(untitled) (American Journal of Language, Literacy and Learning in STEM Education (2993-2769), 2024)
Complex numbers, which are essential in several branches of mathematics and engineering, provide distinctive difficulties and possibilities for study. This study examines the use of numerical theory in analysing complicated numbers, offering valuable insights into their characteristics and behaviours across many situations. Through the use of numerical techniques, our objective is to enhance comprehension of intricate number systems, namely in the resolution of equations, examination of functions, and representation of real-world occurrences. First, we will examine the fundamental characteristics of complex numbers, which include their depiction in Cartesian and polar forms, as well as their operations, such as addition, multiplication, and complex conjugation. The study subsequently explores more sophisticated subjects, such as the origins of complex numbers, and the use of numerical methods to estimate these origins. This research mostly centres on using numerical methods to solve intricate problems. We analyse the convergence qualities and computing efficiency of approaches such as the Newton-Raphson method, iterative refinement, and the Durand-Kerner method. The study also examines the use of these techniques using contemporary computer tools and software, emphasising its tangible applications in the fields of engineering and physics. In addition, we examine the numerical stability and error analysis in the realm of complex number calculations. This is an examination of problems related to floating-point arithmetic and the techniques used to reduce numerical imprecisions. Emphasis is placed on the condition numbers of complex functions and their influence on the resilience of numerical solutions. The practical importance of numerical analysis of complex numbers is shown by examining applications in engineering, such as signal processing and control systems. Case studies exemplify the use of numerical approaches in solving real-world situations that include intricate variables, highlighting the adaptability and efficacy of these techniques.