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Tensor density
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In differential geometry, a tensor density or relative tensor is a generalization of the tensor field concept. A tensor density transforms as a tensor field when passing from one coordinate system to another (see tensor field), except that it is additionally multiplied or weighted by a power of the Jacobian determinant of the coordinate transition function or its absolute value. A tensor density with a single index is called a vector density. A distinction is made among (authentic) tensor densities, pseudotensor densities, even tensor densities and odd tensor densities. Sometimes tensor densities with a negative weight are called tensor capacity.[1][2][3] A tensor density can also be regarded as a section of the tensor product of a tensor bundle with a density bundle.
Motivation
[edit]In physics and related fields, it is often useful to work with the components of an algebraic object rather than the object itself. An example would be decomposing a vector into a sum of basis vectors weighted by some coefficients such as where is a vector in 3-dimensional Euclidean space, are the usual standard basis vectors in Euclidean space. This is usually necessary for computational purposes, and can often be insightful when algebraic objects represent complex abstractions but their components have concrete interpretations. However, with this identification, one has to be careful to track changes of the underlying basis in which the quantity is expanded; it may in the course of a computation become expedient to change the basis while the vector remains fixed in physical space. More generally, if an algebraic object represents a geometric object, but is expressed in terms of a particular basis, then it is necessary to, when the basis is changed, also change the representation. Physicists will often call this representation of a geometric object a tensor if it transforms under a sequence of linear maps given a linear change of basis (although confusingly others call the underlying geometric object which hasn't changed under the coordinate transformation a "tensor", a convention this article strictly avoids). In general there are representations which transform in arbitrary ways depending on how the geometric invariant is reconstructed from the representation. In certain special cases it is convenient to use representations which transform almost like tensors, but with an additional, nonlinear factor in the transformation. A prototypical example is a matrix representing the cross product (area of spanned parallelogram) on The representation is given by in the standard basis by
If we now try to express this same expression in a basis other than the standard basis, then the components of the vectors will change, say according to where is some 2 by 2 matrix of real numbers. Given that the area of the spanned parallelogram is a geometric invariant, it cannot have changed under the change of basis, and so the new representation of this matrix must be: which, when expanded is just the original expression but multiplied by the determinant of which is also In fact this representation could be thought of as a two index tensor transformation, but instead, it is computationally easier to think of the tensor transformation rule as multiplication by rather than as 2 matrix multiplications (In fact in higher dimensions, the natural extension of this is matrix multiplications, which for large is completely infeasible). Objects which transform in this way are called tensor densities because they arise naturally when considering problems regarding areas and volumes, and so are frequently used in integration.
Definition
[edit]This article needs additional citations for verification. (September 2012) |
Some authors classify tensor densities into the two types called (authentic) tensor densities and pseudotensor densities in this article. Other authors classify them differently, into the types called even tensor densities and odd tensor densities. When a tensor density weight is an integer there is an equivalence between these approaches that depends upon whether the integer is even or odd.
Note that these classifications elucidate the different ways that tensor densities may transform somewhat pathologically under orientation-reversing coordinate transformations. Regardless of their classifications into these types, there is only one way that tensor densities transform under orientation-preserving coordinate transformations.
In this article we have chosen the convention that assigns a weight of +2 to , the determinant of the metric tensor expressed with covariant indices. With this choice, classical densities, like charge density, will be represented by tensor densities of weight +1. Some authors use a sign convention for weights that is the negation of that presented here.[4]
In contrast to the meaning used in this article, in general relativity "pseudotensor" sometimes means an object that does not transform like a tensor or relative tensor of any weight.
Tensor and pseudotensor densities
[edit]For example, a mixed rank-two (authentic) tensor density of weight transforms as:[5][6]
- ((authentic) tensor density of (integer) weight )
where is the rank-two tensor density in the coordinate system, is the transformed tensor density in the coordinate system; and we use the Jacobian determinant. Because the determinant can be negative, which it is for an orientation-reversing coordinate transformation, this formula is applicable only when is an integer. (However, see even and odd tensor densities below.)
We say that a tensor density is a pseudotensor density when there is an additional sign flip under an orientation-reversing coordinate transformation. A mixed rank-two pseudotensor density of weight transforms as
- (pseudotensor density of (integer) weight )
where sgn() is a function that returns +1 when its argument is positive or −1 when its argument is negative.
Even and odd tensor densities
[edit]The transformations for even and odd tensor densities have the benefit of being well defined even when is not an integer. Thus one can speak of, say, an odd tensor density of weight +2 or an even tensor density of weight −1/2.
An even tensor density transforms as follows. Although the formula works for any real valued weight W, the name arises because the transformation is equivalent to the transformation of an (authentic) tensor density transform when its weight is even.
- (even tensor density of weight )
Similarly, an odd tensor density transforms as follows. Although the formula works for any real valued weight W, the name arises because the transformation is equivalent to the transformation of an (authentic) tensor density transform when its weight is odd.
- (odd tensor density of weight )
Weights of zero and one
[edit]A tensor density of any type that has weight zero is also called an absolute tensor. An authentic tensor density of weight zero, which is also an even tensor density of weight zero, is also called an ordinary tensor.
If a weight is not specified but the word "relative" or "density" is used in a context where a specific weight is needed, it is usually assumed that the weight is +1.
Algebraic properties
[edit]- A linear combination (also known as a weighted sum) of tensor densities of the same type and weight is again a tensor density of that type and weight.
- A product of two tensor densities of any types, and with weights and , is a tensor density of weight Furthermore, a product of authentic tensor densities and pseudotensor densities will be an authentic tensor density when an even number of the factors are pseudotensor densities; it will be a pseudotensor density when an odd number of the factors are pseudotensor densities. Similarly, a product of even tensor densities and odd tensor densities will be an even tensor density when an even number of the factors are odd tensor densities; it will be an odd tensor density when an odd number of the factors are odd tensor densities.
- The contraction of indices on a tensor density with weight again yields a tensor density of weight [7]
- Raising and lowering indices using the metric tensor (which is authentic, even, and of weight 0) leaves the weight unchanged,[8] as can be proved by combining (2) and (3).
Matrix inversion and matrix determinant of tensor densities
[edit]If is a non-singular matrix and a rank-two tensor density of weight with covariant indices then its matrix inverse will be a rank-two tensor density of weight with contravariant indices. Similar statements apply when the two indices are contravariant or are mixed covariant and contravariant.
If is a rank-two tensor density of weight with covariant indices then the matrix determinant will have weight where is the number of space-time dimensions. If is a rank-two tensor density of weight with contravariant indices then the matrix determinant will have weight The matrix determinant will have weight
General relativity
[edit]| General relativity |
|---|
Relation of Jacobian determinant and metric tensor
[edit]Any non-singular ordinary tensor transforms as
where the right-hand side can be viewed as the product of three matrices. Taking the determinant of both sides of the equation (using that the determinant of a matrix product is the product of the determinants), dividing both sides by and taking their square root gives
When the tensor is the metric tensor, and is a locally inertial coordinate system where diag(−1,+1,+1,+1), the Minkowski metric, then −1 and so
where is the determinant of the metric tensor
Use of metric tensor to manipulate tensor densities
[edit]Consequently, an even tensor density, of weight , can be written in the form
where is an ordinary tensor. In a locally inertial coordinate system, where it will be the case that and will be represented with the same numbers.
When using the metric connection (Levi-Civita connection), the covariant derivative of an even tensor density is defined as
For an arbitrary connection, the covariant derivative is defined by adding an extra term, namely to the expression that would be appropriate for the covariant derivative of an ordinary tensor.
Equivalently, the product rule is obeyed
where, for the metric connection, the covariant derivative of any function of is always zero,
Examples
[edit]The expression is a scalar density. By the convention of this article it has a weight of +1.
The density of electric current (for example, is the amount of electric charge crossing the 3-volume element divided by that element — do not use the metric in this calculation) is a contravariant vector density of weight +1. It is often written as or where and the differential form are absolute tensors, and where is the Levi-Civita symbol; see below.
The density of Lorentz force (that is, the linear momentum transferred from the electromagnetic field to matter within a 4-volume element divided by that element — do not use the metric in this calculation) is a covariant vector density of weight +1.
In -dimensional space-time, the Levi-Civita symbol may be regarded as either a rank- contravariant (odd) authentic tensor density of weight +1 () or a rank- covariant (odd) authentic tensor density of weight −1 (): Notice that the Levi-Civita symbol (so regarded) does not obey the usual convention for raising or lowering of indices with the metric tensor. That is, it is true that but in general relativity, where is always negative, this is never equal to
The determinant of the metric tensor, is an (even) authentic scalar density of weight +2, being the contraction of the product of 2 (odd) authentic tensor densities of weight +1 and four (even) authentic tensor densities of weight 0.
See also
[edit]- Action (physics) – Physical quantity of dimension energy × time
- Conservation law – Scientific law regarding conservation of a physical property
- Noether's theorem – Statement relating differentiable symmetries to conserved quantities
- Pseudotensor – Type of physical quantity
- Relative scalar
- Variational principle – Scientific principles enabling the use of the calculus of variations
Notes
[edit]- ^ Weinreich, Gabriel (July 6, 1998). Geometrical Vectors. University of Chicago Press. pp. 112, 115. ISBN 978-0226890487.
- ^ Papastavridis, John G. (Dec 18, 1998). Tensor Calculus and Analytical Dynamics. CRC Press. ISBN 978-0849385148.
- ^ Ruiz-Tolosa, Juan R.; Castillo, Enrique (30 Mar 2006). From Vectors to Tensors. Springer Science & Business Media. ISBN 978-3540228875.
- ^ E.g. Weinberg 1972 pp 98. The chosen convention involves in the formulae below the Jacobian determinant of the inverse transition x → x, while the opposite convention considers the forward transition x → x resulting in a flip of sign of the weight.
- ^ M.R. Spiegel; S. Lipcshutz; D. Spellman (2009). Vector Analysis (2nd ed.). New York: Schaum's Outline Series. p. 198. ISBN 978-0-07-161545-7.
- ^ C.B. Parker (1994). McGraw Hill Encyclopaedia of Physics (2nd ed.). McGraw-Hill. p. 1417. ISBN 0-07-051400-3.
- ^ Weinberg 1972 p 100.
- ^ Weinberg 1972 p 100.
References
[edit]- Spivak, Michael (1999), A Comprehensive Introduction to Differential Geometry, Vol I (3rd ed.), p. 134.
- Charles Misner; Kip S Thorne & John Archibald Wheeler (1973). Gravitation. W. H. Freeman. p. 501ff. ISBN 0-7167-0344-0.
{{cite book}}: CS1 maint: multiple names: authors list (link) - Weinberg, Steven (1972), Gravitation and Cosmology, John Wiley & sons, Inc, ISBN 0-471-92567-5
Tensor density
View on GrokipediaMotivation and Fundamentals
Role in Coordinate Transformations
In differential geometry, standard tensors, which transform linearly under coordinate changes via the Jacobian matrix without additional scaling factors, fail to preserve volumes or integrals when subjected to diffeomorphisms that distort local metrics or orientations. For instance, the volume element defined by a standard tensor, such as the Cartesian dx dy dz, alters its measure under a nonlinear coordinate transformation, leading to inconsistencies in physical or geometric quantities like mass distribution or flux across manifolds. This limitation arises because diffeomorphisms can stretch or compress regions unevenly, requiring compensation to maintain invariance of integrals over arbitrary domains.[6] The Jacobian determinant addresses this by quantifying the local volume scaling under coordinate transformations, serving as the key factor in the transformation laws for tensor densities. Specifically, it measures the determinant of the partial derivatives of the new coordinates with respect to the old ones, |det(∂x'/∂x)|, which multiplies the original volume element to yield the transformed one, ensuring that densities adjust accordingly for uniform behavior. In this way, tensor densities incorporate powers of the Jacobian determinant to counteract the distortion, allowing quantities like probability densities or mass densities to remain consistent across coordinate systems.[6] Tensor densities thus function as essential tools for achieving invariant integration over manifolds, where integrals of density fields yield coordinate-independent results, such as total mass or action in variational principles. By embedding the Jacobian scaling directly into their structure, these objects enable the construction of volume forms that are preserved under diffeomorphisms, facilitating computations in curved spaces or non-orthogonal coordinates without ad hoc adjustments. This approach ensures that geometric invariants, like those in symplectic mechanics or optics, hold regardless of the chosen chart.[6] The historical motivation for tensor densities traces back to early 20th-century differential geometry, particularly Élie Cartan's development of integral invariants in the 1920s, where densities were introduced to preserve measures under transformations in continuous media and variational problems. In his 1922 work, Cartan employed densities, such as mass per unit volume ρ, to form absolute integral invariants like ∫∫∫ ρ δx δy δz over volumes, addressing the failure of unadjusted forms to remain invariant under diffeomorphisms. This framework laid the groundwork for modern uses in invariant integration, emphasizing densities' role in handling orientation and volume preservation in geometric contexts.[7]Distinction from Standard Tensors
Standard tensors, whether contravariant or covariant, are multilinear maps that transform linearly under changes of coordinates via the partial derivatives of the coordinate functions, without any additional scaling factors.[8] This ensures that their components in different coordinate systems are related in a way that preserves the intrinsic geometric structure, independent of the specific coordinate choice.[9] In contrast, tensor densities incorporate a weight factor , modifying the standard tensor transformation by multiplying it with the absolute value of the Jacobian determinant raised to the power .[8] Pseudotensors form a related but distinct category, typically referring to densities that also change sign under orientation-reversing transformations, such as the Levi-Civita symbol, which behaves as a pseudotensor density of weight -1.[9] Physically, tensor densities describe quantities that scale with volume elements, such as mass density, which transforms with weight in -dimensional space to maintain invariance of total mass under coordinate rescaling.[9] Similarly, probability densities in continuous distributions scale inversely with volume to preserve total probability.[8] Tensor densities generalize standard tensors by accounting for the scaling introduced by the Jacobian determinant in non-orthogonal or curvilinear coordinate systems, enabling consistent descriptions of volume-dependent quantities.[9]Formal Definition
General Transformation Law
A tensor density of weight generalizes the transformation behavior of standard tensors by incorporating an additional factor involving the Jacobian determinant of the coordinate transformation. Under a change of coordinates from to , the components of a scalar tensor density transform according to [10][11] This law accounts for the scaling under orientation-reversing transformations, where the sign of the determinant affects densities with non-zero integer weights.[8][11] For a general -tensor density of weight , the transformation law extends the standard tensor rule by multiplying it with the Jacobian factor: [10][2] The products of partial derivatives arise directly from the chain rule applied to the multilinearity of tensor components under differentiation.[10] The determinant factor, raised to the power , is introduced to account for the scaling of the volume element , which modifies the transformation beyond the pure tensor case.[2][8] This convention with the signed determinant is standard for oriented manifolds, where the sign may vary, allowing densities to reflect orientation.[11][8]Parity and Weight Classification
Tensor densities are classified by their weight , which is typically a real number, most commonly an integer, that determines the power to which the Jacobian determinant is raised in the transformation law. Specifically, under a coordinate transformation with Jacobian matrix , the components transform as (standard tensor transformation). When , this reduces to the transformation law for standard tensors, recovering their behavior without the additional determinant factor.[12] The parity of a tensor density refers to its behavior under orientation-reversing coordinate transformations, where . Assuming for simplicity (as in orthogonal transformations), the factor . Thus, for even integer weights ( even), the density is invariant under such reversals, exhibiting even parity similar to true tensors but with scaling by . For odd integer weights ( odd), the density acquires an extra minus sign, exhibiting odd parity akin to pseudotensors, which is essential for quantities sensitive to orientation, such as oriented volumes.[13][1] A representative example is the Levi-Civita symbol , which serves as a covariant pseudotensor density of weight (odd) in dimensions. It changes sign under orientation reversal, reflecting its role in defining oriented structures like determinants and volume elements. In contrast, the scalar density has weight (odd) and also flips sign, while products like have even weight and remain invariant.| Property | Even Weight (e.g., ) | Odd Weight (e.g., ) |
|---|---|---|
| Behavior under orientation reversal () | Invariant (factor ) | Changes sign (factor ) |
| Parity type | Even (true tensor-like) | Odd (pseudotensor-like) |
| Example | Determinant of metric $ | \det g |
| Implications | Suitable for absolute volumes or invariants | Essential for oriented volumes and antisymmetric forms |
