Vector calculus identities

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The following identities are important in vector calculus:

Operator notations[edit]


Main article: Gradient

Gradient of a tensor field, \mathbf{A}, of order n, is generally written as

\operatorname{grad}(\mathbf{A}) = \nabla \mathbf{A}

and is a tensor field of order n + 1. In particular, if the tensor field has order 0 (i.e. a scalar), \psi, the resulting gradient,

\operatorname{grad}(\psi) = \nabla \psi

is a vector field.


Main article: Divergence

The divergence of a tensor field, \mathbf{A}, of non-zero order n, is generally written as

\operatorname{div}(\mathbf{A}) = \nabla \cdot \mathbf{A}

and is a contraction to a tensor field of order n − 1. Specifically, the divergence of a vector is a scalar. The divergence of a higher order tensor field may be found by decomposing the tensor field into a sum of outer products, thereby allowing the use of the identity,

\nabla \cdot (\mathbf{B} \otimes \hat{\mathbf{A}}) = \hat{\mathbf{A}}(\nabla \cdot \mathbf{B})+(\mathbf{B}\cdot \nabla) \hat{\mathbf{A}}

where  \mathbf{B}\cdot\nabla is the directional derivative in the direction of  \mathbf{B} multiplied by its magnitude. Specifically, for the outer product of two vectors,

\nabla \cdot (\mathbf{a} \mathbf{b}^\mathrm{T}) = \mathbf{b}(\nabla \cdot \mathbf{a})+(\mathbf{a}\cdot \nabla) \mathbf{b} \ .


Main article: Curl (mathematics)

For a 3-dimensional vector field  \mathbf{v} , curl is is also a 3-dimensional vector field, generally written as:

 \nabla \times \mathbf{v}

or in Einstein notation as:

 \varepsilon_{ijk} \frac {\partial v_k}{\partial x_j}

where ε is the Levi-Civita symbol.


Main article: Laplace operator

For a tensor field,  \mathbf{A} , the laplacian is generally written as:

\Delta\mathbf{A} = \nabla^2 \mathbf{A} = (\nabla \cdot \nabla) \mathbf{A}

and is a tensor field of the same order.

Special notations[edit]

In Feynman subscript notation,

 \nabla_\mathbf{B} \left( \mathbf{A \cdot B} \right) = \mathbf{A} \times \left( \nabla \times \mathbf{B} \right) + \left( \mathbf{A} \cdot \nabla \right) \mathbf{B}

where the notation ∇B means the subscripted gradient operates on only the factor B.[1][2]

A less general but similar idea is used in geometric algebra where the so-called Hestenes overdot notation is employed.[3] The above identity is then expressed as:

 \dot{\nabla} \left( \mathbf{A} \cdot \dot{\mathbf{B}} \right) = \mathbf{A} \times \left( \nabla \times \mathbf{B} \right) + \left( \mathbf{A} \cdot \nabla \right) \mathbf{B}

where overdots define the scope of the vector derivative. The dotted vector, in this case B, is differentiated, while the (undotted) A is held constant.

For the remainder of this article, Feynman subscript notation will be used where appropriate.


Distributive properties[edit]

 \nabla ( \psi + \phi ) = \nabla \psi + \nabla \phi
 \nabla \cdot ( \mathbf{A} + \mathbf{B} ) = \nabla \cdot \mathbf{A} + \nabla \cdot \mathbf{B}
 \nabla \times ( \mathbf{A} + \mathbf{B} ) = \nabla \times \mathbf{A} + \nabla \times \mathbf{B}

Product rule for the gradient[edit]

The gradient of the product of two scalar fields \psi and \phi follows the same form as the product rule in single variable calculus.

 \nabla (\psi \, \phi) = \phi \,\nabla \psi  + \psi \,\nabla \phi

Product of a scalar and a vector[edit]

 \nabla \cdot ( \psi \mathbf{A} ) = \mathbf{A} \cdot \nabla \psi + \psi ( \nabla \cdot \mathbf{A} )
 \nabla \times ( \psi \mathbf{A} ) = \psi ( \nabla \times \mathbf{A}) + ( \nabla \psi ) \times \mathbf{A}

Quotient rule[edit]

 \nabla\left(\frac{f}{g}\right) = \frac{g\nabla f - f\nabla g}{g^2}
 \nabla \cdot \left(\frac{\mathbf{A}}{g}\right) = \frac{(\nabla \cdot \mathbf{A})g - \mathbf{A} \cdot \nabla g}{g^2}
 \nabla \times \left(\frac{\mathbf{A}}{g}\right) = \frac{(\nabla \times \mathbf{A})g + \mathbf{A} \times \nabla g}{g^2}

Chain rule[edit]

\nabla(f \circ g) = (f' \circ g) \nabla g
\nabla(f \circ \mathbf{A}) = (\nabla f \circ \mathbf{A}) \nabla \mathbf{A}
\nabla \cdot (\mathbf{A} \circ f) = (\mathbf{A}' \circ f) \cdot \nabla f
\nabla \times (\mathbf{A} \circ f) = -(\mathbf{A}' \circ f) \times \nabla f

Vector dot product[edit]

\nabla(\mathbf{A} \cdot \mathbf{B})
&= \mathbf{J}^\mathrm{T}_\mathbf{A} \mathbf{B} + \mathbf{J}^\mathrm{T}_\mathbf{B} \mathbf{A} \\
&= (\mathbf{A} \cdot \nabla)\mathbf{B} + (\mathbf{B} \cdot \nabla)\mathbf{A} + \mathbf{A} \times (\nabla \times \mathbf{B}) + \mathbf{B} \times (\nabla \times \mathbf{A}) \ .

where JA denotes the Jacobian of A.

Alternatively, using Feynman subscript notation,

 \nabla(\mathbf{A} \cdot \mathbf{B}) = \nabla_\mathbf{A}(\mathbf{A}  \cdot \mathbf{B}) +  \nabla_\mathbf{B} (\mathbf{A} \cdot \mathbf{B}) \ .

As a special case, when A = B,

\frac{1}{2} \nabla \left( \mathbf{A}\cdot\mathbf{A} \right)
&= \mathbf{J}^\mathrm{T}_\mathbf{A} \mathbf A \\
&= (\mathbf{A} \cdot \nabla) \mathbf{A} + \mathbf{A} \times (\nabla \times \mathbf{A}) \ .

Vector cross product[edit]

 \nabla \cdot (\mathbf{A} \times \mathbf{B}) = (\nabla \times \mathbf{A}) \cdot \mathbf{B} - \mathbf{A} \cdot (\nabla \times \mathbf{B})
 \begin{align}\nabla \times (\mathbf{A} \times \mathbf{B}) &= \mathbf{A} (\nabla \cdot \mathbf{B}) - \mathbf{B} (\nabla \cdot \mathbf{A}) + (\mathbf{B} \cdot \nabla) \mathbf{A} - (\mathbf{A} \cdot \nabla) \mathbf{B} \\
&= (\nabla \cdot \mathbf{B}  + \mathbf{B} \cdot \nabla)\mathbf{A} -(\nabla \cdot \mathbf{A} + \mathbf{A} \cdot \nabla )\mathbf{B} \\
&= \nabla \cdot (\mathbf{B} \mathbf{A}^\mathrm{T}) - \nabla \cdot (\mathbf{A} \mathbf{B}^\mathrm{T})  \\
&= \nabla \cdot (\mathbf{B} \mathbf{A}^\mathrm{T} - \mathbf{A} \mathbf{B}^\mathrm{T}) \end{align}

Second derivatives[edit]

Curl of the gradient[edit]

The curl of the gradient of any scalar field \ \phi with continuous second derivatives is always the zero vector:

\nabla \times ( \nabla \phi )  = \mathbf{0}

Divergence of the curl[edit]

The divergence of the curl of any vector field A is always zero:

\nabla \cdot ( \nabla \times \mathbf{A} ) = 0

Divergence of the gradient[edit]

The Laplacian of a scalar field is defined as the divergence of the gradient:

 \nabla^2 \psi = \nabla \cdot (\nabla \psi)

Note that the result is a scalar quantity.

Curl of the curl[edit]

 \nabla \times \left( \nabla \times \mathbf{A} \right) = \nabla(\nabla \cdot \mathbf{A}) - \nabla^{2}\mathbf{A}

Here,∇2 is the vector Laplacian operating on the vector field A.

Summary of important identities[edit]

Addition and multiplication[edit]



  •  \nabla(\psi+\phi)=\nabla\psi+\nabla\phi
  •  \nabla (\psi \, \phi) = \phi \,\nabla \psi  + \psi \,\nabla \phi
  •  \nabla\left(\mathbf{A}\cdot\mathbf{B}\right)=\left(\mathbf{A}\cdot\nabla\right)\mathbf{B}+\left(\mathbf{B}\cdot\nabla\right)\mathbf{A}+\mathbf{A}\times\left(\nabla\times\mathbf{B}\right)+\mathbf{B}\times\left(\nabla\times\mathbf{A}\right)


  •  \nabla\cdot(\mathbf{A}+\mathbf{B})=\nabla\cdot\mathbf{A}+\nabla\cdot\mathbf{B}
  •  \nabla\cdot\left(\psi\mathbf{A}\right)=\psi\nabla\cdot\mathbf{A}+\mathbf{A}\cdot\nabla \psi
  •  \nabla\cdot\left(\mathbf{A}\times\mathbf{B}\right)=\mathbf{B}\cdot (\nabla\times\mathbf{A})-\mathbf{A}\cdot(\nabla\times\mathbf{B})


  •  \nabla\times(\mathbf{A}+\mathbf{B})=\nabla\times\mathbf{A}+\nabla\times\mathbf{B}
  •  \nabla\times\left(\psi\mathbf{A}\right)=\psi\nabla\times\mathbf{A}+\nabla\psi\times\mathbf{A}
  •  \nabla\times\left(\mathbf{A}\times\mathbf{B}\right)=\mathbf{A}\left(\nabla\cdot\mathbf{B}\right)-\mathbf{B}\left(\nabla\cdot\mathbf{A}\right)+\left(\mathbf{B}\cdot\nabla\right)\mathbf{A}-\left(\mathbf{A}\cdot\nabla\right)\mathbf{B}

Second derivatives[edit]

DCG chart: A simple chart depicting all rules pertaining to second derivatives. D, C, G, L and CC stand for divergence, curl, gradient, Laplacian and curl of curl, respectively. Arrows indicate existence of second derivatives. Blue circle in the middle represents curl of curl, whereas the other two red circles(dashed) mean that DD and GG do not exist.

Third derivatives[edit]

  • \nabla^{2}(\nabla\psi) = \nabla(\nabla\cdot(\nabla\psi)) = \nabla(\nabla^{2}\psi)
  •  \nabla^{2}(\nabla\cdot\mathbf{A}) = \nabla\cdot(\nabla(\nabla\cdot\mathbf{A})) =\nabla\cdot(\nabla^{2}\mathbf{A})
  •  \nabla^{2}(\nabla\times\mathbf{A}) = -\nabla\times(\nabla\times(\nabla\times\mathbf{A})) = \nabla\times(\nabla^{2}\mathbf{A})


Below, the curly symbol ∂ means "boundary of".

Surface–volume integrals[edit]

In the following surface–volume integral theorems, V denotes a 3d volume with a corresponding 2d boundary S = ∂V (a closed surface):

  • \oiint\scriptstyle \partial V\psi d \mathbf{S} = \iiint_V \nabla \psi\, dV
  • \oiint\scriptstyle \partial V\left(\hat{\mathbf{n}}\times\mathbf{A}\right)dS=\iiint _{V}\left(\nabla\times\mathbf{A}\right)dV

Curve–surface integrals[edit]

In the following curve–surface integral theorems, S denotes a 2d open surface with a corresponding 1d boundary C = ∂S (a closed curve):

  •  \oint_{\partial S}\psi d\boldsymbol{\ell}=\iint_{S}\left(\hat{\mathbf{n}}\times\nabla\psi\right)dS

Integration around a closed curve in the clockwise sense is the negative of the same line integral in the counterclockwise sense (analogous to interchanging the limits in a definite integral):

\ointclockwise{\scriptstyle \partial S}\mathbf{A}\cdot{\rm d}\boldsymbol{\ell}=-\ointctrclockwise{\scriptstyle \partial S}\mathbf{A}\cdot{\rm d}\boldsymbol{\ell}.

See also[edit]

Notes and references[edit]

  1. ^ Feynman, R. P.; Leighton, R. B.; Sands, M. (1964). The Feynman Lecture on Physics. Addison-Wesley. Vol II, p. 27–4. ISBN 0-8053-9049-9. 
  2. ^ Kholmetskii, A. L.; Missevitch, O. V. (2005). "The Faraday induction law in relativity theory". arXiv:physics/0504223 [physics.class-ph]. 
  3. ^ Doran, C.; Lasenby, A. (2003). Geometric algebra for physicists. Cambridge University Press. p. 169. ISBN 978-0-521-71595-9. 

Further reading[edit]

  • Balanis, Constantine A. Advanced Engineering Electromagnetics. ISBN 0-471-62194-3. 
  • Schey, H. M. (1997). Div Grad Curl and all that: An informal text on vector calculus. W. W. Norton & Company. ISBN 0-393-96997-5. 
  • Griffiths, David J. (1999). Introduction to Electrodynamics. Prentice Hall. ISBN 0-13-805326-X.