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The query model (or black-box model) has attracted much attention from the communities of both classical and quantum computing. Usually, quantum advantages are revealed by presenting a quantum algorithm that has a better query complexity than its classical counterpart. In the history of quantum algorithms, the Deutsch algorithm and the Deutsch-Jozsa algorithm play a fundamental role and both are exact one-query quantum algorithms. This leads us to consider the problem: what functions can be computed by exact one-query quantum algorithms? This problem has been addressed in the literature for total Boolean functions and symmetric partial Boolean functions, but is still open for general partial Boolean functions. Thus, in this paper, we continue to characterize the computational power of exact one-query quantum algorithms for general partial Boolean functions. First, we present several necessary and sufficient conditions for a partial Boolean function to be computed by exact one-query quantum algorithms. Second, inspired by these conditions, we discover some new representative functions that can be computed by exact one-query quantum algorithms but have an essential difference from the already known ones. Specially, it is worth pointing out that before our work, the known functions that can be computed by exact one-query quantum algorithms are all symmetric functions and the quantum algorithm used is essentially the Deutsch-Jozsa algorithm, whereas the functions discovered in this paper are generally asymmetric and new algorithms to compute these functions are required. Thus, this expands the class of functions that can be computed by exact one-query quantum algorithms. [ABSTRACT FROM AUTHOR]

The classical hypercontractive inequality for the noise operator on the discrete cube plays a crucial role in many of the fundamental results in the Analysis of Boolean functions, such as the Kahn-Kalai-Linial theorem, Friedgut's junta theorem and the invariance principle of Mossel, O'Donnell and Oleszkiewicz. In these results the cube is equipped with the uniform (1/2-biased) measure, but it is desirable, particularly for applications to the theory of sharp thresholds, to also obtain such results for general p-biased measures. However, simple examples show that when p is small there is no hypercontractive inequality that is strong enough for such applications. In this paper, we establish an effective hypercontractivity inequality for general p that applies to 'global functions', i.e. functions that are not significantly affected by a restriction of a small set of coordinates. This class of functions appears naturally, e.g. in Bourgain's sharp threshold theorem, which states that such functions exhibit a sharp threshold. We demonstrate the power of our tool by strengthening Bourgain's theorem, making progress on two conjectures of Kahn and Kalai (both these conjectures were open when we arXived this paper in 2019; one of them was solved in 2022; the other is still open), and proving a p-biased analogue of the seminal invariance principle of Mossel, O'Donnell, and Oleszkiewicz. In this 2023 version of our paper we will also survey many further applications of our results that have been obtained by various authors since we arXived the first version in 2019. [ABSTRACT FROM AUTHOR]

The Boolean map χ n : F 2 n → F 2 n , x ↦ y defined by y i = x i + (x i + 1 + 1) x i + 2 (where i ∈ Z / n Z ) is used in various permutations that are part of cryptographic schemes, e.g., Keccak-f (the SHA-3-permutation), ASCON (the winner of the NIST Lightweight competition), Xoodoo, Rasta and Subterranean (2.0). In this paper, we study various algebraic properties of this map. We consider χ n (through vectorial isomorphism) as a univariate polynomial. We show that it is a power function if and only if n = 1 , 3 . We furthermore compute bounds on the sparsity and degree of these univariate polynomials, and the number of different univariate representations. Secondly, we compute the number of monomials of given degree in the inverse of χ n (if it exists). This number coincides with binomial coefficients. Lastly, we consider χ n as a polynomial map, to study whether the same rule ( y i = x i + (x i + 1 + 1) x i + 2 ) gives a bijection on field extensions of F 2 . We show that this is not the case for extensions whose degree is divisible by two or three. Based on these results, we conjecture that this rule does not give a bijection on any extension field of F 2 . [ABSTRACT FROM AUTHOR]

Digital systems are nowadays ubiquitous and often comprise an extremely high level of complexity. Guaranteeing the correct behavior of such systems has become an ever more pressing need for manufacturers. The correctness of digital systems can be addressed resorting to formal verification techniques, such as model checking. Currently, it is usually impossible to determine a priori the best algorithm to use given a verification task and, thus, portfolio approaches have become the de facto standard in model checking verification suites. This paper describes the most relevant algorithms and techniques, at the foundations of bit-level SAT-based model checking itself. [ABSTRACT FROM AUTHOR]

Using logic gates is the traditional way of designing logic circuits. However, in many cases, the use of modules is advantageous as the module is considered a uniform structure composed of multiple gates. In this paper, a nonlinear approach is proposed for designing logic circuits for use as modules multiplexers (MUXs) or Reed–Muller universal blocks (RMs). The experimental results show that the method gives better results compared to other methods available in the literature. The main advantages of the method are that it guarantees minimality and it can also handle Boolean functions for incompletely specified functions. The method is general enough and can be used for any kind of modules. [ABSTRACT FROM AUTHOR]

Determining the weight distribution of all Reed-Muller codes is a huge and exciting problem that has been around since the sixties. Some progress has been made very recently, but we are still far from a solution. In this paper, we addressed the subproblem of determining as many codeword weights as possible in Reed-Muller codes of any lengths and any orders, which is decisive for determining their weight spectra (i.e., the lists of all possible weights in these codes). New approaches seem necessary for both the main problem and the subproblem. We first studied the difficulties and the limits of the approach, which consisted of using the usual primary and secondary constructions of Boolean functions for the purpose of determining as many weights as possible in Reed-Muller codes. We then introduced a way, different from the usual constructions, to generate Boolean functions in n variables having an algebraic degree bounded from above, without any restriction on n, and whose Hamming weights can be determined. This provided weights in Reed-Muller codes of any lengths 2n and any orders, allowing us to reach potentially new values in the weight spectra of Reed-Muller codes (as we illustrate with all Reed-Muller codes of lengths up to 221), with the related codewords being given with their supports and their algebraic normal forms being mathematically derived. [ABSTRACT FROM AUTHOR]

In this paper we give three constructions of cyclic self-orthogonal codes over Z 2 k , for k ≥ 3 , from Boolean functions on n variables. The first construction for each k, 3 ≤ k ≤ n , yields a self-orthogonal Z 2 k -code of length 2 n + 2 with all Euclidean weights divisible by 2 k + 1. In the remaining two constructions, for each even n and k ≥ 3 , we generate a self-orthogonal Z 2 k -code of length 2 n + 1. All Euclidean weights in the constructed code are divisible by 2 2 k - 1 or 2 k + 1 , depending on which of the two constructions is used. [ABSTRACT FROM AUTHOR]

In-memory computing is the method of running computer computations completely in memory. Memristive device (e.g., 1 selector-1 resistor (1S1R)) is preferably utilized for in-memory computing with the appearance of hybrid CMOS nano-crossbar arrays. The parallelism of resistive arrays is considered in parallel adder designs to reduce the critical path delay. However, they minimize latency at the cost of hardware resources. In addition, the resistive random-access memory (ReRAM) is suffered by sneak–path problem because of the incapability for accessing a specific cell without impeding its neighbors. To tackle this issue, an analytical model of Pt/TaO x /TiO2/TaO x /Pt selector device is developed and it is integrated with ReRAM model for reducing the sneak path current. In this paper, a novel mapping scheme is proposed for in-memory variable stage size carry skip adder (VSS-CSKA) to harness the parallelism of 1S1R resistive memory. The VSS-CSKA considers variable block lengths and uses basic Boolean functions as skip logic to improve the speed without requiring huge area. Also, the selector device is modeled by considering the Pt/TaO x /TiO2/TaO x /Pt crested barrier for suppressing the sneak current in the resistive memory. The macro-model of the 1S1R resistive memory model is modeled in Verilog-A netlist and the simulations are executed on Spectre circuit simulator from Cadence Virtuoso. The proposed in-memory adder reduced the latency to 6 + 3 log 2 (k) for k -bit addition and it consumes less energy because of the minimization of sneak currents in 1S1R. [ABSTRACT FROM AUTHOR]

This paper considers inequivalent monotone Boolean functions of an arbitrary number of variables, two monotone Boolean functions are equivalent if one can be obtained from the other by permuting the variables. It focuses on some inequivalent monotone Boolean functions with three and four types of equivalent variables, where the variables are either dominant or dominated. The paper provides closed formulas for their enumeration as a function of the number of variables. The problem we deal with is very versatile since inequivalent monotone Boolean functions are monotonic simple games, structures that are used in many fields such as game theory, neural networks, artificial intelligence, reliability or multiple-criteria decision-making. [ABSTRACT FROM AUTHOR]

Horn functions form a subclass of Boolean functions possessing interesting structural and computational properties. These functions play a fundamental role in algebra, artificial intelligence, combinatorics, computer science, database theory, and logic. In the present paper, we introduce the subclass of hypergraph Horn functions that generalizes matroids and equivalence relations. We provide multiple characterizations of hypergraph Horn functions in terms of implicate-duality and the closure operator, which are, respectively, regarded as generalizations of matroid duality and the Mac Lane-Steinitz exchange property of matroid closure. We also study algorithmic issues on hypergraph Horn functions and show that the recognition problem (i.e., deciding if a given definite Horn CNF represents a hypergraph Horn function) and key realization (i.e., deciding if a given hypergraph is realized as a key set by a hypergraph Horn function) can be done in polynomial time, while implicate sets can be generated with polynomial delay. [ABSTRACT FROM AUTHOR]

In computer science, a binary decision diagram is a data structure that is used to represent a Boolean function and to consider a compressed representation of relations. This paper considers the notation of T.B.T (total binary truth table), and introduces a novel concept of binary decision (hyper)tree and binary decision (hyper)diagram, directly and in as little time as possible, unlike previous methods. This study proves that every T.B.T corresponds to a binary decision (hyper)tree via minimum Boolean expression and presents some conditions on any given T.B.T for isomorphic binary decision (hyper)trees. Finally, for faster calculations and more complex functions, we offer an algorithm and so Python programming codes such that for any given T.B.T, it introduces a binary decision (hyper)tree. [ABSTRACT FROM AUTHOR]

In this paper, we study the value distributions of perfect nonlinear functions, i.e., we investigate the sizes of image and preimage sets. Using purely combinatorial tools, we develop a framework that deals with perfect nonlinear functions in the most general setting, generalizing several results that were achieved under specific constraints. For the particularly interesting elementary abelian case, we derive several new strong conditions and classification results on the value distributions. Moreover, we show that most of the classical constructions of perfect nonlinear functions have very specific value distributions, in the sense that they are almost balanced. Consequently, we completely determine the possible value distributions of vectorial Boolean bent functions with output dimension at most 4. Finally, using the discrete Fourier transform, we show that in some cases value distributions can be used to determine whether a given function is perfect nonlinear, or to decide whether given perfect nonlinear functions are equivalent. [ABSTRACT FROM AUTHOR]

An endomorphism of a finite algebra is said to be highest if its pre-period is greater than or equal to the pre-period of all its endomorphisms. In this paper, we characterize all highest endomorphisms of a Boolean lattice. [ABSTRACT FROM AUTHOR]

Rotation symmetric Boolean functions are good candidates for stream ciphers because they have such advantages as simple structure, high operational speed and low implement cost. Recently, Mesnager et al. proposed for the first time an efficient method to construct balanced rotation symmetric Boolean functions with optimal algebraic immunity and good nonlinearity for an arbitrary even number of variables. However, the algebraic degree of their constructed n -variable (n > 4) function is always less than the maximum value n − 1. In this paper, by modifying the support of Boolean functions from Mesnager et al.'s construction, we present two new constructions of balanced even-variable rotation symmetric Boolean functions with optimal algebraic immunity as well as higher algebraic degree and nonlinearity. The algebraic degree of Boolean functions in the first construction reaches the maximum value n − 1 if n 2 is odd and n 2 ≠ (2 k + 1) 2 or (2 k + 1) 2 + 2 for integer k , while that of the second construction reaches the maximum value for all n. Moreover, the nonlinearities of Boolean functions in both two constructions are higher than that of Mesnager et al.'s construction. [ABSTRACT FROM AUTHOR]

Dynamic linear functions on the boolean hypercube are functions which assign to each bit a positive weight, but the weights change over time. Throughout optimization, these functions maintain the same global optimum, and never have defecting local optima. Nevertheless, it was recently shown [Lengler, Schaller, FOCI 2019] that the (1 + 1) -Evolutionary Algorithm needs exponential time to find or approximate the optimum for some algorithm configurations. In this experimental paper, we study the effect of larger population sizes for dynamic binval, the extreme form of dynamic linear functions. We find that moderately increased population sizes extend the range of efficient algorithm configurations, and that crossover boosts this positive effect substantially. Remarkably, similar to the static setting of monotone functions in [Lengler, Zou, FOGA 2019], the hardest region of optimization for (μ + 1) -EA is not close the optimum, but far away from it. In contrast, for the (μ + 1) -GA, the region around the optimum is the hardest region in all studied cases.Kindly check and confirm the inserted city name is correctly identified.Correct. [ABSTRACT FROM AUTHOR]

Recently, several interesting constructions of vectorial Boolean functions with the maximum number of bent components (MNBC functions, for short) were proposed. However, many of them have component functions from the completed Maiorana-McFarland class M # . Moreover, no examples of MNBC functions containing component functions provably outside M # are known. In this paper, we classify all MNBC functions in six variables. Based on the analysis of the obtained equivalence classes, we propose several infinite families of MNBC functions with component functions outside the M # class. In particular, two of our new constructions are solutions to the open problem [Bapić et al (eds) Proceedings of the twelfth international workshop on coding and cryptography, 2022, Item 1., p. 9]. [ABSTRACT FROM AUTHOR]

Legal text retrieval serves as a key component in a wide range of legal text processing tasks such as legal question answering, legal case entailment, and statute law retrieval. The performance of legal text retrieval depends, to a large extent, on the representation of text, both query and legal documents. Based on good representations, a legal text retrieval model can effectively match the query to its relevant documents. Because legal documents often contain long articles and only some parts are relevant to queries, it is quite a challenge for existing models to represent such documents. In this paper, we study the use of attentive neural network-based text representation for statute law document retrieval. We propose a general approach using deep neural networks with attention mechanisms. Based on it, we develop two hierarchical architectures with sparse attention to represent long sentences and articles, and we name them Attentive CNN and Paraformer. The methods are evaluated on datasets of different sizes and characteristics in English, Japanese, and Vietnamese. Experimental results show that: (i) Attentive neural methods substantially outperform non-neural methods in terms of retrieval performance across datasets and languages; (ii) Pretrained transformer-based models achieve better accuracy on small datasets at the cost of high computational complexity while lighter weight Attentive CNN achieves better accuracy on large datasets; and (iii) Our proposed Paraformer outperforms state-of-the-art methods on COLIEE dataset, achieving the highest recall and F2 scores in the top-N retrieval task. [ABSTRACT FROM AUTHOR]

Biological systems are noisy by nature. This aspect is reflected in our experimental measurements and should be reflected in the models we build to better understand these systems. Noise can be especially consequential when trying to interpret specific regulatory interactions, i.e. regulatory network edges. In this paper, we propose a method to explicitly encode edge-noise in Boolean dynamical systems by probabilistic edge-weight (PEW) operators. PEW operators have two important features: first, they introduce a form of edge-weight into Boolean models through the noise, second, the noise is dependent on the dynamical state of the system, which enables more biologically meaningful modeling choices. Moreover, we offer a simple-to-use implementation in the already well-established BooleanNet framework. In two application cases, we show how the introduction of just a few PEW operators in Boolean models can fine-tune the emergent dynamics and increase the accuracy of qualitative predictions. This includes fine-tuning interactions which cause non-biological behaviors when switching between asynchronous and synchronous update schemes in dynamical simulations. Moreover, PEW operators also open the way to encode more exotic cellular dynamics, such as cellular learning, and to implementing edge-weights for regulatory networks inferred from omics data. Author summary: The life and decision-making of cells is regulated by a complex web of dynamically interacting molecules. The strength and nature of individual interactions is very diverse, and it is especially important to understand such diversity when it comes to defects and disease. For example, the mutation of a protein binding site can critically alter the probability and strength of its interactions with its binding partners. Boolean network models have become an increasingly potent tool for understanding the complex dynamical interactions within cellular regulatory systems, however, there is no straightforward and explicit way to encode weights on individual interactions. In this paper we offer a way to add weights to interactions by simple noise operators which alter the behavior of edges (or groups of edges) in in-silico simulations of Boolean network models. We show with multiple applications that adding just a few PEW (probabilistic edge-weight) operators dramatically improves the biological plausibility of Boolean models and reproduces much more nuanced experimental results. [ABSTRACT FROM AUTHOR]

In this paper, we first introduce a class of quartic Boolean functions. And then, the construction of weightwise perfectly balanced Boolean functions on $ 2^m $ variables are given by modifying the support of the quartic functions, where $ m $ is a positive integer. The algebraic degree, the weightwise nonlinearity, and the algebraic immunity of the newly constructed weightwise perfectly balanced functions are discussed at the end of this paper. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for testing Boolean expressions. It is based on spectral, aka Fourier analysis of Boolean functions which is exploited to generate test inputs. The approach has three important contributions: (i) It generates a relatively small test suite with a high capability of fault detection, (ii) The test suite is prioritized such that expected fault detection time is shorter, (iii) It is entirely mathematical relying on a simple and straightforward formula. The proposed method is formulated and evaluations are performed on both synthetic and real expressions. It is also compared with two common test generation criteria, MC/DC and Minimal MUMCUT. Evaluations show that the test suite generated by the spectral approach is relatively small while expressing the capability of a better and quicker fault detection. The approach presented in this paper provides a useful insight into how spectral/Fourier analysis of Boolean functions can be exploited in software testing. [ABSTRACT FROM AUTHOR]

A Boolean function in $ n $ variables is 2-rotation symmetric if it is invariant under even powers of $ \rho(x_1, \ldots, x_n) = (x_2, \ldots, x_n, x_1) $, but not under the first power (ordinary rotation symmetry); we call such a function a 2-function. A 2-function is called monomial rotation symmetric (MRS) if it is generated by applying powers of $ \rho^2 $ to a single monomial. If the quartic MRS 2-function in $ 2n $ variables has a monomial $ x_1 x_q x_r x_s $, then we use the notation $ {2-}(1,q,r,s)_{2n} $ for the function. A detailed theory of equivalence of quartic MRS 2-functions in $ 2n $ variables was given in a $ 2020 $ paper by Cusick, Cheon and Dougan. This theory divides naturally into two classes, called $ mf1 $ and $ mf2 $ in the paper. After describing the equivalence classes, the second major problem is giving details of the linear recursions that the Hamming weights for any sequence of functions $ {2-}(1,q,r,s)_{2n} $ (with $ q < r < s, $ say), $ n = s, s+1, \ldots $ can be shown to satisfy. This problem was solved for the $ mf1 $ case only in the $ 2020 $ paper. Using new ideas about 'short' functions, Cusick and Cheon found formulas for the $ mf2 $ weights in a $ 2021 $ sequel to the $ 2020 $ paper. In this paper the actual recursions for the weights in the $ mf2 $ case are determined. [ABSTRACT FROM AUTHOR]

Graph states are present in quantum information and found applications ranging from quantum network protocols (like secret sharing) to measurement based quantum computing. In this paper, we extend the notion of graph states, which can be regarded as pure quantum graph states, or as homogeneous quadratic Boolean functions associated to simple undirected graphs, to quantum states based on mixed graphs (graphs which allow both directed and undirected edges), obtaining mixed quantum states, which are defined by matrices associated to the measurement of homogeneous quadratic Boolean functions in some (ancillary) variables. In our main result, we describe the extended graph state as the sum of terms of a commutative subgroup of the stabilizer group of the corresponding mixed graph with the edges' directions reversed. [ABSTRACT FROM AUTHOR]

We address the problem of reducing the size of Craig’s interpolants (ITPs) used in SAT-based model checking. Whereas it is well known that ITPs are highly redundant, their compaction is typically tackled by reducing the proof graph and/or by exploiting standard logic synthesis techniques. Furthermore, strengthening and weakening have been studied as options to control ITP quality. In this paper, we propose an SAT-based ITP weakening/strengthening technique, for ITP compaction, where the UNSAT core extracted from an additional SAT query is used to obtain a gate-level abstraction of the ITP. The abstraction introduces fresh new variables at gate cuts that must be quantified out in order to obtain a valid ITP. We show how to efficiently quantify them out, by working on a negation normal form representation of the circuit. This paper includes an experimental evaluation, showing the benefits of the proposed approach, on a set of benchmark ITPs arising from hardware model checking problems. 1 Some of the techniques here described were presented in a preliminary version at FMCAD’16. [ABSTRACT FROM AUTHOR]

The variable-length source coding problem allowing the error probability up to some constant is considered for general sources. In this problem, the optimum mean codeword length of variable-length codes has already been determined. On the other hand, in this paper, we focus on the overflow (or excess codeword length) probability instead of the mean codeword length. The infimum of overflow thresholds under the constraint that both of the error probability and the overflow probability are smaller than or equal to some constant is called the optimum overflow threshold. In this paper, we first derive finite-length upper and lower bounds on these probabilities so as to analyze the optimum overflow thresholds. Then, by using these bounds, we determine the general formula of the optimum overflow thresholds in both of the first-order and second-order forms. Next, we consider another expression of the derived general formula so as to reveal the relationship with the optimum coding rate in the fixed-length source coding problem. Finally, we apply the general formula derived in this paper to the case of stationary memoryless sources. [ABSTRACT FROM AUTHOR]

Let m be an even positive integer. A Boolean bent function ƒ on F2m-1 × F2 is called a cyclic bent function if for any a ≠ b ∈ F2m-1 and ε ∈ F2, ƒ(ax1, x2)+ ƒ(bx1, x2 + ε) is always bent, where x1 ∈ F2m-1, x2 ∈ F2. Cyclic bent functions look extremely rare. This paper focuses on cyclic bent functions on F2m-1 × F2 and their applications. The first objective of this paper is to establish a link between quadratic cyclic bent functions and a special type of prequasifields, and construct a class of quadratic cyclic bent functions from the Kantor-Williams prequasifields. The second objective is to use cyclic bent functions to construct families of optimal sequences. The results of this paper show that cyclic bent functions have nice applications in several fields such as coding theory, symmetric cryptography, and CDMA communication. [ABSTRACT FROM AUTHOR]

In this paper, based on the theory of -valued quadratic forms we propose several classes of generalized Boolean bent functions over , and new families of codebooks are constructed from these functions. The codebooks constructed in this paper are nearly optimal with respect to the Welch bound, and their parameters are new. Furthermore, some Boolean bent functions are also derived. [ABSTRACT FROM AUTHOR]

The solution of nonlinear Boolean equations in a binary field plays a crucial part in cryptanalysis and computational mathematics. To speed up the process of solving Boolean equations is an urgent task that needs to be addressed. In this paper, we propose a method for solving Boolean equations based on the Grover algorithm combined with preprocessing using classical algorithms, optimizing the quantum circuit for solving the equations, and implementing the automatic generation of quantum circuits. The method first converted Boolean equations into Boolean expressions to construct the oracle in the Grover algorithm. The quantum circuit was emulated based on the IBM Qiskit framework and then simulated the Grover algorithm on this basis. Finally, the solution of the Boolean equation was implemented. The experimental results proved the feasibility of using the Grover algorithm to solve nonlinear Boolean equations in a binary field, and the correct answer was successfully found under the conditions that the search space was 221 and three G iterations were used. The method in this paper increases the solving scale and solving speed of Boolean equations and enlarges the application area of the Grover algorithm. [ABSTRACT FROM AUTHOR]

The goal of this study is to improve an existing encryption algorithm using a faster convergent iterative method, providing secure convergence of the corresponding numerical scheme, and improved security by a using rotation-translation formula [[12]]. 10.3390/sym12040506 11 Zhang G., Ding W., Li L. Image encryption algorithm based on tent delay-sine cascade with logistic map. Furthermore, the cross-correlation coefficient, phase space diagram, and sample entropy algorithm prove that the 2D-ICSM has a high sensitivity to initial values and parameters, extreme complexity performance, and a much larger hyperchaotic range than existing maps. The simulation results show that after encryption using the proposed algorithm, the entropy of the cipher is extremely close to the ideal value of eight, and the correlation coefficients between the pixels are lower than 0.01, thus the algorithm can resist statistical attacks. [Extracted from the article]

Let (0 , a 1 , ... , a d − 1) n denote the function f n (x 0 , x 1 , ... , x n − 1) of degree d in n variables generated by the monomial x 0 x a 1 ⋯ x a d − 1 and having the property that f n is invariant under cyclic permutations of the variables. Such a function f n is called monomial rotation symmetric (MRS). Much of this paper extends the work on quadratic MRS functions in a 2020 paper of the authors to the case of binomial RS functions, that is sums of two quadratic MRS functions. There are also some results for the sum of any number of quadratic MRS functions. [ABSTRACT FROM AUTHOR]

In this paper, we study the class of those Boolean functions that are coset leaders of first order Reed-Muller codes. We study their properties and try to better understand their structure (which seems complex), by studying operations on Boolean functions that can provide coset leaders (we show that these operations all provide coset leaders when the operands are coset leaders, and that some can even produce coset leaders without the operands being coset leaders). We characterize those coset leaders that belong to the well known classes of direct sums of monomial Boolean functions and Maiorana-McFarland functions. Since all the functions of Hamming weight at most 2 n - 2 are automatically coset leaders, we are interested in constructing infinite classes of coset leaders having possibly Hamming weight larger than 2 n - 2 . [ABSTRACT FROM AUTHOR]

Encoding a dictionary into another representation means that all the words can be stored in the dictionary in a more efficient way. In this way, we can complete common operations in dictionaries, such as (1) searching for a word in the dictionary, (2) adding some words to the dictionary, and (3) removing some words from the dictionary, in a shorter time. Binary decision diagrams (BDDs) are one of the most famous representations of such encoding and are widely popular due to their excellent properties. Recently, some people have proposed encoding dictionaries into BDDs and some variants of BDDs and showed that it is feasible. Hence, we further investigate the topic of encoding dictionaries into decision diagrams. Tagged sentential decision diagrams (TSDDs), as one of these variants based on structured decomposition, exploit both the standard and zero-suppressed trimming rules. In this paper, we first introduce how to use Boolean functions to represent dictionary files and then design an algorithm that encodes dictionaries into TSDDs with the help of tries and a decoding algorithm that restores TSDDs to dictionaries. We utilize the help of tries in the encoding algorithm, which greatly accelerates the encoding process. Considering that TSDDs integrate two trimming rules, we believe that using TSDDs to represent dictionaries would be more effective, and the experiments also show this. [ABSTRACT FROM AUTHOR]

The Quantum-dot Cellular Automata (QCA), an emerging technology, is observed to be the most viable solution to current CMOS. It is capable of finding solutions to challenges, like high power consumptionand device density. The elementary logic primitives are the majority gate, inverter and wire. In QCA, two different event cell orientations for the realisation of the inverter are available, where the diagonally oriented structure (DOS) is mostly utilised in logic synthesis. However, considering the cell misalignment and displacement, the DOS prevails with a more stable polarised output. But the use of DOS increases cell count which increases the area of the circuit. So, it is desirable to minimise the inverter in a circuit due to the non-availability of the simple logic unit of the inverter. In this paper, two algorithms are proposed for the synthesis of cost-efficient QCA circuits from any boolean function to minimize logic primitives. The proposed role-based mechanism for boolean function synthesis results in the reduction of inverter gate, circuit size, QCA cost and power dissipation. The efficiency of the proposed algorithms has been verified with the realization of standard functions, adders and symmetric functions. A significant improvement in inverter reduction has been reported. [ABSTRACT FROM AUTHOR]

In this paper, we study quantum Ordered Binary Decision Diagrams(OBDD ) model; it is a restricted version of read-once quantum branching programs, with respect to "width" complexity. It is known that the maximal gap between deterministic and quantum complexities is exponential. But there are few examples of functions with such a gap. We present a new technique ("reordering") for proving lower bounds and upper bounds for OBDD with an arbitrary order of input variables if we have similar bounds for the natural order. Using this transformation, we construct a total function REQ such that the deterministic OBDD complexity of it is at least 2 Ω (n / log n) , and the quantum OBDD complexity of it is at most O (n 2 / log n) . It is the biggest known gap for explicit functions not representable by OBDD s of a linear width. Another function(shifted equality function) allows us to obtain a gap 2 Ω (n) vs O (n 2) . Moreover, we prove the bounded error quantum and probabilistic OBDD width hierarchies for complexity classes of Boolean functions. Additionally, using "reordering" method we extend a hierarchy for read-k-times Ordered Binary Decision Diagrams ( k - OBDD ) of polynomial width, for k = o (n / log 3 n) . We prove a similar hierarchy for bounded error probabilistic k - OBDD s of polynomial, superpolynomial and subexponential width. The extended abstract of this work was presented on International Computer Science Symposium in Russia, CSR 2017, Kazan, Russia, June 8 – 12, 2017 Khadiev and Khadieva (2017) [ABSTRACT FROM AUTHOR]

We address the problem of reducing the size of Craig’s interpolants used in SAT-based model checking. Craig’s interpolants are AND-OR circuits, generated by post-processing refutation proofs of SAT solvers. Being highly redundant, their compaction is typically tackled by reducing the proof graph and/or by exploiting standard logic synthesis techniques. In this paper, we propose a set of ad-hoc logic synthesis functions that, revisiting known logic synthesis approaches, specifically address speed and scalability. Though general and not restricted to interpolants, these techniques target the main sources of redundancy in combinational circuits. This paper includes an experimental evaluation, showing the benefits of the proposed techniques, on a set of benchmark interpolants arising from hardware model checking problems. [ABSTRACT FROM AUTHOR]

Zero correlation zone (ZCZ) sequence sets and Golay complementary sets (GCSs) have different correlation properties and hence have different engineering applications. A number of constructions of ZCZ sequence sets and GCSs have been proposed, respectively, in the literature. In addition, some ZCZ sequence sets can be constructed from mutually orthogonal GCSs. In this paper, the relationship between GCSs and ZCZ sets is discovered further. We propose a new type of sequence sets which are ZCZ sequence sets and also GCSs. They are called the Golay-ZCZ sequence sets in this paper. Therefore, they have low peak-to-average power ratios when employed in OFDM systems due to the good autocorrelation properties of GCSs. Besides, the Golay-ZCZ sets possess zero autocorrelations and cross-correlations within their ZCZ and hence have the potential application to synchronization. Furthermore, a construction of Golay-ZCZ sequence family with flexible set sizes, various sequence lengths, and large ZCZ widths is proposed in this paper. [ABSTRACT FROM AUTHOR]

As an optimal combinatorial object, zero-difference balanced (ZDB) functions introduced by Ding in 2008, are a generalization of the well-known perfect nonlinear functions. ZDB functions have received much attention in recent years due to its important applications in coding theory and sequence design. One objective of this paper is to present a construction of ZDB functions based on a kind of generalized cyclotomy. It generates ZDB functions over cyclic group with new parameters which can not be produced by earlier constructions. Another objective of this paper is to employ these ZDB functions to obtain at the same time: 1) optimal constant-composition codes; 2) perfect difference systems of sets; and 3) optimal frequency-hopping sequences, all with new parameters. [ABSTRACT FROM PUBLISHER]

A classical method of constructing a linear code over \mathrm GF(q) with a $t$ -design is to use the incidence matrix of the $t$ -design as a generator matrix over \mathrm GF(q) of the code. This approach has been extensively investigated in the literature. In this paper, a different method of constructing linear codes using specific classes of 2-designs is studied, and linear codes with a few weights are obtained from almost difference sets, difference sets, and a type of 2-designs associated to semibent functions. Two families of the codes obtained in this paper are optimal. The linear codes presented in this paper have applications in secret sharing and authentication schemes, in addition to their applications in consumer electronics, communication and data storage systems. A coding-theory approach to the characterization of highly nonlinear Boolean functions is presented. [ABSTRACT FROM AUTHOR]

The need for computation speed is ever increasing. A promising solution for this requirement is parallel computing but the degree of parallelism in electronic computers is limited due to the physical and technological barriers. DNA computing proposes a fascinating level of parallelism that can be utilized to overcome this problem. This paper presents a new computational model and the corresponding design methodology using the massive parallelism of DNA computing. We proposed an automatic design algorithm to synthesis the logic functions on the DNA strands with the maximum degree of parallelism. In the proposed model, billions of DNA strands are utilized to compute the elements of the Boolean function concurrently to reach an extraordinary level of parallelism. Experimental and analytic results prove the feasibility and efficiency of the proposed method. Moreover, analyses and results show that a delay of a circuit in this method is independent of the complexity of the function and each Boolean function can be computed with O(1) time complexity. [ABSTRACT FROM AUTHOR]

This paper describes a purely functional library for computing level- p -complexity of Boolean functions and applies it to two-level iterated majority. Boolean functions are simply functions from n bits to one bit, and they can describe digital circuits, voting systems, etc. An example of a Boolean function is majority, which returns the value that has majority among the n input bits for odd n. The complexity of a Boolean function f measures the cost of evaluating it: how many bits of the input are needed to be certain about the result of f. There are many competing complexity measures, but we focus on level- p -complexity — a function of the probability p that a bit is 1. The level- p -complexity $D_p(f)$ is the minimum expected cost when the input bits are independent and identically distributed with Bernoulli(p) distribution. We specify the problem as choosing the minimum expected cost of all possible decision trees — which directly translates to a clearly correct, but very inefficient implementation. The library uses thinning and memoization for efficiency and type classes for separation of concerns. The complexity is represented using (sets of) polynomials, and the order relation used for thinning is implemented using polynomial factorization and root counting. Finally, we compute the complexity for two-level iterated majority and improve on an earlier result by J. Jansson. [ABSTRACT FROM AUTHOR]

Decomposition is a technology-independent process, in which a large complex function is broken into smaller, less complex functions. The costs of two-level or factored-form representations (cubes and literals) are used in most decomposition methods, as they have a high correlation with the area of cell-based designs. However, this correlation is weaker for field-programmable gate arrays (FPGAs) based on look-up tables. Furthermore, local optimizations have limited power due to the structural bias of the circuit descriptions. This paper tries to reduce the structural biasing by remapping the look-up table network and decomposing the derived functions using the support as cost function. The proposed method improves the FPGA mapping results of a commercial tool for the 20 largest MCNC benchmarks, with gains of 28% in delay plus 18% in area when targeting delay, and a reduction of 28% in area plus 14% in delay with area as cost function. Results with 23% less area and 6% less delay are obtained after physical synthesis (post place-and-route). Moreover, 12 of the best known results for delay (and 3 for area) of the EPFL benchmarks are improved. [ABSTRACT FROM AUTHOR]

This paper presents a method for generating optimum multi-level implementations of Boolean functions based on Satisfiability (SAT) and Pseudo-Boolean Optimization (PBO) problems solving. The method is able to generate one or enumerate all optimum implementations, while the allowed target gate types and gates costs can be arbitrarily specified. Polymorphic circuits represent a newly emerging computation paradigm, where one hardware structure is capable of performing two or more different intended functions, depending on instantaneous conditions in the target operating environment. In this paper we propose the first method ever, generating provably size-optimal polymorphic circuits. Scalability and feasibility of the method are documented by providing experimental results for all NPN-equivalence classes of four-input functions implemented in AND–Inverter and AND–XOR–Inverter logics without polymorphic behavior support being used and for all pairs of NPN–equivalence classes of three-input functions for polymorphic circuits. Finally, several smaller benchmark circuits were synthesized optimally, both in standard and polymorphic logics. [ABSTRACT FROM AUTHOR]

Boolean functions with high algebraic immunity are important cryptographic primitives in some stream ciphers. In this paper, two methodologies for constructing minimal binary codes from sets, Boolean functions and vectorial Boolean functions with high algebraic immunity, are proposed. More precisely, a general construction of new minimal codes using minimal codes contained in Reed-Muller codes and sets without nonzero low degree annihilators is presented. The other construction allows us to yield minimal codes from certain subcodes of Reed-Muller codes and vectorial Boolean functions with high algebraic immunity. Via these general constructions, infinite families of minimal binary linear codes of dimension $m$ and length less than or equal to $m(m+1)/2$ are obtained. Besides, a lower bound on the minimum distance of the proposed minimal linear codes is established. Conjectures and open problems are also presented. The results of this paper show that Boolean functions with high algebraic immunity have nice applications in several fields additionally to symmetric cryptography, such as coding theory and secret sharing schemes. [ABSTRACT FROM AUTHOR]

Future Industry 4.0 scenarios are characterized by seamless integration between computational and physical processes. To achieve this objective, dense platforms made of small sensing nodes and other resource constraint devices are ubiquitously deployed. All these devices have a limited number of computational resources, just enough to perform the simple operation they are in charge of. The remaining operations are delegated to powerful gateways that manage sensing nodes, but resources are never unlimited, and as more and more devices are deployed on Industry 4.0 platforms, gateways present more problems to handle massive machine-type communications. Although the problems are diverse, those related to security are especially critical. To enable sensing nodes to establish secure communications, several semiconductor companies are currently promoting a new generation of devices based on Physical Unclonable Functions, whose usage grows every year in many real industrial scenarios. Those hardware devices do not consume any computational resource but force the gateway to keep large key-value catalogues for each individual node. In this context, memory usage is not scalable and processing delays increase exponentially with each new node on the platform. In this paper, we address this challenge through predictor-corrector models, representing the key-value catalogues. Models are mathematically complex, but we argue that they consume less computational resources than current approaches. The lightweight models are based on complex functions managed as Laurent series, cubic spline interpolations, and Boolean functions also developed as series. Unknown parameters in these models are predicted, and eventually corrected to calculate the output value for each given key. The initial parameters are based on the Kane Yee formula. An experimental analysis and a performance evaluation are provided in the experimental section, showing that the proposed approach causes a significant reduction in the resource consumption. [ABSTRACT FROM AUTHOR]