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The (matricial) solution set of a Linear Matrix Inequality (LMI) is a convex basic non-commutative semi-algebraic set. The main theorem of this paper is a converse, a result which has implications for both semidefinite programming and…

Functional Analysis · Mathematics 2011-08-31 J. William Helton , Scott McCullough

Let $\Rx$ denote the ring of polynomials in $g$ freely non-commuting variables $x=(x_1,...,x_g)$. There is a natural involution * on $\Rx$ determined by $x_j^*=x_j$ and $(pq)^*=q^* p^*$ and a free polynomial $p\in\Rx$ is symmetric if it is…

Functional Analysis · Mathematics 2012-08-20 Sriram Balasubramanian , Scott McCullough

Consider a convex set S defined by a matrix inequality of polynomials or rational functions over a domain. The set S is called semidefinite programming (SDP) representable or just semidefinite representable if it equals the projection of a…

Optimization and Control · Mathematics 2011-03-30 Jiawang Nie

There has recently been ample interest in the question of which sets can be represented by linear matrix inequalities (LMIs). A necessary condition is that the set is rigidly convex, and it has been conjectured that rigid convexity is also…

Rings and Algebras · Mathematics 2012-04-18 Petter Brändén

By a result of Helton and McCullough, open bounded convex free semialgebraic sets are exactly open (matricial) solution sets D_L of a linear matrix inequality (LMI) L(X)>0. This paper gives a precise algebraic certificate for a polynomial…

Functional Analysis · Mathematics 2018-04-27 J. William Helton , Igor Klep , Christopher S. Nelson

This paper concerns free analytic maps on noncommutative domains. These maps are free analogs of classical holomorphic functions in several complex variables, and are defined in terms of noncommuting variables amongst which there are no…

Functional Analysis · Mathematics 2013-04-16 J. William Helton , Igor Klep , Scott McCullough

Given a monic linear pencil L in g variables let D_L be its positivity domain, i.e., the set of all g-tuples X of symmetric matrices of all sizes making L(X) positive semidefinite. Because L is a monic linear pencil, D_L is convex with…

Rings and Algebras · Mathematics 2018-04-27 J. William Helton , Igor Klep , Scott McCullough

This article studies algebraic certificates of positivity for noncommutative (nc) operator-valued polynomials on matrix convex sets, such as the solution set $D_L$, called a free Hilbert spectrahedron, of the linear operator inequality…

Operator Algebras · Mathematics 2016-10-06 Aljaž Zalar

Linear matrix inequalities (LMIs) $I_d + \sum_{j=1}^g A_jx_j + \sum_{j=1}^g A_j^*x_j^*\succeq0$ play a role in many areas of applications and the set of solutions to one is called a spectrahedron. LMIs in (dimension--free) matrix variables…

Functional Analysis · Mathematics 2018-12-10 Meric Augat , J. William Helton , Igor Klep , Scott McCullough

Given a polynomial $x \in {\mathbb R}^n \mapsto p(x)$ in $n=2$ variables, a symbolic-numerical algorithm is first described for detecting whether the connected component of the plane sublevel set ${\mathcal P} = \{x : p(x) \geq 0\}$…

Optimization and Control · Mathematics 2008-01-24 Didier Henrion

Consider the matrix power function X^p defined over the cone of positive definite matrices S^{n}_{++}. It is known that X^p is convex over S^{n}_{++} if p is in [-1,0] or [1,2] and X^p is concave over S^{n}_{++} if p is in [0,1]. We show…

Optimization and Control · Mathematics 2014-10-13 J. William Helton , Jiawang Nie , Jeremy S. Semko

A linear matrix inequality (LMI) is a condition stating that a symmetric matrix whose entries are affine linear combinations of variables is positive semidefinite. Motivated by the fact that diagonal LMIs define polyhedra, the solution set…

Optimization and Control · Mathematics 2009-12-18 Tim Netzer , Daniel Plaumann , Markus Schweighofer

Consider the closed convex hull $K$ of a monomial curve given parametrically as $(t^{m_1},\ldots,t^{m_n})$, with the parameter $t$ varying in an interval $I$. We show, using constructive arguments, that $K$ admits a lifted semidefinite…

Optimization and Control · Mathematics 2023-03-08 Gennadiy Averkov , Claus Scheiderer

Let a and x denote tuples of (jointly) freely noncommuting variables. A square matrix valued polynomial p in these variables is naturally evaluated at a tuple (A,X) of symmetric matrices with the result p(A,X) a square matrix. The…

Functional Analysis · Mathematics 2017-06-21 Harry Dym , J. William Helton , Scott McCullough

Noncommutative rational functions, i.e., elements of the universal skew field of fractions of a free algebra, can be defined through evaluations of noncommutative rational expressions on tuples of matrices. This interpretation extends their…

Rings and Algebras · Mathematics 2018-04-24 Jurij Volčič

Consider a monic linear pencil $L(x) = I - A_1x_1 - \cdots - A_gx_g$ whose coefficients $A_j$ are $d \times d$ matrices. It is naturally evaluated at $g$-tuples of matrices $X$ using the Kronecker tensor product, which gives rise to its…

Rings and Algebras · Mathematics 2018-04-27 Igor Klep , Jurij Volčič

This article resides in the realm of the noncommutative (free) analog of real algebraic geometry - the study of polynomial inequalities and equations over the real numbers - with a focus on matrix convex sets $C$ and their projections $\hat…

Functional Analysis · Mathematics 2018-04-27 J. William Helton , Igor Klep , Scott McCullough

A set is called semidefinite representable or semidefinite programming (SDP) representable if it can be represented as the projection of a higher dimensional set which is represented by some Linear Matrix Inequality (LMI). This paper…

Optimization and Control · Mathematics 2008-07-01 Jiawang Nie

Hermitian linear matrix pencils are ubiquitous in control theory, operator systems, semidefinite optimization, and real algebraic geometry. This survey reviews the fundamental features of the matricial solution set of a linear matrix…

Functional Analysis · Mathematics 2024-07-12 Jurij Volčič

Given linear matrix inequalities (LMIs) L_1 and L_2, it is natural to ask: (Q1) when does one dominate the other, that is, does L_1(X) PsD imply L_2(X) PsD? (Q2) when do they have the same solution set? Such questions can be NP-hard. This…

Operator Algebras · Mathematics 2018-04-27 J. William Helton , Igor Klep , Scott McCullough
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