Appendix C Solutions¶
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Table of Contents
Basic
- B-1. Fourier coefficients (a_n) and (b_n) of a function (constant function) defined on an interval, using equations (C.6) and (C.7)
- B-2. Using the orthogonality of complex exponentials (Eq. (C.12)), evaluate the following integral
- B-3. Using Euler's formula, show the following
- B-4. Find all Fourier coefficients and on the interval
- B-5. Gaussian Integral Formula
- B-6. Following the definition of convolution (Eq. (C.21)), compute the convolution of and ( is a constant). Here is D
- B-7. Evaluate the following integral using the Fourier integral representation of the δ function (Eq. (C.19))
- B-8. Verify the following using Parseval's equality (Eq. (C.18)) for the case
Medium
- M-1. Find the Fourier coefficients and of the function defined on the interval , and write down the Fourier series (Equation (C.5
- M-2. Fourier Transform of a Gaussian Function and Parseval's Theorem
- M-3. Solve the following problem using the convolution theorem (Eq. (C.22))
- M-4. Fourier Integral Representation of the δ Function
- M-5. Differentiation Property of the Fourier Transform
Advanced
Basic¶
B-1. Fourier coefficients (a_n) and (b_n) of a function (constant function) defined on an interval, using equations (C.6) and (C.7)¶
Problem:
Find all the Fourier coefficients \(a_n\) (\(n = 0, 1, 2, \ldots\)) and \(b_n\) (\(n = 1, 2, 3, \ldots\)) of the function \(f(x) = 1\) (constant function) defined on the interval \([0, L]\), using equations (C.6) and (C.7).
Solution Strategy: Substitute \(f(x) = 1\) directly into equations (C.6) and (C.7) and compute.
Detailed Calculation:
Calculation of \(a_n\):
- When \(n = 0\):
- When \(n \geq 1\):
Calculation of \(b_n\) (\(n \geq 1\)):
Final Answer:
Verification: Substituting into the Fourier series gives \(f(x) = \frac{a_0}{2} = \frac{2}{2} = 1\). The constant function is correctly reproduced. ✓
B-2. Using the orthogonality of complex exponentials (Eq. (C.12)), evaluate the following integral¶
Problem:
Using the orthogonality of complex exponentials (Eq. (C.12)), evaluate the following integral.
Solution Strategy: Combine the integrand into the form \(e^{i\frac{2\pi(m-n)}{L}x}\) and apply equation (C.12).
Detailed Calculation:
From equation (C.12), with \(m = 3\), \(n = 5\) and \(m \neq n\):
Final Answer:
Verification: Confirmed by direct calculation:
B-3. Using Euler's formula, show the following¶
Problem:
Using Euler's formula \(e^{i\theta} = \cos\theta + i\sin\theta\), show the following.
Furthermore, derive the relations between the real Fourier coefficients \(a_n, b_n\) and the complex Fourier coefficients \(c_n\) of a real function \(f(x)\):
by comparing Eq. (C.5) and Eq. (C.10).
Part 1: Complex Exponential Representation of \(\cos\):
Solution strategy: Add \(e^{i\theta}\) and \(e^{-i\theta}\) using Euler's formula.
From Euler's formula:
Adding both expressions:
Therefore:
Substituting \(\theta = \frac{2\pi n}{L}x\):
Part 2: Relationship Between Real and Complex Fourier Coefficients:
Solution strategy: Rewrite \(\cos\) and \(\sin\) in Eq. (C.5) as complex exponentials and compare with Eq. (C.10).
Rewriting Eq. (C.5) using Eq. (C.9):
where \(k_n = \frac{2\pi n}{L}\). Using \(\frac{1}{2i} = -\frac{i}{2}\) and rearranging:
On the other hand, Eq. (C.10) gives:
Comparing both expressions:
Verification: When \(f(x)\) is real, we should have \(c_{-n} = c_n^*\). Indeed:
(since \(a_n, b_n\) are real.)
B-4. Find all Fourier coefficients and on the interval¶
Problem:
Find all the Fourier coefficients \(a_n\) and \(b_n\) of \(f(x) = \sin\!\left(\frac{2\pi}{L}x\right)\) on the interval \([0, L]\).
Solution Strategy: Directly apply the orthogonality relations (C.3) and (C.4).
Detailed Calculation:
Calculation of \(a_n\):
From equation (C.4), the integral of the product of \(\sin\) and \(\cos\) is always zero:
Calculation of \(b_n\):
From equation (C.3):
Therefore:
Final Answer:
Verification: Substituting into the Fourier series gives \(f(x) = b_1 \sin\!\left(\frac{2\pi}{L}x\right) = \sin\!\left(\frac{2\pi}{L}x\right)\). The original function is reproduced. ✓
B-5. Gaussian Integral Formula¶
Problem:
Using the Gaussian integral formula
compute the Fourier transform \(\tilde{f}(k)\) of the function \(f(x) = e^{-3x^2}\) using convention (b) (Eq. (C.16)).
Solution Strategy: Using convention (b), we complete the square in \(\tilde{f}(k) = \frac{1}{\sqrt{2\pi}}\int_{-\infty}^{\infty} e^{-3x^2} e^{-ikx}\,dx\) and reduce it to a Gaussian integral.
Detailed Calculation:
Completing the square in the exponent:
Verification: \(-3\left(x + \frac{ik}{6}\right)^2 = -3\left(x^2 + \frac{ik}{3}x + \frac{(ik)^2}{36}\right) = -3x^2 - ikx + \frac{k^2}{12}\)
Therefore \(-3\left(x + \frac{ik}{6}\right)^2 - \frac{k^2}{12} = -3x^2 - ikx\). ✓
Substituting \(t = x + \frac{ik}{6}\) gives \(dt = dx\). The integration path is shifted in the complex plane, but since the integrand is Gaussian, it yields the same value as integration along the real axis (by Jordan's lemma):
Therefore:
Final Answer:
Verification: For the general formula \(f(x) = e^{-ax^2}\), convention (b) gives \(\tilde{f}(k) = \frac{1}{\sqrt{2a}}\,e^{-k^2/(4a)}\). Substituting \(a = 3\) yields \(\tilde{f}(k) = \frac{1}{\sqrt{6}}\,e^{-k^2/12}\). This agrees. ✓
B-6. Following the definition of convolution (Eq. (C.21)), compute the convolution of and ( is a constant). Here is D¶
Problem:
Following the definition of convolution (Eq. (C.21)), compute the convolution \((f * g)(x)\) of \(f(x) = e^{-|x|}\) and \(g(x) = \delta(x - a)\) (where \(a\) is a constant). Here \(\delta\) is the Dirac delta function, which satisfies \(\int_{-\infty}^{\infty} h(x')\,\delta(x' - a)\,dx' = h(a)\).
Solution Strategy: Apply the sifting property of the δ function to the definition of convolution.
Detailed Calculation:
From the definition of convolution in Eq. (C.21):
Since \(g(x) = \delta(x - a)\), we have \(g(x - x') = \delta((x - x') - a) = \delta(x - x' - a)\):
Using the sifting property of the δ function \(\int h(x')\,\delta(x' - c)\,dx' = h(c)\). Here, \(\delta(x - x' - a) = \delta(-(x' - (x-a))) = \delta(x' - (x-a))\) (since the δ function is an even function):
Substituting \(f(x) = e^{-|x|}\):
Final Answer:
Verification: This is consistent with the general property that convolution with a δ function simply translates the function. When \(a = 0\), we get \((f * \delta)(x) = f(x) = e^{-|x|}\), confirming that the δ function is the identity element for convolution. ✓
B-7. Evaluate the following integral using the Fourier integral representation of the δ function (Eq. (C.19))¶
Problem:
Evaluate the following integral using the Fourier integral representation of the δ function (Eq. (C.19)):
Solution Strategy: Set \(k' = 0\) in equation (C.19).
Detailed Calculation:
Equation (C.19) is:
Setting \(k = 7\), \(k' = 0\):
Since \(\delta(7) = 0\) (the \(\delta(x)\) function is zero for \(x \neq 0\)):
Final Answer:
Verification: From a physical perspective, \(e^{i7x}\) is an oscillating function, and when integrated over the entire real line, the positive and negative contributions cancel each other out, yielding zero. This is consistent with \(\delta(7) = 0\). ✓
B-8. Verify the following using Parseval's equality (Eq. (C.18)) for the case¶
Problem:
Using Parseval's equality (Eq. (C.18)), verify the following. For \(f(x) = e^{-|x|}\),
holds. Show this by directly computing the left-hand side, computing the right-hand side using \(\tilde{f}(k) = \sqrt{\frac{2}{\pi}}\,\frac{1}{1+k^2}\) (convention (b)), and demonstrating that the two results agree.
Solution Strategy: Compute the left-hand side and right-hand side independently, then confirm they are equal.
Detailed Calculation:
Left-hand side:
Right-hand side:
From \(\tilde{f}(k) = \sqrt{\frac{2}{\pi}}\,\frac{1}{1+k^2}\):
Using the formula \(\int_{-\infty}^{\infty}\frac{dk}{(1+k^2)^2} = \frac{\pi}{2}\):
Final Answer:
Parseval's theorem is confirmed to hold.
Verification: We verify the derivation of \(\tilde{f}(k)\). The Fourier transform of \(f(x) = e^{-|x|}\) (convention (b)):
Medium¶
M-1. Find the Fourier coefficients and of the function defined on the interval , and write down the Fourier series (Equation (C.5¶
Problem:
Find the Fourier coefficients \(a_n\) and \(b_n\) of the function \(f(x) = x\) defined on the interval \([0, L]\), and write down the Fourier series (Equation (C.5)). Furthermore, verify that the value of the series obtained by substituting \(x = L/2\) agrees with \(f(L/2) = L/2\).
Solution Strategy: Substitute \(f(x) = x\) into equations (C.6) and (C.7), and compute using integration by parts.
Detailed Calculation:
Calculation of \(a_0\):
Calculation of \(a_n\) (\(n \geq 1\)):
Integration by parts (\(u = x\), \(dv = \cos\!\left(\frac{2\pi n}{L}x\right)dx\)):
First term: At \(x = L\), \(\sin(2\pi n) = 0\); at \(x = 0\), it is \(0\). Therefore the first term \(= 0\).
Second term:
Therefore:
Calculation of \(b_n\) (\(n \geq 1\)):
Integration by parts (\(u = x\), \(dv = \sin\!\left(\frac{2\pi n}{L}x\right)dx\)):
First term: \(-\frac{L}{2\pi n}\left[L\cos(2\pi n) - 0\right] = -\frac{L^2}{2\pi n}\)
Second term:
Therefore:
Fourier series:
Verification at \(x = L/2\):
Since \(\sin(\pi n) = 0\) for all integers \(n\):
This is consistent with \(f(L/2) = L/2\). ✓
Verification: Check at \(x = 0\): \(f(0) = \frac{L}{2} - \frac{L}{\pi}\sum_{n=1}^{\infty}\frac{1}{n}\sin(0) = \frac{L}{2}\). However, \(f(0) = 0\) is expected. This is because the Fourier series represents a periodic function, so at \(x = 0\) it converges to the average of \(f(0^+) = 0\) and \(f(L^-) = L\), which is \(L/2\) (Dirichlet's theorem). This is the correct behavior of a Fourier series at a point of discontinuity. ✓
M-2. Fourier Transform of a Gaussian Function and Parseval's Theorem¶
Problem:
Find the Fourier transform of the Gaussian function \(f(x) = e^{-ax^2}\) (\(a > 0\)) using convention (b), and show that the result is again a Gaussian function. Furthermore, using Parseval's theorem (Eq. (C.18)), verify that
holds.
Solution Strategy: As in D5, we perform completing the square and obtain the result for general \(a\).
Detailed Calculation:
Fourier Transform Calculation:
Completing the square in the exponent:
Therefore:
The result is again a Gaussian function. ✓
Verification of Parseval's Theorem:
Left-hand side:
Right-hand side:
Final Answer:
Both sides equal \(\sqrt{\frac{\pi}{2a}}\), confirming Parseval's theorem. ✓
M-3. Solve the following problem using the convolution theorem (Eq. (C.22))¶
Problem:
Solve the following problem using the convolution theorem (Eq. (C.22)).
For \(f(x) = e^{-x^2}\) and \(g(x) = e^{-x^2}\), find the convolution \((f * g)(x)\) not by direct calculation, but by computing the product in Fourier transform space and then taking the inverse transform.
Solution Strategy: Find the Fourier transforms of \(f(x) = g(x) = e^{-x^2}\), apply the convolution theorem, and then take the inverse transform.
Detailed Calculation:
Step 1: Computing the Fourier Transforms
Setting \(a = 1\) in the result from S2:
Step 2: Applying the Convolution Theorem
The convolution theorem from equation (C.22) (convention (b)):
Step 3: Inverse Fourier Transform
Completing the square in the exponent:
Final Answer:
(We simplified \(\frac{\sqrt{2\pi}}{2} = \sqrt{\frac{\pi}{2}}\).)
Verification: We confirm by direct calculation. \((f*g)(x) = \int_{-\infty}^{\infty} e^{-x'^2}\,e^{-(x-x')^2}\,dx'\).
The exponent: \(-x'^2 - (x-x')^2 = -2x'^2 + 2xx' - x^2 = -2(x' - x/2)^2 - x^2/2\)
M-4. Fourier Integral Representation of the δ Function¶
Problem:
Starting from the Fourier integral representation of the δ function
derive the following.
(a) \(\delta(x)\) is an even function: \(\delta(-x) = \delta(x)\)
(b) Scaling rule: \(\delta(\alpha x) = \frac{1}{|\alpha|}\,\delta(x)\) (\(\alpha \neq 0\))
(c) \(x\,\delta(x) = 0\)
(a) \(\delta(-x) = \delta(x)\) (Even Function):
Starting from the Fourier integral representation:
Substituting \(x \to -x\):
Changing the integration variable \(k \to -k\) (\(dk \to -dk\), the limits of integration reverse and return to the original):
(b) Scaling Property \(\delta(\alpha x) = \frac{1}{|\alpha|}\,\delta(x)\):
From the Fourier integral representation:
Substituting \(k' = \alpha k\) gives \(dk = dk'/\alpha\):
Case 1: \(\alpha > 0\)
Case 2: \(\alpha < 0\)
When \(k' = \alpha k\) with \(\alpha < 0\), the limits of integration are reversed:
(Since \(\alpha < 0\), we have \(-1/\alpha = 1/|\alpha|\))
(c) \(x\,\delta(x) = 0\):
For any test function \(\phi(x)\):
By the sifting property of the δ function, letting \(h(x) = x\,\phi(x)\):
Since the integral is zero for any test function, in the distributional sense:
Verification: Special case of (b): when \(\alpha = -1\), we get \(\delta(-x) = \delta(x)\). This is consistent with (a). ✓
Alternative confirmation of (c): \(\delta(x)\) is nonzero only at \(x = 0\). At \(x = 0\), the factor of \(x\) is zero, so the product is zero everywhere. ✓
M-5. Differentiation Property of the Fourier Transform¶
Problem:
Derive the differentiation property of the Fourier transform. In convention (b), given that the Fourier transform of \(f(x)\) is \(\tilde{f}(k)\):
(a) Show that the Fourier transform of \(f'(x) \equiv \frac{df}{dx}\) is \(ik\,\tilde{f}(k)\).
(b) Using this result, solve the differential equation \(f'(x) + \beta f(x) = 0\) (\(\beta > 0\)) in Fourier transform space, and reproduce \(f(x) = Ce^{-\beta x}\) (\(x > 0\)).
(a) Proof that the Fourier transform of \(f'(x)\) is \(ik\,\tilde{f}(k)\):
Calculation using convention (b):
Integration by parts (\(u = e^{-ikx}\), \(dv = f'(x)\,dx\)):
Assuming \(f(x) \to 0\) as \(x \to \pm\infty\), the boundary terms vanish:
(b) Solution of the differential equation \(f'(x) + \beta f(x) = 0\):
Method: Directly compute the Fourier transform of \(f(x) = Ce^{-\beta x}\theta(x)\).
Let \(f(x) = Ce^{-\beta x}\) for \(x > 0\) and \(f(x) = 0\) for \(x < 0\). That is, \(f(x) = Ce^{-\beta x}\theta(x)\).
Fourier transform:
Verification: Examining \(f'(x) + \beta f(x) = 0\) (for \(x > 0\)) in Fourier space.
\(f'(x) = -\beta Ce^{-\beta x}\theta(x) + C\delta(x)\) (the delta function arises from differentiating \(\theta\))
Taking the Fourier transform:
This equals \(\mathcal{F}[C\delta(x)] = \frac{C}{\sqrt{2\pi}}\). Thus \(f' + \beta f = C\delta(x)\) holds, and since the right-hand side is zero for \(x > 0\), the equation \(f' + \beta f = 0\) is satisfied.
Alternative solution (more direct): The general solution of the differential equation \(f' + \beta f = 0\) is \(f(x) = Ce^{-\beta x}\). When \(\beta > 0\), a physically decaying solution is obtained for \(x > 0\).
Verification: Substituting \(f(x) = Ce^{-\beta x}\) into the differential equation: \(f' = -\beta Ce^{-\beta x}\), so \(f' + \beta f = -\beta Ce^{-\beta x} + \beta Ce^{-\beta x} = 0\). ✓
Advanced¶
A-1. Fourier-Analytic Proof of the Uncertainty Relation¶
Problem:
Fourier-Analytic Proof of the Uncertainty Relation
Suppose a function \(f(x)\) and its Fourier transform \(\tilde{f}(k)\) (convention (b)) are both normalized (\(\int |f(x)|^2\,dx = 1\)). Define the "width" in position and the "width" in wave number respectively as
(for simplicity, assume \(\langle x \rangle = 0\), \(\langle k \rangle = 0\)).
(a) In the Cauchy–Schwarz inequality
set \(u(x) = x\,f(x)\), \(v(x) = f'(x)\) and derive \(\Delta x \cdot \Delta k \geq \frac{1}{2}\).
(b) Find the condition for equality to hold, and show that it corresponds to the Gaussian function \(f(x) = \left(\frac{1}{2\pi\sigma^2}\right)^{1/4} e^{-x^2/(4\sigma^2)}\).
(c) Confirm that by setting \(p = \hbar k\), one obtains the quantum mechanical uncertainty relation \(\Delta x \cdot \Delta p \geq \frac{\hbar}{2}\).
(a) Derivation of \(\Delta x \cdot \Delta k \geq \frac{1}{2}\):
Solution strategy: Substitute \(u(x) = xf(x)\), \(v(x) = f'(x)\) into the Cauchy–Schwarz inequality, and evaluate the left-hand side using integration by parts.
Step 1: Applying the Cauchy–Schwarz inequality
The first factor on the right-hand side is \((\Delta x)^2\):
Step 2: Proof that \(\int |f'(x)|^2\,dx = (\Delta k)^2\)
From the result of S5(a), \(\mathcal{F}[f'](appendix_c/k) = ik\,\tilde{f}(k)\). Applying Parseval's theorem:
Step 3: Evaluating the left-hand side
\(f(x)^*f'(x) = \frac{1}{2}\frac{d}{dx}|f(x)|^2 + \frac{i}{2}\frac{d}{dx}[\text{phase term}]\)...
More directly, we use integration by parts. Let \(I = \int_{-\infty}^{\infty} x\,f^*\,f'\,dx\).
From \(\frac{d}{dx}[x|f|^2] = |f|^2 + x\,f^*\,f' + x\,f\,(f^*)'\), we get:
Integration by parts:
(\(f(x) \to 0\) sufficiently fast as \(x \to \pm\infty\), normalization condition \(\int|f|^2\,dx = 1\))
Therefore \(I + I^* = 2\,\text{Re}(I) = -1\), i.e., \(\text{Re}(I) = -\frac{1}{2}\).
Thus \(|I| \geq |\text{Re}(I)| = \frac{1}{2}\).
Step 4: Completing the inequality
From Cauchy–Schwarz:
(b) Equality condition:
The equality condition for Cauchy–Schwarz is \(v(x) = \lambda\,u(x)\) (\(\lambda\) is a complex constant):
This is a separable differential equation:
For \(f(x)\) to converge to \(0\) as \(x \to \pm\infty\), we need \(\text{Re}(\lambda) < 0\).
Furthermore, examining the equality condition in detail: for \(|I| = |\text{Re}(I)|\) to hold, \(I\) must be real (and negative). Since \(I = \text{Re}(I) = -1/2\), \(I\) is indeed real.
\(I = \int x|f|^2 \cdot \frac{f'}{f}\,dx = \lambda\int x^2|f|^2\,dx = \lambda(\Delta x)^2\)
Since \(I\) is real, \(\lambda\) must also be real. Writing \(\lambda < 0\) as \(\lambda = -1/(2\sigma^2)\):
From the normalization condition \(\int|f|^2\,dx = 1\):
This is a Gaussian function (Gaussian wave packet).
(c) The quantum mechanical uncertainty relation:
Since \(p = \hbar k\), we have \(\Delta p = \hbar\,\Delta k\). Multiplying both sides of the result from (a), \(\Delta x \cdot \Delta k \geq \frac{1}{2}\), by \(\hbar\):
This is the Heisenberg uncertainty relation of quantum mechanics. Equality is achieved for Gaussian wave packets (coherent states).
Verification: For the Gaussian function \(f(x) = (2\pi\sigma^2)^{-1/4}e^{-x^2/(4\sigma^2)}\):
- \((\Delta x)^2 = \int x^2|f|^2\,dx = \sigma^2\) (variance of the Gaussian distribution)
- \(\tilde{f}(k) = (2\sigma^2/\pi)^{1/4}e^{-\sigma^2 k^2}\), so \((\Delta k)^2 = \frac{1}{4\sigma^2}\)
- \(\Delta x \cdot \Delta k = \sigma \cdot \frac{1}{2\sigma} = \frac{1}{2}\)
Equality holds. ✓
A-2. From Fourier Series to Parseval's Identity: Derivation of \(\zeta(2) = \pi^2/6\)¶
Problem:
From Fourier Series to Parseval's Identity: Derivation of \(\zeta(2) = \pi^2/6\)
(a) Using the Fourier series of \(f(x) = x\) on the interval \([0, L]\) (the result from S1), derive the Fourier series version of Parseval's identity:
(Hint: Integrate \(|f(x)|^2\) from Eq. (C.5) and use orthogonality.)
(b) By substituting the Fourier coefficients of \(f(x) = x\) into the result from (a), prove that
This is the value of \(\zeta(2)\) for the Riemann zeta function \(\zeta(s) = \sum_{n=1}^{\infty} n^{-s}\) (the Basel problem).
(a) Derivation of Parseval's Equality for Fourier Series:
Solution strategy: Integrate \(|f(x)|^2\) and use the orthogonality of the Fourier series.
From Eq. (C.5):
Integrate \(|f(x)|^2 = f(x) \cdot f(x)\) from \(0\) to \(L\):
Substituting the Fourier series twice into the right-hand side and expanding, the cross terms vanish by orthogonality (C.2)–(C.4). The surviving terms are:
- Constant term with itself: \(\left(\frac{a_0}{2}\right)^2 \cdot L = \frac{a_0^2}{4} \cdot L\)
- \(\cos\) terms with themselves (only \(n = m\)): \(a_n^2 \cdot \frac{L}{2}\)
- \(\sin\) terms with themselves (only \(n = m\)): \(b_n^2 \cdot \frac{L}{2}\)
Therefore:
Dividing both sides by \(L\):
(b) Proof that \(\zeta(2) = \pi^2/6\):
Substitute the results from S1. For \(f(x) = x\):
Left-hand side:
Right-hand side:
Setting up the equality:
Dividing by \(L^2\):
Final Answer:
Verification: Numerical check: \(1 + \frac{1}{4} + \frac{1}{9} + \frac{1}{16} + \frac{1}{25} + \cdots \approx 1.000 + 0.250 + 0.111 + 0.063 + 0.040 + \cdots \approx 1.55\)
\(\frac{\pi^2}{6} \approx \frac{9.870}{6} \approx 1.645\)
The partial sums converge to \(\pi^2/6\) from below, which is consistent. ✓
Also, the left-hand side of Parseval's equality \(\frac{1}{3}\) equals the right-hand side \(\frac{1}{4} + \frac{1}{2\pi^2} \cdot \frac{\pi^2}{6} = \frac{1}{4} + \frac{1}{12} = \frac{3+1}{12} = \frac{4}{12} = \frac{1}{3}\). ✓
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