Idempotent Turing Machines

A function f is said to be idempotent if f(f(x)) = f(x) holds whenever f(x) is defined. This paper presents a computation model for idempotent functions, called an idempotent Turing machine. The computation model is necessarily and sufficiently expressive in the sense that not only does it always compute an idempotent function but also every idempotent computable function can be computed by an idempotent Turing machine. Furthermore, a few typical properties of the computation model such as robustness and universality are shown. Our computation model is expected to be a basis of special-purpose (or domain-specific) programming languages in which only but all idempotent computable functions can be defined

Quantum Algorithms for Unate and Binate Covering Problems with Application to Finite State Machine Minimization

Covering problems find applications in many areas of computer science and engineering, such that numerous combinatorial problems can be formulated as covering problems. Combinatorial optimization problems are generally NPhard problems that require an extensive search to find the optimal solution. Exploiting the benefits of quantum computing, we present a quantum oracle design for covering problems, taking advantage of Grover’s search algorithm to achieve quadratic speedup. This paper also discusses applications of the quantum counter in unate covering problems and binate covering problems with some important practical applications, such as finding prime implicants of a Boolean function, implication graphs, and minimization of incompletely specified Finite State Machines

A new operational representation of dependencies in Event Structures

The execution of an event in a complex and distributed system where the dependencies vary during the evolution of the system can be represented in many ways, and one of them is to use Context-Dependent Event structures. Event structures are related to Petri nets. The aim of this paper is to propose what can be the appropriate kind of Petri net corresponding to Context-Dependent Event structures, giving an operational flavour to the dependencies represented in a Context/Dependent Event structure. Dependencies are often operationally represented, in Petri nets, by tokens produced by activities and consumed by others. Here we shift the perspective using contextual arcs to characterize what has happened so far and in this way to describe the dependencies among the various activities

Quantum Search Algorithms for Constraint Satisfaction and Optimization Problems Using Grover\u27s Search and Quantum Walk Algorithms with Advanced Oracle Design

The field of quantum computing has emerged as a powerful tool for solving and optimizing combinatorial optimization problems. To solve many real-world problems with many variables and possible solutions for constraint satisfaction and optimization problems, the required number of qubits of scalable hardware for quantum computing is the bottleneck in the current generation of quantum computers. In this dissertation, we will demonstrate advanced, scalable building blocks for the quantum search algorithms that have been implemented in Grover\u27s search algorithm and the quantum walk algorithm. The scalable building blocks are used to reduce the required number of qubits in the design. The proposed architecture effectively scales and optimizes the number of qubits needed to solve large problems with a limited number of qubits. Thus, scaling and optimizing the number of qubits that can be accommodated in quantum algorithm design directly reflect on performance. Also, accuracy is a key performance metric related to how accurately one can measure quantum states. The search space of quantum search algorithms is traditionally created by using the Hadamard operator to create superposition. However, creating superpositions for problems that do not need all superposition states decreases the accuracy of the measured states. We present an efficient quantum circuit design that the user has control over to create the subspace superposition states for the search space as needed. Using only the subspace states as superposition states of the search space will increase the rate of correct solutions. In this dissertation, we will present the implementation of practical problems for Grover\u27s search algorithm and quantum walk algorithm in logic design, logic puzzles, and machine learning problems such as SAT, MAX-SAT, XOR-SAT, and like SAT problems in EDA, and mining frequent patterns for association rule mining