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电动力学 第2周作业

Chasse_neige

本作业所有求和默认采用爱因斯坦求和约定。

1. 矢量分析

(a)

\(\epsilon_{ijk}\) 满足: $$ \sum_{k=1}^{3} \epsilon_{ijk} \epsilon_{lmk} = \delta_{il} \delta_{jm} - \delta_{im} \delta_{jl} $$

证明:

先除去所有 \(\epsilon_{ijk} \epsilon_{lmk} = 0\) 的情况,仅考虑\(i,j,k \text{和} l,m,k\) 互不相同的时侯。此时仅存在两种情况, \(i=l\)\(j=m\)\(i=m \text{且} j=l\) 。显然,当 \(i=l\)\(j=m\)时,\(\epsilon_{ijk} = \epsilon_{lmk}\) ;当 \(i=m \text{且} j=l\) 时,\(\epsilon_{ijk} = - \epsilon_{lmk}\)。所以 \(\epsilon_{ijk} \epsilon_{lmk} = \delta_{il} \delta_{jm} - \delta_{im} \delta_{jl}\),因为求和时仅有一个 \(k\) 满足\(i,j,k \text{和} l,m,k\) 互不相同的条件。

(b)

\(\delta_{ij}\)\(\epsilon_{ijk}\) 证明,

1. $$ \vec{a} \times (\vec{b} \times \vec{c}) = (\vec{a} \cdot \vec{c}) \vec{b} - (\vec{a} \cdot \vec{b}) \vec{c} $$ 证明: $$ \begin{aligned} \vec{a} \times (\vec{b} \times \vec{c}) &= \epsilon_{lkm} \epsilon_{ijk} a_{l} b_{i} c_{j} \vec{e_{m}} = \epsilon_{mlk} \epsilon_{ijk} a_{l} b_{i} c_{j} \vec{e_{m}} \\ &= (\delta_{mi} \delta_{lj} - \delta_{mj} \delta_{li}) a_{l} b_{i} c_{j} \vec{e_{m}} = a_{j} b_{i} c_{j} \vec{e_{i}} - a_{i} b_{i} c_{j} \vec{e_{m}} = (\vec{a} \cdot \vec{c}) \vec{b} - (\vec{a} \cdot \vec{b}) \vec{c} \end{aligned} $$ 2. $$ (\vec{a} \times \vec{b}) \times (\vec{c} \times \vec{d}) = [\vec{a} \cdot (\vec{b} \times \vec{d})] \vec{c} - [\vec{a} \cdot (\vec{b} \times \vec{c})] \vec{d} = [\vec{a} \cdot (\vec{c} \times \vec{d})] \vec{b} - [\vec{b} \cdot (\vec{c} \times \vec{d})] \vec{a} $$ 证明: $$ \begin{aligned} (\vec{a} \times \vec{b}) \times (\vec{c} \times \vec{d}) &= (\epsilon_{ijk} a_{i} b_{j} \vec{e_{k}}) \times (\epsilon_{lmn} c_{l} d_{m} \vec{e_{n}}) \\ &= \epsilon_{kns} \epsilon_{ijk} \epsilon_{lmn} a_{i} b_{j} c_{l} d_{m} \vec{e_{s}} = \epsilon_{ijk} (\delta_{sl} \delta_{km} - \delta_{sm} \delta_{kl}) a_{i} b_{j} c_{l} d_{m} \vec{e_{s}} \\ &= \epsilon_{ijk} (a_{i} b_{j} c_{l} d_{k} \vec{e_{l}} - a_{i} b_{j} c_{k} d_{m} \vec{e_{m}}) = [\vec{a} \cdot (\vec{b} \times \vec{d})] \vec{c} - [\vec{a} \cdot (\vec{b} \times \vec{c})] \vec{d} \\ \epsilon_{kns} \epsilon_{ijk} \epsilon_{lmn} a_{i} b_{j} c_{l} d_{m} \vec{e_{s}} &= (\delta_{ni} \delta_{sj} - \delta_{nj} \delta_{si}) \epsilon_{lmn} a_{i} b_{j} c_{l} d_{m} \vec{e_{s}} \\ &= \epsilon_{lmn} (a_{n} b_{s} c_{l} d_{m} \vec{e_{s}} - a_{s} b_{n} c_{l} d_{m} \vec{e_{s}}) = [\vec{a} \cdot (\vec{c} \times \vec{d})] \vec{b} - [\vec{b} \cdot (\vec{c} \times \vec{d})] \vec{a} \end{aligned} $$

(c) 思考选做题

试证明

i. 一阶张量除零矢量外,都不是各向同性的

证明:矢量\(\vec{A} = \begin{pmatrix} A_{1}, A_{2}, \cdots, A_{n} \end{pmatrix}\) 各向同性意味着对所有方向的单位矢量而言,\(\vec{A}\) 在它们上的投影值相同。 $$ \vec{A} \cdot \hat{e} = |\vec{A}| \cos<\vec{A}, \hat{e}> = const $$

\[ \therefore \,\, |\vec{A}| = 0 \]

ii. 二阶张量中的各向同性的张量必为 \(\lambda \delta_{ij}\)

证明:设二阶张量 $T_{ij} $ 满足 $ Q_{ki} Q_{lj} T_{ij} = T_{kl} $ 对所有正交阵 \(Q \(均成立。取\)Q\)为绕 \(z\) 轴的旋转阵,代入条件可得: $$ \begin{aligned} \begin{bmatrix} \cos \theta & \sin \theta \\ - \sin \theta & \cos \theta \end{bmatrix} \begin{bmatrix} T_{11} & T_{12} \\ T_{21} & T_{22} \end{bmatrix} \begin{bmatrix} \cos \theta & - \sin \theta \\ \sin \theta & \cos \theta \end{bmatrix} = \begin{bmatrix} T_{11} & T_{12} \\ T_{21} & T_{22} \end{bmatrix} \end{aligned} $$

$$ \begin{aligned} \therefore \,\, \begin{cases} T_{11} &= T_{12} \\ T_{22} &= T_{21} = 0 \end{cases} \end{aligned} $$ 同理,可以得到 $$ \begin{aligned} \begin{cases} T_{11} &= T_{33} \\ T_{13} &= T_{31} = 0 \\ T_{22} &= T_{33} \\ T_{23} &= T_{32} = 0 \end{cases} \end{aligned} $$ 即\(T_{ij} = \lambda \delta_{ij}\)

iii. 三阶张量中的各向同性的张量必为 \(\lambda \epsilon_{ijk}\)

证明:此时用上面的方法去凑变换消去自由度太繁琐,尝试再换一种方法:

考虑坐标架的一个无穷小转动 \(\delta \vec{\theta}\) 则任意三阶张量在转动后可以表达为: $$ T_{ijk}^{'} = T_{ijk} + \delta \theta_{l} (\epsilon_{lim}T_{mjk} + \epsilon_{ljm} T_{imk} + \epsilon_{lkm} T_{ijm}) $$ 要求转动前后分量相等,所以 $$ \epsilon_{lim}T_{mjk} + \epsilon_{ljm} T_{imk} + \epsilon_{lkm} T_{ijm} = 0 $$ 假设 $T $是完全反对称的,即满足: $$ T_{ijk} = A \epsilon_{ijk}, $$ 将 $ T_{ijk} = A \epsilon_{ijk} $ 代入原方程: $$ \epsilon_{lim} (A \epsilon_{mjk}) + \epsilon_{ljm} (A \epsilon_{imk}) + \epsilon_{lkm} (A \epsilon_{ijm}) = 0. $$ 提取常数 \( A \): $$ A \left( \epsilon_{lim} \epsilon_{mjk} + \epsilon_{ljm} \epsilon_{imk} + \epsilon_{lkm} \epsilon_{ijm} \right) = 0. $$ 将三项相加: $$ \begin{aligned} & (\delta_{lj}\delta_{ik} - \delta_{lk}\delta_{ij}) \\ + & (-\delta_{li}\delta_{jk} + \delta_{lk}\delta_{ij}) \\ + & (\delta_{li}\delta_{kj} - \delta_{lj}\delta_{ki}) \\ = & \delta_{lj}\delta_{ik} - \delta_{lk}\delta_{ij} -\delta_{li}\delta_{jk} + \delta_{lk}\delta_{ij} + \delta_{li}\delta_{kj} - \delta_{lj}\delta_{ki} = 0 \end{aligned} $$ 对于非完全反对称的一般 \(T\) ,对其做对称反对称分解,其中的对称部分设为\(S_{ijk}\)

带入: $$ \epsilon_{lim} S_{mjk} + \epsilon_{ljm} S_{imk} + \epsilon_{lkm} S_{ijm} = 0 $$

\[ \epsilon_{lnm} (\epsilon_{lim} S_{mjk} + \epsilon_{ljm} S_{imk} + \epsilon_{lkm} S_{ijm}) = 0 \]
\[ 2(\delta_{ni} S_{mjk} + \delta_{nj} S_{imk} + \delta_{nk} S_{ijm}) = 0 \]

\(n = i\) 时: $$ \delta_{ni} S_{mjk} + \delta_{nj} S_{imk} + \delta_{nk} S_{ijm} = S_{mjk} + \delta_{ij} S_{imk} + \delta_{ik} S_{ijm} = S_{mjk} + S_{jmk} + S_{kjm} = 3 S_{mjk} $$

\(n = j\)\(n = k\) 时同理。 $$ \therefore \,\, \delta_{ni} S_{mjk} + \delta_{nj} S_{imk} + \delta_{nk} S_{ijm} = 3 (S_{mjk} + S_{imk} + S_{ijm}) = 0 $$

\[ S_{ijk} = 0 \]

即不能存在对称分量。

iv. 四阶张量中的各向同性的张量必为 \(\lambda \delta_{ij} \delta_{kl} + \alpha \delta_{ik} \delta_{jl} + \beta \delta_{il} \delta_{jk}\)

对于四阶各向同性张量,推广形式为:

\(\epsilon_{mis}\,a_{sjkl} + \epsilon_{mjs}\,a_{iskl} + \epsilon_{mks}\,a_{ijsl} + \epsilon_{mls}\,a_{ijks} = 0\)

分别乘以\(\epsilon_{mit}\)\(\epsilon_{mjt}\)\(\epsilon_{mkt}\)\(\epsilon_{mlt}\),并令\(t=i\)\(t=j\)\(t=k\)\(t=l\),得到:

\(2\,a_{ijkl} + a_{jikl} + a_{kjil} + a_{ljki} = a_{sskl}\,\delta_{ij} + a_{sjsl}\,\delta_{ik} + a_{sjks}\,\delta_{il}\) \(2\,a_{ijkl} + a_{jikl} + a_{ikjl} + a_{iljk} = a_{sskl}\,\delta_{ij} + a_{isks}\,\delta_{jl} + a_{issl}\,\delta_{jk}\) \(2\,a_{ijkl} + a_{kjil} + a_{ikjl} + a_{ijlk} = a_{ijss}\,\delta_{kl} + a_{sjsl}\,\delta_{ik} + a_{issl}\,\delta_{jk}\) \(2\,a_{ijkl} + a_{ljki} + a_{ilkj} + a_{ijlk} = a_{ijss}\,\delta_{kl} + a_{isks}\,\delta_{jl} + a_{sjks}\,\delta_{il}\)

由于\(a_{sskl}\)\(a_{sjsl}\)\(a_{sjks}\)是二阶各向同性张量,我们有:

\(a_{sskl} = \lambda\,\delta_{kl}\) \(a_{sjsl} = \mu\,\delta_{jl}\) \(a_{sjks} = \nu\,\delta_{jk}\)

因此,

\(a_{ijkl} = \alpha\,\delta_{ij}\,\delta_{kl} + \beta\,\delta_{ik}\,\delta_{jl} + \gamma\,\delta_{il}\,\delta_{jk}\)

其中:

\(\alpha = \frac{4\lambda - \mu - \nu}{10}\) \(\beta = \frac{4\mu - \nu - \lambda}{10}\) \(\gamma = \frac{4\nu - \lambda - \mu}{10}\)

2. 场论

1.1

根据算符∇的微分性与矢量性,推导下列公式: $$ \nabla(\mathbf{A} \cdot \mathbf{B}) = \mathbf{B} \times (\nabla \times \mathbf{A}) + (\mathbf{B} \cdot \nabla) \mathbf{A} + \mathbf{A} \times (\nabla \times \mathbf{B}) + (\mathbf{A} \cdot \nabla) \mathbf{B} $$

\[ \mathbf{A} \times (\nabla \times \mathbf{A}) = \frac{1}{2} \nabla A^2 - (\mathbf{A} \cdot \nabla) \mathbf{A} \]

证明:第一个式子从右推左 $$ \mathbf{B} \times (\nabla \times \mathbf{A}) + \mathbf{A} \times (\nabla \times \mathbf{B}) = \nabla_{A} (\mathbf{A} \cdot \mathbf{B}) + \nabla_{B} (\mathbf{A} \cdot \mathbf{B}) - (\mathbf{B} \cdot \nabla) \mathbf{A} - (\mathbf{A} \cdot \nabla) \mathbf{B} $$ 其中 \(\nabla\) 的下标表示仅对该分量做微分。 $$ \begin{aligned} &\therefore \,\, \mathbf{B} \times (\nabla \times \mathbf{A}) + (\mathbf{B} \cdot \nabla) \mathbf{A} + \mathbf{A} \times (\nabla \times \mathbf{B}) + (\mathbf{A} \cdot \nabla) \mathbf{B} \\ &= \nabla_{A} (\mathbf{A} \cdot \mathbf{B}) + \nabla_{B} (\mathbf{A} \cdot \mathbf{B}) - (\mathbf{B} \cdot \nabla) \mathbf{A} - (\mathbf{A} \cdot \nabla) \mathbf{B} + (\mathbf{B} \cdot \nabla) \mathbf{A} + (\mathbf{A} \cdot \nabla) \mathbf{B} \\ &= \nabla_{A} (\mathbf{A} \cdot \mathbf{B}) + \nabla_{B} (\mathbf{A} \cdot \mathbf{B}) = \nabla (\mathbf{A} \cdot \mathbf{B}) \end{aligned} $$ 第二个式子从左推右,为了区分,给两个A加上下标,但是它们本质上是一样的。 $$ \mathbf{A_{1}} \times (\nabla \times \mathbf{A_{2}}) = \nabla_{\mathbf{A_{2}}} (\mathbf{A_{1}} \cdot \mathbf{A_{2}}) - (\mathbf{A_{1}} \cdot \nabla) \mathbf{A_{2}} $$

\[ \because \,\, \nabla_{\mathbf{A_{2}}} (\mathbf{A_{1}} \cdot \mathbf{A_{2}}) = \nabla_{\mathbf{A_{1}}} (\mathbf{A_{1}} \cdot \mathbf{A_{2}}) \]
\[ \therefore \,\, \nabla_{\mathbf{A_{2}}} (\mathbf{A_{1}} \cdot \mathbf{A_{2}}) = \frac{1}{2} (\nabla_{\mathbf{A_{1}}} (\mathbf{A_{1}} \cdot \mathbf{A_{2}}) + \nabla_{\mathbf{A_{2}}} (\mathbf{A_{1}} \cdot \mathbf{A_{2}})) = \frac{1}{2} \nabla A^2 \]
\[ \therefore \,\, \mathbf{A} \times (\nabla \times \mathbf{A}) = \frac{1}{2} \nabla A^2 - (\mathbf{A} \cdot \nabla) \mathbf{A} \]

1.3

\(r=\sqrt{(x-x')^2+(y-y')^2+(z-z')^2}\) 为源点 \(x'\) 到场点 \(x\) 的距离,\(r\) 的方向规定为从源点指向场点。

(1) 证明下列结果,并体会对源变数求微商 \(\left(\nabla'=\mathbf{e}_x \frac{\partial}{\partial x'}+\mathbf{e}_y \frac{\partial}{\partial y'}+\mathbf{e}_z \frac{\partial}{\partial z'}\right)\) 与对场变数求微商 \(\left(\nabla=\mathbf{e}_x \frac{\partial}{\partial x}+\mathbf{e}_y \frac{\partial}{\partial y}+\mathbf{e}_z \frac{\partial}{\partial z}\right)\) 的关系:

$$ \begin{aligned} \nabla r &= -\nabla' r = \frac{\mathbf{r}}{r} \\ \nabla \frac{1}{r} &= -\nabla' \frac{1}{r} = -\frac{\mathbf{r}}{r^3} \\ \nabla \times \frac{\mathbf{r}}{r^3} &= 0 \\ \nabla \cdot \frac{\mathbf{r}}{r^3} &= -\nabla' \cdot \frac{\mathbf{r}}{r^3} = 0 \quad (r \neq 0) \end{aligned} $$ (最后一式在 \(r=0\) 点不成立,见第二章 §5)。

证明:将 \(r\) 表示为直角坐标下的分量式 \(\vec{r} = (x-x^{'}) \vec{e_{x}} + (y - y^{'}) \vec{e_{y}} + (z - z^{'}) \vec{e_{z}}\)\(r=\sqrt{(x-x')^2+(y-y')^2+(z-z')^2}\)
$$ \nabla r = \partial_{i} \sqrt{(x_{i} - x_{i}^{'})^{2}} \vec{e_{i}} = \frac{(x_{i} - x_{i}^{'}) \vec{e_{i}}}{\sqrt{(x_{i} - x_{i}^{'})^{2}}} = \frac{\vec{r}}{r} $$

\[ \nabla^{'} r = \partial_{i}^{'} \sqrt{(x_{i} - x_{i}^{'})^{2}} \vec{e_{i}} = - \frac{(x_{i} - x_{i}^{'}) \vec{e_{i}}}{\sqrt{(x_{i} - x_{i}^{'})^{2}}} = - \frac{\vec{r}}{r} \]
\[ \nabla \frac{1}{r} = \partial_{i} \frac{1}{\sqrt{(x_{i} - x_{i}^{'})^{2}}} \vec{e_{i}} = - \frac{(x_{i} - x_{i}^{'}) \vec{e_{i}}}{\sqrt{(x_{i} - x_{i}^{'})^{2}}^{3}} = - \frac{\vec{r}}{r^{3}} \]
\[ \nabla^{'} \frac{1}{r} = \partial_{i}^{'} \frac{1}{\sqrt{(x_{i} - x_{i}^{'})^{2}}} \vec{e_{i}} = \frac{(x_{i} - x_{i}^{'}) \vec{e_{i}}}{\sqrt{(x_{i} - x_{i}^{'})^{2}}^{3}} = \frac{\vec{r}}{r^{3}} \]
\[ \nabla \times \frac{\vec{r}}{r^{3}} = - \nabla \times (\nabla \frac{1}{r}) = 0 \]
\[ \nabla \cdot \frac{\vec{r}}{r^3} = -\nabla' \cdot \frac{\vec{r}}{r^3} = \frac{3}{r^{3}} - 3 \frac{\vec{r}}{r^{5}} \cdot \vec{r} = 0 \,\, (r \neq 0 ) \]

(2) 求 \(\nabla \cdot \mathbf{r}\)\(\nabla \times \mathbf{r}\)\((\mathbf{a} \cdot \nabla) \mathbf{r}\)\(\nabla (\mathbf{a} \cdot \mathbf{r})\)\(\nabla \cdot [\mathbf{E}_0 \sin (\mathbf{k} \cdot \mathbf{r})]\)\(\nabla \times [\mathbf{E}_0 \sin (\mathbf{k} \cdot \mathbf{r})]\),其中 \(\mathbf{a}\)\(\mathbf{k}\)\(\mathbf{E}_0\) 均为常矢量。 $$ \nabla \cdot \vec{r} = 3 $$

\[ \nabla \times \vec{r} = 0 \]
\[ (\vec{a} \cdot \nabla)\vec{r} = \vec{a} \cdot \overset{\leftrightarrow}{I} = \vec{a} \]
\[ \nabla (\vec{a} \cdot \vec{r}) = (\vec{a} \cdot \nabla) \vec{r} + (\vec{r} \cdot \nabla) \vec{a} + \vec{a} \times (\nabla \times \vec{r}) + \vec{r} \times (\nabla \times \vec{a}) = \vec{a} + 0 + 0 + 0 = \vec{a} \]
\[ \nabla \cdot [\mathbf{E}_0 \sin (\mathbf{k} \cdot \mathbf{r})] = (\nabla \sin(\vec{k} \cdot \vec{r})) \cdot \vec{E_{0}} + \sin(\vec{k} \cdot \vec{r}) \nabla \cdot \vec{E_{0}} = \cos (\vec{k} \cdot \vec{r}) \,\, \nabla(\vec{k} \cdot \vec{r}) \cdot \vec{E_{0}} + 0 = \cos (\vec{k} \cdot \vec{r}) (\vec{k} \cdot \vec{E_{0}}) \]
\[ \nabla \times [\mathbf{E}_0 \sin (\mathbf{k} \cdot \mathbf{r})] = (\nabla \sin(\vec{k} \cdot \vec{r})) \times \vec{E_{0}} + \sin(\vec{k} \cdot \vec{r}) \nabla \times \vec{E_{0}} = \cos (\vec{k} \cdot \vec{r}) \vec{k} \times \vec{E_{0}} + 0 = \cos (\vec{k} \cdot \vec{r}) (\vec{k} \times \vec{E_{0}}) \]

1.6

\(\mathbf{m}\) 是常矢量,证明除 \(R=0\) 点以外,矢量 \(\mathbf{A} = \frac{\mathbf{m} \times \mathbf{R}}{R^3}\) 的旋度等于标量 \(\varphi = \frac{\mathbf{m} \cdot \mathbf{R}}{R^3}\) 的梯度的负值,即 $$ \nabla \times \mathbf{A} = -\nabla \varphi \qquad (R \neq 0) $$

其中 \(\mathbf{R}\) 为坐标原点到场点的距离,方向由原点指向场点。

证明: $$ \begin{aligned} \nabla \times \vec{A} &= - \nabla \times (\vec{m} \times \nabla \frac{1}{r}) = - (\vec{m} \nabla^{2} \frac{1}{r} - \vec{m} \cdot \nabla \nabla \frac{1}{r} + (\nabla \frac{1}{r}) \cdot (\nabla \vec{m}) - (\nabla \frac{1}{r})(\nabla \cdot \vec{m})) \\ &= -(0 - \frac{3 (\vec{m} \cdot \vec{r}) \vec{r}}{r^{5}} + \frac{\vec{m}}{r^{3}} + 0 - 0) = - \frac{\vec{m}}{r^{3}} + \frac{3(\vec{m} \cdot \vec{r})}{r^{5}} \qquad (R \neq 0) \end{aligned} $$

\[ \begin{aligned} - \nabla \varphi &= \nabla (\vec{m} \cdot \nabla \frac{1}{r}) = \vec{m} \times (\nabla \times \nabla \frac{1}{r}) + \nabla \frac{1}{r} \times (\nabla \times \vec{m}) + (\vec{m} \cdot \nabla) \nabla \frac{1}{r} + (\nabla \frac{1}{r} \cdot \nabla) \vec{m} \\\\ &= 0 + 0 + \vec{m} \cdot \nabla \nabla \frac{1}{r} + 0 = - \frac{\vec{m}}{r^{3}} + \frac{3(\vec{m} \cdot \vec{r})}{r^{5}} \qquad (R \neq 0) \end{aligned} \]

思考题

\(\nabla \cdot \vec{A} > 0\)\(\nabla \cdot \vec{A} = 0\)\(\nabla \cdot \vec{A} < 0\) 在直观图像上有什么差别?\(\nabla \times \vec{A} > 0\)\(\nabla \times \vec{A} = 0\)\(\nabla \times \vec{A} < 0\) 呢?

\(\nabla \cdot \vec{A} > 0\) 在直观上表示为矢量场\(\vec{A}\) 在图像上从该点向四周“发射”,总体作用向外的;

\(\nabla \cdot \vec{A} = 0\) 在直观上表现为该点的矢量场在打转或者干脆没有,进出相互抵消,总通量为0;

\(\nabla \cdot \vec{A} < 0\) 在直观上表现为该点的矢量场向内汇聚,总体作用向内。

\(\nabla \times \vec{A} = 0\) 表现为该点的矢量场沿着径向或者为0。

我不知道\(\nabla \times \vec{A} > 0\) \(\nabla \times \vec{A} < 0\)是什么意思。如果是针对一个特定方向定义的话那么代表着二者旋转方向相反。

3. \(\delta\) 函数

2.14

画出函数 \(\frac{\mathrm{d}\delta(x)}{\mathrm{d}x}\) 的图,说明 \(\rho = -(\mathbf{p} \cdot \nabla)\delta(\mathbf{x})\) 是一个位于原点的偶极子的电荷密度。

函数 \(\frac{\mathrm{d}\delta(x)}{\mathrm{d}x}\) 的图:

image-20250228141027350

注:因为严格的图像画出后函数曲线和坐标轴不太好分辨,此图是利用高斯函数在极限情况下的一个近似图像,可以体现函数的部分性质。

证明: $$ \begin{aligned} \int \rho \vec{r} \, d \tau &= \int -(\vec{p} \cdot \nabla)\delta(\vec{r}) \, \vec{r} \, d \tau = \int ( (\nabla \cdot \vec{p}) \delta(\vec{r}) - \nabla \cdot (\delta(\vec{r}) \vec{p})) \vec{r} d \tau \\ &= - \int \nabla \cdot (\delta(\vec{r}) \vec{p} \vec{r}) d \tau + \int \delta(\vec{r}) \vec{p} \cdot \nabla \vec{r} \, d \tau = \int \delta(\vec{r}) \vec{p} \, d \tau = \vec{p} \end{aligned} $$

思考题:

(1) \(\delta(ax) = \frac{1}{|a|}\delta(x), a > 0\). (若 \(a < 0\),结果如何?)

证明: $$ \begin{aligned} \delta(ax) \, d (ax) &= \delta (x) \, dx \\ \therefore \,\, \delta(ax) &= \frac{1}{|a|}\delta(x), a > 0 \end{aligned} $$ 当 \(a < 0\) 时, $$ \delta(ax) = - \frac{1}{|a|}\delta(x), a > 0 $$

(2) \(x\delta(x) = 0\). $$ \because \,\, f(x) \delta(x-x_{0}) = f(x_{0}) $$

\[ \therefore \,\, x \delta (x-0) = 0 \]