For a nonzero constant-coefficient polynomial differential operator in one variable, every homogeneous distribution solution is a classical solution, indeed analytic. Factor the polynomial into powers of distinct characteristic roots of a constant-coefficient differential equation. The kernel decomposition for coprime polynomials reduces the equation to , and multiplication of a distribution by a smooth function reduces this to . The fact that a distribution with zero derivative is constant, iterated, makes the latter distribution a polynomial of degree less than .
Evaluate Bézout's identity for polynomials at :All these linear operators commute because they are polynomials in the same operator. Thus every can be writtenThe first summand belongs to and the second to , since applying the corresponding operator introduces the product .
If lies in both kernels, the same identity gives . Therefore the sum is direct:This is the kernel decomposition for coprime polynomials. It uses both annihilation by and the coprimality expressed by the Bézout identity.
Past exam of the mathematics course of the University of Cambridge 2013 iii Paper 60 1 Solution Created 2026-10-03 Updated 2026-10-07
The space of test functions is : its elements are smooth functions with compact support. For a fixed compact set , put and use the seminorms . The space of test functions carries the usual test-function inductive limit topology of these spaces. In particular, a sequence converges precisely when its supports eventually lie in one compact set and every derivative converges uniformly. Thus means that a common contains their supports and for every .
A distribution is a continuous linear functional on this space of test functions, and denotes their space. We use complex-linear, bilinear pairings . Equivalently, for every compact set there are and a nonnegative integer such thatThe usual weak convergence of distributions is if for every test function. This specifies the convergence used below; it does not require convergence in any norm.
The distributional derivative is defined byThe derivative map sends continuously to itself, with . The preceding continuity estimate therefore proves that is again a distribution. This definition extends the ordinary derivative of a smooth function, by integration by parts.
Choose the translation of a distribution convention . Its action on a test function isFor fixed , the translated test functions have translated compact support and unchanged derivative sup norms, so this defines a distribution. For the differentiability of distribution translations, apply the Taylor theorem in integral form:All supports lie in one slightly enlarged compact set for , and the same identity for every derivative proves uniform convergence. The continuity of now givesThe minus sign in the translation parameter is necessary for this convention.
For (a), choose a test function with . If , then is a test function, since the zero integral makes it vanish beyond both ends of the compact support. If , then . Decompose to obtainConversely, these constant regular distributions have zero distributional derivative. This also proves the general fact that a distribution with zero derivative is constant.
For (b), choose a cutoff function equal to one near zero. Every test function decomposes asThe quotient extends as a smooth function at zero, and it has compact support. If , the definition of multiplication of a distribution by a smooth function gives . Conversely, . Thus the kernel of multiplication by a coordinate is exactlyIn particular, derivatives of the Dirac delta distribution are not additional solutions: .
Now write and , where . The characteristic roots of a constant-coefficient differential equation are the distinct roots of a polynomial of , with multiplicities . The distributional regularity of a constant-coefficient ordinary differential equation can be proved without assuming regularity in advance. Put and . Since the are coprime polynomials, polynomial division and Bezout identity give polynomials such thatFor example, invert modulo , sum the resulting expressions, and absorb a remaining multiple of into one coefficient. For , the kernel decomposition for coprime polynomials therefore givesThe Leibniz rule for multiplication of a distribution by a smooth function implies . Repeatedly using a distribution with zero derivative is constant shows that a distribution with th derivative zero is a polynomial of degree at most : subtract the polynomial primitive of its constant st derivative, and induct on . Consequently the most general exponential polynomial solution of a constant-coefficient differential equation isEvery displayed term is annihilated by , so all coefficients are allowed. For the linear independence of these functions, on a relation, apply ; on times a polynomial of degree less than , each remaining factor acts invertibly on that polynomial space. Hence the th polynomial must vanish. Every distributional solution is an analytic function, and in particular a classical solution. For real coefficients and real-valued distributions, take complex conjugate coefficients at conjugate characteristic roots of a constant-coefficient differential equation, or equivalently use the corresponding real sine and cosine forms.
For the last equation, the operator is : the coordinate multiplies the result of differentiation. The kernel of multiplication by a coordinate says precisely thatChoose the retarded fundamental solution of a constant-coefficient ordinary differential operator , where is the Heaviside function and is the analytic solution of withSuch exists uniquely by the elementary initial value problem for a constant-coefficient ordinary differential equation; alternatively the residue construction in the next solution gives it explicitly. The distributional jump formula for a Heaviside product isIt follows by induction from , using integration by parts. With the chosen initial derivatives, every lower-order jump term vanishes and the leading coefficient gives . Subtracting reduces the last equation to the homogeneous one. Thus the coordinate-degenerate constant-coefficient differential equation has exactly the solutionsThere are independent constants. For , derivatives through order match at zero, while the derivative of order may jump; for , the function itself may jump. An arbitrary distribution concentrated at zero cannot be added, because its image under the nonzero leading derivative would contain a nonvanishing highest derivative of the Dirac delta distribution.
Past exam of the mathematics course of the University of Cambridge 2022 ib Paper 3 9F b Solution Created 2026-09-24 Updated 2026-09-25
If for nonzero , thenso is an eigenvalue. Let . Since , the three factors ofare pairwise coprime. The kernel decomposition for coprime polynomials therefore giveswhere an absent eigenspace is interpreted as zero.
Suppose for a linear operator , and Bézout's identity for polynomials gives . The kernel decomposition for coprime polynomials is . The displayed operators are the corresponding projection operators: is the identity on and zero on , while has the opposite action. Thus , , and . These actions also prove independence from the choice of Bézout coefficients. Every summand is an invariant subspace of , since the projections are polynomials in and commute with it.