Integers as Sums of Squares

2021 ◽  
pp. 307-322
Author(s):  
Satyabrota Kundu ◽  
Sypriyo Mazumder
Keyword(s):  
2021 ◽  
Vol 107 ◽  
pp. 67-105
Author(s):  
Elisabeth Gaar ◽  
Daniel Krenn ◽  
Susan Margulies ◽  
Angelika Wiegele

Author(s):  
Mareike Dressler ◽  
Adam Kurpisz ◽  
Timo de Wolff

AbstractVarious key problems from theoretical computer science can be expressed as polynomial optimization problems over the boolean hypercube. One particularly successful way to prove complexity bounds for these types of problems is based on sums of squares (SOS) as nonnegativity certificates. In this article, we initiate optimization problems over the boolean hypercube via a recent, alternative certificate called sums of nonnegative circuit polynomials (SONC). We show that key results for SOS-based certificates remain valid: First, for polynomials, which are nonnegative over the n-variate boolean hypercube with constraints of degree d there exists a SONC certificate of degree at most $$n+d$$ n + d . Second, if there exists a degree d SONC certificate for nonnegativity of a polynomial over the boolean hypercube, then there also exists a short degree d SONC certificate that includes at most $$n^{O(d)}$$ n O ( d ) nonnegative circuit polynomials. Moreover, we prove that, in opposite to SOS, the SONC cone is not closed under taking affine transformation of variables and that for SONC there does not exist an equivalent to Putinar’s Positivstellensatz for SOS. We discuss these results from both the algebraic and the optimization perspective.


2000 ◽  
Vol 23 (4) ◽  
pp. 869-875 ◽  
Author(s):  
José Marcelo Soriano Viana

It was studied the parametric restrictions of the diallel analysis model of Griffing, method 2 (parents and F1 generations) and model 1 (fixed), in order to address the questions: i) does the statistical model need to be restricted? ii) do the restrictions satisfy the genetic parameter values? and iii) do they make the analysis and interpretation easier? Objectively, these questions can be answered as: i) yes, ii) not all of them, and iii) the analysis is easier, but the interpretation is the same as in the model with restrictions that satisfy the parameter values. The main conclusions were that: the statistical models for combining ability analysis are necessarily restricted; in the Griffing model (method 2, model 1), the restrictions relative to the specific combining ability (SCA) effects, <img src="http:/img/fbpe/gmb/v23n4/6246s1.gif" align="absmiddle"> and <img src="http:/img/fbpe/gmb/v23n4/6246s2.gif" align="absmiddle"> for all j, do not satisfy the parametric values, and the same inferences should be established from the analyses using the model with restrictions that satisfy the parametric values of SCA effects and that suggested by Griffing. A consequence of the restrictions of the Griffing model is to allow the definition of formulas for estimating the effects, their variances and the variances of contrasts of effects, as well as for calculating orthogonal sums of squares.


2007 ◽  
Vol 13 (1-3) ◽  
pp. 7-25 ◽  
Author(s):  
Shaun Cooper ◽  
Michael Hirschhorn

2016 ◽  
Vol 66 (3) ◽  
Author(s):  
Emrah Kiliç ◽  
Helmut Prodinger

AbstractWe give a systematic approach to compute certain sums of squares of Fibonomial coefficients with finite products of generalized Fibonacci and Lucas numbers as coefficients. The technique is to rewrite everything in terms of a variable


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