Quantum technology has garnered considerable attention for its transformative potential across various industries since the early 2000s, precipitating a surge in quantum start-ups and substantial investments worldwide. However, comprehensive research on quantum technology in industries, particularly start-ups in the quantum field, remains limited. This study analyzes a dataset of 1,200 quantum start-ups from 40 countries, specifically focusing on 430 notable active start-ups. The analysis provides a thorough perspective on the industry’s progress, including trends in growth, geographical distribution, industry categorization, and investment patterns. The study categorizes start-ups into five domains: quantum computing, communication, sensing, hardware, and software. The analysis further captures the progress made by ten prominent quantum start-ups, six major technology companies, and quantum consortia regarding their technological innovations and strategic partnerships. We provide a comparative analysis of prior research to identify current conditions and future implications validated by notable studies, focusing on key parameters such as dataset scope, geographical distribution, growth trends, industry categorization, taxonomy, main interests in quantum fields, key players, and ecosystem identification. This approach underscores the dynamic growth of the quantum industry, which will drive future advancements.
Quantum technology has garnered considerable attention for its transformative potential across various industries since the early 2000s, precipitating a surge in quantum start-ups and substantial investments worldwide. However, comprehensive research on quantum technology in industries, particularly start-ups in the quantum field, remains limited. This study analyzes a dataset of 1,200 quantum start-ups from 40 countries, specifically focusing on 430 notable active start-ups. The analysis provides a thorough perspective on the industry’s progress, including trends in growth, geographical distribution, industry categorization, and investment patterns. The study categorizes start-ups into five domains: quantum computing, communication, sensing, hardware, and software. The analysis further captures the progress made by ten prominent quantum start-ups, six major technology companies, and quantum consortia regarding their technological innovations and strategic partnerships. We provide a comparative analysis of prior research to identify current conditions and future implications validated by notable studies, focusing on key parameters such as dataset scope, geographical distribution, growth trends, industry categorization, taxonomy, main interests in quantum fields, key players, and ecosystem identification. This approach underscores the dynamic growth of the quantum industry, which will drive future advancements.
Abstract The second quantum revolution has been producing groundbreaking scientific and technological outputs since the early 2000s; however, the scientific literature on the impact of this revolution on the industry, specifically on start-ups, is limited. In this paper, we present a landscaping study with a gathered dataset of 441 companies from 42 countries that we identify as quantum start-ups, meaning that they mainly focus on quantum technologies (QT) as their primary priority business. We answer the following questions: (1) What are the temporal and geographical distributions of the quantum start-ups? (2) How can we categorize them, and how are these categories populated? (3) Are there any patterns that we can derive from empirical data on trends? We found that more than 92% of these companies have been founded within the last 10 years, and more than 50% of them are located in the US, the UK, and Canada. We categorized the QT start-ups into six fields: (i) complementary technologies, (ii) quantum computing (hardware), (iii) quantum computing (software/application/simulation), (iv) quantum cryptography/communication, (v) quantum sensing and metrology, and (vi) supporting companies, and analyzed the population of each field both for countries, and temporally. Finally, we argue that low levels of quantum start-up activity in a country might be an indicator of a national initiative to be adopted afterwards, which later sees both an increase in the number of start-ups, and a diversification of activity in different QT fields.
This paper presents a formative market assessment of the quantum computing landscape in terms of market readiness of the technologies and the reported levels of investments. The findings presented in this paper are based on a quick scan of available literature combined with a perceptual map of the state-of-play. The paper considers the role of ‘big tech’ companies, the start-up ecosystem, and funding by nation states to identify key implications for the future of quantum computing developments. It highlights that although quantum computing technologies offer scope to revolutionise computing hardware and software, the development of a universal quantum computer will require breakthroughs in several areas including improvements in the quality of qubits, error correction, and demonstrable set of practical applications.
Abstract - Quantum computing has evolved from a physics-driven theoretical concept into a rapidly expanding technological ecosystem encompassing computation, communication, sensing, and security. This paper presents a timeline-based analytical study of this evolution, examining how successive scientific and technological eras shaped the transition from foundational quantum theory to modern noisy intermediate-scale quantum (NISQ) platforms and distributed quantum infrastructures. Rather than offering a purely chronological account, the study evaluates each phase using comparative metrics such as scientific maturity, technological capability, scalability, error resilience, application readiness, and interdisciplinary integration. Beyond technical progress, the paper highlights the growing role of academic institutions in developing foundational methods and workforce capacity, alongside industrial efforts in hardware engineering, cloud-based access, and commercialization. These developments are further reinforced by large-scale public investments through national quantum missions and regional innovation programs, positioning quantum technologies as strategic components of future digital infrastructure. By integrating historical evolution with ecosystem and policy perspectives, this work aims to clarify how scientific constraints, engineering challenges, and institutional drivers collectively shape the current trajectory and future direction of quantum technologies. Key Words: quantum, timeline, global impact, hybrid, evolution
This review article examines the current landscape and recent advancements in quantum computing, emphasizing its roots in quantum mechanics and its growing influence across various computational fields. A thorough analysis of recent literature, including academic publications and industry white papers, highlights significant progress in qubit technologies, quantum algorithms, and the emerging area of quantum networking. The findings indicate enhanced fabrication of quantum processors with higher qubit counts and improved stability and coherence. Additionally, developments in quantum algorithms suggest the potential for considerable speedups compared to classical methods for specific problems. Research into quantum key distribution and the prospect of a quantum internet points to promising advancements in secure communication. However, challenges surrounding error correction, scalability, and the practical implementation of quantum systems remain critical. In conclusion, quantum computing is pivotal, showcasing tangible progress toward solving real-world problems. However, it continues to grapple with substantial hurdles in achieving fully fault-tolerant and scalable systems. Ongoing interdisciplinary research and development efforts are vital to unlocking this technology's transformative potential and addressing its broader societal implications.
This study provides a comprehensive review of the advancements, challenges, and potential implications of quantum computing in the field of big data analytics. The primary objective is to assess how quantum computing paradigms are transforming data processing and analysis, with a focus on their application across various sectors, including healthcare, finance, and scientific research. Employing a systematic literature review and content analysis, the study analyzes peer-reviewed articles, conference proceedings, and academic journals from databases such as PubMed, IEEE Xplore, and ScienceDirect. Key findings reveal that quantum computing, with its advanced algorithms and machine learning techniques, offers significant improvements in computational speed and efficiency over classical computing methods. This technological advancement enables the handling of large and complex datasets, presenting new opportunities in data analytics. However, the study also identifies challenges such as scalability, error correction, and integration with existing systems, which currently limit the full potential of quantum computing in big data analytics. The study concludes with strategic recommendations for industry leaders and policymakers, emphasizing the need for investment in research and development, the establishment of regulatory frameworks, and the development of educational programs to support this emerging field. Future research directions are suggested, focusing on overcoming technological limitations and exploring the long-term implications of quantum computing in various industries. This study contributes valuable insights into the evolving landscape of quantum computing and its significant impact on big data analytics. Keywords: Quantum Computing, Big Data Analytics, Advanced Algorithms, Data Processing.
This survey report presents an overview of the field of quantum computing, focusing on the application of quantum technologies in machine learning, deep learning, image processing, and other related areas. A comprehensive analysis of research papers published between 2005 and 2022 is conducted, covering the latest advancements in quantum-based techniques. The report provides insights into various types of quantum technologies, including quantum machine learning, deep learning, computing, learning, and image processing. The survey encompasses a wide range of topics, such as quantum algorithms, quantum data encoding, quantum feature extraction, quantum neural networks, quantum image recognition, quantum optimization, and quantum simulations. It also identifies the emerging trends, challenges, and future research directions in this rapidly evolving field. The findings of this survey report are expected to provide valuable insights for researchers, practitioners, and decision-makers interested in the field of quantum and its applications in machine learning, deep learning, image processing, and related areas. Comprehensive analysis of the research papers and the identification of the current trends and challenges in this field can serve as a valuable reference for future research and development in the quantum computing domain.