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.
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.
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.
Quantum computing has moved from a theoretical curiosity to a strategic technological priority for governments, hyperscale technology companies, and a fast-growing ecosystem of specialized start-ups. This survey provides a comprehensive, self-contained overview of the field as it stands in 2026. We first lay out the physical and mathematical foundations of quantum computation, superposition, entanglement, interference, and measurement, and contrast them systematically with classical computing. We then survey the competing hardware modalities (superconducting, trapped-ion, photonic, neutral-atom, topological, and spin qubits) and the logic gates and circuit model that operate on them, before reviewing the canonical quantum algorithms that motivate the field. We classify the major computing paradigms (gate-based, annealing, adiabatic, measurement-based, and topological), and examine the current state of the market, the national strategies of leading countries, and the roles played by IBM, Google, Microsoft, Amazon, NVIDIA, and a cohort of pure-play companies. Dedicated sections map undergraduate and graduate education pathways, including specific universities offering quantum-focused degrees, the domains in which quantum computers are expected to create value, and the career paths now opening in the field. We close with an explicit three-phase roadmap \qtoday{}, \qtomorrow{}, and the \qfuture{} and a candid discussion of the open scientific and engineering problems that stand between the present noisy intermediate-scale quantum (NISQ) era and a fault-tolerant, utility-scale quantum computing industry.
The digital ecosystem continues to expand around the world and is revolutionising the way markets are researched. Indeed, consumer experiences are advertised and disseminated through so many channels and media that it has become a major challenge for researchers and marketing practitioners to collect, process and generate valuable information to support strategic and operational decisions. In this article, the authors explore how advances in quantum computing, which can be used to process huge amounts of data quickly and accurately, could offer an unprecedented opportunity for researchers to address the challenges of the digital ecosystem. Three studies are presented to define the state of the art and future expectations of quantum computing in market research and business. By means of a bibliometric analysis of 209 publications and a content analysis of the 30 highest-impact articles, we describe the present landscape, and also forecast the future with the help of in-depth interviews with eight experts. The findings reveal that the US and China are at the forefront of scientific development, but the contributions from four other countries (India, the UK, Canada and Spain) are also in double figures. However, graphical analysis identifies four poles of development: the US orbit, which includes Canada and Spain; the Chinese orbit, which includes India; the UK orbit; and the Australian orbit. In terms of expectations, the experts agree on the opportunities offered by quantum computing, but there is less consensus as to how long it will take to develop.
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.