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Convex Hulls of Quadratically Parameterized Sets With Quadratic Constraints

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Part of the book series: Operator Theory: Advances and Applications ((OT,volume 222))

Abstract

Let V be a semialgebraic set parameterized as

$$\{(f_1(x),\ldots,f_m(x)):x\in T)\}$$

for quadratic polynomials f 0,…,f m and a subset T of Rn. This paper studies semidefinite representation of the convex hull conv(V) or its closure, i.e., describing conv(V) by projections of spectrahedra (defined by linear matrix inequalities). When T is defined by a single quadratic constraint, we prove that conv(V) is equal to the first-order moment type semidefinite relaxation of V, up to taking closures. Similar results hold when every f i is a quadratic form and T is defined by two homogeneous (modulo constants) quadratic constraints, or when all f i are quadratic rational functions with a common denominator and T is defined by a single quadratic constraint, under some proper conditions.

Mathematics Subject Classification. 14P10, 90C22, 90C25.

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References

  1. C. Bayer and J. Teichmann. The proof of Tchakaloff’s Theorem. Proc. Amer. Math. Soc., 134(2006), 3035–3040.

    Article  MathSciNet  MATH  Google Scholar 

  2. L. Fialkow and J. Nie. Positivity of Riesz functionals and solutions of quadratic and quartic moment problems. J. Functional Analysis, Vol. 258, No. 1, pp. 328–356, 2010

    Article  MathSciNet  MATH  Google Scholar 

  3. S. He, Z. Luo, J. Nie and S. Zhang. Semidefinite Relaxation Bounds for Indefinite Homogeneous Quadratic Optimization. SIAM Journal on Optimization, Vol. 19, No. 2, pp. 503–523, 2008.

    Article  MathSciNet  MATH  Google Scholar 

  4. J.W. Helton and J. Nie. Semidefinite representation of convex sets. Mathematical Programming, Ser. A, Vol. 122, No. 1, pp. 21–64, 2010.

    Google Scholar 

  5. J.W. Helton and J. Nie. Sufficient and necessary conditions for semidefinite representability of convex hulls and sets. SIAM Journal on Optimization, Vol. 20, No. 2, pp. 759–791, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  6. J.W. Helton and J. Nie. Structured semidefinite representation of some convex sets. Proceedings of 47th IEEE Conference on Decision and Control, pp. 4797–4800, Cancun, Mexico, Dec. 9–11, 2008.

    Google Scholar 

  7. D. Henrion. Semidefinite representation of convex hulls of rational varieties. Acta Applicandae Mathematicae, Vol. 115, No. 3, pp. 319–327, 2011.

    Article  MathSciNet  MATH  Google Scholar 

  8. J. Lasserre. Convex sets with semidefinite representation. Mathematical Programming, Vol. 120, No. 2, pp. 457–477, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  9. 10] J. Lasserre. Convexity in semi-algebraic geometry and polynomial optimization. SIAM Journal on Optimization, Vol. 19, No. 4, pp. 1995–2014, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  10. J. Nie. First order conditions for semidefinite representations of convex sets defined by rational or singular polynomials. Mathematical Programming, Ser. A, Vol. 131, No. 1, pp. 1–36, 2012.

    Google Scholar 

  11. J. Nie. Polynomial matrix inequality and semidefinite representation. Mathematics of Operations Research, Vol. 36, No. 3, pp. 398–415, 2011.

    Article  MathSciNet  MATH  Google Scholar 

  12. P. Parrilo. Exact semidefinite representation for genus zero curves. Talk at the Banff workshop "Positive Polynomials and Optimization", Banff, Canada, October 8–12, 2006.

    Google Scholar 

  13. G. Pataki. On the rank of extreme matrices in semidefinite programs and the multiplicity of optimal eigenvalues. Mathematics of Operations Research, 23 (2), 339–358, 1998.

    Article  MathSciNet  MATH  Google Scholar 

  14. M. Putinar. Positive polynomials on compact semi-algebraic sets, Ind. Univ. Math. J. 42 (1993) 203–206.

    Article  MathSciNet  Google Scholar 

  15. K. Schmüdgen. The K-moment problem for compact semialgebraic sets. Math. Ann. 289 (1991), 203–206.

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Jiawang Nie .

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Dedicated to Bill Helton on the occasion of his 65th birthday.

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Nie, J. (2012). Convex Hulls of Quadratically Parameterized Sets With Quadratic Constraints. In: Dym, H., de Oliveira, M., Putinar, M. (eds) Mathematical Methods in Systems, Optimization, and Control. Operator Theory: Advances and Applications, vol 222. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-0411-0_18

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