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This document presents a PhD thesis by Cristian Ruican focusing on developing methodologies for the automatic synthesis of quantum circuits through the use of genetic algorithms. It addresses the
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How to fill out Developing Automatic Synthesis Methodologies for Quantum Circuits using Genetic Algorithms

01
Identify the quantum circuit specifications and requirements.
02
Select the appropriate genetic algorithm framework for synthesis.
03
Define the representation of quantum circuits in the chosen framework.
04
Establish the fitness function that evaluates circuit performance.
05
Initialize a population of random quantum circuits.
06
Iteratively apply genetic operations such as selection, crossover, and mutation.
07
Evaluate the fitness of each new generation of circuits.
08
Select the best-performing circuits to form the next generation.
09
Repeat the process until a satisfactory synthesis solution is found.
10
Document and analyze the results of the automatic synthesis.

Who needs Developing Automatic Synthesis Methodologies for Quantum Circuits using Genetic Algorithms?

01
Quantum computing researchers seeking to optimize circuit performance.
02
Developers of quantum algorithms looking for efficient circuit synthesis methods.
03
Academics in the field of quantum information science.
04
Companies investing in quantum technologies for practical applications.
05
Engineers designing quantum hardware that requires optimized circuit structures.
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It refers to the creation of automated processes for generating quantum circuits utilizing genetic algorithms, which are search heuristics inspired by the process of natural selection.
Researchers and developers in the field of quantum computing and algorithm design are typically those who would engage with this methodology.
To engage in this process, one would outline the specific parameters of the quantum circuits to be synthesized, the genetic algorithm approach to be used, and criteria for optimization and evaluation.
The purpose is to enhance the efficiency and effectiveness of quantum circuit design, making it easier to create complex circuits that can solve specific problems in quantum computing.
Reports should include details on the quantum circuits produced, the genetic algorithm parameters, optimization results, and any comparisons with traditional synthesis methods.
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