}}) exp(-\beta \Sigma_{i} \frac{p_i^{2}}{2m}) exp(-\beta U(q_{1}, q_{n})) = Z_{0}(T,V,N)<exp(-\beta U)>^{0}$
    • where $Z_{0} = (\frac{V}{\lambda^{3}})^{N}\frac{1}{N!}$ and $\lambda = \sqrt{\frac{h^{2}}{2\pi m k_{b} T}}$
    • and $<O>^{0}$ is the expectation value of O computed with with probability distribution of the non-interacting system
  • We can write the above in terms of the cumulants
    • $\ln Z = \ln Z_{0} + \Sigma_{i=1}^{\infty} <U^{i}>_{c}^{0}$
      • Considering that the $q_{i}$ are uniformly and independently distributed within the box V, we have the moments $<U^i>^{0} = \int \Pi_{j}^{N} \frac{d^{3}q_{j}}{V} U(q_{1},…q_{N})^{i}$

Mean Field Theory of Condensation

  • Phase transitions are characterized by discontinuities in various state functions, and correspond to singularities in the partition functions
  • Start with the same integral for the partition functions of an dilute gas $Z = \int \frac{\Pi_{i=1}^{N} d^{3}p_{i}d^{3}q_{i}}{N! h^{3N}} exp(-\beta\Sigma_{i}^{N} \frac{p_{i}^{2}}{2m} -\beta \Sigma_{i<j} V(q_{i}-q_{j}))$
  • For a non-ideal gas
    • particles take up some space
    • There is some potential between each particle
  • We can approximate the potential via an average attraction energy, where we assume some uniform density $n = \frac{N}{V}$
    • $\bar{U} = \frac{1}{2}\Sigma_{i,j}V_{attr}(\vec{q_{i}}-\vec{q_{j}}) = \frac{1}{2}\int d^{3}\vec{r_{1}}d^{3}\vec{r_{2}} n(\vec{r_{1}}) n(\vec{r_{2}}) V_{attr}(\vec{r_{1}}-\vec{r_{2}}) \approx \frac{n^{2}}{2}V \int d^{3} r V_{attr}(\vec{r}) = -\frac{N^{2}}{2V} u$
  • We can approximate the volume integral via
    • $\Pi_{i=0}^{N-1} (V-i\Omega) \approx (V-\frac{N\Omega}{2})^{N}$
    • Can take the log to turn the product into a sum, then use the (very handwavy) argument that on average $i=\frac{N}{2}$, and there are N terms, so you have $\Pi_{i=0}^{N-1} \ln(Vi-\Omega)\approx N \ln(V-\frac{N\Omega}{2})$. Invert the log to get the final result
  • Hence, the total partition function is $Z \approx \frac{(V-\frac{N\Omega}{2})^{N}}{N! \lambda^{3N}} exp(\frac{\beta u N^{2}}{2V})$
  • You can rederive the Van-derWals equation of state by finding the free energy, then using $P = -\frac{\partial F}{\partial V}$
Critical Points
  • In a P,T plot, there is a line of coexistence along with two phases of matter can coexist. This line terminates at the so called “critical point”
  • The critical point can be found by taking the equation of state ($P = P(N,V,T)$), setting it’s first derivative and second derivatives to 0
    • The first derivative constraint comes from the fact that the critical point is the limit of flat coexistence portion of the isotherms
    • The second derivative constraint comes from stability reasons
    • Solve this system of equations for $P_{c},T_{c},V_{c}$
  • One can use these critical values to rescale the equation of state into a material independent equation of state (ie $P_{r} = \frac{P}{P_{c}}$ and similar variables)

Quantum Statistical Mechanics

Dilute Polyatomic Gases

  • The Hamiltonian for each molecule of n atoms is $H = \Sigma_{i=1}^{n} \frac{p_{i}^{2}}{2m}+V(q)$
    • If the atoms have different masses, you can rescale the coordinates by scaling $\vec{q_{i}}$ by $\sqrt{\frac{m_{i}}{m}}$ and scaling $\vec{p_{i}}$ by $\sqrt{\frac{m}{m_{i}}}$
    • Ignoring the interactions between molecules, you can define the partition function as $Z(N) = \frac{1}{N!} (\int \Pi_{i=1}^{N} \frac{d^{3}p d^{3}q}{h^{3}} exp(-\beta \Sigma_{i=1}^{n} \frac{p_{i}^{2}}{2m}-\beta V))^{N}$
  • If the temperatures are smaller than than the dissociation energies ($\approx 1E4 K$), then there are only small deformations. The procedure to find the contributions of the deformations to the single particle partition function goes like:
    • Find the equilibrium positions by minimizing V
    • Do a small perturbation of $\vec{q_{i}} = \vec{q_{i*}} +\vec{u}$ around these equilibrium positions. This expand V around the minimum via $V+ V_{*}+\frac{1}{2}\Sigma_{i,j=1}^{n}\Sigma_{\alpha,\beta = 1}^{3} \frac{\partial ^{2} V}{\partial q_{i,\alpha} \partial q_{j,\beta}} u_{i,\alpha} u_{j,\beta}$
    • The second derivative matrix is a 3nx3n positive definite, which means that you can diagonalize it and do a change of basis from $u_{i}$ to $u_{s}$. This allows you to write the deformation Hamiltonian as $H_{1} = V_{*} + \Sigma_{s=1}^{3n} (\frac{p_{s}^{2}}{2m} + \frac{K_{s}}{2} u_{s}^{2})$
  • What is the average energy of each molecule? This is the expectation value of the deformation hamiltonian. Fro equipartition, there are 3n quadratic momentum degrees of freedom and $m\leq 3n$ number of modes with non-zero $K_{s}$
    • Some of these eigenmodes are forced to be 0 from symmetries
      • Translational symmetry: the original potential is invariant under translation by c. This means that no energy is stored in the center of mass coordinate $\vec{Q} = \Sigma_{\alpha} \frac{\vec{q_{\alpha}}}{n}$, which means the 3 $K_{trans}$ associated with this coordinate are 0
      • Rotational symmetry: There is no potential energy associated with rotation. There can be at most 3 degrees of freedom in rotations. Some molecule shapes will have less (a rod will have 2, since rotation along the axis is not unique)
    • This implies that $m = 3n-3-r$ (assuming no unique molecule shape). These are the vibrational modes
  • If you calculate $\gamma = \frac{C_{p}}{C_{v}}$ for various gases and compare to the experimental values, you get an overestimation. This gets solved if you quantize the vibrational modes

Quantized Vibrational Modes

  • The vibrational partition function becomes $Z_{vib} = \Sigma_{n=0}^{\infty} exp(-\beta \hbar \omega (n+\frac{1}{2})) = \frac{e^{\frac{-\beta \hbar \omega}{2}}}{1-e^{-\beta \hbar \omega}}$
    • The expectation value of the energy is then $E_{vib} = -\frac{\partial \ln Z}{\partial \beta} = \frac{\hbar \omega}{2} + \hbar \omega \frac{e^{-\beta \hbar \omega}}{1-e^{-\beta \hbar \omega}}$

Quantized Rotational Modes

  • The classical Hamiltonian is $H_{rot} = \frac{\vec{L^{2}}}{2I}$. The quantized version of angular momentum is $L^{2} = \hbar^{2} l(l+1)$
  • Hence, the partition function is $Z = \Sigma_{l=0}^{\infty} exp(-\frac{\beta \hbar^{2} l(l+1)}{2I}) (2l+1)$, where the 2l+1 comes from the degeneracy of the m quantum number
  • Defining some characteristic function $\theta_{rot} = \frac{\hbar^{2}}{2I k_{b}}$, the partition function can be rewritten as $Z = \Sigma_{l=0}^{\infty} exp(-\frac{\theta_{rot} l(l+1)}{T}) (2l+1)$
    • Doing this sum in hard, but in high and low temperatures limits, you can approximate the sum as an integral and only keep the first few terms in the sum respectively

Blackbody Radiation

  • Imagine EM waves with wave-number $\vec{k}$ and two polarizations $\alpha$. The Hamiltonian for the EM field can then be written as a sum of harmonic oscillators
    • $H = \frac{1}{2}\Sigma_{k,\alpha} (\tilde{p_{k,\alpha}})^{2} + \omega_{\alpha}(\vec{k})^{2} |\tilde{u_{\alpha}}|^{2}$
  • There is no limit on the size of the Brillouin zone for k, so you can have an arbitrarily large number in the sum. This causes the ultraviolet catastrophe
    • In more details: you can have an arbitrary number of high frequency modes and each of those modes has an energy of $k_{b}T$ associated with it. This implies there is an infinite amount of energy
  • This is solved by quantizing the allowed value of the EM energy
    • $H = \Sigma_{k,\alpha} = \hbar c k (n_{\alpha}(k) + \frac{1}{2})$ where $n_{\alpha}(k) = 0,1,2,…$
    • The internal energy can be calculated as per usual
    • $E = <H> = \Sigma_{k,\alpha} \hbar c k (\frac{1}{2}+\frac{e^{-\beta \hbar c k}}{1-e^{-\beta \hbar c k}}) = VE_{0} + \frac{2V}{(2\pi)^3}\int d^{3}\vec{k}\frac{\hbar c k}{e^{\beta \hbar c k}-1}$
      • $VE_{0}$ is the infinite zero point energy, but only energy differences can be measured, so this cancels out
      • The integral can be calculated by making the change of variable $x = \beta \hbar c k$ and using the identity $\int_{0}^{\infty} \frac{dx x}{e^{x}-1} = \frac{\pi^{2}}{6}$
      • Hence: $\frac{E}{V} = \frac{\pi^{2}}{15}(\frac{k_{b} T}{\hbar c})^{3} k_{b}T$
  • Imagine that you poke a hole in the side of the box. The energy flux per unit area per unit time is then $\phi = v_{\perp} \frac{E}{V}$
    • $v_{\perp}$ for the photons is $v_{\perp} = c * \frac{1}{4\pi} \int_{0}^{\frac{\pi}{2}} 2\pi \sin \theta d\theta \cos \theta = \frac{c}{4}$
    • Hence $\phi = \sigma T^{4}$ where $\sigma = \frac{\pi^{2}}{60}\frac{k_{b}^{4}T^{4}}{\hbar^{3}c^{2}}$ is the Stefan-Boltzmann constant

Formalism

  • The micro-state of a quantum system is completely specified by a unit vector $|\Phi>$
    • This can be decomposed into its components along any suitable orthonormal basis: $|\Phi> = \Sigma_{n} <n|\Phi> |n>$
  • Observables become operators $O(\vec{p_{i}},\vec{q_{i}})$, where we have the commutation relation: $[p_{j},q_{k}] = \frac{\hbar}{i}\delta_{j,k}$
    • These operators must be Hermitian
  • The time evolution operator is defined as
    • $\Psi(t)> = U(t,t_{0}) | \Psi(t_{0})>$
    • U can be related to the Hamiltonian: $U(t,t_{0}) = exp(-\frac{i}{\hbar}H(t-t_{0}))$
  • Macrostates are now ensemble values:
    • $\bar{O(p_{i},q_{j},t)} = \Sigma_{\alpha} p_{\alpha}O = \int \Pi_{i=1}^{N} d^{3}p_{i} d^{3}q_{i} O \rho$
    • $\rho = \Sigma_{\alpha} \Pi_{i}^{N} \delta^{3}(\vec{q_{i}}-\vec{q_{i}(t)}) \delta^{3}(\vec{p_{i}}-\vec{p_{i}(t)}_{\alpha})$ is the ensemble density
    • We can then write the expectation value of O as $\bar{O} = \Sigma_{m,n}<n|\rho|m> <m|O|n> = tr(\rho O)$
      • We can define the density matrix as $<n|\rho(t)|m> = \Sigma_{\alpha} p_{\alpha} <n|\Phi_{\alpha}(t)><\Phi_{\alpha}(t)|m>$ or alternatively: $\rho(t) = \Sigma_{\alpha} p_{\alpha} | \Phi_{\alpha}(t)>< \Phi_{\alpha}(t)|$
      • The density matrix has some nice properties
        • $tr(\rho) = 1$ due to normalization of states
        • $\rho$ is Hermitian
        • $\rho$ is positive definite
        • Being in equillibrium demands that $\frac{\partial \rho}{\partial t} = 0$, which implies via Heisenberg equation of motion that $i\hbar \frac{\partial \rho}{\partial t} = [H,\rho]$
  • Given the above, we can define some ensembles:
    • Micro: $\rho(E) = \frac{\delta(H-E)}{\Omega(E)}$. This allows the density matrix to obey the constraint of a fixed energy E
    • Canonical: A fixed temperature $T = \frac{1}{k_{b}\beta}$ can be assigned by being in contact with a reservoir
      • $\rho(\beta) = \frac{exp(-\beta H)}{Z(\beta)}$, and from the normalization condition on $\rho$, we have that $Z = tr(e^{-\beta H})$ (remember, Z is a scalar, not an operator!)
    • Grand Canonical: Similarly, if we vary the particle number, we have that the grand canocial ensemble is $Q = tr(exp(-\beta H \beta \mu_{i}N_{i}))$

Identical Particles

  • If we have N particles, we have N! permutations P which form a group $S_{N}$.
    • We can label the identity permutation by the ascending positive integers (ie. if N=3, the identity is (1,2,3))
    • We can define the parity of a permutations as $(-1)^{P} = \pm 1$ with the plus being associated with an even number of exchanges from ascending order, and minus being associated with an odd number of exchanges
    • Aside: Draw lines connecting the initial and final locations of each integer. The parity is (-1) raised to the number of intersections of these lines
  • Two types of particles:
    • Bosons, which are even under permutation: $P|\Psi(1,…N)> = |\Psi(1,…N)>$
    • Fermions, which are odd under permutation: $P|\Psi(1,…N)> = (-1)^{P}|\Psi(1,…N)>$
  • Suppose that we have a Hamiltonian of N non-interacting particles in a box of volume V. This gives $H = \Sigma_{\alpha=1}^{N} (-\frac{\hbar^{2}}{2m}\nabla^{2}_{\alpha})$
    • Assuming distinguishable particles: $<x_{1}…x_{n}|k_{1}…k_{n}> = \frac{1}{V^{N/2}} exp(i\Sigma_{\alpha=1}^{N} \vec{k_{\alpha}}\cdot \vec{x_{\alpha}})$ and $H|k_{1}…k_{n}> = (\Sigma_{\alpha=1}^{N} \frac{\hbar^{2}}{2m} k_{\alpha}^{2}) |k_{1}…k_{n}>$
    • If we are to make the particle indistinguishable, then depending on their nature, only a subspace of the distinguishable Fock space
      • We can bundle both cases like $|\vec{k} >= \frac{1}{\sqrt{N_{\eta}}} \Sigma_{P} \eta^{P} P | \vec{k}>$ where $\eta$ is 1 for bosons and -1 for fermions
      • Each state is uniquely specified by a set of occupation numbers ${n_{\vec{k}}}$ such that $\Sigma_{\vec{k}} n_{\vec{k}} = N$
      • For fermions, $|\vec{k}> = 0$ unless $n_{k}$ is 0 or 1
      • For bosons, any k may be repeated $n_{k}$ times
      • The normalization for both fermions and bosons is N!

Grand Canonical Formulation

  • $Q_{n}(T,\mu) = tr(exp(-\beta H)) = \Sigma_{n}^{N} \Pi_{\vec{k}} exp(-\beta(\Epsilon(\vec{k}) -\mu) n_{\vec{k}})$
  • For fermions, $n_{\vec{k}}$ can be 0 or 1, while bosons can range from 0 to $\infty$. In either case, we have
    • $ln Q_{\eta} = -\eta \Sigma_{k} \ln (1-\eta exp(\beta\mu-\beta\Epsilon(k)))$ with $\eta=-1$ for fermions and $\eta=+1$ for bosons
    • Just do the sum of two terms for fermions, and for bosons, do the infinite geometric series
  • The average occupation number of a state of energy $\Epsilon(k)$ is given by $<n_{\vec{k}}> = -\frac{\partial \ln Q_{\eta}}{\partial (\beta \Epsilon(\vec{k}))} = \frac{1}{z^{-1}exp(\beta \Epsilon(\vec{k}))-\eta}$
  • The average particle number and internal energy are then just $N_{\eta} = \Sigma_{\vec{k}} <n_{\vec{k}}>$ and $E_{\eta} = \Sigma_{\vec{k}} \Epsilon(\vec{k}) <n_{\vec{k}}>_{\eta}$
  • Both of these quantities can be extended to a continuum spectrum via the substitution $\Sigma_{\vec{k}} \rightarrow \int d^{3}k \frac{1}{(2\pi)^{3}}$

Degenerate Fermi Gas

  • Fermi occupation is $<n_{\vec{k}}> = \frac{1}{exp(\beta(\Epsilon(k)-\mu))+1}$
    • At T=0, $\mu=\epsilon_{F}$ or the Fermi energy
    • At T=0, all one-particle states of energy less than $\epsilon_{F}$ are occupied. For an ideal gas, we can $\Epsilon(k) = \frac{\hbar^{2}k_{F}^{2}}{2m}$ where $k_{F}$ is the Fermi wavenumber $k_{F}$
    • Using the above definition for average N, you can define the number density as $n = \frac{N}{V}$. For an ideal gas, we have that $\Epsilon(k) = \frac{\hbar^{2}}{2m}(\frac{6\pi^{2}n}{g})^{\frac{2}{3}}$ wher g is the spin degeneracy
$f_{m}^{\eta}(z)$
  • The function $f_{m}^{\eta}(z) = \frac{1}{(m-1)!}\int_{0}^{\infty} \frac{dx x^{m-1}}{z^{-1}e^{x}-\eta}$ shows up a lot when dealing with degenerate gases.
    • Namely, the number density is proportional to this function.
    • $\eta = \pm 1 $ for bosons and fermions respectively and $z = exp(\beta \mu)$
  • $f_{m}^{\eta}(z) = \Sigma_{\alpha=1}^{\infty} \eta^{\alpha+1} \frac{z^{\alpha}}{\alpha^{m}}$ in the high temperature (small z), low density limit
  • There is a recursion relationship for this function: $\frac{d}{dz}f_{m}^{\eta} = \frac{1}{z} f_{m-1}^{\eta}(z)$

Denegerate Bose Gas

  • In the low T limit, we have that z approaches unity. Hence, we need to find $f_{+}^{1}(1)$ in order to calculate the maximum number density $n_{max}$
  • For m<1, the integral diverges, while for m>1, the integral is finite
  • Hence, this sets an upper bound on the density of excited states.
    • For instance, in a bosonic, non-relativistic gas, we have $n \leq \frac{g}{\lambda^{3}}f_{\frac{3}{2}}^{+}(1)$ where $\lambda = \frac{h}{\sqrt{2\pi m k_{b}T}}$
    • The critical temperature $T_{c}$ is when the above is at equality. For $T<T_{C}$, z gets pinned to 1. The remaining density $n_{0} = n-n_{max}$ occupied the lowest energy state
      • This is Bose-Einstein condensation