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Given a Schubert variety $\mathcal{S}$ contained in a Grassmannian $\mathbb{G}_{k}(\mathbb{C}^{l})$, we show how to obtain further information on the direct summands of the derived pushforward $R \pi_{*} \mathbb{Q}_{\tilde{\mathcal{S}}}$…

Algebraic Geometry · Mathematics 2022-03-22 Francesca Cioffi , Davide Franco , Carmine Sessa

We present Ca$\Sigma$oS, the first MATLAB software specifically designed for nonlinear sum-of-squares optimization. A symbolic polynomial algebra system allows to formulate parametrized sum-of-squares optimization problems and facilitates…

Optimization and Control · Mathematics 2025-09-30 Torbjørn Cunis , Jan Olucak

We present a new algorithm for determining the satisfiability of conjunctions of non-linear polynomial constraints over the reals, which can be used as a theory solver for satisfiability modulo theory (SMT) solving for non-linear real…

Symbolic Computation · Computer Science 2021-06-17 Erika Ábrahám , James H. Davenport , Matthew England , Gereon Kremer

We introduce the notion of $t$-sum of squares (sos) submodularity, which is a hierarchy, indexed by $t$, of sufficient algebraic conditions for certifying submodularity of set functions. We show that, for fixed $t$, each level of the…

Optimization and Control · Mathematics 2025-10-29 Anna Deza , Georgina Hall

In order to obtain the best-known guarantees, algorithms are traditionally tailored to the particular problem we want to solve. Two recent developments, the Unique Games Conjecture (UGC) and the Sum-of-Squares (SOS) method, surprisingly…

Data Structures and Algorithms · Computer Science 2014-05-28 Boaz Barak , David Steurer

We study the design of polylogarithmic depth algorithms for approximately solving packing and covering semidefinite programs (or positive SDPs for short). This is a natural SDP generalization of the well-studied positive LP problem.…

Data Structures and Algorithms · Computer Science 2016-01-12 Zeyuan Allen-Zhu , Yin Tat Lee , Lorenzo Orecchia

We study robust convex quadratic programs where the uncertain problem parameters can contain both continuous and integer components. Under the natural boundedness assumption on the uncertainty set, we show that the generic problems are…

Optimization and Control · Mathematics 2018-12-19 Areesh Mittal , Can Gokalp , Grani A. Hanasusanto

In this paper, we examine structured tensors which have sum-of-squares (SOS) tensor decomposition, and study the SOS-rank of SOS tensor decomposition. We first show that several classes of even order symmetric structured tensors available…

Spectral Theory · Mathematics 2015-10-13 Haibin Chen , Guoyin Li , Liqun Qi

We introduce some general tools to design exact splitting methods to compute numerically semigroups generated by inhomogeneous quadratic differential operators. More precisely, we factorize these semigroups as products of semigroups that…

Analysis of PDEs · Mathematics 2020-11-30 Joackim Bernier

The classic method for computing the spectral decomposition of a real symmetric matrix, the Jacobi algorithm, can be accelerated by using mixed precision arithmetic. The Jacobi algorithm is aiming to reduce the off-diagonal entries…

Numerical Analysis · Mathematics 2025-09-03 Zhengbo Zhou

This paper presents for the first time a robust exact line-search method based on a full pseudospectral (PS) numerical scheme employing orthogonal polynomials. The proposed method takes on an adaptive search procedure and combines the…

Optimization and Control · Mathematics 2023-03-06 Kareem T. Elgindy

We describe and prove correctness of two practical algorithms for finding indecomposable summands of finitely generated modules over a finitely generated k-algebra R. The first algorithm applies in the (multi)graded case, which enables the…

Commutative Algebra · Mathematics 2026-05-28 Devlin Mallory , Mahrud Sayrafi

Algorithms are presented for the tanh- and sech-methods, which lead to closed-form solutions of nonlinear ordinary and partial differential equations (ODEs and PDEs). New algorithms are given to find exact polynomial solutions of ODEs and…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 D. Baldwin , U. Goktas , W. Hereman , L. Hong , R. S. Martino , J. Miller

Let $S_0$ be a smooth and compact real variety given by a reduced regular sequence of polynomials $f_1, ..., f_p$. This paper is devoted to the algorithmic problem of finding {\em efficiently} a representative point for each connected…

Algebraic Geometry · Mathematics 2007-05-23 B. Bank , M. Giusti , J. Heintz , G. M. Mbakop

We introduce two families of sum-of-squares (SOS) decompositions for the Bell operators associated with the tilted CHSH expressions introduced in Phys. Rev. Lett. 108, 100402 (2012). These SOS decompositions provide tight upper bounds on…

Quantum Physics · Physics 2015-05-20 Cédric Bamps , Stefano Pironio

We consider the Moment-SOS hierarchy in polynomial optimization. We first provide a sufficient condition to solve the truncated K-moment problem associated with a given degree-$2n$ pseudo-moment sequence $\phi$ n and a semi-algebraic set $K…

Optimization and Control · Mathematics 2025-01-13 Jean B Lasserre

In this paper we consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore…

Numerical Analysis · Mathematics 2016-05-30 Oliver J. D. Barrowclough , Tor Dokken

In this paper we discuss how to generate inductive invariants for safety verification of hybrid systems. A hybrid symbolic-numeric method is presented to compute inequality inductive invariants of the given systems. A numerical invariant of…

Software Engineering · Computer Science 2015-03-19 Wang Lin , Min Wu , Zhengfeng Yang , Zhenbing Zeng

Hamiltonian representations based on the sum-of-squares (SOS) hierarchy provide rigorous lower bounds on ground-state energies and facilitate the design of efficient classical and quantum simulation algorithms. This work presents a unified…

Quantum Physics · Physics 2026-02-06 Nicholas C. Rubin , Guang Hao Low , A. Eugene DePrince

A hierarchy of semidefinite programming (SDP) relaxations approximates the global optimum of polynomial optimization problems of noncommuting variables. Generating the relaxation, however, is a computationally demanding task, and only…

Mathematical Software · Computer Science 2015-06-15 Peter Wittek
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