Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Smart innovation, systems and technologies

Green Qubits: Exploring the Sustainability of Quantum Computing

Teodor Cervinski, Toma Cristian, Mihai Doinea, Marius Florentin Popa

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1007/978-981-95-6136-0_5

Related papers

Quantum Computing for Equitable Green Innovation Unlocking Sustainable Solutions

Muniraju Hullurappa, Sudheer Panyaram

Quantum computing offers unprecedented opportunities to revolutionize equitable green innovation by addressing complex sustainability challenges with enhanced computational power. This chapter explores how quantum algorithms can optimize resource management, improve energy efficiency, and accelerate the adoption of green technologies. By leveraging quantum-based predictive models and optimization techniques, industries can achieve sustainable practices while ensuring equity in resource distribution and access. The chapter also delves into the potential of quantum computing to tackle intricate problems in supply chain sustainability, renewable energy integration, and environmental impact analysis. Challenges such as scalability, accessibility, and ethical considerations are addressed, alongside proposed solutions to overcome these barriers. Real-world use cases and emerging research highlight the transformative potential of quantum computing in fostering a sustainable and inclusive future, bridging the gap between innovation and equity.

Advances in environmental engineering and green technologies book series•Feb 13, 2025•6 citations

Green quantum computers

Gregory D. Scholes

Nature Physics•Jun 1, 2010•31 citations

Exploring the Role of Quantum Computing in Advancing Green Computing Technologies

Safaa Kadhum Hussaine, ‪Noor Aldeen‬‏

The rapid growth of data-intensive applications and cloud computing has significantly increased the energy consumption of modern computing infrastructures, particularly data centers, raising critical sustainability and environmental concerns. Green computing seeks to address these challenges by improving energy efficiency and reducing carbon footprints without sacrificing performance. Quantum computing has emerged as a promising paradigm due to its ability to exploit quantum mechanical principles such as superposition and entanglement to achieve computational speedups beyond classical limits. This paper examines the role of quantum computing in advancing green computing technologies by analyzing its algorithmic capabilities, application domains, and hardware-related energy implications. Key quantum algorithms, including Shor’s algorithm, Grover’s search, the Quantum Approximate Optimization Algorithm (QAOA), and quantum simulation methods, are reviewed with respect to their potential to reduce execution time and energy consumption for computationally intensive tasks such as cryptography, optimization, and system modeling. The study further explores sustainability-oriented applications, including energy systems optimization, materials discovery for renewable technologies, and quantum machine learning for resource forecasting and management. Comparative analysis indicates that quantum approaches may offer substantial energy-efficiency advantages over classical methods as hardware matures. However, significant challenges remain, including qubit decoherence, error correction overhead, cryogenic cooling requirements, and scalability limitations. The paper concludes that continued advances in hybrid quantum–classical architectures and fault-tolerant hardware are essential for realizing quantum computing’s potential contribution to sustainable and energy-efficient computing.

Journal of Sustainable Smart Systems in Education & Environment•May 2, 2026•1 citation

Quantum Computing Quibits and Beyond

Dr. N. Kohila Mr. M.Sakthivel Mrs. V.V. Lakshmi Swathi Mrs. K. Pandi Meena Dr. D. Priyadharsini

•Sep 22, 2026•0 citations

Quantum Computing with Qubits

Samuel L. Braunstein, Arun Kumar Pati

Springer eBooks•Jan 1, 2003•1 citation

Quantum Green Computing for the Next Generation of Renewable Resources

Quantum Green Computing represents a transformative paradigm that merges the power of quantum computational techniques with the principles of sustainability to drive innovation in renewable resource management.This paper investigates the interplay between quantum algorithms, energy-efficient system architectures, and advanced renewable energy technologies-including solar photovoltaics, wind energy systems, and bioenergy solutions.By leveraging the unique capabilities of quantum computing, such as superior optimization, high-dimensional modeling, and rapid problem-solving, the study explores novel strategies for addressing the inherent complexities of renewable energy integration.The research emphasizes three core dimensions: (1) the application of quantum optimization algorithms to enhance grid stability, load balancing, and real-time decision-making; (2) the development of energy-efficient quantum-inspired hardware architectures that align with green computing objectives; and (3) the formulation of predictive and adaptive models for renewable resource allocation using quantum-inspired approaches.Furthermore, the paper highlights case studies that demonstrate how quantum techniques can significantly improve grid management, predictive maintenance of renewable infrastructures, and long-term forecasting of resource availability under dynamic environmental conditions.By critically evaluating these emerging pathways, the study outlines a vision where quantum-enabled sustainability not only reduces carbon emissions but also maximizes energy utilization efficiency.This integration holds the potential to revolutionize the global renewable energy landscape, enabling resilient, lowcarbon ecosystems capable of supporting the growing demands of a sustainable future.

International Research Journal of Modernization in Engineering Technology and Science•Sep 7, 2025•0 citations
Quantum computing offers unprecedented opportunities to revolutionize equitable green innovation by addressing complex sustainability challenges with enhanced computational power. This chapter explores how quantum algorithms can optimize resource management, improve energy efficiency, and accelerate the adoption of green technologies. By leveraging quantum-based predictive models and optimization techniques, industries can achieve sustainable practices while ensuring equity in resource distribution and access. The chapter also delves into the potential of quantum computing to tackle intricate problems in supply chain sustainability, renewable energy integration, and environmental impact analysis. Challenges such as scalability, accessibility, and ethical considerations are addressed, alongside proposed solutions to overcome these barriers. Real-world use cases and emerging research highlight the transformative potential of quantum computing in fostering a sustainable and inclusive future, bridging the gap between innovation and equity.
The rapid growth of data-intensive applications and cloud computing has significantly increased the energy consumption of modern computing infrastructures, particularly data centers, raising critical sustainability and environmental concerns. Green computing seeks to address these challenges by improving energy efficiency and reducing carbon footprints without sacrificing performance. Quantum computing has emerged as a promising paradigm due to its ability to exploit quantum mechanical principles such as superposition and entanglement to achieve computational speedups beyond classical limits. This paper examines the role of quantum computing in advancing green computing technologies by analyzing its algorithmic capabilities, application domains, and hardware-related energy implications. Key quantum algorithms, including Shor’s algorithm, Grover’s search, the Quantum Approximate Optimization Algorithm (QAOA), and quantum simulation methods, are reviewed with respect to their potential to reduce execution time and energy consumption for computationally intensive tasks such as cryptography, optimization, and system modeling. The study further explores sustainability-oriented applications, including energy systems optimization, materials discovery for renewable technologies, and quantum machine learning for resource forecasting and management. Comparative analysis indicates that quantum approaches may offer substantial energy-efficiency advantages over classical methods as hardware matures. However, significant challenges remain, including qubit decoherence, error correction overhead, cryogenic cooling requirements, and scalability limitations. The paper concludes that continued advances in hybrid quantum–classical architectures and fault-tolerant hardware are essential for realizing quantum computing’s potential contribution to sustainable and energy-efficient computing.
Quantum Green Computing represents a transformative paradigm that merges the power of quantum computational techniques with the principles of sustainability to drive innovation in renewable resource management.This paper investigates the interplay between quantum algorithms, energy-efficient system architectures, and advanced renewable energy technologies-including solar photovoltaics, wind energy systems, and bioenergy solutions.By leveraging the unique capabilities of quantum computing, such as superior optimization, high-dimensional modeling, and rapid problem-solving, the study explores novel strategies for addressing the inherent complexities of renewable energy integration.The research emphasizes three core dimensions: (1) the application of quantum optimization algorithms to enhance grid stability, load balancing, and real-time decision-making; (2) the development of energy-efficient quantum-inspired hardware architectures that align with green computing objectives; and (3) the formulation of predictive and adaptive models for renewable resource allocation using quantum-inspired approaches.Furthermore, the paper highlights case studies that demonstrate how quantum techniques can significantly improve grid management, predictive maintenance of renewable infrastructures, and long-term forecasting of resource availability under dynamic environmental conditions.By critically evaluating these emerging pathways, the study outlines a vision where quantum-enabled sustainability not only reduces carbon emissions but also maximizes energy utilization efficiency.This integration holds the potential to revolutionize the global renewable energy landscape, enabling resilient, lowcarbon ecosystems capable of supporting the growing demands of a sustainable future.