Heat coefficient $a_4$ for nonminimal Laplace type operators
Bruno Iochum, Thierry Masson

TL;DR
This paper computes the heat coefficient $a_4$ for nonminimal Laplace type operators on vector bundles over Riemannian manifolds, extending previous work on the $a_2$ coefficient with explicit universal formulas.
Contribution
The authors provide a detailed computation of the $a_4$ heat coefficient for nonminimal Laplace type operators, including universal spectral functions and $u$-dependent operators, advancing the understanding of heat kernel asymptotics.
Findings
Explicit formulas for the $a_4$ heat coefficient involving universal spectral functions.
Extension of previous $a_2$ coefficient computations to $a_4$ for nonminimal operators.
Universal operators acting on tensor products of functions and derivatives.
Abstract
Given a smooth hermitean vector bundle of fiber over a compact Riemannian manifold and a covariant derivative on , let be a nonminimal Laplace type operator acting on smooth sections of where are -valued functions with positive and invertible. For any , we consider the asymptotics where the coefficients can be written as an integral of the functions . This paper revisits the previous computation of by the authors and is mainly devoted to a computation of . The results are presented with…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Heat coefficient for non minimal Laplace type operators
B. Iochum, T. Masson
Centre de Physique Théorique [email protected], [email protected]
Aix Marseille Univ, Université de Toulon, CNRS, CPT, Marseille, France
Abstract
Given a smooth hermitean vector bundle of fiber over a compact Riemannian manifold and a covariant derivative on , let be a non minimal Laplace type operator acting on smooth sections of where are -valued functions with positive and invertible. For any , we consider the asymptotics where the coefficients can be written as an integral of the functions .
This paper revisits the previous computation of by the authors and is mainly devoted to a computation of . The results are presented with -dependent operators which are universal (i.e. -independent) and which act on tensor products of , , and their derivatives via (also universal) spectral functions which are fully described.
Keywords: Heat kernel, Nonminimal operator, Asymptotic heat trace, Laplace type operator
1 An introduction to the method
Let be a smooth hermitean vector bundle of fiber over a compact -dimensional boundaryless Riemannian manifold and let be a non minimal Laplace type operator acting on the smooth sections , written locally as the partial differential operator where and are matrices in with positive and invertible.
For a smooth section , the existence of an asymptotics for the heat-trace is known (see [10, 12]), with coefficients given by , where and ; more precisely given by
[TABLE]
where is the trace on , and is a (local) section of .
The explicit knowledge of the and is important both in mathematics and physics, and several attempts can be found in the literature for many classes of operators , see the books [7, 10, 4, 18]. While here we extend a previous method [13, 14], this paper is actually self-contained.
To start with, it is convenient to use a covariant derivative on and to parameterize the differential operator as:
[TABLE]
where are sections of (see [13, Appendix A.4] for the swap between and ) and
[TABLE]
The computation of is realized through , where is the diagonal of the kernel of defined for any section by . Recall that this kernel can be computed using a compactly supported section with support in a open subset of which gives at the same time a chart of and a trivialization of (and ). In that situation, we can look at as a map .
The use of the Fourier transform of with inverse yields to
[TABLE]
For fixed , we can look at , and then at , as maps , because the function “absorbs” all the derivatives operators in . We now give another expression for the matrix . Since for any ,
[TABLE]
where we have introduced
[TABLE]
one gets .
The operators and being essential here, they will be also decomposed as and where
[TABLE]
and thus
[TABLE]
The introduction of the variable will be justified in Lemma 3.1.
Then, for any and at fixed values and ,
[TABLE]
and the diagonal part of the kernel is .
From now on, will be considered as a locally constant section of .
The computation of this matrix-valued function is based on the Volterra series
[TABLE]
where
[TABLE]
and by convention . This gives, for and (omitting the -dependence),
[TABLE]
where for any , the map is defined, for any , by
[TABLE]
Here the are matrix-valued differential operators in depending on and (linearly in) , and .
Remark 1.1** (Notation and convention).**
By convention, each in acts on all its right remaining terms. Since is constant, this allows to identify as matrix valued functions, , even if the ’s contain derivative operators.
Proposition 4.1 will get rid of these explicit differential operators in the arguments of and will produce formulas with matrix-valued arguments only. This is an essential result for the method.
The first terms of (1.7) are (omitting again the -dependence)
[TABLE]
Since the -integral cancels the non-integers powers of , one recovers the coefficients via the asymptotics behavior : at the point ,
[TABLE]
where the convention of Remark 1.1 is adopted.
While it is tempting to generalize to an arbitrary strictly positive matrix (with ), it is almost impossible to obtain simple expression for the . For instance the -integral of cannot be done explicitly (see for instance [13] for details and [2, Section 3.3] for a link with Finsler metrics).
The computation of goes the following way.
First the calculus of the -integral of (1.8) leads, via the spectral decomposition of , to the universal functions , see Section 2.1 or [13, 14].
Then, as shown in Section 2.1, the family of functions satisfies a few relations. Moreover, in the same section, these relations are translated in terms of operators (see Definition 2.15) acting on the tensor product of -valued differential operators and can be seen as the spectral functions associated to the action of . The differential aspect, which is an important part of the game here, is not a difficulty because the family of is compatible with derivations, see Proposition 2.11.
The previous described approach and formulae for are well-known, see especially [5, 6, 1, 2, 3]. The originality of this work, compared to previous quoted ones and [13, 14], is however to perform the computations using operators instead of spectral functions. One can follow this way more precisely what is the contribution of each term, an information that is a priori lost when adding spectral functions coming from different contributions. These operators, respectively and , have a universal property since they only depend of a positive invertible matrix-valued which can be either or . Thus, in this formal algebraic level, the computations are reduced to a control of the propagation of derivatives inside the arguments, see for instance Proposition 4.1.
However, to secure the results on the matrices , we need a covariant formulation of all tools. This is the aim of Section 3 where is presented in a covariant way in equation (3.7) and, since we know that must then be invariant under a change of coordinates, we choose a normal coordinate system. This implies that the covariant derivative has to be extended to the total covariant derivative combining both and the Levi-Civita connection on . Such an extension requires for the sequel to compute beforehand a few formulae on the action of on all ingredients.
In particular, in Section 4, we present a formula for the propagation of within the arguments and show several simplifications due to a few Riemannian contractions which appear all along the computations. This leads to an operational version of the method exposed in Proposition 4.3.
In Section 5 the whole intermediate steps for the calculation of are given and, of course, we recover in this new algebraic setting the previous results of [13, 14].
While all computations can be done “by hand” for , the case of requires the use of a computer due to the huge number of generated terms. The hard and long part of this work was to develop a code ab initio. The elaboration of such a code is explained in Section 6. It takes care of all intricate aspects of the computations: the algebraic manipulations quoted before, the use of normal coordinates for higher derivatives and last but not least, the simplification of a large number of terms via a reduction process, see (2.24).
Finally, a formula for is exhibited in Section 7 which is a new result. Of course, it is compatible with old known results like when , see [12, 10], but is written here in full generality when the section is parallel for and the are not zero, while the standard presentation always assumes that (see Lemma 3.1).
2 The universal operators
The aim of this section is to define and study the operators which depends only on a strictly positive matrix-valued function where is a given parameter space. Later on, when the differential operator will play a role, will be either with or with .
2.1 The universal spectral functions
Let us first consider the algebra (although many of the theory could be generalized to a unital -algebra ) and which is a positive invertible matrix:
[TABLE]
For any and , let (bounded operator from into itself) be defined by . For some reason we want to apply such operators to and to do so, we need the injection of into :
[TABLE]
where 1 is the unit of . Now we define the operator as
[TABLE]
We also need, for , the following family of operators:
[TABLE]
For any , denote by the multiplication in . Then is given by
[TABLE]
We now consider the functional calculus on , with the shorthand notation
[TABLE]
Keep in mind that is not the index of a spectral value but is the index of the position in the -tensor product.
The need to compute the -integrals of the operators drives us to
[TABLE]
where , permuting the integrals in the first equality and using a Gaussian integration with spherical coordinates in the second one, see [13, Eq. (4.4)]. Thus the functional calculus for naturally leads us to the following functions (when ):
Definition 2.1**.**
For any and , let defined by
[TABLE]
For instance,
[TABLE]
and see [13, 14] for other explicit expressions for these integrals.
We will need the following recursion formulas on the functions , seen as generalizations of [13, eq. (3.1)]:
Lemma 2.2**.**
For any and the family of functions satisfies
[TABLE]
ii) Moreover, for any , and ,
[TABLE]
Proof
i) For , the integrand in the defining integral of reduces to
[TABLE]
and then does not depend anymore of the variable . Using
[TABLE]
*the integration along produces, respectively, the factors , , and .
Let us perform the change of variables*
[TABLE]
There is no need to change the variables for . Then, for all , the remaining integration is over and all the brackets in (2.9) coincide (with the case ). This implies that the RHS of (2.7) can be recombined, through the factorization of this common bracket, as a single integral
[TABLE]
which is nothing else but .
*ii) For any , , one has .
Performing the last integration along , one gets*
[TABLE]
*An integration along the other variables ’s gives the equation (2.8). *
2.2 Definitions and properties of the operators
As before, is a positive invertible element in .
Definition 2.3**.**
For any , given a function , we define the operator acting on as
[TABLE]
*with an (implicit) summation over -tuples of spectral values of . *
In particular, using (2.2) for ,
[TABLE]
If , where is a measured space, then
[TABLE]
since the implicit summation over is finite and is -independent.
The spectral function in the equation (2.12) has a peculiar modification if one of the variables is a function of :
Lemma 2.4**.**
For any continuous function and , we have
[TABLE]
Proof
Since , we get
[TABLE]
*which, after a relabeling of the summation indices for , can be written as in (2.14). *
Since this result will be widely used, let us give an example: for and
[TABLE]
An important case of operators is the family of operators associated to the universal functions (see Definition 2.1) and to , which will play a crucial role in the sequel precisely because of their universality.
[TABLE]
Again, for brevity of notation on the use of , both the -dependence and the summation when applied to arguments will be implicit.
From the equations (2.5) and (2.4) we immediately check that
[TABLE]
We also remark that for any matrices in such that , we have the two following factorizations:
[TABLE]
For and , let be defined by
[TABLE]
which inserts at the -th place in . For instance, one easily checks that
[TABLE]
Lemma 2.5**.**
*The operators satisfy .
More explicitly, the following expansion holds true for any :*
[TABLE]
Proof
*This follows from equation (2.7). *
Corollary 2.6**.**
For any and any , one has
[TABLE]
Proof
We prove the first relation (2.21) by induction. When , the use of Lemma 2.5 yields to the desired relation: . Assuming the relation holds for , then
[TABLE]
*after changes of summation parameters and in the two sums.
Then, extending the summation ranges with and since they do not contribute, one gets*
[TABLE]
*and (2.21) holds true. The relation (2.21) is proved similarly. *
We will also use the notion of expansion: for is defined for by
[TABLE]
and the previous lemma can be read as:
[TABLE]
or seen as a reduction process after the expansion .
Lemma 2.7**.**
*Assume .
i) For any ,*
[TABLE]
ii) For any , , and ,
[TABLE]
iii) For any and any ,
[TABLE]
Proof
i) Thanks to the definition (2.15), (2.8) and (2.6), we have
[TABLE]
because the implicit summation over (resp. ) of (resp. ) gives 1.
ii) The LHS of (2.28) is equal to
[TABLE]
*because the missing summations in and implies that and are replaced by 1.
iii) Similarly, the LHS of (2.29) is equal to*
[TABLE]
* *
As a consequence of the previous lemma, we get the following:
Corollary 2.8**.**
For any , , and ,
[TABLE]
For instance, using also (2.17) and (2.18),
[TABLE]
For a potential use of this corollary, see Remark 3.2.
2.3 If commutes with the ’s
When commutes with the arguments acted upon by the operator , the action of the latter is quite simple:
Lemma 2.9**.**
Let , and with . If for any , then
[TABLE]
This is for instance the case either when or when and the ’s are diagonal matrices.
Proof
We have, using the equality (2.5),
[TABLE]
* *
This shows that in this situation the operators act as a polynomial in and the ’s.
2.4 Action of a derivation and finite differences
It is immediate to extend all previous definitions and results to the algebra that we consider from now on, namely
[TABLE]
where is a parameter space. Later on, when will play a role, will be either with (an open set in ) or and . This extension is necessary because we have derivations in the play and consequently, the operators now depend on . With the definitions
[TABLE]
where , we can rewrite the functions as
[TABLE]
and the operator defined in (1.8) and restricted to (i.e. to arguments without derivatives), is associated for to the spectral function :
[TABLE]
Let be an arbitrary derivation of the algebra , namely a linear combination of a derivative of a -valued function along a parameter and a commutator with an element of . Then
[TABLE]
Recall that a proof for is based on the following relation: If for and , then
[TABLE]
see also [4]. For an inner derivation like where , a similar argument can be applied if one begins with .
By functional calculus on , we deduce from (2.35)
[TABLE]
(still an implicit summation over repeated indices) where from now on we use the symbolic notation of finite differences instead of when .
Remark that the peculiar case is compatible with (2.36).
The relation (2.36) can be extended in the following way. Let be a Laplace transform of a Borel signed -valued measure on , i.e. . We consider the derivability of at the point : since for any and , and , we may use the differentiation lemma for parameter dependent integrals to commute and the integral (recall also that by Bernstein’s theorem, is completely monotonic, see [17, Theorem 1.4]). This commutation property can be first extended when is a Laplace transform of a signed -valued measure on and then extended again to for any smooth function : consider again the derivability of in an open ball around such that where and ; as before we get so that we can commute with the integral. In particular, for such ,
[TABLE]
It is then natural to define the set of functions
[TABLE]
which is large because contains all functions of type with defined as above.
Since for , the definition (2.4) shows in particular that if and since ,
[TABLE]
With the help of (2.33), the functions
[TABLE]
for are nothing else but integrals of products of elements in .
Then, let us introduce the following generalization of the finite difference appearing in the RHS of (2.37) to functions of several variables: for and with , define the “partial” finite differences
[TABLE]
We can generalize (2.37) to operators by defining:
[TABLE]
or more explicitly, . The next proposition shows that the families of and are indeed invariant respectively by and modulo dilations and insertion of :
Proposition 2.10**.**
For any , any with , we have
[TABLE]
Proof
*The first relation follows from (2.8) applied to with instead of and the second one from the definition (2.15). The third one can be shown using a straightforward adaptation of the proof of Lemma 2.2 ii) beginning with . The last relation is a consequence of (2.34) and (2.45). *
2.5 Propagation of derivations
Let be a derivation acting on elements in , for instance along a parameter in . Suppose that we have a representation of the algebra on a vector space on which is also defined (with the same notations) in such a way that the Leibniz rule holds: for any and .
Proposition 2.11**.**
Assume that the function is either with , or , or with . Then, for any such that and any which is a -valued differential operator in , the following propagation rule holds true:
[TABLE]
Before looking at a proof, remark first that, using (2.44) for , see (2.15), (resp. , see (2.34)), the RHS of (2.47) is written only in terms of the operators and (resp. and , using (2.46)). This is a key point in the method exhibited in Section 4.
Proof
First case: Since \pi_{f}={\bf m}\circ\big{(}(f_{0}(r_{0})\,E_{0})^{R}\otimes\cdots\otimes(f_{k}(r_{k})\,E_{k})^{R}\big{)}, one gets
[TABLE]
*Thus, in the parenthesis, acts either on the ’s or on the ’s or on . When it acts on the ’s, this reproduces the first sum in (2.47) while when it acts on , it gives the last term.
For the action on the , we can apply (2.37) and get the total contribution*
[TABLE]
Swapping to and to for , each spectral function in the last sum is
[TABLE]
which contributes to the second term of the RHS of (2.47).
Case : From (2.31), (2.32) and using (2.13), we can apply the previous argument under the integration over . The only point to take care of, is the commutation of with the integral in the second term of the RHS of (2.47). Since is compact and the integrand is smooth in and , this commutation occurs even at coincidence points (where partial derivatives arise, see (2.41)).
*Case : For , the result is direct and the second term of (2.47) vanishes since is constant.
Assume now . From (2.40), once again the same argument can be applied under the integral and we only need to prove the commutation with integral along . With*
[TABLE]
we have to show that
[TABLE]
coincides with
[TABLE]
By linearity, this is true for but at coincidence points we still have to show that the -integral commutes with . For we have, using when ,
[TABLE]
*and the RHS is -integrable uniformly along which secures the commutation of the integral with . *
3 Total covariant derivative and normal coordinates
In this section, we come back to the differential operator defined in (1.1) but we do not use Section 2. Firstly, we rewrite in terms of a total covariant derivative, and since we know that the coefficients are invariant under a change of coordinates, we secondly gather the computation of several derivatives within a normal coordinate system.
3.1 Total covariant derivative
We need the total covariant derivative , which combines the (gauge) connection on with the Levi-Civita covariant derivative induced by the metric . To avoid a definition of on the tensor products of , and via heavy notations, and since we only need the action on -valued tensors, it is sufficient to remark that satisfies
[TABLE]
for any -valued -tensor , -tensor , and -tensor . Here is the (local) gauge potential associated to . General formulas for -valued -tensors are easily obtained from these conventions.
As usual, we use the short notation and .
We first recall few formulae of Riemannian geometry:
[TABLE]
The curvature of the Levi-Civita connection is
[TABLE]
([11, p. 23]) and this expression is an endomorphism of the tangent bundle .
The Riemann tensors
[TABLE]
satisfy , with .
The Ricci tensor and the scalar curvature are
[TABLE]
The Riemann tensor yields to some -symmetries and to the first Bianchi identity:
[TABLE]
This also yields to some -symmetries, to the derivative of the first Bianchi identity and the second Bianchi identity:
[TABLE]
In (3.2), after a contraction over and first and then over and , and using the fact that , one obtains and , so that
[TABLE]
If we define
[TABLE]
then, by the first Bianchi identity, with a relabeling for the second equality, so that
[TABLE]
In the same vein, let us store
[TABLE]
Given the field strength
[TABLE]
one has for any section of and similarly, for any tensors and ,
[TABLE]
Combining these expressions, for any -valued tensors and , one obtains
[TABLE]
and for any
[TABLE]
Moreover,
[TABLE]
Let us now come back to the operator . Applying the definition (1.5), we can rewrite in a (fully) covariant way as
[TABLE]
and the following result is a generalization of [12, Lemma 1.2.1]:
Lemma 3.1**.**
Given as in (3.8), there exist a connection and a section of such that
[TABLE]
*given by and . *
Proof
This follows from a direct computation (omitting the section applied upon):
[TABLE]
* *
Remark 3.2**.**
Compared with (3.8), this rewriting of in (3.9) greatly simplifies the computations of because it means that we may assume for all . This is the traditional way to present the results on the heat kernel coefficients, see for instance [11, 12]. In particular, for all is equivalent to in (1.6).
If one insists on keeping , Corollary 2.8 can be useful because .
3.2 Covariant derivatives and normal coordinates
In this subsection, some results on the iterated covariant derivatives of are shown and they will be used for the computation of . The code generates their generalizations to higher orders in derivatives for the computation of .
In the following, for any and indices , we use the compact notation
[TABLE]
Comparing the action of and on , we get
[TABLE]
We deduce from (3.10) that if is parallel for (i.e. ), then is also parallel for . Similarly,
[TABLE]
For ,
[TABLE]
To compute the RHS of these expressions, we also need to know the derivatives of and :
[TABLE]
Thus, for ,
[TABLE]
The swap of to in (3.10–3.12) can be reduced to a peculiar coordinate system and we now present some results concerning derivatives of quantities in normal coordinates, namely a geodesic coordinate system centered at a pinned point .
Let us use the notation to map a quantity to its value in normal coordinates at . We warn the reader that, to alleviate the presentation, we omit in the sequel the explicit dependency to .
For the following results on the metric and its inverse or on the Christoffel symbols, see for instance [11, Sect. 1.11.3], [12, p. 5], [16] or [8].
[TABLE]
where \operatorname*{\mathchoice{\sum\kern-7.0pt\raise-0.5pt\hbox{\small\mathsf{P}}}{\sum\kern-5.5pt\raise-0.4pt\hbox{\scriptsize\mathsf{P}}}{}{}}_{\nu_{1},\dots,\nu_{n}}A_{\nu_{1}\dots\nu_{n}}\vcentcolon=\sum_{\,\sigma\in\mathbb{S}_{n}}A_{\nu_{\sigma(1)}\dots\nu_{\sigma(n)}} and is the permutation group of elements.
Similarly,
[TABLE]
Thus we obtain
[TABLE]
For , we also get from (3.12):
[TABLE]
The corresponding expressions given in terms of are
[TABLE]
Finally, for , we obtain directly from (3.15):
[TABLE]
4 The method and its simplifications
In this section, we start with equal to , so that the definition (2.10) is specialized to the operator as seen in (2.34). With acting on any local section of by , so that the required Leibniz rule holds, and using (2.46), Proposition 2.11 becomes
Proposition 4.1**.**
Given a local trivialization of a section in , and , , which are matrix-valued differential operators in depending on and (linearly in) , the following holds true:
[TABLE]
When contains more than one covariant derivative to propagate, they can accumulate on as , and this produces complicated expressions.
We are interested in the computation of as a matrix-valued function, that is as a linear map: . In that case, and because is constant.
In general, we can write the result after the propagation of some as a sum of terms like , where is a matrix-valued function written as a polynomial expression in the and their derivatives.
We begin the process with where (the constant unital section in ) and after applying covariant derivatives, we get where
[TABLE]
It is easy to establish that is an homogeneous polynomial of degree when counting a degree for each and . In the final expression, these factors generate “gauge invariant” contributions, in term of the curvature of and its derivatives.
Finally, notice that Proposition 4.1 reduces to [13, Lemma 2.1] for , i.e. for .
For , let be the operators from to itself defined by
[TABLE]
with the notations
[TABLE]
where is the symmetric group of permutations on elements and the parenthesis in the index of is the complete symmetrization over all indices and with the convention that, when , is just 1. For instance, and
[TABLE]
Let us also introduce the operators
[TABLE]
which are justified as
[TABLE]
because, in (2.3), and there is the following relations between the and the :
[TABLE]
The appearance of in (4.1) forces to consider the -dependence of the arguments : each factor depends polynomially on because with independent of .
Thus is a sum of terms like and the symmetry of the -integral implies that the ones which only survive are when for some .
As a consequence, each function is expressed formally as a sum
[TABLE]
and the wanted factor is a sum
[TABLE]
because .
Before we give a precise way to compute (4.8), we now store two technical lemmas
Lemma 4.2**.**
For any , and ,
[TABLE]
Proof
To compute the -integration defining , we use spherical coordinates with and , the unit sphere in (). Then
[TABLE]
*and the equality (4.10) follows from the definition (4.5). *
The full method to compute consists to apply (4.1) starting from terms of the form
[TABLE]
generated by the series in (1.7) (the convention of Remark 1.1 is used). Considering the last term in (4.1), the most general expression to start with is (see discussion after Proposition 4.1):
[TABLE]
Then the LHS of (4.1) produces three kinds of terms. The first ones come from the propagation of on the arguments:
[TABLE]
The second ones consist of adding as an argument after , so we get:
[TABLE]
The third ones modify the matrix-valued polynomials as:
[TABLE]
Replacing the ’s and the integrations along with the as in (4.6), we finally obtain
[TABLE]
This relation is the “integrated” version of (4.1). One has to look inside as the tensor product over the field and not over functions. In other words, it is necessary to keep the functions and their derivatives in front of their arguments in the tensor product until all the derivations in the arguments have propagated. Working with the matrix-valued functions prevents this temptation.
From this result, we then get the following simplification in the computation of :
Proposition 4.3**.**
*All the terms of (4.8) can be obtained starting from their analogs in (1.7) with the replacement of operators by as in (4.6) and iteratively applying the rule (4.11). At the end of this iteration, one can use (4.10) to deal with any remaining function together with normal coordinates to deal with derivatives of the metric. *
In order to simplify the computation, we can omit the operators in (4.11) and work directly at the level of their arguments. We will also make use of two other useful symbolic notations.
Let us adopt the notation to express the development of arguments induced by (4.11). In order to take into account the presence of the matrix-valued polynomials (appearing in (4.11)) multiplied on the right of the application of on the arguments, we denote its presence with the separation symbol , except if .
Then the computation consists to perform the propagation of all the derivatives by applying, as many times as necessary, the following symbolic rule: If , , are matrix-valued differential operators in depending on and independent of , then,
[TABLE]
Once this rule has been used, the operators to apply on each argument in the obtained sum are uniquely determined by the number of free indices and the number of arguments in tensor products.
Remark 4.4**.**
When , the previous formula (4.12) cannot be simplified because commutes with matrix-valued functions but not with some differential operators possibly contained in some for . This implies in particular that we can not hope for simplifications at this computation stage even if , and the number of terms produced by successive applications of (4.12) is independent of the exact form of . Only subsequent computations can use some hypothesis on for simplifications.
Remark 4.5**.**
It is tempting in the previous method to start with written in terms of as in (3.8) and to propagate instead of . But this requires to get an analogue of formula (1) which needs to make sense of : the variables are the Fourier dual of the variables and, even if they carry a space index, they are not the component of a tensor field on . While here these variables are silent since only confined in the -tensors (as a consequence of ), they would have to remain both in the and to be sensitive to the action of in (4.12), thus generating more terms. This would give directly the result in terms of while here, we are obliged to exchange with some efforts the with (in normal coordinates) at the end.
5 Results on and
After the direct result on , this section is devoted to a complete computation of via the above method and is a more algebraic version than the similar result obtained in [14, Thm 2.4].
The computation of is straighforward thanks to (2.30):
Lemma 5.1**.**
[TABLE]
We plane to follow Proposition 4.3 to compute in and start with
[TABLE]
We perform the computation at the level of arguments using (4.12). Notice that all the used spectral operators (and those appearing in the final result) are in the series .
Consider first :
[TABLE]
Similarly for :
[TABLE]
We can now apply the operators , , and according to the obtained arguments, use (4.10) when necessary, and finally collect all the terms.
Let us first collect the terms with and show that they all cancel thanks to (2.20).
The terms with do not contribute:
[TABLE]
The sum of terms containing and vanishes:
[TABLE]
Finally the contribution of terms containing and also vanishes:
[TABLE]
There are 3 terms which contain tensor products of only:
[TABLE]
by the complete symmetry of and the skew symmetry of the first and second couples of indices in .
Since by (2.16), , this amounts to .
The only term in is .
The sum of 3 terms containing is
[TABLE]
The sum of 10 terms in and is:
[TABLE]
The only term in is
[TABLE]
The 4 terms in and are
[TABLE]
The 2 terms in and are
[TABLE]
Finally, the term in and is
[TABLE]
Since the computation has been performed in normal coordinates, using (3.16), (3.17) and (3.18), one can replace the gauge covariant derivative by the total derivative to get a fully covariant expression:
[TABLE]
In this expression the contribution of a few terms can be simplified using Lemma 2.5 like:
[TABLE]
Finally, we get:
Theorem 5.2**.**
The section of is
[TABLE]
A lengthy computation shows that this is compatible with [14, Thm 2.4].
According to Lemma 2.5, the writing of (5.2) is not unique. For instance, using
[TABLE]
this expression can be factorized as:
Corollary 5.3**.**
[TABLE]
We do not know if this proposed factorization has some structural origin.
As explained just after Lemma 3.1, it can be useful to rewrite this result in terms of :
Corollary 5.4**.**
[TABLE]
6 The code
The computation of exposed in Section 5 shows that the simplified method summarized in Proposition 4.3 consists to apply a set of (mainly algebraic) rules at the level of the arguments of operators. This is to be contrasted with other methods based on more analytical properties of the heat coefficients, where for instance all possible expressions (based on the theory of invariants) are given by hand and their respective weights are computed (see [10] for instance). While these latter methods cannot be easily managed with a computer, the present method, being algebraic, can be translated into an algorithm.
The first step in the computation of makes appear a collection of fewer than 30 terms: they can be managed by hand. However, the same part of the computation for produces thousands of terms. This is why a computer is needed to perform this computation.
Let us describe in this non-technical section the main characteristics of the computer code elaborated to make possible this computation.
Some computer algebraic systems (CAS) have been evaluated as a possible basis for this code. But, to our best knowledge, none of them was able to manage, in a easy way and without adding external modules, all the complexity of this computation. Indeed, formal manipulations have to be performed, to list a few, on commutative and noncommutative objects, on derivations (, , ), on Riemannian structures (metric, Christoffel symbols, Ricci and Riemann tensors…), on contraction of tensors, on gauge structures ( and its curvature ), on tensor products, on polynomials (in the dimension parameter )… Starting a formal computational code from the very beginning, as we did, has the following two main advantages: its purpose is to manipulate the necessary structures encountered in the computation, and only these structures; its internal model is based on the “mathematical model” that the method reveals.
This last point is a strong motivation to use an object oriented language in order to internally reproduce and manipulate, in a “natural” way, all the mathematical structures describing the key ingredient in which the method (and so the code) focuses: the “arguments” of the operators , as explained in Proposition 4.3. So, the code is built from the beginning on objects such as polynomials, commutative and noncommutative “elements” (for instance Riemannian tensors or matrix-valued functions), derivations (which can be applied, in a repetitive way, on the previously mentioned elements), products of elements (respecting commutative and noncommutative rules), tensor products, and finally the “arguments” of the operators with collected commutative elements in front and the presence of the matrix-valued polynomials “on the right”.
The object oriented language selected is JavaScript, the powerful language used in web browsers. This choice relies on various motivations. One of us was familiar with this language, and this helped to produce an efficient code quickly. The Node runtime222https://nodejs.org permits to execute JavaScript as a scripting language in a terminal and it makes possible to read and write files.333Since it uses an extension of the “strict” JavaScript language used in web browsers. Moreover, the execution relies on the open source version of the very optimized JavaScript engine V8:444On which a lot of software engineers are working in a big private company… benchmarks are very favorably compared to Python for instance (a language that would have been a good choice also). All the results are saved in files using the (open and native) format JSON555“JavaScript Object Notation”, a very convenient human readable structure format for data, that any modern language can read and write. and these results can be read as inputs for further computations. The translation of the code could be done into any other modern object oriented language.
On top of the main objects that the code can manipulate (with “natural methods” from a mathematical point of view), specific (higher level) functions have been coded to reproduce mathematical rules, like for instance contractions of Riemannian tensors, raising of indices, some simplifications… Substitutions of “elements” by more complicated structures are also made possible: these permits to reproduce the steps described in Section 5, where the computation is first done on the mathematical objects , , and and then, in a second step, these objects (and their derivatives) are substituted using rules given in Section 3.2 (into normal coordinates). Substitutions rules can be hard coded or computed.
One of the main challenges when constructing such a code is to be able to simplify expressions to collect similar terms. This has required quite a lot of work to construct a “normalized” internal representation of terms (taking into account ambiguities on commutativity of elements, ambiguities on labeling indices in tensor contractions…). In that respect, the code may not compare to more mature CAS. A way to bypass this weakness was to make the exportation possible to inject expressions into another CAS: Our choice was to use Mathematica to perform formal computations (mainly to simplify the results at the very end of the computation) and to inject back the obtained results in the code.
The code can also export the generated expressions in LaTeX, and all the results presented in this paper are those directly obtained in this way. Only the final layout has been adapted to reduce space.
Let us now explain the main steps of the computation of . One of the main ingredients in the computation is the substitution rule described in Section 3.2. In order to avoid as much as possible any transcription errors, the choice was made to only hard code the substitutions (3.13) and (3.14) for the metric and its derivatives (up to four) to normal coordinates. So, a preliminary step consists in computing (and save for later use) all the necessary substitutions of covariant derivatives of , , and (up to the necessary number of derivations for the computation of ) in terms of Riemannian tensors and derivations of , and . The subsequent preliminary step is to compute the replacement of the covariant derivative by the total covariant derivative (up to the necessary number of derivations) on these latter elements.
Then, after these preliminary results are stored, the main computation starts with the propagation of covariant derivations as given by the rule (4.12). Terms are next collected according to in order to apply, sequentially to these reduced numbers of terms, the following steps:
- •
Substitutions are performed to generate expressions in normal coordinates.
- •
The necessary contractions with the tensors (computed on the fly) are performed.
- •
A series of rules (contractions of tensors, raising of indices…) is applied to all the terms as long as these rules can be applied.
- •
The “expansion” rules of Lemma 2.5 are applied to leverage terms with same patterns666A “pattern” of an argument is the reduced ordered list of elements appearing in this argument (forgetting the polynomials in dimension in front of it) where the elements (without applied derivation) are omitted. to a common number of arguments, so that they can be compared.
- •
A full simplification of the obtained sum is performed by adding similar terms.
- •
The results are then saved in JSON file format for later use and in LaTeX for human reading.
Terms with same patterns are then collected in partial sums since they can produce simpler expressions, thanks to the use of Lemma 2.5, this time to reduce, as much as possible, the number of arguments and the number of terms. There is no uniqueness in this simplification procedure and a balance has to be found to produce these simplified expressions. This process has been mainly done in Mathematica after exportation of these partial sums. Once simplified expressions are obtained, they are written (by hand) in files that the code uses as inputs to compare them to their original (non simplified) versions. This series of checks, the last step of the computation, also exports the simplified expressions in LaTeX: they are the expressions presented in this paper.
The code produces new results for which, to our best knowledge, never appeared before. So, some comparisons against known results have to be performed to confirm the validity of the code (at least partially). Three tests have been successful:
The computation of reproduces the result obtained by hand (this is the result given in Corollary 5.4). 2. 2.
The computation of for the -dimensional noncommutative torus produces results in agreement with those in [14] (once translated back into spectral functions): the interested reader will find this result in LaTeX files accompanying the open source code [15]. 3. 3.
The case parallel (Section 7.3) is a special case for in which all the derivations of are put to zero. With the further specifications and , the result agrees with [12, Theorem 3.3.1].
Notice that the consistency of gauge invariant expressions in the -part of the results (see Section 7.1) is also a strong requirement for the global validity of the code.
The code has been written with the method in mind, not for the computation of in particular. This means that it can be used to compute for (and then the number of generated terms will be huge!) and it can also be appropriate in situations where some elements take specific values (for instance, in the -dimensional noncommutative torus case, all the elements are written in terms of a single positive element in the noncommutative algebra). This makes the code flexible enough for further computations of heat coefficients for non minimal Laplace type operators.
Anyone can contribute to the open-source code (GNU GPL v3 License) we produced [15] and can use it as a starting point for his/her projects as far as the required computations are accessible by the method exposed in this paper.
7 Results on produced by computer
To compute in , we start with
[TABLE]
Here, the series of spectral operators appearing in the computation are for . Thus, in this section we adopt the shorthands for .
Application of (4.12) is done using a computer because it gives too many terms. Actually, after simplification, it produces thousands of terms, that can be sorted according to only 5 values of produced for : , , , , and . These five sums are denoted for , thus
[TABLE]
Since the factors in front of have homogeneous gauge transformations, the result should be written as (explicitly) gauge homogeneous expressions to ensure that transforms homogeneously.
To simplify, the results are presented with , but the interested reader will find the general case in LaTeX files accompanying the open source code [15].
7.1 Computation of for
When , the factor can be computed by hand from the very beginning because only few terms contribute. The only possible gauge homogeneous expression is and indeed the computer returns directly only one term:
[TABLE]
For , the computer produces terms that can be sorted following a repeating pattern:
[TABLE]
In this expression, changing the summation variables and using the symmetry of metric indices, the gauge homogeneous expression appears automatically:
[TABLE]
because using (3.6),
[TABLE]
More precisely, this gives, since ,
[TABLE]
When , the symmetric part with respect to does not produce a gauge homogeneous term, thus must be zero. This is checked by the computer which only returns the skew symmetric part (the tensor):
[TABLE]
The contribution with does not transform homogeneously because , and one cannot produce a gauge homogeneous expression as a polynomial of of degree 1 with no derivations. As a consequence, should vanish and this is what the computer returns:
[TABLE]
7.2 Computation of
Here we use the following notations: and
[TABLE]
so that and .
The computer produces around 400 terms for , but after simplifications based on (2.24), this reduces to the following 180 terms collected according to their pattern:
[TABLE]
As explained for , this presentation is not unique.
Remark 7.1**.**
This series of terms may quite seem rather useless per se. But the attentive reader will see that these simplified expressions show some repeated structures, for instance the use of the inclusion operator in the form and the possible factorization by common polynomials in the dimension parameter for a large number of terms sharing the same pattern. As can be seen in Corollary 5.3, the results can also be presented in a more factorized way (something we have not really tried to get for ). Splitting the results into -universal operators and -dependent arguments on which they are applied was a strong motivation to get a better structural perception of heat coefficients. Hitherto, we are not in position to offer more perspectives in that regard but further investigations may reveal structures hidden so far. The computation of higher-order heat coefficients via the present method could also offer the detection of possible (hidden) structures. We encourage insightful readers to take an interest in this problem.
7.3 If is parallel for
We first remark that when , the contribution of reduces to (even if is non zero) while vanishes (even if is non zero) and the contribution of is
[TABLE]
More generally, when is parallel for the connection , we get the following 55 terms for ; recall from (4.4) that G_{\nu_{1}\nu_{2}\nu_{3}\nu_{4}}\vcentcolon=\tfrac{1}{4}\big{(}g_{\nu_{1}\nu_{2}}g_{\nu_{3}\nu_{4}}+g_{\nu_{1}\nu_{3}}g_{\nu_{2}\nu_{4}}+g_{\nu_{1}\nu_{4}}g_{\nu_{2}\nu_{3}}):
[TABLE]
With , this shrinks to 8 terms:
[TABLE]
and agrees with [12, Theorem 3.3.1] when using (2.30).
8 Conclusion
In this work we have developed for a non minimal Laplace type operator a new method to compute any in terms of universal operators with explicit details of the case . A computer code issued by this method has already produced new results for . This code is ready for such computations when and moreover it can be particularized and adapted to more specific situations like the (rational) noncommutative torus, see for instance [9], or in quantum field theory as described in [13, Section 5.4]. Among possible perspectives, the method could also be generalized to operators acting on operator algebras, for instance constructed from spectral triples.
Acknowledgments
The authors are strongly indebted to Laurent Raymond for helpful discussions concerning some aspects of the computer code at the early stage of this work.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Avramidi [2004] Ivan G. Avramidi. Gauged gravity via spectral asymptotics of non-Laplace type operators. Journal of High Energy Physics , 07:030, 2004.
- 2Avramidi [2005] Ivan G. Avramidi. Dirac operators in matrix geometry. International Journal of Geometric Methods in Modern Physics , 02:227–264, 2005.
- 3Avramidi [2006] Ivan G. Avramidi. Non-Laplace type operators on manifolds with boundary. In Analysis, Geometry and Topology of Elliptic Operators , pages 107–140. World Scientific, 2006.
- 4Avramidi [2015] Ivan G. Avramidi. Heat kernel method and its applications . Springer, 2015.
- 5Avramidi and Branson [2001] Ivan G. Avramidi and Thomas P. Branson. Heat kernel asymptotics of operators with non-Laplace principal part. Reviews in Mathematical Physics , 13(07):847–890, 2001.
- 6Avramidi and Branson [2002] Ivan G. Avramidi and Thomas P. Branson. A discrete leading symbol and spectral asymptotics for natural differential operators. Journal of Functional Analysis , 190(1):292–337, 2002.
- 7Berline et al. [1992] Nicole Berline, Ezra Getzler, and Michele Vergne. Heat kernels and Dirac operators . Springer-Verlag, 1992.
- 8Brewin [2009] Leo Brewin. Riemann normal coordinate expansions using Cadabra. Classical and Quantum Gravity , 26:175017, 2009.
