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Regular Wick-star contractions are well defined and associative
Statement
Let , , and let be any continuous complex bidistribution. For a real formal parameter and , define The pairing is over independent pairs of variables; is formed by iterated distributional tensor products, not by multiplying distributions at coincident points. The sum is finite because the inputs are polynomial. It defines an element of , and is associative. Here complex conjugation is for . If is Hermitian in the sense , then , where . For ,
Facts & Assumptions
Given: [A1], the regular polynomial class, the continuous bidistribution , and the supplier statements below.
The formal parameter is fixed by the involution and has no analytic or physical interpretation in this mathematical item.
A regular polynomial is a finite sum with unique symmetric test kernels; its -th derivative is the smooth compact kernel displayed in the definition, and complex Riemann integrals of its compact kernels are evaluated componentwise as defined there (Regular polynomial field functional algebra, Tensor-product tests are dense in smooth compact kernel topology).
Tensor products of distributions exist as continuous distributions; their iterated pairings associate and agree on product tests (Tensor product distributions and iterated pairings).
Pairing a distribution against a smooth parameter family with locally common compact support produces a smooth function, and derivatives pass through the pairing (Distribution pairing with smooth parameter families).
Proof
Given: [A1] and [F1]–[F3].
For each , [F2] constructs on the independent variable pairs. The kernels and in [F1] are smooth and compactly supported, so the displayed pairing is defined. In each homogeneous term of and , pairing the contracted variables leaves a smooth compact kernel in the remaining variables: the support lies in the projection of the original compact coefficient supports, and [F3] passes every remaining-variable derivative through the pairing. The raw remaining-variable kernel need not be symmetric under permutations exchanging a variable from the block with one from the block. For each output degree , replace it by its full symmetrization . This preserves smoothness and compact support, and its field evaluation is unchanged because both the product and the product integration measure are invariant under permutations. The resulting symmetric coefficient therefore represents each summand in .
If and have degrees and , then for and for . Hence only contribute; the sum is finite, independent of a coefficient presentation by [F1], and belongs to .
For , define the auxiliary formal generator by in the formal power-series ring; it is not asserted to be an element of . For a zero-constant formal series , means , with all equalities interpreted coefficientwise. The -th derivative of in is . Substitution into the finite coefficient formula gives, coefficientwise in ,
Applying step 2.2 twice, both bracketings of three generators equal by bilinearity of . Comparing coefficients of proves associativity for powers of linear functionals. For distinct tests in one input, replace by in the same coefficientwise identity; its coefficient of is the symmetrized product . Make this substitution independently in each of the three inputs. Thus the associator vanishes for every symmetrized elementary tensor-product coefficient kernel and for their finite sums.
By [F1], symmetrized finite product-test kernels are dense in every coefficient test space. Each fixed coefficient of the associator is a finite sum of compositions of continuous tensor-distribution pairings from [F2] and smooth parameter pairings from [F3], hence is continuous in the coefficient kernels. Passing to the limits of the product-test approximants from the preceding coefficient comparison proves associativity for arbitrary .
For linear functionals only occur. The term cancels in the commutator, while the terms are and ; this gives the displayed commutator. If is Hermitian, conjugating each finite contraction reverses its two variable groups and gives .