The remote set problem on lattices

We initiate studying the Remote Set Problem (\({\mathsf{RSP}}\)) on lattices, which given a lattice asks to find a set of points containing a point which is far from the lattice. We show a polynomial-time deterministic algorithm that on rank n lattice \({\mathcal{L}}\) outputs a set of points, at least one of which is \({\sqrt{\log n / n} \cdot \rho(\mathcal{L})}\) -far from \({\mathcal{L}}\) , where \({\rho(\mathcal{L})}\) stands for the covering radius of \({\mathcal{L}}\) (i.e., the maximum possible distance of a point in space from \({\mathcal{L}}\)). As an application, we show that the covering radius problem with approximation factor \({\sqrt{n / \log n}}\) lies in the complexity class \({\mathsf{NP}}\) , improving a result of Guruswami et al. (Comput Complex 14(2): 90–121, 2005) by a factor of \({\sqrt{\log n}}\) .Our results apply to any \({\ell_p}\) norm for \({2 \leq p \leq \infty}\) with the same approximation factors (except a loss of \({\sqrt{\log \log n}}\) for \({p = \infty}\)). In addition, we show that the output of our algorithm for \({\mathsf{RSP}}\) contains a point whose \({\ell_2}\) distance from \({\mathcal{L}}\) is at least \({(\log n/n)^{1/p} \cdot \rho^{(p)}(\mathcal{L})}\) , where \({\rho^{(p)}(\mathcal{L})}\) is the covering radius of \({\mathcal{L}}\) measured with respect to the \({\ell_p}\) norm. The proof technique involves a theorem on balancing vectors due to Banaszczyk (Random Struct Algorithms 12(4):351–360, 1998) and the “six standard deviations” theorem of Spencer (Trans Am Math Soc 289(2):679–706, 1985).     

A general framework for architecture composability

Architectures depict design principles: paradigms that can be understood by all, allow thinking on a higher plane and avoiding low-level mistakes. They provide means for ensuring correctness by construction by enforcing global properties characterizing the coordination between components. An architecture can be considered as an operator A that, applied to a set of components \({\mathcal{B}}\), builds a composite component \({A(\mathcal{B})}\) meeting a characteristic property \({\Phi}\). Architecture composability is a basic and common problem faced by system designers. In this paper, we propose a formal and general framework for architecture composability based on an associative, commutative and idempotent architecture composition operator \({\oplus}\). The main result is that if two architectures A ₁ and A ₂ enforce respectively safety properties \({\Phi_{1}}\) and \({\Phi_{2}}\), the architecture \({A_{1} \oplus A_{2}}\) enforces the property \({\Phi_{1} \land \Phi_{2}}\), that is both properties are preserved by architecture composition. We also establish preservation of liveness properties by architecture composition. The presented results are illustrated by a running example and a case study.     

Byzantine gathering in networks

This paper investigates an open problem introduced in Dieudonné et al. (ACM Trans Algorithms 11(1):1, 2014). Two or more mobile agents start from nodes of a network and have to accomplish the task of gathering which consists in getting all together at the same node at the same time. An adversary chooses the initial nodes of the agents and assigns a different positive integer (called label) to each of them. Initially, each agent knows its label but does not know the labels of the other agents or their positions relative to its own. Agents move in synchronous rounds and can communicate with each other only when located at the same node. Up to f of the agents are Byzantine. A Byzantine agent can choose an arbitrary port when it moves, can convey arbitrary information to other agents and can change its label in every round, in particular by forging the label of another agent or by creating a completely new one. What is the minimum number \({\mathcal {M}}\) of good agents that guarantees deterministic gathering of all of them, with termination? We provide exact answers to this open problem by considering the case when the agents initially know the size of the network and the case when they do not. In the former case, we prove \({\mathcal {M}}=f+1\) while in the latter, we prove \({\mathcal {M}}=f+2\). More precisely, for networks of known size, we design a deterministic algorithm gathering all good agents in any network provided that the number of good agents is at least \(f+1\). For networks of unknown size, we also design a deterministic algorithm ensuring the gathering of all good agents in any network but provided that the number of good agents is at least \(f+2\). Both of our algorithms are optimal in terms of required number of good agents, as each of them perfectly matches the respective lower bound on \({\mathcal {M}}\) shown in Dieudonné et al. (2014), which is of \(f+1\) when the size of the network is known and of \(f+2\) when it is unknown. Perhaps surprisingly, our results highlight an interesting feature when put in perspective with known results concerning a relaxed variant of this problem in which the Byzantine agents cannot change their initial labels. Indeed under this variant \({\mathcal {M}}=1\) for networks of known size and \({\mathcal {M}}=f+2\) for networks of unknown size. Following this perspective, it turns out that when the size of the network is known, the ability for the Byzantine agents to change their labels significantly impacts the value of \({\mathcal {M}}\). However, the relevance for \({\mathcal {M}}\) of such an ability completely disappears in the most general case where the size of the network is unknown, as \({\mathcal {M}}=f+2\) regardless of whether Byzantine agents can change their labels or not.     

$${\mathcal {}}$$-matrix Accelerated Second Moment Analysis for Potentials with Rough Correlation

We consider the efficient solution of partial differential equations for strongly elliptic operators with constant coefficients and stochastic Dirichlet data by the boundary integral equation method. The computation of the solution’s two-point correlation is well understood if the two-point correlation of the Dirichlet data is known and sufficiently smooth. Unfortunately, the problem becomes much more involved in case of roughly correlated data. We will show that the concept of the \({\mathcal {H}}\)-matrix arithmetic provides a powerful tool to cope with this problem. By employing a parametric surface representation, we end up with an \({\mathcal {H}}\)-matrix arithmetic based on balanced cluster trees. This considerably simplifies the implementation and improves the performance of the \({\mathcal {H}}\)-matrix arithmetic. Numerical experiments are provided to validate and quantify the presented methods and algorithms.     

Producibility in hierarchical self-assembly

Three results are shown on producibility in the hierarchical model of tile self-assembly. It is shown that a simple greedy polynomial-time strategy decides whether an assembly α is producible. The algorithm can be optimized to use \(O(|\alpha | \log ^2 |\alpha |)\) time. Cannon et al. (STACS 2013: proceedings of the thirtieth international symposium on theoretical aspects of computer science. pp 172–184, 2013) showed that the problem of deciding if an assembly α is the unique producible terminal assembly of a tile system \({\mathcal {T}}\) can be solved in \(O(|\alpha |^2 |{\mathcal {T}}| + |\alpha | |{\mathcal {T}}|^2)\) time for the special case of noncooperative “temperature 1” systems. It is shown that this can be improved to \(O(|\alpha | |{\mathcal {T}}| \log |{\mathcal {T}}|)\) time. Finally, it is shown that if two assemblies are producible, and if they can be overlapped consistently—i.e., if the positions that they share have the same tile type in each assembly—then their union is also producible.     

Collapse of the Hierarchy of Constant-Depth Exact Quantum Circuits

We study the quantum complexity class \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) of quantum operations implementable exactly by constant-depth polynomial-size quantum circuits with unbounded fan-out gates. Our main result is that the quantum OR operation is in \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\), which is an affirmative answer to the question posed by Høyer and ?palek. In sharp contrast to the strict hierarchy of the classical complexity classes: \({\mathsf{NC}^{0} \subsetneq \mathsf{AC}^{0} \subsetneq \mathsf{TC}^{0}}\), our result with Høyer and ?palek’s one implies the collapse of the hierarchy of the corresponding quantum ones: \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}=\mathsf{QAC}^\mathsf{0}_\mathsf{f}=\mathsf{QTC}^\mathsf{0}_\mathsf{f}}\). Then, we show that there exists a constant-depth subquadratic-size quantum circuit for the quantum threshold operation. This allows us to obtain a better bound on the size difference between the \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) and \({\mathsf{QTC}^\mathsf{0}_\mathsf{f}}\) circuits for implementing the same operation. Lastly, we show that, if the quantum Fourier transform modulo a prime is in \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\), there exists a polynomial-time exact classical algorithm for a discrete logarithm problem using a \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) oracle. This implies that, under a plausible assumption, there exists a classically hard problem that is solvable exactly by a \({\mathsf{QNC}^\mathsf{0}_\mathsf{f}}\) circuit with gates for the quantum Fourier transform.     

Tensor ethods for Solving Symmetric $${\mathcal {}}$$-tensor Systems

Tensor systems involving tensor-vector products (or polynomial systems) are considered. We solve these tensor systems, especially focusing on symmetric \({\mathcal {M}}\)-tensor systems, by some tensor methods. A new tensor method is proposed based on the rank-1 approximation of the coefficient tensor. Numerical examples show that the tensor methods could be more efficient than the Newton method for some \({\mathcal {M}}\)-tensor systems.     

Quantum Query Complexity of Almost All Functions with Fixed On-set Size

This paper considers the quantum query complexity of almost all functions in the set \({\mathcal{F}}_{N,M}\) of \({N}\)-variable Boolean functions with on-set size \({M (1\le M \le 2^{N}/2)}\), where the on-set size is the number of inputs on which the function is true. The main result is that, for all functions in \({\mathcal{F}}_{N,M}\) except its polynomially small fraction, the quantum query complexity is \({ \Theta\left(\frac{\log{M}}{c + \log{N} - \log\log{M}} + \sqrt{N}\right)}\) for a constant \({c > 0}\). This is quite different from the quantum query complexity of the hardest function in \({\mathcal{F}}_{N,M}\): \({\Theta\left(\sqrt{N\frac{\log{M}}{c + \log{N} - \log\log{M}}} + \sqrt{N}\right)}\). In contrast, almost all functions in \({\mathcal{F}}_{N,M}\) have the same randomized query complexity \({\Theta(N)}\) as the hardest one, up to a constant factor.     

Exact exponential algorithms for 3-machine flowshop scheduling problems

In this paper, we focus on the design of an exact exponential time algorithm with a proved worst-case running time for 3-machine flowshop scheduling problems considering worst-case scenarios. For the minimization of the makespan criterion, a Dynamic Programming algorithm running in \({\mathcal {O}}^*(3^n)\) is proposed, which improves the current best-known time complexity \(2^{{\mathcal {O}}(n)}\times \Vert I\Vert ^{{\mathcal {O}}(1)}\) in the literature. The idea is based on a dominance condition and the consideration of the Pareto Front in the criteria space. The algorithm can be easily generalized to other problems that have similar structures. The generalization on two problems, namely the \(F3\Vert f_\mathrm{max}\) and \(F3\Vert \sum f_i\) problems, is discussed.     

Cubature formulae for nearly singular and highly oscillating integrals

The paper deals with the approximation of integrals of the type

$$\begin{aligned} I(f;{\mathbf {t}})=\int _{{\mathrm {D}}} f({\mathbf {x}}) {\mathbf {K}}({\mathbf {x}},{\mathbf {t}}) {\mathbf {w}}({\mathbf {x}}) d{\mathbf {x}},\quad \quad {\mathbf {x}}=(x_1,x_2),\quad {\mathbf {t}}\in \mathrm {T}\subseteq \mathbb {R}^p, \ p\in \{1,2\} \end{aligned}$$

where \({\mathrm {D}}=[-\,1,1]^2\), f is a function defined on \({\mathrm {D}}\) with possible algebraic singularities on \(\partial {\mathrm {D}}\), \({\mathbf {w}}\) is the product of two Jacobi weight functions, and the kernel \({\mathbf {K}}\) can be of different kinds. We propose two cubature rules determining conditions under which the rules are stable and convergent. Along the paper we diffusely treat the numerical approximation for kernels which can be nearly singular and/or highly oscillating, by using a bivariate dilation technique. Some numerical examples which confirm the theoretical estimates are also proposed.

     

Identifying the minor set cover of dense connected bipartite graphs via random matching edge sets

Using quantum annealing to solve an optimization problem requires minor embedding a logic graph into a known hardware graph. In an effort to reduce the complexity of the minor embedding problem, we introduce the minor set cover (MSC) of a known graph \({\mathcal {G}}\): a subset of graph minors which contain any remaining minor of the graph as a subgraph. Any graph that can be embedded into \({\mathcal {G}}\) will be embeddable into a member of the MSC. Focusing on embedding into the hardware graph of commercially available quantum annealers, we establish the MSC for a particular known virtual hardware, which is a complete bipartite graph. We show that the complete bipartite graph \(K_{N,N}\) has a MSC of N minors, from which \(K_{N+1}\) is identified as the largest clique minor of \(K_{N,N}\). The case of determining the largest clique minor of hardware with faults is briefly discussed but remains an open question.     

Finding vertex-surjective graph homomorphisms

The Surjective Homomorphism problem is to test whether a given graph G called the guest graph allows a vertex-surjective homomorphism to some other given graph H called the host graph. The bijective and injective homomorphism problems can be formulated in terms of spanning subgraphs and subgraphs, and as such their computational complexity has been extensively studied. What about the surjective variant? Because this problem is NP-complete in general, we restrict the guest and the host graph to belong to graph classes \({{\mathcal G}}\) and \({{\mathcal H}}\), respectively. We determine to what extent a certain choice of \({{\mathcal G}}\) and \({{\mathcal H}}\) influences its computational complexity. We observe that the problem is polynomial-time solvable if \({{\mathcal H}}\) is the class of paths, whereas it is NP-complete if \({{\mathcal G}}\) is the class of paths. Moreover, we show that the problem is even NP-complete on many other elementary graph classes, namely linear forests, unions of complete graphs, cographs, proper interval graphs, split graphs and trees of pathwidth at most 2. In contrast, we prove that the problem is fixed-parameter tractable in k if \({{\mathcal G}}\) is the class of trees and \({{\mathcal H}}\) is the class of trees with at most k leaves, or if \({{\mathcal G}}\) and \({{\mathcal H}}\) are equal to the class of graphs with vertex cover number at most k.     

From LTL to deterministic automata

We present a new algorithm to construct a (generalized) deterministic Rabin automaton for an LTL formula \(\varphi \). The automaton is the product of a co-Büchi automaton for \(\varphi \) and an array of Rabin automata, one for each \({\mathbf {G}}\)-subformula of \(\varphi \). The Rabin automaton for \({\mathbf {G}}\psi \) is in charge of recognizing whether \({\mathbf {F}}{\mathbf {G}}\psi \) holds. This information is passed to the co-Büchi automaton that decides on acceptance. As opposed to standard procedures based on Safra’s determinization, the states of all our automata have a clear logical structure, which allows for various optimizations. Experimental results show improvement in the sizes of the resulting automata compared to existing methods.     

Tight bounds for parallel randomized load balancing

Given a distributed system of \(n\) balls and \(n\) bins, how evenly can we distribute the balls to the bins, minimizing communication? The fastest non-adaptive and symmetric algorithm achieving a constant maximum bin load requires \(\varTheta (\log \log n)\) rounds, and any such algorithm running for \(r\in {\mathcal {O}}(1)\) rounds incurs a bin load of \(\varOmega ((\log n/\log \log n)^{1/r})\). In this work, we explore the fundamental limits of the general problem. We present a simple adaptive symmetric algorithm that achieves a bin load of 2 in \(\log ^* n+{\mathcal {O}}(1)\) communication rounds using \({\mathcal {O}}(n)\) messages in total. Our main result, however, is a matching lower bound of \((1-o(1))\log ^* n\) on the time complexity of symmetric algorithms that guarantee small bin loads. The essential preconditions of the proof are (i) a limit of \({\mathcal {O}}(n)\) on the total number of messages sent by the algorithm and (ii) anonymity of bins, i.e., the port numberings of balls need not be globally consistent. In order to show that our technique yields indeed tight bounds, we provide for each assumption an algorithm violating it, in turn achieving a constant maximum bin load in constant time.     

On-line integrated production and outbound distribution scheduling to minimize the maximum delivery completion time

In this paper, we consider the on-line integrated production and outbound distribution scheduling problem to minimize the maximum delivery completion time. All jobs arrive over time, and each job and its processing time become known at its arrival time. The jobs are first processed on a single machine and then delivered by a vehicle to a single customer. The vehicle can deliver at most c jobs to the customer at a time. When preemption is allowed and c≥2, we can provide an on-line algorithm with the best competitive ratio \(\frac{\sqrt{5}+1}{2}\approx1.618\). When preemption is not allowed, we provide an on-line algorithm which has the best competitive ratio \(\frac{\sqrt{5}+1}{2}\approx1.618\) for the case c=1 and has an asymptotic competitive ratio \(\frac{\sqrt{5}+1}{2}\approx1.618\) for the case c≥2.     

The complexity of online voter control in sequential elections

Previous work on voter control, which refers to situations where a chair seeks to change the outcome of an election by deleting, adding, or partitioning voters, takes for granted that the chair knows all the voters’ preferences and that all votes are cast simultaneously. However, elections are often held sequentially and the chair thus knows only the previously cast votes and not the future ones, yet needs to decide instantaneously which control action to take. We introduce a framework that models online voter control in sequential elections. We show that the related problems can be much harder than in the standard (non-online) case: For certain election systems, even with efficient winner problems, online control by deleting, adding, or partitioning voters is \(\mathrm {PSPACE}\)-complete, even if there are only two candidates. In addition, we obtain (by a new characterization of coNP in terms of weight-bounded alternating Turing machines) completeness for \({\mathrm {coNP}}\) in the deleting/adding cases with a bounded deletion/addition limit, and we obtain completeness for \({\mathrm {NP}}\) in the partition cases with an additional restriction. We also show that for plurality, online control by deleting or adding voters is in \({\mathrm {P}}\), and for partitioning voters is \({\mathrm {coNP}}\)-hard.     

Fast Iterative Method with a Second-Order Implicit Difference Scheme for Time-Space Fractional Convection–Diffusion Equation

In this paper we intend to establish fast numerical approaches to solve a class of initial-boundary problem of time-space fractional convection–diffusion equations. We present a new unconditionally stable implicit difference method, which is derived from the weighted and shifted Grünwald formula, and converges with the second-order accuracy in both time and space variables. Then, we show that the discretizations lead to Toeplitz-like systems of linear equations that can be efficiently solved by Krylov subspace solvers with suitable circulant preconditioners. Each time level of these methods reduces the memory requirement of the proposed implicit difference scheme from \({\mathcal {O}}(N^2)\) to \({\mathcal {O}}(N)\) and the computational complexity from \({\mathcal {O}}(N^3)\) to \({\mathcal {O}}(N\log N)\) in each iterative step, where N is the number of grid nodes. Extensive numerical examples are reported to support our theoretical findings and show the utility of these methods over traditional direct solvers of the implicit difference method, in terms of computational cost and memory requirements.     

Partially Ordered Connectives and Monadic Monotone Strict NP

Motivated by constraint satisfaction problems, Feder and Vardi (SIAM Journal of Computing, 28, 57–104, 1998) set out to search for fragments \({\mathcal{L}}\) of \(\Sigma_1^1\) satisfying the dichotomy property: every problem definable in \({\mathcal{L}}\) is either in P or else NP-complete. Feder and Vardi considered in this connection two logics, strict NP (or SNP) and monadic, monotone, strict NP without inequalities (or MMSNP). The former consists of formulas of the form \(\exists \vec{X}\forall \vec{x} \phi\), where \(\phi\) is a quantifier-free formula in a relational vocabulary; and the latter is the fragment of SNP whose formulas involve only negative occurrences of relation symbols, only monadic second-order quantifiers, and no occurrences of the equality symbol. It remains an open problem whether MMSNP enjoys the dichotomy property. In the present paper, SNP and MMSNP are characterized in terms of partially ordered connectives. More specifically, SNP is characterized using the logic D of partially ordered connectives introduced in Blass and Gurevich (Annals of Pure and Applied Logic, 32, 1–16, 1986), Sandu and Väänänen (Zeitschrift für Mathematische Logik und Grundlagen der Mathematik, 38, 361–372 1992), and MMSNP employing a generalization C of D introduced in the present paper.     

Discovering dispatching rules from data using imitation learning: A case study for the job-shop problem

Dispatching rules can be automatically generated from scheduling data. This paper will demonstrate that the key to learning an effective dispatching rule is through the careful construction of the training data, \(\{\mathbf {x}_i(k),y_i(k)\}_{k=1}^K\in {\mathscr {D}}\), where (i) features of partially constructed schedules \(\mathbf {x}_i\) should necessarily reflect the induced data distribution \({\mathscr {D}}\) for when the rule is applied. This is achieved by updating the learned model in an active imitation learning fashion; (ii) \(y_i\) is labelled optimally using a MIP solver; and (iii) data need to be balanced, as the set is unbalanced with respect to the dispatching step k. Using the guidelines set by our framework the design of custom dispatching rules, for a particular scheduling application, will become more effective. In the study presented three different distributions of the job-shop will be considered. The machine learning approach considered is based on preference learning, i.e. which dispatch (post-decision state) is preferable to another.     

Weighted Finite Fourier Transform Operator: Uniform Approximations of the Eigenfunctions,Eigenvalues Decay and Behaviour

In this paper, we investigate two uniform asymptotic approximations as well as some spectral properties of the eigenfunctions of the weighted finite Fourier transform operator, defined by \({\displaystyle {\mathcal {F}}_c^{(\alpha )} f(x)=\int _{-1}^1 e^{icxy} f(y)\,(1-y^2)^{\alpha }\, dy.}\) Here, \( c >0, \alpha \ge -1/2\) are two fixed real numbers. These eigenfunctions are called generalized prolate spheroidal wave functions (GPSWFs) and they are firstly introduced and studied in Wang and Zhang (Appl Comput Harmon Anal 29(3):303–329, 2010). The present study is motivated by the promising concrete applications of the GPSWFs in various scientific area such as numerical analysis, mathematical physics and signal processing. We should mention that these two uniform approximation results of the GPSWFs can be considered as generalizations of the results given in the joint work of one of us (Bonami and Karoui in Constr Approx 43(1):15–45, 2016). As it will be seen, these generalizations require some involved extra work, especially in the case where \(\alpha > 1/2.\) By using the uniform asymptotic approximations of the GPSWFs, we prove the super-exponential decay rate of the eigenvalues of the operator \({\mathcal {F}}_c^{(\alpha )}\) in the case where \(0<\alpha < 3/2.\) Moreover, by computing the trace and an estimate of the norm of the operator \({\displaystyle {\mathcal {Q}}_c^{(\alpha )}=\frac{c}{2\pi } {\mathcal {F}}_c^{{(\alpha )}^*} \circ {\mathcal {F}}_c^{(\alpha )},}\) we give a lower bound for the counting number of the eigenvalues of \(Q_c^{(\alpha )},\) when \(c>>1.\) Finally, we provide the reader with some numerical examples that illustrate the different results of this work.