Today, humanity cannot advance without the help of computation. There are still many problems that need resolving that would never be solved without the help of a powerful computer. It is also impossible to build a large enough memory to allow us to solve these complex problems. However, even if we manage to achieve the impossible, with the unprecedented rise of data and the ever-evolving complexity of algorithms, computing the answers in the traditional way would require billions of MWs of power consumption. Not to mention the energy required to cool down the powerful computers from the significant amount of heat they produce. Humanity is quickly reaching the limits of computations that can be currently achieved, raising concerns about the sustainability and environmental impact these power-hungry machines require. Enter quantum computing – the revolutionary technology holding the promise of not only enhancing computational speeds and capabilities but also potentially alleviating the energy burden imposed by traditional computing methods.
Today, humanity cannot advance without the help of computation. There are still many problems that need resolving that would never be solved without the help of a powerful computer. It is also impossible to build a large enough memory to allow us to solve these complex problems. However, even if we manage to achieve the impossible, with the unprecedented rise of data and the ever-evolving complexity of algorithms, computing the answers in the traditional way would require billions of MWs of power consumption. Not to mention the energy required to cool down the powerful computers from the significant amount of heat they produce. Humanity is quickly reaching the limits of computations that can be currently achieved, raising concerns about the sustainability and environmental impact these power-hungry machines require. Enter quantum computing – the revolutionary technology holding the promise of not only enhancing computational speeds and capabilities but also potentially alleviating the energy burden imposed by traditional computing methods.
There are signs that we are approaching a technical revolution that might take humankind’s computational capabilities to a new level. Quantum Computing leverages the principles of quantum mechanics, enabling the computational power to solve specific problems currently intractable for classical computers (e.g., cracking cryptographic keys). Since we are getting to a point where we can no longer build smaller, more powerful, more efficient devices with conventional methodologies, we need to think of new ways for technological progress. The manufacturing of microchips is reaching its limits in the use of traditional architectures. Hence, new and more advanced technologies need to address the challenges of increasing energy consumption and data processing. Connectivity, scalable architectures and concepts like Cloud Computing and Software-as-a-Service have already helped to scale computational-intense applications in the last years and have attracted the interest of IS researchers (e.g., Benlian et al. 2009 ; Benlian et al. 2018 ; Messerschmidt and Hinz 2013 ). Looking ahead to the next generation, computing will comprise technologies that enable high-performance applications far beyond today’s possibilities. One prominent example with a disruptive potential is Quantum Computing. While there are abundant open questions and directions for further developments, researchers in this area have made substantial progress in the last decade, indicating that, after medical imaging, lasers, and superconductors, another quantum-technological innovation might be approaching. We, therefore, intend to provide an overview of the current state of Quantum Computing research and outline how this new technology might stimulate research in Information Systems.
Quantum computing (QC) offers a pathway to solving certain problems that classical computers struggle with, such as advanced drug discovery, secure cryptography, and the design of new materials. While these capabilities are promising, the field also raises serious sustainability concerns. Running quantum processors demands significant amounts of energy, rare elements, and specialized infrastructure, often without clear guidelines for environmentally responsible design. This paper reviews the environmental impact of QC by examining inefficiencies in energy use, cooling, and hardware manufacturing. The findings indicate that integrating renewable energy sources, adopting energy-efficient quantum hardware designs, and developing optimized, low-power quantum algorithms are the most effective strategies for reducing QC’s environmental footprint. In addition, a set of potential sustainability metrics is proposed to guide future research and implementation. The discussion points to one clear message: if sustainability is not embedded into quantum technology now, we risk repeating the environmental mistakes made in past computing revolutions.
Quantum computing represents a revolutionary leap in computational power, leveraging the principles of quantum mechanics to process information in fundamentally new ways. Unlike classical computers, which use bits to represent data as 0s or 1s, quantum computers use quantum bits or qubits, enabling the phenomena of superposition and entanglement to perform complex calculations more efficiently (Nielsen & Chuang, 2010). This article explores the basic principles of quantum computing, the different models and algorithms that have been developed, and the current state of quantum hardware. The power of quantum computing lies in its ability to solve certain types of problems exponentially faster than classical computers. For instance, Shor's algorithm can factorize large integers in polynomial time, posing a significant threat to classical encryption methods (Shor, 1997). Similarly, Grover's algorithm provides a quadratic speedup for unstructured search problems, showcasing the potential for dramatic improvements in database search capabilities (Grover, 1996). These algorithms exemplify how quantum computing can revolutionize fields that rely on complex computations. Quantum hardware, however, is still in its nascent stage, with significant challenges to be overcome. Current quantum computers, such as those developed by IBM and Google, have demonstrated quantum supremacy but are limited by issues of qubit coherence and error rates (Arute et al., 2019). Quantum error correction and the development of more stable qubit technologies are critical areas of ongoing research (Preskill, 2018). Despite these challenges, recent advancements in quantum hardware and algorithms continue to drive the field forward, promising transformative impacts on industries such as cryptography, drug discovery, and artificial intelligence. As quantum computing continues to advance, it holds the promise of solving problems that are currently intractable for classical computers, paving the way for unprecedented technological and scientific advancements (Shor, 1997; Grover, 1996). This article provides a comprehensive overview of the current landscape of quantum computing, discussing its foundational principles, key algorithms, hardware challenges, and potential applications. By understanding these aspects, we can better appreciate the profound implications of quantum computing for the future of technology and science.
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.
Pollution and global warming become more and more of a threat recently, so creative solutions are required to tackle their overwhelming complexity, surpassing the limitations of traditional computational methods. Using the concepts of quantum physics, quantum computing presents a revolutionary approach for solving such environmental problems. With the help of a variety of data in usage from reputable global scientific sources, including world databases, pollution monitoring networks, and climate models in addition, the current scientific paper explores the quickly developing potential of quantum computing to reduce pollution and global warming. The complexities of quantum algorithms are object of our exploration, focusing on those that have relevance in resource management, in order to shed light on how quantum computers might transform decision-making processes toward global environmental sustainability. Techniques for quantum optimization show promise in maximizing energy grid distribution and reducing waste generation in complex supply chains.
Quantum computing is considered a revolutionary technology due to its ability to solve computational problems that are beyond the capabilities of classical computers. However, quantum computing requires great amounts of energy to run. Therefore, a factor in deciding whether to use quantum computing should be not only the complexity of the problem to be solved, but also the energy required to solve it. This paper presents an empirical study developed with the aim of comparing classical and quantum computing in terms of energy efficiency to determine whether the increased power of quantum computers is offset by their higher energy consumption. To achieve this, a variety of problems with different levels of complexity were tested on both types of computers. Specifically, we used the IBM Quantum computers with a maximum of 5 qubits and an Intel i7, as a classical computer. In addition to this we have also analysed the evolution of the quantum computers, performing measurements on three time periods. Our empirical study showed that there is a variability of results obtained in the three time periods and that quantum computing is not recommended for low-complexity problems, given its high energy consumption, particularly when compared to traditional computing.