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ass3-draft
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ass3-final
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60
ass3-12-a-weak-junction.py
Executable file
60
ass3-12-a-weak-junction.py
Executable file
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#!/bin/env python3
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import numpy as np
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from scipy.integrate import odeint
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from matplotlib import pyplot as plt
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import pandas as pd
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def phi_dot(phi, t, I_DC, I_RF):
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R = 10.e-3 #Ohm
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I_J = 1.e-3 #A
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omega_RF = 2*np.pi*.96e9 #rad/s
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hbar = 1.0545718e-34 #m^2kg/s
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e = 1.60217662e-19 #C
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return 2*e*R/hbar*( I_DC + I_RF*np.cos(omega_RF*t) - I_J*(np.sin(phi)) )
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# I attempted to solve it without the constants, as I suspected overflows
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# were occurring. The next line did not improve the result.
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#return R*( I_DC + I_RF*np.sin(omega_RF*t) - I_J*(np.sin(phi)) )
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# We need an initial value to phi
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phi_0 = 0
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# Let's try it for a lot of periods
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N_points = 10000
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t = np.linspace(0, 100, N_points)
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hbar = 1.0545718e-34 #m^2kg/s
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e = 1.60217662e-19 #C
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df = pd.DataFrame(columns=['I_DC','I_RF','V_DC_bar'])
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# For testing:
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#phi = odeint(phi_dot, phi_0, t, (.5e-3, .5e-3))[:, 0]
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#for I_DC in [1e-4, .5e-3, 1.e-3, 1.5e-3, 2.e-3, 2.5e-3]:
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for I_DC in np.arange(0, 1e-3, 1e-5):
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for I_RF in [0., .5e-3, 2.e-3]:
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# The individual solutions for phi do seem sane, at least, the ones
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# I inspected.
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phi = odeint(phi_dot, phi_0, t, (I_DC, I_RF))
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# I initially thought to average over the tail to look at the asymptotic behaviour.
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#N_asymp = N_points//2
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#V_DC_bar = hbar/(2*e)*np.mean(phi[N_asymp:]/t[N_asymp:])
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# Then I choose to just take the last point to see if that gave better results.
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V_DC_bar = hbar/(2*e)*phi[-1]/t[-1]
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print("For I_DC =", I_DC, "\t I_RF = ", I_RF, "\twe find V_DC_bar =", V_DC_bar)
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df = df.append({'I_DC': I_DC, 'I_RF': I_RF, 'V_DC_bar': V_DC_bar}, ignore_index = True)
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## Plotting the thing
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plt.figure()
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plt.xlabel("$\\overline{V_{DC}}$")
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plt.ylabel("$I_{DC}$")
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for I_RF in df.I_RF.unique():
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x, y = df[df.I_RF == I_RF][["V_DC_bar", "I_DC"]].to_numpy().T
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plt.plot(x, y, label="$I_{RF} = " + str(I_RF) + "$")
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plt.legend()
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plt.show()
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BIN
lec4-vortexlattice.png
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BIN
lec4-vortexlattice.png
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@ -32,6 +32,7 @@
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\usepackage{todonotes}
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\usepackage{todonotes}
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\setuptodonotes{inline}
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\setuptodonotes{inline}
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\usepackage{mhchem}
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\usepackage{mhchem}
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\usepackage{listings}
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\newcommand{\pfrac}[2]{\frac{\partial #1}{\partial #2}}
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\newcommand{\pfrac}[2]{\frac{\partial #1}{\partial #2}}
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@ -57,31 +58,119 @@ $\kappa = \frac{\lambda}{\xi} = 34 > \frac{1}{\sqrt{2}}$,
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which means we are indeed dealing with a type-II superconductor.
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which means we are indeed dealing with a type-II superconductor.
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As $B_{c1} < B_E < B_{c2}$, the cylinder is in the vortex state.
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As $B_{c1} < B_E < B_{c2}$, the cylinder is in the vortex state.
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From the previous set of assignments, we know what the currents in the cylinder look like.
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From the previous set of assignments, we know what the currents in the cylinder look like.
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From free energy considerations, we have found in lecture 4 that for type-II superconductors, it is favorable to allow flux quanta inside the superconductor in this vortex state.
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In this derivation, the contribution of one flux quantum is considered, but the consideration holds for many vortices, until they start to interact and repel eachother.
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At that point, the vortex-vortex interaction orders the vortices in a lattice.
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When the vortex cores start to overlap, there are no superconducting regions left, thus the material enters the normal conducting state.\footnote{I wanted to paint a complete picture althought it is not needed to answer the question.}
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Minimizing the free energy over the flux shows the energy is lowered for determined thresholds $B_{c1} < B_E < B_{c2}$.
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The average field inside the cylinder is gives as
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Let's start with the result from said free energy considerations.
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The average field inside the cylinder is given by the following self-consisting equation as
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\[
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\[
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\langle \vec{B} \rangle = \frac{1}{V_{\text{cylinder}}} \int_{\text{cylinder}} \vec{B}(\vec{r}) d\vec{r} .
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B = B_E - \frac{\phi_0}{8\pi\lambda^2}\ln{\frac{\phi_0}{4\exp{(1)}\xi^2B}}.
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\]
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\]
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Plugging in the values for \ce{Nb3Sn}, $B_E = \SI{1}{\tesla}$, and $\phi_0 = \SI{2.0678}{\weber}$, $B$ is found as $B = \SI{.986}{\tesla} \approx B_E$ by intersection.
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%https://www.wolframalpha.com/input?i=B+%3D+1+-+%282.0678*10%5E-15%29%2F%288*pi*%28124*10%5E-9%29%5E2%29+*+ln%282.0678*10%5E-15%2F%284*exp%281%29*%283.65*10%5E-9%29%5E2+*+B%29%29
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This is in the range as provided in the assignment ($B = \SI[separate-uncertainty]{.981\pm.019}{\tesla}$).
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To determine this $\vec{B}$ inside the material, we first need to know how many vortices there are.
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To investigate the inhomogenity of the field inside the cylinder, we look at the gradient $\nabla B$ inside the material.
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We assume that every vortex lets through only one flux quantum $\Phi_0$,
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As we assume a vortex lattice that fully fills the cross section of the cylinder,
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and that the vortices will arange themselves as far as possible from eachother.
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and we assume that the fields due to each vortex die out quickly enough to not overlap,
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If their distance then is large enough to assume there is no overlap between regions of finite $\vec{B}$ around them,
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it suffices to calculate the gradient over just one vortex.
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we can calculate the average field by just summing over the quanta and lastly over the field that penetrates the material in the outside of the cylinder.
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These assumptions coincide with slide 15 of lecture 4, from which I took figure \ref{fig:lec4-vortexlattice}.
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For this latter calculation, we can use the field for a type-I superconductor.
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\begin{figure}[H]
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\centering
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\label{fig:lec4-vortexlattice}
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\includegraphics[width=.4\textwidth]{lec4-vortexlattice.png}
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\caption{The vortices are arranged in a lattice to maximize their distance, as this lowers their repulsive interaction and thus the energy.}
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\end{figure}
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On slide 19 from the same week, we find an expression $B(r)$ for the field at distance $r$ from the vortex core as
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\[
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B = \frac{\phi_0}{2\pi\lambda^2} K_0(r/\lambda) = B_0 K_0(r/\lambda),
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\]
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where $K_0$ is the modified Bessel function of the second kind.
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For small $r$ (i.e. $r << \lambda$), we can approximate this and find that
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\[
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K_0 \propto - \ln{(r/\lambda)},
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\]
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and notice a singularity at $r = 0$.
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For the gradient we thus find
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\[
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\nabla B \propto \pfrac{K_0}{r}(r/\lambda) \propto \pfrac{-\ln{(r/\lambda)}}{r} = -\lambda/r.
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\]
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The size of the supercurrent density has the same relation, $J_S \propto 1/r$.
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\section{Superconducting wire}
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\section{Superconducting wire}
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\textbf{(a)}
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The voltage $U = \SI{1.5e-5}{\volt}$ across the wire of length $\ell = \SI{.08}{\meter}$ induces a current $J_t$. % through the resistive wire with unknown resistivity $\rho$ according to Ohm's law.
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Due to the presence of the magnetic field $B = \SI{5}{\tesla}$, if the vortices move with velocity $v_L$, a Lorentz force $f_L$ per vortex acts on the vortices.
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This results in a power input $P_L = f_Lv_L = J_tBv_L$ per vortex.
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%$\epsilon = Bv_L$
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This power should come from the current induced by the voltage, thus $P_L = \epsilon J_t = \frac{U}{\ell}J_t$.
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Equating these expressions and rewriting yields
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\[
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v_L = \frac{U}{B\ell} = \SI{3.75e5}{\meter\per\second}.
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% https://www.wolframalpha.com/input?i=1.5*10%5E-5+%2F+%285*+.08%29
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\]
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\textbf{(b)}
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The vortices are aranged in a lattice with separation $r_{sep} = \sqrt{\frac{\Phi_0}{B}}$.
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They move along the wire with velocity $v_L$ as determined above.
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The expected frequency is then given by their velocity over the separation, as that is the period of the changing fields due to the vortices:
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\[
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f = \frac{v_L}{r_{sep}} = \frac{U}{B\ell}\sqrt{\frac{B}{\Phi_0}} = \frac{U}{\ell\sqrt{B\Phi_0}} = \SI{1.84}{\kilo\hertz},
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% https://www.wolframalpha.com/input?i=1.5*10%5E-5+%2F+%28.08%29+%2Fsqrt%285+*+2.067*10%5E%28-15%29%29
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\]
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where we used that $\Phi_0 = \SI{2.067e-15}{\volt\second}$.
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This is very close to what is written in the assignment, but not precisely the same, so maybe I used a different value for $\Phi_0$.
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\section{Fine type-II superconducting wire}
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\section{Fine type-II superconducting wire}
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\section{Critical currents}
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\section{Critical currents}
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\textbf{(a)}
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Silsbee's rule states that the supercurrents through the wire must not generate magnetic fields in excess of $B_c$ at the surface of the wire.
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We assume that the supercurrent is maximal at the surface with a maximum value of $J_{max}$, and that the supercurrent decays linearly from the surface to zero at a penetration depth $\lambda$ deep.
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We thus find a relation for the supercurrent as function of the cylindrical radius $r$ as
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\[
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J_s(r) = \frac{J_{max}}{\lambda} \left[ r - R + \lambda \right].
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\]
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Now we can use the Maxwell-Amp\`ere law to find this value for $J_{max}$.
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\[
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\oint \vec{B}\cdot d\vec{\ell} = \mu_r\mu_0\iint\vec{J_s}\cdot d\vec{S}
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\]
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Using $\vec{B} = \vec{B_c}$, $\mu_r = 1$ as we're calculating the field outside the sc, $J_s = J_s(r)$, the area over which $d\vec{S}$ runs to be the small ring from $r = R - \lambda$ to $r = R$, and the path along which $d\vec{\ell}$ runs to be the loop $2\pi R$ along the surface of the wire.
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This gives us
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\[
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2\pi R B_c = \mu_0 \int_{\phi = 0}^{2\pi}\int_{r=R-\lambda}^R \frac{J_{max}}{\lambda}\left[ r - R + \lambda \right] rdr d\phi.
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\]
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Solving the integral over $\phi$ results in
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\[
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R B_c = \mu_0 \int_{r=R-\lambda}^R \frac{J_{max}}{\lambda}\left[ r - R + \lambda \right] rdr = \frac{\mu_0J_{max}}{\lambda} \left[ \frac{r^3}{3} - \frac{(R + \lambda)r^2}{2} \right]_{r = R-\lambda}^R.
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\]
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Solving for $J_{max}$, this yields the beautiful expression
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\[
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J_{max} = \frac{6B_c\lambda R}{\mu \left[ 4\lambda^3 - 9\lambda^2R + 3\lambda R^2- 3\lambda R + 3R^3 -3R^2 \right]}.
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% https://www.wolframalpha.com/input?i=R*B+%3D+m*x%2Fl*%28%28R%5E3-%28R-l%29%5E3%29%2F3+-+%28R%2Bl%29*%28R+-+%28R-l%29%5E2%29%2F2%29
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\]
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\textbf{(b)}
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\section{A weak junction}
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\section{A weak junction}
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See the code in appendix \ref{appendix:program-task-12}.
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It unfortunately does not seem to produce any useful results.
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In the code, I left many comments as it is mostly in a debugging state.
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\bibliographystyle{vancouver}
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\bibliographystyle{vancouver}
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\bibliography{references.bib}
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\bibliography{references.bib}
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%\appendix
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\appendix
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\section{Program to task 12}
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\label{appendix:program-task-12}
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\lstinputlisting[language=python,breaklines=true]{ass3-12-a-weak-junction.py}
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\end{document}
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\end{document}
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