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This paper presents a new Matlab toolbox, aimed at facilitating the use of polynomial optimization for stability analysis of nonlinear systems. In the past decade several decisive contributions made it possible to recast this type of…

Optimization and Control · Mathematics 2024-04-03 Stéphane Drobot , Matteo Tacchi , Carmen Cardozo , Colin N. Jones

Genuine entanglement is the strongest form of multipartite entanglement. Genuinely entangled pure states contain entanglement in every bipartition and as such can be regarded as a valuable resource in the protocols of quantum information…

Quantum Physics · Physics 2021-12-07 K. V. Antipin

We investigate the set a) of positive, trace preserving maps acting on density matrices of size N, and a sequence of its nested subsets: the sets of maps which are b) decomposable, c) completely positive, d) extended by identity impose…

Quantum Physics · Physics 2009-11-13 Stanislaw J. Szarek , Elisabeth Werner , Karol Zyczkowski

MAP inference for general energy functions remains a challenging problem. While most efforts are channeled towards improving the linear programming (LP) based relaxation, this work is motivated by the quadratic programming (QP) relaxation.…

Machine Learning · Computer Science 2012-06-22 Patrick Pletscher , Sharon Wulff

A map $\mathcal{P}$ is tensor stable positive (tsp) if $\mathcal{P}^{\otimes n}$ is positive for all $n$, and essential tsp if it is not completely positive or completely co-positive. Are there essential tsp maps? Here we prove that there…

Quantum Physics · Physics 2023-01-18 Mirte van der Eyden , Tim Netzer , Gemma De las Cuevas

Quantum entanglement is essential to the development of quantum computation, communications, and technology. The controlled SWAP test, widely used for state comparison, can be adapted to an efficient and useful test for entanglement of a…

Quantum Physics · Physics 2022-01-12 Steph Foulds , Viv Kendon , Tim Spiller

This paper presents PIQP, a high-performance toolkit for solving generic sparse quadratic programs (QP). Combining an infeasible Interior Point Method (IPM) with the Proximal Method of Multipliers (PMM), the algorithm can handle…

Optimization and Control · Mathematics 2023-09-18 Roland Schwan , Yuning Jiang , Daniel Kuhn , Colin N. Jones

Computing maximum a posteriori (MAP) estimation in graphical models is an important inference problem with many applications. We present message-passing algorithms for quadratic programming (QP) formulations of MAP estimation for pairwise…

Artificial Intelligence · Computer Science 2012-02-20 Akshat Kumar , Shlomo Zilberstein

We analyze positivity of a tensor product of two linear qubit maps, $\Phi_1 \otimes \Phi_2$. Positivity of maps $\Phi_1$ and $\Phi_2$ is a necessary but not a sufficient condition for positivity of $\Phi_1 \otimes \Phi_2$. We find a…

Quantum Physics · Physics 2017-01-11 Sergey N. Filippov , Kamil Yu. Magadov

Two fundamental contributions to categorical quantum mechanics are presented. First, we generalize the CP-construction, that turns any dagger compact category into one with completely positive maps, to arbitrary dimension. Second, we…

Category Theory · Mathematics 2020-10-15 Bob Coecke , Chris Heunen

Copositive optimization is a special case of convex conic programming, and it consists of optimizing a linear function over the cone of all completely positive matrices under linear constraints. Copositive optimization provides powerful…

Optimization and Control · Mathematics 2022-10-05 Zhijian Lai , Akiko Yoshise

Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been applied in several applications, it does not always result in…

Machine Learning · Computer Science 2007-05-23 Patrik O. Hoyer

The problem of minimizing a (nonconvex) quadratic form over the unit simplex, referred to as a standard quadratic program, admits an exact convex conic formulation over the computationally intractable cone of completely positive matrices.…

Optimization and Control · Mathematics 2020-03-02 Y. Gorkem Gokmen , E. Alper Yildirim

Matrices with low numerical rank are omnipresent in many signal processing and data analysis applications. The pivoted QLP (p-QLP) algorithm constructs a highly accurate approximation to an input low-rank matrix. However, it is…

Machine Learning · Computer Science 2021-06-16 Maboud F. Kaloorazi , Jie Chen

Clustering is a popular unsupervised learning tool often used to discover groups within a larger population such as customer segments, or patient subtypes. However, despite its use as a tool for subgroup discovery and description - few…

Machine Learning · Computer Science 2021-12-13 Connor Lawless , Jayant Kalagnanam , Lam M. Nguyen , Dzung Phan , Chandra Reddy

In quantum information theory, it is a fundamental problem to construct multipartite unextendible product bases (UPBs). We show that there exist two families UPBs in Hilbert space…

Quantum Physics · Physics 2022-12-06 Yize Sun , Baoshan Wang , Shiru Li

We investigate the problem of reversing quantum dynamics, specifically via optimal Petz recovery maps. We focus on typical decoherence channels, such as dephasing, depolarizing and amplitude damping. We illustrate how well a physically…

Quantum Physics · Physics 2022-05-06 Lea Lautenbacher , Fernando de Melo , Nadja K. Bernardes

We investigate certain classes of normal completely positive (CP) maps on the hyperfinite $II_1$ factor $\mathcal A$. Using the representation theory of a suitable irrational rotation algebra, we propose some computable invariants for such…

Operator Algebras · Mathematics 2007-05-23 Debashish Goswami , Lingaraj Sahu

A quantile sheet is a global estimator for multiple quantile curves. A quantile sheet estimator is proposed to maintain the non-crossing properties for different quantiles. The proposed estimator utilizes SCOP: shape-constrained P-spline to…

Methodology · Statistics 2023-03-13 Zhuolin Song

In this paper we propose the Graduated NonConvexity and Graduated Concavity Procedure (GNCGCP) as a general optimization framework to approximately solve the combinatorial optimization problems on the set of partial permutation matrices.…

Computer Vision and Pattern Recognition · Computer Science 2013-08-30 Zhi-Yong Liu , Hong Qiao