Mutually unbiased special entangled bases with Schmidt number 2 in $${\mathbb {C}}^3 \otimes {\mathbb {C}}^{4k}$$

A way of constructing special entangled basis with fixed Schmidt number 2 (SEB2) in \({\mathbb {C}}^3 \otimes {\mathbb {C}}^{4k}(k\in z^+,3\not \mid k)\) is proposed, and the conditions mutually unbiased SEB2s (MUSEB2s) satisfy are discussed. In addition, a very easy way of constructing MUSEB2s in \({\mathbb {C}}^3 \otimes {\mathbb {C}}^{4k}(k=2^l)\) is presented. We first establish the concrete construction of SEB2 and MUSEB2s in \({\mathbb {C}}^3 \otimes {\mathbb {C}}^{4}\) and \({\mathbb {C}}^3 \otimes {\mathbb {C}}^{8}\), respectively, and then generalize them into \({\mathbb {C}}^3 \otimes {\mathbb {C}}^{4k}(k\in z^+,3\not \mid k)\) and display the condition that MUSEB2s satisfy; we also give general form of two MUSEB2s as examples in \({\mathbb {C}}^3 \otimes {\mathbb {C}}^{4k}(k=2^l)\).     

Unextendible maximally entangled bases in $${\mathbb {C}}^{pd}\otimes {\mathbb {C}}^{qd}$$

The construction of unextendible maximally entangled bases is tightly related to quantum information processing like local state discrimination. We put forward two constructions of UMEBs in \({\mathbb {C}}^{pd}\otimes {\mathbb {C}}^{qd}\)(\(p\le q\)) based on the constructions of UMEBs in \({\mathbb {C}}^{d}\otimes {\mathbb {C}}^{d}\) and in \({\mathbb {C}}^{p}\otimes {\mathbb {C}}^{q}\), which generalizes the results in Guo (Phys Rev A 94:052302, 2016) by two approaches. Two different 48-member UMEBs in \({\mathbb {C}}^{6}\otimes {\mathbb {C}}^{9}\) have been constructed in detail.     

About the Decidability of Polyhedral Separability in the Lattice $$\mathbb {Z}^d$$

The recognition of primitives in digital geometry is deeply linked with separability problems. This framework leads us to consider the following problem of pattern recognition : given a finite lattice set \(S\subset \mathbb {Z}^d\) and a positive integer n, is it possible to separate S from \(\mathbb {Z}^d \setminus S\) by n half-spaces? In other words, does there exist a polyhedron P defined by at most n half-spaces satisfying \(P\cap \mathbb {Z}^d = S\)? The difficulty comes from the infinite number of constraints generated by all the points of \(\mathbb {Z}^d\setminus S\). It makes the decidability of the problem non-straightforward since the classical algorithms of polyhedral separability can not be applied in this framework. We conjecture that the problem is nevertheless decidable and prove it under some assumptions: in arbitrary dimension, if the interior of the convex hull of S contains at least one lattice point or if the dimension d is 2 or if the dimension \(d=3\) and S is not in a specific configuration of lattice width 0 or 1. The proof strategy is to reduce the set of outliers \(\mathbb {Z}^d\setminus S\) to its minimal elements according to a partial order “is in the shadow of.” These minimal elements are called the lattice jewels of S. We prove that under some assumptions, the set S admits only a finite number of lattice jewels. The result about the decidability of the problem is a corollary of this fundamental property.     

Quaternary Codes and Biphase Sequences from $$\mathbb{Z}_8 $$ -Codes

Composing the Carlet map with the inverse Gray map, a new family of cyclic quaternary codes is constructed from 5-cyclic -codes. This new family of codes is inspired by the quaternary Shanbag–Kumar–Helleseth family, a recent improvement on the Delsarte–Goethals family. We conjecture that these -codes are not linear. As applications, we construct families of low-correlation quadriphase and biphase sequences.     

Tile-Packing Tomography Is \mathbb{NP}-hard

Discrete tomography deals with reconstructing finite spatial objects from their projections. The objects we study in this paper are called tilings or tile-packings, and they consist of a number of disjoint copies of a fixed tile, where a tile is defined as a connected set of grid points. A row projection specifies how many grid points are covered by tiles in a given row; column projections are defined analogously. For a fixed tile, is it possible to reconstruct its tilings from their projections in polynomial time? It is known that the answer to this question is affirmative if the tile is a bar (its width or height is 1), while for some other types of tiles $\mathbb {NP}$ -hardness results have been shown in the literature. In this paper we present a complete solution to this question by showing that the problem remains $\mathbb {NP}$ -hard for all tiles other than bars.     

Square roots of $${3\times 3}$$ matrices

We find square roots of a complex-valued matrix \(A_{3 \times 3}\) using equation \(B^{2}=A\). The proposed method is faster than Higham’s method and provides up to 8 square roots with less relative residual and error.     

Grid-Oriented Computation: Modified Bessel Functions $$\mathcal{J}_V \left( Z \right)$$ ν(z) and $$\mathcal{K}_V \left( Z \right)$$ ν (z)

Programming and Computer Software - The problem of computation of modified real and complex Bessel functions $\mathcal{J}_V \left( Z \right)$ ν(z) and $\mathcal{K}_V \left( Z \right)$...     

Singular $$\mathcal{H}$$ 2-optimization problems for discrete-time systems

Singular ₂-optimization problems are considered for the standard discrete-time control system. Two types of singularity (type I and type II) are distinguished. A detailed treatment of problems with singularity of type II, which leads to nonuniqueness of solution, is presented. New algorithms for design of optimal controllers are presented both in frequency domain and state space, which generalize standard procedures onto the case of singular ₂-problems. A parameterization of the set of optimal controllers is given.Translated from Avtomatika i Telemekhanika, No. 3, 2005, pp. 20–33.Original Russian Text Copyright © 2005 by Polyakov.This paper was recommended for publication by B.T. Polyak, a member of the Editorial Board     

Parameterized Complexity of Satisfying Almost All Linear Equations over \mathbb{F}_{2}

The problem MaxLin2 can be stated as follows. We are given a system S of m equations in variables x ₁,…,x _n , where each equation $\sum_{i \in I_{j}}x_{i} = b_{j}$ is assigned a positive integral weight w _j and $b_{j} \in\mathbb{F}_{2}$ , I _j ?{1,2,…,n} for j=1,…,m. We are required to find an assignment of values in $\mathbb{F}_{2}$ to the variables in order to maximize the total weight of the satisfied equations. Let W be the total weight of all equations in S. We consider the following parameterized version of MaxLin2: decide whether there is an assignment satisfying equations of total weight at least W?k, where k is a nonnegative parameter. We prove that this parameterized problem is W[1]-hard even if each equation of S has exactly three variables and every variable appears in exactly three equations and, moreover, each weight w _j equals 1 and no two equations have the same left-hand side. We show the tightness of this result by proving that if each equation has at most two variables then the parameterized problem is fixed-parameter tractable. We also prove that if no variable appears in more than two equations then we can maximize the total weight of satisfied equations in polynomial time.     

Subspace Learning by $$\ell ^{0}$$-Induced Sparsity

Subspace clustering methods partition the data that lie in or close to a union of subspaces in accordance with the subspace structure. Such methods with sparsity prior, such as sparse subspace clustering (SSC) (Elhamifar and Vidal in IEEE Trans Pattern Anal Mach Intell 35(11):2765–2781, 2013) with the sparsity induced by the \(\ell ^{1}\)-norm, are demonstrated to be effective in subspace clustering. Most of those methods require certain assumptions, e.g. independence or disjointness, on the subspaces. However, these assumptions are not guaranteed to hold in practice and they limit the application of existing sparse subspace clustering methods. In this paper, we propose \(\ell ^{0}\)-induced sparse subspace clustering (\(\ell ^{0}\)-SSC). In contrast to the required assumptions, such as independence or disjointness, on subspaces for most existing sparse subspace clustering methods, we prove that \(\ell ^{0}\)-SSC guarantees the subspace-sparse representation, a key element in subspace clustering, for arbitrary distinct underlying subspaces almost surely under the mild i.i.d. assumption on the data generation. We also present the “no free lunch” theorem which shows that obtaining the subspace representation under our general assumptions can not be much computationally cheaper than solving the corresponding \(\ell ^{0}\) sparse representation problem of \(\ell ^{0}\)-SSC. A novel approximate algorithm named Approximate \(\ell ^{0}\)-SSC (A\(\ell ^{0}\)-SSC) is developed which employs proximal gradient descent to obtain a sub-optimal solution to the optimization problem of \(\ell ^{0}\)-SSC with theoretical guarantee. The sub-optimal solution is used to build a sparse similarity matrix upon which spectral clustering is performed for the final clustering results. Extensive experimental results on various data sets demonstrate the superiority of A\(\ell ^{0}\)-SSC compared to other competing clustering methods. Furthermore, we extend \(\ell ^{0}\)-SSC to semi-supervised learning by performing label propagation on the sparse similarity matrix learnt by A\(\ell ^{0}\)-SSC and demonstrate the effectiveness of the resultant semi-supervised learning method termed \(\ell ^{0}\)-sparse subspace label propagation (\(\ell ^{0}\)-SSLP).     

On Projection Matrices $$\mathcal{P}^k \to \mathcal{P}^2 ,k = 3,...,6, $$ and their Applications in Computer Vision

Projection matrices from projective spaces have long been used in multiple-view geometry to model the perspective projection created by the pin-hole camera. In this work we introduce higher-dimensional mappings for the representation of various applications in which the world we view is no longer rigid. We also describe the multi-view constraints from these new projection matrices (where k > 3) and methods for extracting the (non-rigid) structure and motion for each application.     

$$\mathbf {L^\infty }$$-error estimates for the obstacle problem revisited

In this paper, we present an alternative approach to a priori \(L^\infty \)-error estimates for the piecewise linear finite element approximation of the classical obstacle problem. Our approach is based on stability results for discretized obstacle problems and on error estimates for the finite element approximation of functions under pointwise inequality constraints. As an outcome, we obtain the same order of convergence proven in several works before. In contrast to prior results, our estimates can, for example, also be used to study the situation where the function space is discretized but the obstacle is not modified at all.     

Sufficient conditions for robustness of $$\mathcal{K}\mathcal{L}$$ -stability for difference inclusions

Difference inclusions arise naturally in the study of discrete-time or sampled-data systems. We develop two novel sufficient conditions for robustness of a stability property referred to as -stability with respect to an arbitrary measure; i.e., where a continuous positive definite function of the solutions satisfies a class- estimate of time and the continuous positive definite function of the initial condition. Christopher M. Kellett was supported by the Australian Research Council under Discovery Project Grant DP0771131. Andrew R. Teel was supported by NSF grants ECS-0324679, ECS-0622253, and AFOSR grants F49620-03-1-0203 and FA9550-06-1-0134.     

A semantically complete extension sequence of the system $$\mathcal{L}^* $$

In this paper, the method of well-combined semantics and syntax proposed by Pavelka is applied to the research of the propositional calculus formal system . The partial constant values are taken as formulas, formulas are fuzzified in two manners of semantics and syntax, and inferring processes are fuzzified. A sequence of new extensions { } of the system is proposed, and the completeness of is proved.     

Mutually unbiased bases in dimension six containing a product-vector basis

Excluding the existence of four MUBs in \(\mathbb {C}^6\) is an open problem in quantum information. We investigate the number of product-vectors in the set of four mutually unbiased bases (MUBs) in dimension six, by assuming that the set exists and contains a product-vector basis. We show that in most cases the number of product-vectors in each of the remaining three MUBs is at most two. We further construct the exceptional case in which the three MUBs respectively contain at most three, two and two product-vectors. We also investigate the number of vectors mutually unbiased to an orthonormal basis.     

The preparation of organic light-emitting diode encapsulation barrier layer by low-temperature plasma-enhanced chemical vapor deposition: a study on the $$\hbox {SiO}_\mathrm{x}\hbox {N}_\mathrm{y}$$ film parameter optimization

This study prepared \(\hbox {SiO}_\mathrm{x}\hbox {N}_\mathrm{y}\) film by using plasma-enhanced chemical vapor deposition in organic light-emitting diode (OLED) encapsulation to prevent the invasion of moisture and oxygen for longer light-emitting lifetime of OLED components. It applied high density inductively coupled plasma for the coating of film on polyethersulfone, silicon and glass substrate, and discussed the relevance between process parameters and quality characteristics including coating uniformity, coating thickness and moisture permeation. This study used Taguchi method to plan the experiment and calculated the optimal parameters of each quality, used technique for order preference by similarity to ideal solution and grey relational analysis to determine the optimal parameter of all qualities. The back-propagation neural network was combined with Levenberg–Marquardt algorithm to construct the simulation and prediction system. Based on the quality optimization design, the single layer film’s moisture permeation rate was 0.02 g/m\(^{2}\)/day, the maximum coating thickness reached 420 nm, and the fastest rate was 21 nm/min, which was higher than the industrial standard specification (10 nm/min) by 110 %.     

Experimental estimation of discord in an antiferromagnetic Heisenberg compound $$\hbox {Cu}(\hbox {NO}_{3})_{2}\cdot 2.5\,\hbox {H}_{2}\hbox {O}$$

Temperature-dependent static magnetic susceptibility and heat capacity data were employed to quantify quantum discord in copper nitrate \((\hbox {CN, Cu}(\hbox {NO}_{3})_{2}\cdot 2.5\, \hbox {H}_{2}\hbox {O})\) which is a spin 1/2 antiferromagnetic Heisenberg system. With the help of existing theoretical formulations, quantum discord, mutual information, and purely classical correlation were estimated as a function of temperature using the experimental data. The experimentally quantified correlations estimated from susceptibility and heat capacity data are consistent with each other, and they exhibit a good match with theoretical predictions. Violation of Bell’s inequality was also checked using the static magnetic susceptibility as well as heat capacity data. Quantum discord estimated from magnetic susceptibility as well as heat capacity data is found to be present in the thermal states of the system even when the system is in a separable state.     

Super-quantum correlation for SU(2) invariant state in $$4\otimes 2$$ system

We analytically evaluate the weak one-way deficit and super-quantum discord for a system composed of spin-3/2 and spin-1/2 subsystems possessing SU(2) symmetry. We also make a comparative study of the relationships among the quantum discord, one-way deficit, weak one-way deficit, and super-quantum discord for the SU(2) invariant state. It is shown that super-quantum discord via weak measurement is greater than that via von Neumann measurement. But weak one-way deficit is less than the one-way deficit. As a result, weak measurement do not always reveal more quantumness.