Quantum computing has been a relatively new research area in the physics and computer engineering combined fields since Feynman proposed an abstract model of quantum computer in 1980s. After Shor presented the algorithm for practical implementation of quantum computing in 1994, the research of quantum computing has grown quickly. However, there is a gap between the academic research and the application to industry. This survey paper attempts to fill the gap by presenting the application to the industrial needs specifically to the needs of the aerospace industry.
Quantum computing has been a relatively new research area in the physics and computer engineering combined fields since Feynman proposed an abstract model of quantum computer in 1980s. After Shor presented the algorithm for practical implementation of quantum computing in 1994, the research of quantum computing has grown quickly. However, there is a gap between the academic research and the application to industry. This survey paper attempts to fill the gap by presenting the application to the industrial needs specifically to the needs of the aerospace industry.
Quantum computers have the potential to be transformational for the aerospace industry. However, many aerospace organizations have not considered how this technology will impact their enterprises. Quantum computers are expected to have a greater effect than simply reduce computational runtimes. However, understanding their impact not only requires understanding what quantum computers are capable and incapable of, but can also require re-examining well-established workflows and questioning long-held assumptions. Quantum computation is currently in a stage of rapid maturation. In 2023, a quantum computer demonstrated a computation that goes beyond the capabilities of brute force classical computation. Building upon this, the hardware is rapidly progressing with qubit counts increasing and gate fidelities improving such that a quantum error corrected quantum computer has been announced to arrive in 2029. In parallel, algorithm advancements have decreased hardware requirements, in some cases by orders of magnitude. The result is that first applications are expected in the next few years, and aerospace organizations are advised to become quantum ready now. In the Spring of 2024, representatives from around the US aerospace industry gathered to identify how the expected power of quantum computers may impact the aerospace industry. The outcomes and recommendations from the workshop are summarized in this paper. The paper discusses the current status and trends in quantum computing, the four main application areas of quantum computing (quantum machine learning, search & optimization, chemical & material simulation, and linear algebra), illustrative use case examples from each area, and how these map to challenges in the aerospace industry.
Despite the significant scientific and engineering hurdles in advancing quantum computers, notable strides are being made toward utilizing this technology in commercial domains. Quantum computers are projected to exceed the computational power of classical computers within the next decade, potentially revolutionizing various industries. This study explores a range of fields that have already begun integrating quantum hardware. By presenting these as examples of combinatorial problems, we demonstrate their applications across three key sectors: cryptography, material science, and Machine Learning. Further, we will conduct a survey on various industries and companies to identify the broader usage of quantum computing in their manufacturing. The survey will analyze the diverse potential applications and current advantages of quantum hardware and algorithms. The results will help further researchers identify and segment the companies and understand the rapid application of quantum computing.
This paper is a general literature survey of recent research and publications that will attempt to answer the question: “What are the uses of quantum computing in aerospace systems.” Quantum computing is still in the very early stages of development and appears to be at a technology readiness level where subcomponents are being tested in a relevant environment. For example, NASA’s Jet Propulsion Laboratory (JPL) is planning to send an experiment to the International Space Station that could lead the way to a quantum global network. It will test communication technologies in the harsh environment of space that could enable two quantum computers to securely connect with each other no matter where they were. This paper will reference JPL’s experiment1.and attempt to summarize quantum computing aerospace applications. The use of machine learning algorithms appears to be one of the most significant enablers of quantum computing. Quantum cryptography and cryptanalysis seem to be the most important applications, among many others since our national security and future lunar exploration competitiveness may depend on it.
Quantum computing is rapidly becoming an invaluable component of aerospace analysis. Selecting a programing language that enables efficient quantum algorithm development and integrates seamlessly with classical simulation tools is essential for translating these capabilities into practice. This paper is a general literature survey of recent research and publications that will attempt to answer the question: What may be appropriate quantum computing software programming language(s) for aerospace applications? What quantum programming language(s) would be suitable for scientific and engineering calculations as FORTRAN was for classical computing? Quantum computing has the potential to make complex aerospace simulations like Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), material, and boundary layer analysis much faster and more efficient. Successful quantum enhancement work has already been completed towards secure quantum space networks, space weather detection and early warning alerts, satellite image processing, and flight path optimization. There is a plethora (thirty-six plus) of quantum computing languages and toolkits today. How do they deal effectively with the unique characteristics of quantum computing like entanglement and the no cloning theory? The differences between Artificial Intelligence (AI) and quantum computing will be discussed and a survey of the current quantum computing software and tools will be presented. A framework for choosing an appropriate quantum programming language for aerospace applications is also provided. Findings from the literature show Python used with the Qiskit platform could be the most useful for aerospace applications.
Quantum technology is developing so quickly, that there has been intense research for quantum technologies in both academia and industry in recent years.Documents and literature have been created in vast quantities as the capability of quantum computers continues to increase.After an informative introduction and a summary of key achievements and current advancements in the field of quantum computing.The second phase of the quantum revolution known as continuous research and innovation in the hardware, software, and applications of quantum computers further explained.Quantum computing has long theoretical roots, but in recent years, with the development of useful tools and technologies, the research has moved from theory to reality in Quantum Computers, Quantum Networks, Quantum Cryptography, and Quantum Machine Learning.A framework is presented for creating a quantum engineering education program that will satisfy the demands of both academics and research institutions in the world.The Control, electronics, nanofabrication, cryogenic and solid-state technologies, optics, atoms and ions, and a plan for quantum engineering fields that presents an excellent set of opportunities for education research are all used to outline a hands-on training on quantum hardware software and applications.
This research focuses on surveying in an attractive field of quantum computing. The paper begins by highlighting a brief history of quantum mechanics. Major elements of quantum computing such as quantum superposition, quantum tunnelling and qubits are addressed at next from a physics perspective. In addition, various methods and applications of quantum physics are also examined. This paper discusses the power and efficiencies that a quantum computer provides and the basis for these claims. Furthermore, the level of research in quantum computing and it's commercial markets assays to find out the major contributions and developments in the field of quantum computing. The top two leading organisations in quantum computing are picked and reviewed with their up to date contributions. This paper expresses the methods and techniques which are being used by these two organisations to implement a quantum processor and the level of success that has been achieved. This research attempts to log the challenges and limitations that these organisations face in the development of quantum computing. Finally, the research compares quantum model with classical computing model.