The Future of Quantum Computing

Shrinkhala Shinghai, Jyotir Moy Chatterjee

Jeremy J. Ramsden

Ahmet Efe

Abstract— Studies in the literature argue that solving the memory problem of quantum computers (QC) will lead to groundbreaking developments in artificial intelligence algorithms affecting every process, strategy, business, and polic,es. Quantum adaptive algorithms have been widely applied, which improve existing methods by taking advantage of artificial intelligence and quantum computing. Although new developments are achieved with hybrid quantum systems, which aim to have sub-threads made by quantum computers, it cannot be predicted precisely where these studies will reach in the future and what kind of benefits and risks, they involve. In this study, based on the knowledge of contemporary and interdisciplinary literature, the current and potential uses of quantum computers, super artificial intelligence applications, and quantum computing methods on machine learning, whose applications have just begun in the laboratory environment, are examined, and assessed. It is claimed that the hardware disadvantages of quantum computers will disappear, and new quantum applications will be developed in the future. This is a requirement of adaptation to the prevalent usage of IoT in Industry 4.0 and Society 5.0 applications. Therefore, theoretically, and conceptual aspects of AI and quantum computing are evaluated to realize guidance of the miracles of the Prophets that can be discovered in the future.

Jiří Guth Jarkovský, Jayshankar Nath, Björn Pötter +1 more

Earth Observation (EO) satellites generate a growing amount of data every year and highlight the need for scalable algorithms and adequate computational resources. However, the question about how to leverage quantum computing for enhancing the required computational steps is still largely unanswered. The QC4EO study proposes insightful answers and potential solutions to this question. The study has been conducted in the period March 2023 – October 2023 by a consortium led by Forschungszentrum Jülich, with Thales Alenia Space Italy/France, INFN and IQM, and supported by the European Space Agency. The scope of the study covers 12 use cases and a 15-year timeframe, evaluating a potential practical advantage of quantum computing in specific computational tasks and the availability of the required hardware in the near future. This machine roadmap assessment study (WP3) provides a comprehensive overview of existing quantum computing (QC) technologies and assesses their maturity. For each identified technology, we study the current state of the art, assess their risks, and estimate their future development. Based on these assessments, we provide our judgement on current and future quantum technology readiness levels (QTRL) of these platforms and their suitability to different applications in earth observations.

Seiki Akama

AI Trinity Labo

This paper introduces Quantum Future-Trial Computing (QFTC), a new computational paradigm that extends standard quantum computation by exploiting reversible geometric time-evolution. QFTC enables a quantum processor to explore multiple future computational branches, roll back to its initial state without decoherence, and selectively commit only the successful branches. This “try-future then rewind” architecture produces computational capabilities beyond BQP, offering ultra-efficient search, optimization, quantum simulation, and AI-driven parameter selection. The framework formalizes future-trial operators, rollback operators, and commit mechanisms, establishing QFTC as a next-generation model for superclassical computation.