Operator Positivstellensätze for noncommutative polynomials positive on matrix convex sets

This article studies algebraic certificates of positivity for noncommutative (nc) operator-valued polynomials on matrix convex sets, such as the solution set DLDL, called a free Hilbert spectrahedron, of the linear operator inequality (LOI) L(X)=A0⊗I+∑j=1gAj⊗Xj⪰0, where AjAj are self-adjoint linear operators on a separable Hilbert space, XjXj matrices and I   is an identity matrix. If AjAj are matrices, then L(X)⪰0L(X)⪰0 is called a linear matrix inequality (LMI) and DLDL a free spectrahedron. For monic LMIs, i.e., A0=IA0=I, and nc matrix-valued polynomials the certificates of positivity were established by Helton, Klep and McCullough in a series of articles with the use of the theory of complete positivity from operator algebras and classical separation arguments from real algebraic geometry. Since the full strength of the theory of complete positivity is not restricted to finite dimensions, but works well also in the infinite-dimensional setting, we use it to tackle our problems. First we extend the characterization of the inclusion DL1⊆DL2DL1⊆DL2 from monic LMIs to monic LOIs  L1L1 and L2L2. As a corollary one immediately obtains the description of a polar dual of a free Hilbert spectrahedron DLDL and its projection, called a free Hilbert spectrahedrop. Further on, using this characterization in a separation argument, we obtain a certificate for multivariate matrix-valued nc polynomials F positive semidefinite on a free Hilbert spectrahedron defined by a monic LOI. Replacing the separation argument by an operator Fejér–Riesz theorem enables us to extend this certificate, in the univariate case, to operator-valued polynomials F  . Finally, focusing on the algebraic description of the equality DL1=DL2DL1=DL2, we remove the assumption of boundedness from the description in the LMIs case by an extended analysis. However, the description does not extend to LOIs case by counterexamples.