Divergence
Encyclopedia : D : DI : DIV : Divergence
- For other uses, see Divergence (disambiguation)}}}.
A vector field which has zero divergence everywhere is called solenoidal.
Definition
Let x, y, z be a system of Cartesian coordinates on a 3-dimensional Euclidean space, and let i, j, k be the corresponding basis of unit vectors.
The divergence of a continuously differentiable vector field F = F1 i + F2 j + F3 k is defined to be the scalar-valued function:
- [\operatorname\,\mathbf = \nabla\cdot\mathbf=\frac+\frac+\frac. ]
The common notation for the divergence ∇·F is a convenient mnemonic, where the dot denotes something just reminiscent of the dot product: take the components of ∇ (see del), apply them to the components of F, and sum the results.
Physical interpretation
In physical terms, the divergence of a three dimensional vector field is the extent to which the vector field flow behaves like a source or a sink at a given point. Indeed, an alternative, but logically equivalent definition, gives the divergence as the derivative of the net flow of the vector field across the surface of a small sphere relative to the volume of the sphere. Formally,
- [( \operatorname\,\mathbf) (p) = \lim_\int_ \cdot\mathbfdS \over \frac \pi r^3 }]
In light of the physical interpretation, a vector field with constant zero divergence is called incompressible – in this case, no net flow can occur across any closed surface.
The intuition that the sum of all sources minus the sum of all sinks should give the net flow outwards of a region is made precise by the divergence theorem.
Properties
The following properties can all be derived from the ordinary differentiation rules of calculus. Most important of which, the divergence is a linear operator, i.e.
- [\operatorname( a\mathbf + b\mathbf ) = a\;\operatorname( \mathbf ) + b\;\operatorname( \mathbf ) ]
There is a product rule of the following type: if φ is a scalar valued function and F is a vector field, then
- [\operatorname(\varphi \mathbf) = \operatorname(\varphi) \cdot \mathbf + \varphi \;\operatorname(\mathbf), ]
- [\nabla\cdot(\varphi \mathbf) = (\nabla\varphi) \cdot \mathbf + \varphi \;(\nabla\cdot\mathbf). ]
- [\operatorname(\mathbf\times\mathbf) = \operatorname(\mathbf)\cdot\mathbf \;-\; \mathbf \cdot \operatorname(\mathbf),]
- [\nabla\cdot(\mathbf\times\mathbf)= (\nabla\times\mathbf)\cdot\mathbf- \mathbf\cdot(\nabla\times\mathbf).]
The divergence of the curl of any vector field (in three dimensions) is constant and equal to zero. Conversely, if you have a vector field F with zero divergence defined on a ball in R3, say, then there exists some vector field G on the ball with F = curl(G). For regions in R3 more complicated than balls, this latter statement might not be true anymore (see Poincaré lemma). Indeed, the degree of failure of the truth of the statement, measured by the homology of the chain complex
- [ \U\} \;]
- :[ \to\U\} \;]
- ::[ \to\U\} \;]
- :::[ \to\U\} \;]
Relation with the exterior derivative
One can establish a parallel between the divergence and a particular case of the exterior derivative, when it takes a 2-form to a 3-form in R3. If we define:- [\alpha=F_1\ dy\wedge dz + F_2\ dz\wedge dx + F_3\ dx\wedge dy]
- [d\alpha = \left( \frac+\frac+\frac \right) dx\wedge dy\wedge dz]
Generalizations
The divergence of a vector field can be defined in any number of dimensions. If
- [\mathbf=(F_1, F_2, \dots, F_n),]
- [\operatorname\,\mathbf = \nabla\cdot\mathbf=\frac+\frac+\cdots +\frac. ]
- [\nabla\cdot(\varphi \mathbf) = (\nabla\varphi) \cdot \mathbf + \varphi \;(\nabla\cdot\mathbf). ]
See also
- Gradient
- Curl
- Vector calculus
- Nabla in cylindrical and spherical coordinates
- Divergence theorem
- Non-orthogonal analysis
From Wikipedia, the Free Encyclopedia. Original article here. Support Wikipedia by contributing or donating.
All text is available under the terms of the GNU Free Documentation License See Wikipedia Copyrights for details.
