In vector calculus, divergence is a vector operator that operates on a vector field, producing a scalar field giving the quantity of the vector field's source at each point. More technically, the divergence represents the volume density of the outward flux of a vector field from an infinitesimal volume around a given point.
As an example, consider air as it is heated or cooled. The velocity of the air at each point defines a vector field. While air is heated in a region, it expands in all directions, and thus the velocity field points outward from that region. The divergence of the velocity field in that region would thus have a positive value. While the air is cooled and thus contracting, the divergence of the velocity has a negative value.
In physical terms, the divergence of a vector field is the extent to which the vector field flux behaves like a source at a given point. It is a local measure of its "outgoingness" – the extent to which there are more of the field vectors exiting from an infinitesimal region of space than entering it. A point at which the flux is outgoing has positive divergence, and is often called a "source" of the field. A point at which the flux is directed inward has negative divergence, and is often called a "sink" of the field. The greater the flux of field through a small surface enclosing a given point, the greater the value of divergence at that point. A point at which there is zero flux through an enclosing surface has zero divergence.
The divergence of a vector field is often illustrated using the simple example of the velocity field of a fluid, a liquid or gas. A moving gas has a velocity, a speed and direction at each point, which can be represented by a vector, so the velocity of the gas forms a vector field. If a gas is heated, it will expand. This will cause a net motion of gas particles outward in all directions. Any closed surface in the gas will enclose gas which is expanding, so there will be an outward flux of gas through the surface. So the velocity field will have positive divergence everywhere. Similarly, if the gas is cooled, it will contract. There will be more room for gas particles in any volume, so the external pressure of the fluid will cause a net flow of gas volume inward through any closed surface. Therefore the velocity field has negative divergence everywhere. In contrast, in a gas at a constant temperature and pressure, the net flux of gas out of any closed surface is zero. The gas may be moving, but the volume rate of gas flowing into any closed surface must equal the volume rate flowing out, so the net flux is zero. Thus the gas velocity has zero divergence everywhere. A field which has zero divergence everywhere is called solenoidal.
If the gas is heated only at one point or small region, or a small tube is introduced which supplies a source of additional gas at one point, the gas there will expand, pushing fluid particles around it outward in all directions. This will cause an outward velocity field throughout the gas, centered on the heated point. Any closed surface enclosing the heated point will have a flux of gas particles passing out of it, so there is positive divergence at that point. However any closed surface not enclosing the point will have a constant density of gas inside, so just as many fluid particles are entering as leaving the volume, thus the net flux out of the volume is zero. Therefore the divergence at any other point is zero.
The divergence of a vector field at a point is defined as the limit of the ratio of the surface integral of out of the closed surface of a volume enclosing to the volume of, as shrinks to zero
where is the volume of, is the boundary of, and
\hatn
Since this definition is coordinate-free, it shows that the divergence is the same in any coordinate system. However it is not often used practically to calculate divergence; when the vector field is given in a coordinate system the coordinate definitions below are much simpler to use.
A vector field with zero divergence everywhere is called solenoidal – in which case any closed surface has no net flux across it.
F=Fxi+Fyj+Fzk
\operatorname{div}F=\nabla ⋅ F=\left(
\partial | |
\partialx |
,
\partial | |
\partialy |
,
\partial | |
\partialz |
\right) ⋅ (Fx,Fy,Fz)=
\partialFx | + | |
\partialx |
\partialFy | + | |
\partialy |
\partialFz | |
\partialz |
.
Although expressed in terms of coordinates, the result is invariant under rotations, as the physical interpretation suggests. This is because the trace of the Jacobian matrix of an -dimensional vector field in -dimensional space is invariant under any invertible linear transformation.
The common notation for the divergence is a convenient mnemonic, where the dot denotes an operation reminiscent of the dot product: take the components of the operator (see del), apply them to the corresponding components of, and sum the results. Because applying an operator is different from multiplying the components, this is considered an abuse of notation.
For a vector expressed in local unit cylindrical coordinates as
F=erFr+e\thetaF\theta+ezFz,
\operatorname{div}F=\nabla ⋅ F=
1 | |
r |
\partial | |
\partialr |
\left(rFr\right)+
1r | |||
|
+
\partialFz | |
\partialz |
.
The use of local coordinates is vital for the validity of the expression. If we consider the position vector and the functions,, and, which assign the corresponding global cylindrical coordinate to a vector, in general
r(F(x)) ≠ Fr(x)
\theta(F(x)) ≠ F\theta(x)
z(F(x)) ≠ Fz(x)
\theta(F(x))=\theta ≠ F\theta(x)=0
In spherical coordinates, with the angle with the axis and the rotation around the axis, and again written in local unit coordinates, the divergence is
\operatorname{div}F=\nabla ⋅ F=
1{r | |
2} |
\partial | |
\partialr |
\left(r2Fr\right)+
1{r\sin\theta} | |||
|
(\sin\thetaF\theta)+
1{r\sin\theta} | |||
|
.
Let be continuously differentiable second-order tensor field defined as follows:
A=\begin{bmatrix} A11&A12&A13\\ A21&A22&A23\\ A31&A32&A33\end{bmatrix}
the divergence in cartesian coordinate system is a first-order tensor field and can be defined in two ways:[1]
\operatorname{div}(A)=\cfrac{\partialAik
\nabla ⋅ A=\cfrac{\partialAki
We have
\operatorname{div}
(AT) |
=\nabla ⋅ A
If tensor is symmetric then
\operatorname{div}(A)=\nabla ⋅ A
\nabla ⋅
Expressions of
\nabla ⋅ A
Using Einstein notation we can consider the divergence in general coordinates, which we write as, where is the number of dimensions of the domain. Here, the upper index refers to the number of the coordinate or component, so refers to the second component, and not the quantity squared. The index variable is used to refer to an arbitrary component, such as . The divergence can then be written via the Voss-Weyl formula,[5] as:
\operatorname{div}(F)=
1 | |
\rho |
\partial\left(\rhoFi\right) | |
\partialxi |
,
where
\rho
The volume coefficient is a function of position which depends on the coordinate system. In Cartesian, cylindrical and spherical coordinates, using the same conventions as before, we have, and, respectively. The volume can also be expressed as , where is the metric tensor. The determinant appears because it provides the appropriate invariant definition of the volume, given a set of vectors. Since the determinant is a scalar quantity which doesn't depend on the indices, these can be suppressed, writing . The absolute value is taken in order to handle the general case where the determinant might be negative, such as in pseudo-Riemannian spaces. The reason for the square-root is a bit subtle: it effectively avoids double-counting as one goes from curved to Cartesian coordinates, and back. The volume (the determinant) can also be understood as the Jacobian of the transformation from Cartesian to curvilinear coordinates, which for gives
Some conventions expect all local basis elements to be normalized to unit length, as was done in the previous sections. If we write
\hat{e
\hat{F}i
F=Fiei= Fi\|{ei}\|
ei | |
\|ei\| |
= Fi\sqrt{gii
\hat{e
\operatorname{div}(F)=
1{\rho} | ||||||||
|
i\right)}{\partialxi}=
1{\sqrt{\det | |
g}} |
| ||||||
\hat{F} |
i\right)}{\partialxi}.
See for further discussion.
See main article: Vector calculus identities.
The following properties can all be derived from the ordinary differentiation rules of calculus. Most importantly, the divergence is a linear operator, i.e.,
\operatorname{div}(aF+bG)=a\operatorname{div}F+b\operatorname{div}G
for all vector fields and and all real numbers and .
There is a product rule of the following type: if is a scalar-valued function and is a vector field, then
\operatorname{div}(\varphiF)=\operatorname{grad}\varphi ⋅ F+\varphi\operatorname{div}F,
or in more suggestive notation
\nabla ⋅ (\varphiF)=(\nabla\varphi) ⋅ F+\varphi(\nabla ⋅ F).
Another product rule for the cross product of two vector fields and in three dimensions involves the curl and reads as follows:
\operatorname{div}(F x G)=\operatorname{curl}F ⋅ G-F ⋅ \operatorname{curl}G,
or
\nabla ⋅ (F x G)=(\nabla x F) ⋅ G-F ⋅ (\nabla x G).
The Laplacian of a scalar field is the divergence of the field's gradient:
\operatorname{div}(\operatorname{grad}\varphi)=\Delta\varphi.
The divergence of the curl of any vector field (in three dimensions) is equal to zero:
\nabla ⋅ (\nabla x F)=0.
If a vector field with zero divergence is defined on a ball in, then there exists some vector field on the ball with . For regions in more topologically complicated than this, the latter statement might be false (see Poincaré lemma). The degree of failure of the truth of the statement, measured by the homology of the chain complex
\{scalarfieldsonU\}~\overset{\operatorname{grad}}{\rarr}~\{vectorfieldsonU\}~\overset{\operatorname{curl}}{\rarr}~\{vectorfieldsonU\}~\overset{\operatorname{div}}{\rarr}~\{scalarfieldsonU\}
serves as a nice quantification of the complicatedness of the underlying region . These are the beginnings and main motivations of de Rham cohomology.
See main article: Helmholtz decomposition. It can be shown that any stationary flux that is twice continuously differentiable in and vanishes sufficiently fast for can be decomposed uniquely into an irrotational part and a source-free part . Moreover, these parts are explicitly determined by the respective source densities (see above) and circulation densities (see the article Curl):
For the irrotational part one has
E=-\nabla\Phi(r),
\Phi
(r)=\int | |
R3 |
| |||||
d |
The source-free part,, can be similarly written: one only has to replace the scalar potential by a vector potential and the terms by, and the source density by the circulation density .
This "decomposition theorem" is a by-product of the stationary case of electrodynamics. It is a special case of the more general Helmholtz decomposition, which works in dimensions greater than three as well.
The divergence of a vector field can be defined in any finite number
n
F=(F1,F2,\ldotsFn),
in a Euclidean coordinate system with coordinates, define
\operatorname{div}F=\nabla ⋅ F=
\partialF1 | |
\partialx1 |
+
\partialF2 | |
\partialx2 |
+ … +
\partialFn | |
\partialxn |
.
In the 1D case, reduces to a regular function, and the divergence reduces to the derivative.
For any, the divergence is a linear operator, and it satisfies the "product rule"
\nabla ⋅ (\varphiF)=(\nabla\varphi) ⋅ F+\varphi(\nabla ⋅ F)
for any scalar-valued function .
One can express the divergence as a particular case of the exterior derivative, which takes a 2-form to a 3-form in . Define the current two-form as
j=F1dy\wedgedz+F2dz\wedgedx+F3dx\wedgedy.
dj=\left(
\partialF1 | + | |
\partialx |
\partialF2 | + | |
\partialy |
\partialF3 | |
\partialz |
\right)dx\wedgedy\wedgedz=(\nabla ⋅ {F})\rho
\wedge
Thus, the divergence of the vector field can be expressed as:
\nabla ⋅ {F}={\star}d{\star}({F}\flat).
{\star}d{\star}
The appropriate expression is more complicated in curvilinear coordinates. The divergence of a vector field extends naturally to any differentiable manifold of dimension that has a volume form (or density), e.g. a Riemannian or Lorentzian manifold. Generalising the construction of a two-form for a vector field on, on such a manifold a vector field defines an -form obtained by contracting with . The divergence is then the function defined by
dj=(\operatorname{div}X)\mu.
The divergence can be defined in terms of the Lie derivative as
{lL}X\mu=(\operatorname{div}X)\mu.
This means that the divergence measures the rate of expansion of a unit of volume (a volume element) as it flows with the vector field.
On a pseudo-Riemannian manifold, the divergence with respect to the volume can be expressed in terms of the Levi-Civita connection :
\operatorname{div}X=\nabla ⋅ X=
a} | |
{X | |
;a |
,
where the second expression is the contraction of the vector field valued 1-form with itself and the last expression is the traditional coordinate expression from Ricci calculus.
An equivalent expression without using a connection is
\operatorname{div}(X)=
1 | |
\sqrt{\left|\detg\right| |
where is the metric and
\partiala
Xa
\partiala
\stard\star
d
\star
Divergence can also be generalised to tensors. In Einstein notation, the divergence of a contravariant vector is given by
\nabla ⋅ F=\nabla\muF\mu,
where denotes the covariant derivative. In this general setting, the correct formulation of the divergence is to recognize that it is a codifferential; the appropriate properties follow from there.
Equivalently, some authors define the divergence of a mixed tensor by using the musical isomorphism : if is a -tensor (for the contravariant vector and for the covariant one), then we define the divergence of to be the -tensor
(\operatorname{div}T)(Y1,\ldots,Yq-1)={\operatorname{trace}}(X\mapsto\sharp(\nablaT)(X, ⋅ ,Y1,\ldots,Yq-1));
that is, we take the trace over the first two covariant indices of the covariant derivative.The
\sharp