In celebration of International Women in Engineering Day (INWED) and of the UNESCO Year of Quantum, in this Viewpoint, women who work across a variety of engineering disciplines explore the opportunities and challenges for quantum computing, sensing and/or networks in their field. The perspectives presented cover themes of renewable energy, healthcare, civil engineering, quantum internet, computational mechanics, and finally, the commercialisation of quantum computers.

Yan Li

The renewable energy sector is at the heart of the global push toward sustainability, facing the growing complexity of integrating solar, wind, battery storage, electric vehicles, and flexible loads into the grid. This shift requires enhanced control and coordination, as well as faster, more scalable, and more precise tools for managing energy systems in real time. Quantum technologies1, including quantum computing, sensing, and networking, offer a powerful set of emerging capabilities that could dramatically accelerate innovation and improve performance across the energy landscape.

Credit: Penn State College of Engineering

The integration of quantum technology into the renewable energy sector could significantly enhance our ability to navigate complexity and uncertainty, leading to smarter, more robust, and sustainable power systems. For instance, quantum computing offers new ways to tackle problems that overwhelm classical methods2, such as simulating high-dimensional nonlinear dynamics, optimizing complex power flows, and making real-time decisions in distributed systems. In quantum sensing, researchers are exploring quantum magnetometers and interferometers for grid asset monitoring, renewable resource measurement, and even seismic sensing for energy infrastructure protection. Meanwhile, quantum networking is advancing toward the creation of secure communication links for energy system operators, with long-term potential for quantum cloud computing, where secure data is processed in quantum-enabled remote environments.

Unlocking this potential requires building new pathways between quantum research and real-world energy system applications. For quantum computing, this means developing hybrid quantum-classical algorithms that apply to specific challenges in grid operations, forecasting, control, and planning3. For instance, quantum algorithms can be used to optimize the placement and scheduling of distributed energy resources or simulate how renewable-rich grids respond to disturbances4. Quantum sensors, on the other hand, can detect minute changes in magnetic and electric fields, potentially allowing real-time condition monitoring of transformers, cables, or even grid-wide electromagnetic disturbances with unprecedented precision. Alongside these efforts, quantum networking could secure communication among grid control centres and substations, forming the backbone of a quantum-safe energy infrastructure in an increasingly cyber-physical world.

Yet, the path forward is not without challenges. Quantum devices are still in their early stages—quantum computers have limited qubits and are sensitive to noise, while quantum sensors and networks are still moving from lab prototypes to field-deployable systems. Engineering challenges include adapting power system models to quantum-compatible forms, translating quantum data to and from classical infrastructure, and integrating quantum technologies into existing tools and architectures. There is also a pressing need to co-develop new standards, software interfaces, and validation procedures that will allow energy stakeholders to adopt quantum technologies with confidence.

While these advances are promising, we also confront several fundamental, overarching challenges. For instance, how do we measure and compare the true value of quantum technologies against increasingly powerful classical tools like artificial intelligence and high-performance computing? What new privacy, security, or regulatory frameworks will be needed to safely operate a quantum-enhanced grid? How do we ensure that quantum technologies are effectively applicable and practically useful across the energy landscape—from large utilities and advanced research hubs to grid operators, educational institutions, and technology innovators across the energy ecosystem? How do we cultivate a skilled workforce capable of understanding, developing, and deploying these emerging tools within real-world energy systems?

The coming years will present a unique opportunity to explore how quantum technologies intersect with the evolving needs of the energy sector. As quantum technologies continue to evolve, ongoing efforts in applied research, early-stage demonstrations, and cross-disciplinary learning could play a valuable role in understanding their practical relevance. Collaborative work among researchers, practitioners, and technology developers will help align emerging quantum solutions with real-world energy challenges. Additionally, initiatives that support shared tools, open knowledge exchange, and broader engagement could contribute to making quanftum resources more accessible across the sector.

Melissa Mather

The increasing demands on healthcare systems globally, coupled with resource constraints and skills shortages, necessitate innovative technological solutions. Quantum technologies are emerging as a promising frontier, offering potential breakthroughs in understanding biological processes, enhancing patient care, and optimizing operational efficiency.

Credit: Melissa Mather

What is quantum? The quantum world is the realm of the very small, at the scale of atoms and the particles within them. Quantum sensors are orders of magnitude more sensitive than classical ones because they leverage quantum phenomena like superposition and entanglement to directly measure parameters like temperature and magnetic fields, which classical systems need to transduce. Meanwhile, quantum computing offers the potential to directly model complex quantum systems and address optimization challenges with exponential complexity.

Quantum sensors are already benefiting diagnostics and treatment. The direct detection of tiny magnetic signals from the brain and heart, generated by the underlying electrical activity of these organs, could offer new insights into neurological and cardiovascular conditions. The immense sensitivity of quantum sensors allows for the direct detection of these tiny magnetic signals, which are generated by the underlying electrical activity of these organs. This direct detection provides crucial insights into their function and potential abnormalities, offering a unique way to identify early signatures of disease or dysfunction that are difficult to detect with traditional methods. This can allow for treatment stratification, informing therapy response, and providing clinicians with improved prognostic insights for care planning. Quantum enhanced medical imaging could offer not just enhanced sensitivity but higher signal-to-noise ratios, potentially leading to faster scans and tangible benefits for patient waiting times.

Quantum sensors are a natural fit for quantum computing because their potential to access quantum biological data eliminates the need to encode it, a current bottleneck when using classical data. Quantum computing alone promises to help healthcare by unlocking new drug designs through direct molecular simulations and optimizing resource allocation through efficient scheduling.

Where should we focus to get the greatest impact from quantum technologies on healthcare? The starting point is co-creation. This demands that everyone involved – from basic scientists and engineers to clinicians and policymakers – work together to reshape healthcare systems and release the promise of quantum technologies. This starts by prioritizing research and development that directly addresses the most pressing questions and unmet needs in biology and medicine, ensuring a smooth and effective translation of quantum innovations from the lab to the patient’s bedside. Engineering will play an integral part in this.

The engineering challenges are broad, but there is a permeating need to decode clinical and operational needs into a language relatable to quantum technology performance. We need to know the specification, tolerances, and operating range. Indeed, we relate technical aspects like qubit coherence and fidelity to engineering performance specifications to clinically meaningful outcomes such as treatment stratification or prediction of disease recurrence.

Specific engineering needs lie in realising efficient quantum signal transduction and interfacing for clinical applications. Efficiently converting quantum state information into robust, clinically meaningful metrics is needed, involving technology integration, signal processing, and software for data interpretation. Interfacing between quantum and classical systems is a real engineering need and challenge. Robust environmental noise suppression is also needed in hospitals. Materials engineering, for example semiconductors operating at higher temperatures, could be transformative.

Adoption of new technology is not new to healthcare, so pathways exist. The call to action for engineers and innovators is to become familiar with these pathways, noting the need for safety and efficacy. A barrier is often gathering evidence that quantum technologies offer the cited healthcare benefit, be that to the patient or healthcare system. Access to test beds for demonstrations in relevant environments and on relevant data is extremely valuable in this context.

Ultimately the successful integration of quantum technology into healthcare hinges on collaborative efforts across disciplines, with engineers playing a vital role. Through this synergy, quantum innovations have the potential to deliver transformative benefits to healthcare systems facing significant challenges.

Nicole Metje

The work of civil engineers affects our daily lives, from the construction, maintenance and protection of our buildings and infrastructure, to the development of large-scale energy systems. These structures can be above ground or below, including tunnels, buried pipes, and cables. Many activities require breaking ground to either build in, on top of, or with the material itself. This requires detailed knowledge of existing subsurface structures or archaeological remains. The acquisition of such information can lead to significant additional costs and delays for any construction project. It can also heighten health and safety risks.

Credit: Nicole Metje

Classical sensors exist to look through the ground, but there are no X-ray goggles which reveal the different layers of the subsurface. Many existing active sensing technologies send electromagnetic waves through the ground which are often attenuated by soil properties limiting depth of penetration or resolution. Passive sensing technologies such as classical gravimetry or magnetometry for civil engineering applications suffer from low sensitivity and resolution, particularly with respect to the near-surface (first ~10 metres). Deployment is often slow and affected by other unwanted signals, thereby making them often not the technology of choice. There is an urgent need for a new tool enabling the detection of buried infrastructure in the top 10 metres below the ground surface.

Quantum sensing offers the potential to overcome some of the above limitations5. Different quantum sensing technologies such as gas detection cameras, magnetometers or gravity gradient sensors could be harnessed by civil engineers to look through the ground or monitor environmental changes. Gravity sensors detect small changes in density in the subsurface. Gravity gradient quantum sensors work using atom interferometry, in which pulses of light put atoms into a superposition of two states, causing each atom to simultaneously move along two different paths before recombining them to produce interference. As one of these paths is higher than the other, the output is sensitive to changes in gravity. Performing atom interferometry at two heights with a common laser beam suppresses vibration and other noise sources, with promise for more practical instruments, making the quantum sensor of gravity gradients attractive to civil engineering and other applications.

From a civil engineer’s viewpoint, there are several aspects which are important: sensitivity, resolution or speed of survey, cost and ruggedness. A faster survey saves significant time and thus costs. At the same time, the value is often in the data itself and how this influences decisions. With the improvement quantum sensors have shown and are still promising, surveys using e.g., quantum technology gravity gradient sensors have become a reality for civil engineers as they are more practical in our harsh environments. But outstanding engineering challenges remain. The sensors must be robust enough for engineers and surveyors to operate without quantum physicists. Reducing the size and weight and making the sensor mobile will also be valuable for some applications.

Quantum sensors have already shown significant potential to detect features currently invisible by other sensing technologies6. However, it is vital to ensure that the community does not overpromise the potential of the technology. When Ground Penetrating Radar was first introduced into civil engineering from the archaeology community, there was a lot of promise, but this did not materialise in practice, often due to incorrect methodologies or misunderstanding of how the technology works. This resulted in civil engineers rejecting the technology, and it has taken many years to overcome these reservations. It is vital to involve the end user communities early during the development of the technology. The UK quantum technologies national programme and the UK quantum hubs have realised accelerated research and commercialisation capabilities, successfully demonstrating the benefits of interdisciplinary collaboration. This approach ensures that quantum sensors are developed for different use cases with the required performance, shape factor and user interface to name but a few relevant parameters. It is also important to benchmark quantum sensors against existing sensing technologies to develop confidence. Quantifying the return of investment is vital to ensure pull by the end user community. In short, end users and engineers must be part of the journey and not brought in after the development of the technology. We have seen the value of this approach, and it would be good to see this across other quantum applications or early-stage technologies.

Angela Sara Cacciapuoti, Lorenza Criscuolo and Laura d’Avossa

Credit: Angela Sara Cacciapuoti, Lorenza Criscuolo and Laura d’Avossa (Left to Right)

In 1996, Brian Carpenter, then chair of the Internet Engineering Task Force (IETF), stated that 'the principle of constant change is perhaps the only principle of the Internet that should survive indefinitely'7. Decades later, this assertion continues to retain its validity.

The next paradigm shift will be the Quantum Internet, with the potential to unlock unparalleled communications and computing capabilities, by interconnecting quantum devices through a network infrastructure that leverages both quantum and classical communication links8,9. This breakthrough will transform critical sectors, such as defence, finance and healthcare. Among the most transformative applications emerging from the Quantum Internet are distributed quantum computing, unconditionally secure communications, advanced quantum sensing techniques, and blind quantum computing, ensuring privacy of outsourced quantum computations10.

However, the Quantum Internet operates under fundamentally different principles than the classical Internet. In fact, it is governed by the unique laws of quantum mechanics. Key quantum phenomena and principles, including the no-cloning theorem (which prevents perfect copying of unknown quantum states), quantum measurement postulate, quantum entanglement, and quantum decoherence, challenge the foundations of the classical Internet. Consequently, classical Internet protocols and techniques are inadequate or even inapplicable in the Quantum Internet, and bold new approaches are required for network design and operation.

In this context, as established in the foundational document 'Quantum Internet architectural principles'11, entanglement, a uniquely quantum phenomenon where particles share correlated states regardless of the distance, emerges as the fundamental building block of quantum networking. Indeed, entanglement turns the Quantum Internet into a fundamentally new communication network, enabling functionalities with no counterpart in the classical Internet. A paradigmatic example is quantum teleportation12, which allows the transfer of information between distant nodes, without the physical transmission of the information carrier.

Consequently, a quantum-native protocol suite for the Quantum Internet must be specifically designed:

  • to fully incorporate entanglement unique properties and

  • to leverage its non-classical characteristics for network operation and functionalities13,14.

This requires moving beyond the classical internet networking paradigm, towards designing and developing fundamentally new approaches that properly account for the non-classical correlation exhibited by entangled states.

In the above perspective, the realization of a functional quantum-native Quantum Internet protocol suite13 necessitates substantial research efforts to address critical open challenges spanning multiple dimensions. Among the most pressing issues there are:

  • entanglement preservation across networks: entanglement remains a fragile resource, highly susceptible to environmental decoherence and rapid degradation over long distances;

  • integration with classical network infrastructures: assuring a seamless coexistence and interoperability with the classical Internet is imperative for the Quantum Internet development;

  • scalability and standardization: the harmonization of technologies and methodologies across different platforms is essential to enable scalable deployment and foster the widespread adoption of quantum communication infrastructures.

Overcoming these challenges demands a concerted multidisciplinary approach, integrating the expertise of physicists, computer scientists, communication and network engineers. Such a collaboration fosters the emergence of hybrid research communities beyond traditional disciplinary boundaries, by reshaping the very same structure of research. And this knowledge convergence from diverse domains not only accelerates technological progress, but it also epitomizes a broader social value, by representing a model for future scientific ecosystems rooted in openness, cooperation, and intellectual heterogeneity.

Linked with the above, we believe that equally critical is the commitment to build an inclusive scientific community, where diversity is not merely encouraged but recognized as an indispensable asset. Indeed, the persistent gender disparities in quantum science, which mirror broader trends in STEM fields, require proactive efforts to promote the participation of women. In fact, ensuring diverse representation enriches the field with a multiplicity of perspectives, ultimately strengthening the development of quantum technologies in a manner that reflects the full spectrum of global talent. Let’s reflect on the women’s legacy in the history of telecommunications, which laid the foundation for the sophisticated communication networks we rely on today. Choosing just one of these pioneering women is impossible! Let’s mention Kathleen Booth, whose work on the first assembly language and computer architecture powered breakthroughs in telco infrastructures, especially in data routing and switching. Meanwhile, Hedy Lamarr, the Hollywood star, co-invented frequency-hopping spread spectrum (FHSS), a foundational technology for modern telecommunications.

An additional significant challenge lies in raising public awareness regarding the transformative potential of the Quantum Internet. Nowadays, public engagement remains limited, with understanding largely confined to specialized industrial and academic circles. Strategic outreach initiatives and early education in quantum communication network domain can demystify the subject by fostering broader societal engagement. And we firmly feel that, by empowering future generations with foundational knowledge, we can prepare society for a technological revolution that promises to redefine not only communication networks, but also our very perception of reality.

Mayu Muramatsu

Computational mechanics is an interdisciplinary field that uses mathematical models and numerical analysis to analyze and predict physical phenomena. It is a fundamental technology that supports industry and infrastructure, from structural safety assessment to material design, energy transport, fluid control, and durability prediction of urban infrastructure. In the field of computational mechanics, researchers are actively exploring how best to harness the power of quantum computers.

Credit: Mayu Muramatsu

Quantum computing has two main approaches: gate-based and quantum annealing. The gate-based method, used in the Noisy Intermediate-Scale Quantum (NISQ) era, applies quantum logic gates to qubits to run versatile algorithms. It has been theoretically demonstrated to have advantages over classical computing for specific problems. However, due to noise and hardware limitations, it currently works only at a small scale. Achieving large-scale, stable computation will require Fault-Tolerant Quantum Computing (FTQC), which involves large-scale error correction with thousands to millions of qubits. In contrast, quantum annealing, often formulated via Ising models, uses superposition and tunnelling to solve specific optimization problems. While less general-purpose, it is robust against noise and already practically implemented without error correction. The two methods differ in scalability, technical maturity, and application domains.

In the field of solid mechanics, the quantum annealing method has achieved remarkable results in topology optimization problems, these can lead to design solutions for numerous applications where safer and materially more efficient structures are priorities, such as aerospace and civil engineering. For example, Key and Freinberger used quantum algorithms to find optimal structural designs and compute the structural response of a component in one go using available hardware15. Sukulthanasorn et al. proposed similar research extended to continuous targets16.

In the field of materials science, applications of quantum annealing are also expanding. For example, Endo et al. expressed the phase separation structure of block copolymers using a phase field model and demonstrated a method for solving it quickly on an Ising machine17. Meanwhile, research using gate-based methods is also progressing. For example, Wulff et al. developed a method based on FTQC for optimizing the stacking sequence of layered composites18.

In computational fluid dynamics (CFD), analytical methods using quantum computing are steadily being developed. More and more studies have been conducted, including quantum gate methods by Schalkers and Möller19, which are designed for execution on NISQ devices. Going forward, while demonstrating the potential applications of quantum computing, attention will focus on how quantum computing can address challenges specific to CFD, such as turbulence analysis.

Analyses of Poisson’s equation, which is often used in heat conduction problems, are also actively being conducted. Liu et al. theoretically investigated a framework for continuum mechanics using quantum computing for solving partial differential equations using quantum algorithms20. Research by Arora et al. demonstrating the solution of the Poisson equation using quantum/classical hybrid methods is also noteworthy21.

In the field of control and optimization, quantum gate algorithms for NISQ that can be executed on shallow circuits are actively being researched. Kim and Wang introduced uncertainty evaluation and mixer selection into Bayesian optimization, improved accuracy in constrained optimization22. Suzuki et al. formulated the design update problem in fluid flow channel topology optimization in Ising form23.

Currently, quantum computing in computational mechanics is advancing by choosing annealing or gate methods based on the problem structure and scale, considering NISQ practicality and for FTQC potential. As error correction and hardware improve, quantum computing is expected to become essential, overcoming limits in computation time and enabling high-precision, large-scale simulations. This evolution will help shift computational mechanics into a core design tool for future society.

Maria Maragkou

The potential of quantum technologies to disrupt the way we approach problems today is undeniable. Quantum computers won’t replace but rather will complement existing classical and high-performance supercomputers, transforming industries that rely on large scale calculations. McKinsey estimates that the chemical, life sciences, finance, and mobility sectors alone could gain up to $2 trillion in value gains by 203524.

Credit: Riverlane

Technological progress towards a reliable and sufficiently large quantum computer has been steady with quantum processing units (QPUs) scaling to follow their own Moore’s law. But it’s a process of evolution rather than instant revolution.

The next industry milestone, called 'MegaQuOp' is the ability of a quantum computer to conduct one million error-corrected—and thus reliable—quantum operations25. At this point, classical computers will no longer be able to simulate the operation of a quantum computer which is largely the case with the quantum devices available today. And yet, to be able to solve currently unsolvable scientific problems, quantum computers must sustain trillions of error-free quantum operations ('TeraQuOp').

The company I work for, Riverlane, specialises in one of the key technological challenges of quantum computing: correcting the millions or even billions of errors generated during operation. These errors plague all quantum computers due to unavoidable environmental factors. Quantum error correction (QEC) is thus critical to the seamless and reliable operation of all quantum computers.

This is a crucial problem to solve on its own: quantum computers generate a continuous stream of quantum error correction data volumes that must be processed by sophisticated inference algorithms in real-time. A single commercial-grade quantum computer will stream QEC data at a rate of 100 Terabytes per second26 roughly the equivalent to Netflix’ total global streaming data. All this information must be processed swiftly (<1 μs) and with ultra-precise timing.

But there is more to quantum than pure science and technology. There are more than 250 quantum computing start-ups today globally, most of them springing from academic groups, working alongside big tech companies to bring this exciting technology to the market. Entrepreneurship is not for the faint hearted. In deep tech areas, like quantum technologies, companies are more likely to fail in early stages than those operating in more traditional tech industries27 with successful exits sometimes being >15 years away (about double the time compared to general tech startups)28.

Bringing such a cutting-edge technological solution to the market requires more than solving the challenge itself. It requires bringing together a team with deep knowledge of quantum physics, math, engineering, informatics, classical computing and then enabling them to communicate, so they can turn scientific ideas into impactful and lasting products at a pace. On top of that, we need to devise profitable business models for real users and customers who themselves are going through the same scientific and engineering discovery process. But the most critical enabler of success isn’t technical or scientific. It’s developing from day 1 and sustaining—including during growth—a culture that celebrates and embraces difference and diversity in actions and not just beautiful words.

It is precisely this whirlpool of uncertainty that drew me to quantum. Taking a great idea out of the safety of academia and making it commercially viable is a Herculean labour. Resources are meek, innovation must be quick and pivots to respond to ecosystemic changes are constant—but crucial. And, of course, the team must share the mindset that uncertainty, albeit scary, is ripe with opportunities.

Today, we believe we have all the means (scientific and technological) in place to scale the necessary components to reach the MegaQuOp. We believe it could be as soon as 5 years away. But what about going beyond? About one third of quantum computing companies today are building QPUs across a handful of different qubit types. This leads into fragmentation of capital, talent and effort. We are already seeing huge talent shortage in the industry, and not only for people from quantum backgrounds. Quantum computer start-ups are unable to hire all the software and hardware engineers they need because they are competing with lucrative salaries from big tech across other sectors like AI.

In the next 3 years, I believe consolidation will become inevitable, as the ecosystem will be forced to focus its efforts and resources in scaling the technology and building a robust supply chain—because it’s beyond the MegaQuOp that things will become really interesting.