Vector and tensor

2015-04-01

  • 1 Tensor
    • 1.1 Change of basis
    • 1.2 Cartesian tensors
    • 1.3 1-order and 0-order tensor
      • 1.3.1 1-order tensor forms 0-order tensor.
      • 1.3.2 0-order tensor forms 1-order tensor.
    • 1.4 2-order tensor
      • 1.4.1 1-order tensor form 2-order tensor
    • 1.5 Tensor operations
    • 1.6 Frequently used operations
    • 1.7 Miscellaneous
  • 2 Vector Integral
    • 2.1 Line/Path integral
    • 2.2 Theorem

1 Tensor

  • Resources[fn:1]
  • Key idea: physical results must indeed be independent of the choice of coordinate system

1.1 Change of basis

  • vector \(\vec{x} = x_{i} \vec{e_{i}}\)
  • new basis \(\vec{e^{\prime}_{j}} = S_{ij} \vec{e_{i}}\), \(S_{ij}\) is ith component
  • \(\vec{x} = x^{\prime}_{i} \vec{e^{\prime}_{i}} = x^{\prime}_{i} S_{ij} \vec{e_{ij}} = x_{j} \vec{e_{j}}, S\) is matrix
  • \(x^{\prime}_{i} = (S^{-1})_{ij} x_{j}\)
  • If transformation is rotation of the coordinate axes, then \(S\) is orthogonal and \(L L^{T} = L^{T} L = I\)

1.2 Cartesian tensors

  • define \(L\) as the inverse of \(S\), then \(x^{\prime}_{i} = L_{ij} x_{j}\)
  • Restrict in the type of rigid rotation, so \(L^{-1} = L^{T}\), then \(x_{i} = L_{ji} x^{\prime}_{j}\)

1.3 1-order and 0-order tensor

1.3.1 1-order tensor forms 0-order tensor.

Prove: scalar product of 2 1-order tensors is 0-order tensor

\[ \begin{align} u^{\prime}_{i} v^{\prime}_{i} &= L_{ij} u_{j} L_{ik} v_{k} \\ &= L_{ij} L_{ik} u_{j} v_{k} \\ &= \delta_{jk} u_{j} v_{k} \\ &= u_{j} v_{j} \\ \end{align} \]

1.3.2 0-order tensor forms 1-order tensor.

Suppose electrostatic potential \(\phi\), its component \(E_{i} = - \frac{\partial \phi}{\partial x_{i}}\).

Prove \(\vec{E}\)is 1-order tensor.

\[ \begin{align} E^{\prime}_{i} &= (-\frac{\partial \phi}{\partial x_{i}})^{\prime} \\ &= - \frac{\partial \phi_{\prime}}{\partial x^{\prime}_{i}} \\ &= - \frac{\partial \phi}{\partial x^{\prime}_{i}} \\ &= - \frac{\partial \phi}{\partial x_{j}} \frac{\partial x_{j}}{\partial x^{\prime}_{i}} \\ &= L_{ij} E_{j} \\ \end{align} \]

1.4 2-order tensor

Definition

\[ \begin{equation} T^{\prime}_{ij} = L_{ik} L_{jl} T_{kl} \end{equation} \]

Given the definition, it’s natural to display 2-order tensor in matrix form.

Note: it’s similar to linear operator(???), but it requires both 2 subscript refer to the same coordinate system.

1.4.1 1-order tensor form 2-order tensor

1.4.1.1 The outer product of 2 vectors

Definition

\[ \begin{equation} T_{ij} = u_{i} v_{j} \end{equation} \]

denoted as \(\vec{T} = \vec{u} \bigotimes \vec{v}\), then

\[ \begin{align} \vec{T} &= u_{i} \vec{e_{i}} \bigotimes u_{j} \vec{e_{j}} \\ &= u_{i} v_{j} \vec{e_{i}} \bigotimes \vec{e_{j}} \\ &= T_{ij} \vec{e_{i}} \bigotimes \vec{e_{j}} \\ \end{align} \]

Prove \(T_{ij}\) is 2-order tensor.

\[ \begin{align} T_{ij} &= u^{\prime}_{i} v^{\prime}_{j} \\ &= L_{ik} u_{k} L_{jl} v_{l} \\ &= L_{ik} L_{jl} u_{k} v_{l} \\ &= L_{ik} L_{jl} T_{kl} \\ \end{align} \]

1.4.1.2 The gradient of a vector

Definition

\[ \begin{equation} T_{ij} = \frac{\partial v_{i}}{\partial x_{j}} \end{equation} \]

denoted as \(\vec{T} = \nabla \vec{V}\) (???)

Prove it’s a 2-order tensor

\[ \begin{align} T^{\prime}_{ij} &= \frac{\partial v^{\prime}_{i}}{\partial x^{\prime}_{j}} \\ &= \frac{\partial (L_{ik} v_{k})}{\partial x_{l}} \frac{\partial x_{l}}{\partial x^{\prime}_{j}} \\ &= L_{ik} \frac{\partial v_{k}}{\partial x_{l}} L_{jl}(???) \\ &= L_{ik} L_{jl} T_{kl} \\ \end{align} \]

1.5 Tensor operations

  1. Addition

    \[ \begin{align} S_{ij} = b_{ij} + c_{ij} \end{align} \]

  2. Contraction

    \[ \begin{align} W_{k} \equiv d_{iik} \end{align} \]

    means contracting \(i\) and \(j\). N-order tensor becomes N-2 order tensor. \(W_{k}\) is 1-order tensor.

  3. Tensor products

    \[ \begin{align} d_{ijk} = u_{i} b_{jk} \end{align} \]

  4. Inner products

    \[ \begin{align} d_{ilm} = b_{ij} c_{jlm} \end{align} \]

    N-order and M-order tensors lead to N+M-2 order tensor. (???)

  5. Division

    No such tensor operation.

  6. Gradients

    \[ \begin{align} \nabla & \equiv \vec{e}_{i} \frac{\partial}{\partial x_{i}} \\ h_{kij} &= \nabla \vec{b} = \frac{\partial b_{ij}}{\partial x_{k}} \\ \end{align} \]

    It’s similar to tensor product of \(\nabla, \vec{b}\).

  7. Divergence

    \[ \begin{align} \nabla \cdot \vec{b} = \vec{e}_{j} \frac{\partial b_{ij}}{\partial x_{i}} \end{align} \]

    Take inner product of \(\nabla, \vec{b}\). (???)

  8. Laplacian

    \[ \begin{align} \nabla^{2} = \nabla \cdot \nabla = \frac{\partial^{2}}{\partial x_{i} \partial x_{i}} \end{align} \]

  9. Taylor series

    Let \(\vec{b}(\vec{x})\) is a smooth second-order tensor field, then the value of \(\vec{b}\) at position \(\vec{y} + \vec{r}\) can be obtained as

    \[ \begin{align} b_{ij}(\vec{y} + \vec{r}) = b_{ij}(\vec{y}) + \big ( \frac{\partial b_{ij}}{\partial x_{k}} \big )_{y} r_{k} + \frac{1}{2!} \big ( \frac{\partial^{2} b_{ij}}{\partial x_{k} \partial x_{l}} \big )_{y} r_{k} r_{l} + \ldots \end{align} \]

  10. Gauss’s theorem

    Let \(\mathcal{A}\) be a piecewise smooth closed orientable surface that encloses a volume \(\mathcal{V}\), and let \(\vec{n}\) denote the outward-pointing unit normal on \(\mathcal{A}\). Then

    \[ \begin{align} \iiint_{\mathcal{V}} \frac{\partial b_{ij}}{\partial x_{k}} dV = \iint_{\mathcal{A}} b_{ij} n_{k} dA \end{align} \]

  11. Vector cross product

    The alternating symbol defined by

    \[ \begin{align} \varepsilon_{ijk} &= 1, \quad (i,j,k) \quad cyclic; \\ &= -1, \quad (i,j,k) \quad anticyclic; \\ &= 0, \quad otherwise \\ \end{align} \]

    Cyclice orderings are 123, 231, and 312; anticyclic orderings are 321, 132, and 213, otherwise two or more of the suffixes are the same.

    \[ \begin{align} \vec{r} &= \vec{u} \times \vec{v} = det \begin{vmatrix} \vec{e}_{1} & \vec{e}_{2} & \vec{e}_{3} \\ u_{1} & u_{2} & u_{3} \\ v_{1} & v_{2} & v_{3} \\ \end{vmatrix} \\ &= \varepsilon_{ijk} \vec{e}_{i} u_{j} v_{k} \\ \end{align} \]

    Cross product and curl are not 1-order tensor, they are pseudovectors, And the direction of them is determined by the right handed rule.

1.6 Frequently used operations

1.7 Miscellaneous

  1. In 3D, the pseudovector (or axial vector) \(\vec{p}\) is associated with the cross product of 2 vectors: \(\vec{p} = \vec{a} \times \vec{b}\).

2 Vector Integral

2.1 Line/Path integral

2 main kinds

  • \(\int_{C} \phi d \vec{r}\)

    Since Cartesian unit vectors are of constant magnitude and direction, hence

    \[ \begin{align} \int \phi \vec{i} dx = \vec{i} \int \phi dx \end{align} \]

    Then

    \[ \begin{align} \int_{C} \phi d \vec{r} = \vec{i} \int_{C} \phi(x,y,z) dx + \vec{j} \int_{C} \phi(x,y,z) dy + \vec{k} \int_{C} \phi(x,y,z) dz \end{align} \]

  • \(\int_{C} \vec{a} \cdot d \vec{r}\)

    \[ \begin{align} \int_{C} \vec{a} \cdot d \vec{r} &= \int_{C} \Big ( a_{x} \vec{i} + a_{y} \vec{j} + a_{z} \vec{k} \Big ) \cdot \Big ( dx \vec{i} + dy \vec{j} + dz \vec{k} \Big ) \\ &= \int_{C} \Big ( a_{x} dx + a_{y} dy + a_{z} dz \Big ) \\ \end{align} \]

2.2 Theorem

  1. Helmholtz’s theorem, also known as the fundamental theorem of vector calculus, states that vector field in 3D can be resolved into the sum of the irrotational(curl-free) vector field and a solenoidal(divergence-free) vector field. That’s known as the Helmholtz decomposition.

    \[ \begin{align} \vec{F} = \nabla \phi + \nabla \times \vec{psi} \end{align} \]

    \(\nabla \phi\) is irrotational part since \(\nabla \times \nabla \phi = 0\). \(\nabla \times \vec{psi}\) is solenoidal part since \(\nabla \cdot (\nabla \times \vec{\psi}) = 0\).

Footnotes

[fn:1] Riley K F, Hobson M P, Bence S J. Mathematical methods for physics and engineering: a comprehensive guide[M]. Cambridge University Press, 2006.

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Created on 2015-04-01 with pandoc