Brain metastases – cancerous lesions that have spread from elsewhere in the body – are increasingly treated using stereotactic radiotherapy (SRS), a precision technique that targets each individual lesion with a high dose of radiation. Compared with whole-brain irradiation, SRS may lead to higher local control and increased cognitive sparing, as well as a shorter overall treatment duration. But to target and treat multiple brain metastases, each lesion must first be detected on an MRI scan and accurately delineated. And this can be a complex and time-consuming task.

“There are two challenges that we face in the clinic,” explains Evrim Tezcanli, professor of radiation oncology at Acibadem Atasehir Hospital in Turkey. “First, we want to treat all the lesions. But very small lesions, particularly those under 0.1 cc, can easily be missed by untrained eyes. Larger metastases, meanwhile, are more challenging to contour – you want to cover the whole lesion without missing a pixel, but don’t want to spill radiation over into the brain tissue. It’s time-consuming work, especially if there are multiple lesions.”

To address these challenges, Siemens Healthineers has developed an AI-powered software tool that automates the contouring of brain metastases. The software – integrated into the company’s syngo.via RT Image Suite and AI-Rad Companion Organs RT packages – employs advanced deep-learning algorithms to rapidly analyse a patient’s MR images and contour and label metastatic lesions. Alongside, it delineates key organs at risk, such as the brainstem and optic structures.

“One of the main strengths of this software is that it reduces the manual workloads really well,” says Tezcanli.

Meeting clinical standards

To evaluate the accuracy and time efficiency of the new software tool, Tezcanli and her team compared AI-based delineation with the performance of two experienced radiation oncologists. The study included data from 10 patients with between three and 17 brain metastases. The radiation oncologists manually contoured all lesions (82 in total) based on patients’ contrast-enhanced MRI scans; the same images were also processed by the AI software to automatically contour the metastases.

Tezcanli reports that the software performed remarkably well. “One of the most significant findings was that the manual contours and the AI-generated contours showed strong agreement, especially for lesions larger than 0.1 cc. In terms of geometric similarity, the AI-generated boundaries were well within our clinically acceptable levels,” she says.

Comparing the manual and AI-generated contours revealed a medium Dice similarity coefficient of 0.83, increasing to 0.91 when excluding very small lesions, and a median Hausdorff distance (the maximum distance between the two contours) of 0.3 mm.

AI will definitely have a place because of the time savings and accuracy it delivers

Evrim Tezcanli

To quantify the overall time efficiency, the researchers timed the contouring process for the radiation oncologists and the AI tool. They also measured the time taken for expert review of the AI-generated results, in which a radiation oncologist checks the contours and performs any necessary adjustments before they are approved for treatment planning.

The AI software completed the contouring for each patient in just one to two minutes, reducing the workload by an average of 75%, and in some cases saving over 30 minutes per patient. “We still needed to review the AI contours, but the correction time was only three to four minutes,” says Tezcanli, emphasizing that expert review remains essential when using AI. “One case required nine minutes, but even with that patient we had a time saving of 75%.”

As well as saving time for the oncology staff, AI-based contouring has a lot to offer from the patient’s perspective. Spending less time on demanding manual contouring frees up the physician to spend more time with the patient.

Lesion detection

For their study, the researchers analysed post-contrast T1 MPRAGE sequences recorded using a 3 Tesla MRI scanner. To maximize lesion enhancement, they acquired images several minutes after contrast injection, though Tezcanli notes that this timing may vary between treatment centres. They also used image slices of 1 mm or less. “This is a very precise treatment and we want to make sure everything is accurate,” she adds.

The study deliberately included patients with varying numbers of different sized metastases, to assess the algorithms under diverse clinical scenarios. In terms of lesion detection, the software exhibited an overall sensitivity of 94% – finding 77 of the 82 metastases. The five missed lesions were extremely small, 0.01 to 0.03 cc, a volume that’s challenging even for physicians to detect. The software did, however, find three additional lesions that were not originally identified and which were later confirmed as brain metastases.

The false positive rate was 8.5%, with the software mistakenly identifying seven vascular structures as metastases. “Because the algorithms work with contrast enhancement, any vascular enhancements that mimic the tumour can be mistaken,” says Tezcanli. “Here we needed to use a dedicated MRI sequence to define whether it was a metastasis or not. That’s just one thing to be cautious about. Other than that, we were very satisfied with the software’s ability to detect small lesions and find ones that we hadn’t detected.”

Automation with HyperArc

The contours generated by the AI software are exported in DICOM RT Struct format, enabling direct transfer into the treatment planning system. At Acibadem Atasehir Hospital, this next step is performed using HyperArc, a radiosurgery-specific software module within the Eclipse treatment planning infrastructure. HyperArc performs automated treatment planning and delivery, enabling fast and efficient SRS on the Varian TrueBeam and Edge linacs.

“HyperArc has proven to be highly effective, even when treating patients with multiple brain metastases,” says Burcin Ispir, a medical physicist working alongside Tezcanli. “One of its biggest powers is its ability to perform single isocentre, automated planning for multiple targets, which significantly reduces planning time while maintaining excellent plan quality. In our experience, HyperArc-generated plans offer high conformity and steep dose gradients, which are critical for sparing normal brain tissue.”

Unlike conventional radiotherapy where homogeneity is desirable, SRS plans intentionally allow controlled heterogeneity within the target volume to improve sparing of normal tissue. HyperArc also offers automation of the beam geometry, including collimator and couch angles, ensuring consistent, fast and highly reproducible plans “For selected cases, we have found this enables a same-day workflow where contouring, planning and treatment can all be completed within a single day,” Ispir explains.

The automation in AI contouring and HyperArc planning speeds up the treatment planning process, and when compared to traditional workflows, potentially allows patients to commence radiation therapy treatments earlier. The ability to commence treatment as soon as possible after the MRI scan is imperative when treating brain metastases. Most patients will also be receiving systemic therapies, which need to be delivered on schedule. But perhaps more importantly, the high spatial precision of SRS makes the technique sensitive to even small anatomical changes within lesions. If the delay between MR imaging and radiotherapy treatment is too long, any changes occurring during that time could decrease targeting accuracy.

“We are in an era where we are using the technology to have even same-day treatments,” says Tezcanli. “We have rapid contouring with AI, a quick review of a few minutes by the expert radiation oncologist, treatment planning with HyperArc, and then a few hours later the patient is treated. This is where the technology is taking us.”

Look to the future

Continuing improvements in cancer treatment techniques mean that patients are living longer, but this also increases the likelihood of metastases developing. In addition, higher quality MRI scans and enhanced imaging protocols lead to more metastases being detected. These factors combine to increase the workload on centres treating multiple metastases with SRS.

“I think we will be treating brain metastasis more and more,” says Tezcanli. “And I think radiosurgery will be the main treatment modality in the future. AI will definitely have a place because of the time savings and accuracy it delivers. And this is only the first version of the software; I’m sure it can be improved to find even smaller lesions or differentiate vascular structures.”

Following the initial software evaluation, the team has not yet fully integrated it into their clinical routine, but Tezcanli tells Physics World that they would be happy to use the software in every one of their brain metastases treatments. “I think we will be using it routinely in the future in all of our clinical cases,” she says.

• The statements by customers of Siemens Healthineers described herein are based on results that were achieved in the customer’s unique setting. Because there is no “typical” hospital or laboratory and many variables exist (e.g., hospital size, samples mix, case mix, level of IT and/or automation adoption) there can be no guarantee that other customers will achieve the same results.
  The products/features mentioned herein are not commercially available in all countries. Their future availability cannot be guaranteed.
  Autocontouring results are generated by Siemens. The displayed renderings are created with software that is not commercially available.

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As manufacturers in the nascent quantum supply chain turn their gaze towards at-scale commercial opportunities in quantum computing, the scenic city of Delft in the Netherlands is emerging as a heavyweight player in quantum science, technology and innovation. At the heart of this regional quantum ecosystem is Delft Circuits, a Dutch manufacturer of specialist I/O cabling solutions, which is aligning its product development roadmap to deliver a core enabling technology for the scale-up and industrial deployment of next-generation quantum computing, communications and sensing systems.

In brief, the company’s Cri/oFlex® cryogenic RF cables comprise a stripline (a type of transmission line) based on planar microwave circuitry – essentially a conducting strip encapsulated in dielectric material and sandwiched between two conducting ground planes. The use of the polyimide Kapton® as the dielectric ensures Cri/oFlex® cables remain flexible in cryogenic environments (which are necessary to generate quantum states, manipulate them and read them out), with silver or superconducting NbTi providing the conductive strip and ground layer. The standard product comes as a multichannel flex (eight channels per flex) with a range of I/O channel configurations tailored to the customer’s application needs, including flux bias lines, microwave drive lines, signal lines or read-out lines.

“As quantum computers evolve – think more and more qubits plus increasingly exacting requirements on gate fidelity – system developers will reach a point where current coax cabling technology doesn’t cut it anymore,” explains Daan Kuitenbrouwer, co-founder of Delft Circuits. “The key to our story is that Cri/oFlex® allows us to increase the I/O cabling density easily – and by a lot – to scale the number of channels in a single system while guaranteeing high gate fidelities [minimizing noise and heating] as well as market-leading uptime and reliability.”

Quantum alignment

To put some hard-and-fast performance milestones against that claim, Kuitenbrouwer and colleagues have just published a granular product development roadmap that aligns Cri/oFlex® cabling specifications against the anticipated evolution of quantum computing systems –  from 150+ qubits today out to 40,000 qubits and beyond in 2029 (see figure, “Quantum alignment”).

“Our roadmap is all about enabling, from an I/O perspective, the transition of quantum technologies out of the R&D lab into at-scale practical applications,” says Kuitenbrouwer. “As such, we studied the development roadmaps of more than 10 full-stack quantum computing vendors to ensure that our ‘guiding principles’ align versus the aggregate view of quantity and quality of qubits targeted by the system developers over time.”

Notwithstanding the emphasis on technology innovation and continuous product improvement, Delft Circuits is also “coming of age” in line with the wider quantum community. Most notably, the company’s centre of gravity is shifting inexorably from academic end-users to servicing vendors large and small in the quantum supply chain. “What we see are full-stack quantum computing companies starting to embrace horizontal thinking – which, in our case, means a technology partner able to solve their entire I/O cabling challenge,” explains Kuitenbrouwer.

To gain traction, however, systems integrators at the sub-stack level must, as a given, design their product offering with industrial metrics front-and-centre – for example, scalability, manufacturability, reliability, cost per I/O channel and second-sourcing. Equally important is the need to forge long-term vendor-customer relationships that often move beyond the transactional into the realm of co-development and collaboration – though all against a standardized package of cabling options.

“We integrate Cri/oFlex® with cryostats that have relatively standard vacuum feedthroughs and thermalization – more or less the same across the board,” says Kuitenbrouwer. What changes is the type of qubit – superconducting, spin, photonic – which in turn determines the configuration of the I/O line and where to place the attenuators, low-pass filters and IR filters. “This is something we can adjust relatively easily – at high volume and high reliability – with the whole I/O package installed and tested at the customer premises,” he adds.

Timing is key for quantum advantage

Commercially, Delft Circuits is already making real headway, getting “in the door” with many of the leading developers of quantum computing systems in North America and Europe. One of the main reasons for that is the ability to respond to customer requirements in an agile and timely fashion, argues Sal Bosman, a fellow co-founder of Delft Circuits.

“We work on the basis of a very structured design process, playing to our strengths in superconductor fabrication, integrated microwave components and cryogenic engineering,” Bosman notes. “We have also developed our own in-house software to simulate the performance of Cri/oFlex® cabling in full-stack quantum systems. No other vendor can match this level of customer support and attention to detail.”

Right now, though, it’s all about momentum as Delft Circuits seeks to capitalize on its first-mover advantage and, what Bosman claims, is the unique value proposition of its Cri/oFlex® technology: a complete and inherently scalable I/O solution with integrated flex cables incorporating filters and high-density interconnects to quantum chips or control electronics.

With this in mind, the company is busy constructing a new 750m² clean-room (with an option to double that footprint) alongside its existing 1000m² in-house pilot-production and test facility. “Currently, we are the only industrial supplier able to deliver flexible circuits of superconducting materials at scale,” concludes Bosman.

“Over the next two to three years,” he adds, “we have a credible opportunity to grab significant market share when it comes to cabling I/O for quantum. Watch this space: a lot of customers are already coming to us saying ‘we don’t want to buy more coax, we want to work with you.’”

Location, location, location

Delft Circuits sits within a thriving regional cluster for quantum science and technology called Quantum Delta Delft, which is centred around the canal-ringed city of Delft between The Hague and Rotterdam.

Formed in 2017 and initially located at the Faculty of Applied Sciences at Delft University of Technology (TU Delft), Delft Circuits has since grown as an independent company and is now based in the historic Cable District, where its facilities include a dedicated fabrication, pilot-production and testing area.

TU Delft is itself home to a high-profile interfaculty research institute called QuTech, a collaboration with the Netherlands Organisation for Applied Scientific Research (TNO) that’s tasked with developing full-stack hardware and software layers (including enhanced qubit technologies) for quantum computing and quantum communications systems.

Alongside this academic powerhouse, the Delft region has seen the emergence of other quantum tech start-ups like QuantWare (quantum chips), Qblox (control electronics) and Orange Quantum Systems (test solutions). All three companies work closely with Delft Circuits as part of the ImpaQT UA cooperative, a joint effort to develop open standards and interoperable technologies that enable system integrators to build quantum computing hardware stacks from off-the-shelf components.

“The ImpaQT UA story is ongoing,” explains Kuitenbrouwer. “As partners, we are super-complementary and collaborate closely to shape the future of quantum computing.” That’s why the new development roadmap is so important for Delft Circuits: to communicate a vision from the “component layer” up the value chain to the full-stack quantum computing companies.

As well as the talent pipeline that comes with proximity to TU Delft and QuTech, Quantum Delta Delft is home to TNO’s Quantum Information Technology Testing (QITT) Facility, which enables European companies to evaluate their cryogenic or non-cryogenic quantum devices and software in a full-stack quantum computing set-up.

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Radiotherapy is a precision cancer therapy that employs personalized treatment plans to target radiation to tumours with high accuracy. Such plans are usually created from high-resolution CT scans of the patient. But interest is growing in an alternative approach: MR simulation, in which MR images are used to generate the treatment plans – for delivery on conventional linac systems as well as the increasingly prevalent MR-guided radiotherapy systems.

One site that has transitioned to this approach is the Institut Jules Bordet in Belgium, which in 2021 acquired both an Elekta Unity MR-Linac and a Siemens MAGNETOM Aera MR-Simulator. “It was a long-term objective for our clinic to have an MR-only workflow,” says Akos Gulyban, a medical physicist at Institut Jules Bordet. “When we moved to a new campus, we decided to purchase the MR-Linac. Then we thought that if we are getting into the MR world for treatment adaptation, we also need to step up in terms of simulation.”

The move to MR simulation delivers many clinical benefits, with MR images providing the detailed anatomical information required to delineate targets and organs-at-risk with the highest precision. But it also creates new challenges for the physicists, particularly when it comes to quality assurance (QA) of MR-based systems. “The biggest concern is geometric distortion,” Gulyban explains. “If there is no distortion correction, then the usability of the machine or the sequence is very limited.”

Addressing distortion

While the magnetic field gradient is theoretically linear, and MRI is indeed extremely accurate at the imaging isocentre, moving away from the isocentre increases distortion. Images of regions 30 or 40 cm away from the isocentre – a reasonable distance for a classical linac – can differ from reality by 15 to 20 mm, says Gulyban. Thankfully, 3D correction algorithms can reduce this discrepancy down to just a couple of millimetres. But such corrections first require an accurate way to measure the distortion.

To address this task, the team at Institut Jules Bordet employ a geometric distortion phantom –the QUASAR MRID^3D Geometric Distortion Analysis System from IBA Dosimetry. Gulyban explains that the MRID^3D was chosen following discussions with experienced users, and that key selling points included the phantom’s automated software and its ability to efficiently store results for long-term traceability.

“My concern was how much time we spend cross-processing, generating reports or evaluating results,” he says. “This software is fully automated, making it much easier to perform the evaluation and less dependent on the operator.”

Gulyban adds that the team was looking for a vendor-independent solution. “I think it is a good approach to use the tools provided [by the vendor] but now we have a way to measure the same thing using a different approach. Since our new campus has a mixture of Siemens MRs and the MR-Linac, this phantom provides a vendor-independent bridge between the two worlds.”

For quality control of the MR-Simulator, the team perform distortion measurements every three months, as well as after system interventions such as shimming and following any problems arising during other routine QA procedures. “We should not consider tests as individual islands in the QA process,” says Gulyban. “For instance, the ACR image quality phantom, which is used for more frequent evaluation, also partly assesses distortion. If we see that failing, I would directly trigger measurements with the more appropriate geometric distortion phantom.”

A lightweight option

To perform MR simulation, the images used for treatment planning must encompass both the target volume and the surrounding region, to ensure accurate delineation of the tumour and nearby organs-at-risk. This requires a large field-of-view (FOV) scan – plus geometric distortion QA that covers the same large FOV.

“You’re using this image to delineate the target and also to spare the organs-at-risk, so the image must reflect reality,” explains Kawtar Lakrad, medical physicist and clinical application specialist at IBA Dosimetry. “You don’t want that image to be twisted or the target volume to appear smaller or bigger than it actually is. You want to make sure that all geometric qualities of the image align with what’s real.”

Typically, geometric distortion phantoms are grid-like, with control points spaced every 0.5 or 1 cm. The entire volume is imaged in the MR scanner and the locations of control points seen in the image compared with their actual positions. “If we apply this to a large FOV phantom, which for MRI will be filled with either water or oil, it’s going to be a very large grid and it’s going to be heavy, 40 or 50 kg,” says Lakrad.

To overcome this obstacle, IBA researchers used innovative harmonic analysis algorithms to design a lightweight geometric distortion phantom with submillimetre accuracy and a large (35 x 30 cm) FOV: the MRID^3D. The phantom comprises two concentric hollow acrylic cylinders, the only liquid being a prefilled mineral oil layer between the two shells, reducing its weight to just 21 kg.

“The idea behind the phantom was very smart because it relies on a mathematical tool,” explains Lakrad. “There is a Fourier transform for the linear signal, which is used for standard grids. But there are also spherical harmonics – and this is what’s used in the MRID^3D. The control points are all on the cylinder surface, plus one in the isocentre, creating a virtual grid that measures 3D geometric distortion.” She adds that the MRID^3D can also differentiate distortion due to the main magnetic field from gradient non-linearity distortion.

Moving into the MR world

Gulyban and his team at Institut Jules Bordet first used MR simulation for pelvic treatments, particularly prostate cancer, he tells Physics World. This was followed by abdominal tumours, such as pancreatic and liver cancers (where many patients were being treated on the MR-Linac) and more recently, cranial and head-and-neck irradiations.

Gulyban points out that the introduction of the MR-Simulator was eased by the team’s experience with the MR-Linac, which helped them “step into the MR world”. Here also, the MRID^3D phantom is used to quantify geometric distortion, both for initial commissioning and continuous QA of the MR-Linac.

“It’s like a consistency check,” he explains. “We have certain manufacturer-defined conditions that we need to meet for the MR-Linac – for instance, that distortion within a 40 mm diameter should be less than 1 mm. To ensure that these are met in a consistent fashion, we repeat the measurements with the manufacturer’s phantom and with the MRID^3D. This gives us extra peace of mind that the machine is performing under the correct conditions.”

For other cancer centres looking to integrate MR into their radiotherapy clinics, Gulyban has some key points of advice. These include starting with MR-guided radiotherapy and then adding MR simulation, identifying a suitable pathology to treat first and gain familiarity, and attending relevant courses or congresses for inspiration.

“The biggest change is actually a change in culture because you have an active MRI in the radiotherapy department,” he notes. “We are used to the radioprotection aspects of radiotherapy, wearing a dosimeter and observing radiation protection principles. MRI is even less forgiving – every possible thing that could go wrong you have to eliminate. Closing all the doors and emptying your pockets must become a reflex habit. You have to prepare mentally for that.”

“When you’re used to CT-based machines, moving to an MR workflow can be a little bit new,” adds Lakrad. “Most physicists are already familiar with the MR concept, but when it comes to the QA process, that’s the most challenging part. Some people would just repeat what’s done in radiology – but the use case is different. In radiotherapy, you have to delineate the target and surrounding volumes exactly. You’re going to be delivering dose, which means the tolerance between diagnostic and radiation therapy is different. That’s the biggest challenge.”

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This episode features a wide-ranging interview with the astrochemist Ewine van Dishoeck, who is professor emeritus of molecular astrophysics at Leiden Observatory in the Netherlands. In 2018 she was awarded The Kavli Prize in Astrophysics and in this podcast she talks about her passion for astrochemistry and how her research combines astronomy, astrophysics, theoretical chemistry and laboratory experiments.

Van Dishoeck talks about some of the key unanswered questions in astrochemistry, including how complex molecules form on the tiny specks of dust in interstellar space. We chat about the recent growth in our understanding of exoplanets and protoplanetary discs and the prospect of observing signs of life on distant planets or moons.

The Atacama Large Millimetre Array radio telescope and the James Webb Space Telescope are two of the major facilities that Van Dishoeck has been involved with. She talks about the challenges of getting the astronomy community to agree on the parameters of a new observatory and explains the how collaborative nature of these projects ensures that instruments meet the needs of multiple research communities.

Van Dishoeck looks to the future of astrochemistry and what new observatories could bring to the field. The interview ends with a call for the next generation of scientists to pursue careers in astrochemistry.

This podcast is sponsored by The Kavli Prize.

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The International Year of Quantum Science and Technology (IYQ) has already triggered an explosion of activities around the world to mark 100 years since the emergence of quantum mechanics. In the UK, the UNESCO-backed celebrations have provided the perfect impetus for the University of Edinburgh’s Quantum Software Lab (QSL) to work with the National Quantum Computing Centre (NQCC) to organize and host a festival of events that have enabled diverse communities to explore the transformative power of quantum computing.

Known collectively as the Quantum Fringe, in a clear nod to Edinburgh’s famous cultural festival, some 16 separate events have been held across Scotland throughout June and July. Designed to make quantum technologies more accessible and more relevant to the outside world, the programme combined education and outreach with scientific meetings and knowledge exchange.

The Quantum Fringe programme evolved from several regular fixtures in the quantum calendar. One of these cornerstones was the NQCC’s flagship event, the UK Quantum Hackathon, which is now in its fourth consecutive year. In common with previous editions, the 2025 event challenged teams of hackers to devise quantum solutions to real-world use cases set by mentors from different industry sectors. The teams were supported throughout the three-day event by the industry mentors, as well as by technical experts from providers of various quantum resources.

This year, perhaps buoyed by the success of previous editions, there was a significant uptick in the number of use cases submitted by end-user organizations. “We had twice as many applications as we could accommodate, and over half of the use cases we selected came from newcomers to the event,” said Abby Casey, Quantum Readiness Delivery Lead at the NQCC. “That level of interest suggests that there is a real appetite among the end-user community for understanding how quantum computing could be used in their organizations.”

Reflecting the broader agenda of the IYQ, this year the NQCC particularly encouraged use cases that offered some form of societal benefit, and many of the 15 that were selected aimed to align with the UN’s Sustainable Development Goals. One team investigated the accuracy of quantum-powered neural networks for predicting the progression of a tumour, while another sought to optimize the performance of graphene-based catalysts for fuel cells. Moonbility, a start-up firm developing digital twins to optimize the usage of transport and infrastructure, challenged its team to develop a navigation system capable of mapping out routes for people with specific mobility requirements, such as step-free access or calmer environments for those with anxiety disorders.

During the event the hackers were given just two days to explore the use case, formulate a solution, and generate results using quantum simulators, annealers and physical processors. The last day provided an opportunity for the teams to share their findings with their peers and a five-strong judging panel that was chaired by Sir Peter Knight, one of the architects of the UK’s National Quantum Technologies Programme and co-chair of the IYQ’s Steering Committee a prime mover in the IYQ celebrations. “Your effort, energy and passion have been quite extraordinary,” commented Sir Peter at the end of the event. “It’s truly impressive to see what you have achieved in just two days.”

From the presentations it was clear that some of the teams had adapted their solution to reflect the physical constraints of the hardware platform they had been allocated. Those explorations were facilitated by the increased participation of mentors from hardware developers, including QuEra and Pasqal for cold-atom architectures, and Rigetti and IBM for gate-based superconducting processors. “Cold atoms offer greater connectivity than superconducting platforms, which may make them more suited to solving particular types of problems,” said Gerard Milburn of the University of Sussex, who has recently become a Quantum Fellow at the NQCC.

The winning team, which had been challenged by Aioi R&D Lab to develop a quantum-powered solution for scheduling road maintenance, won particular praise for framing the problem in a way that recognized the needs of all road users, not just motorists. “It was really interesting that they thought about the societal value right at the start, and then used those ethical considerations to inform the way they approached the problem,” said Knight.

The wider impact of the hackathon is clear to see, with the event providing a short, intense and collaborative learning experience for early-career researchers, technology providers, and both small start-up companies and large multinationals. This year, however, the hackathon also provided the finale to the Quantum Fringe, which was the brainchild of Elham Kashefi and her team at the QSL. Taking inspiration from the better-known Edinburgh Fringe, the idea was to create a diverse programme of events to engage and inspire different audiences with the latest ideas in quantum computing.

“We wanted to celebrate the International Year of Quantum in a unique way,” said Mina Doosti, one of the QSL’s lead researchers. “We had lots of very different events, many of which we hadn’t foreseen at the start. It was very refreshing, and we had a lot of fun.”

One of Doosti’s favourite events was a two-day summer school designed for senior high-school students. As well as introducing the students to the concepts of quantum computing, the QSL researchers challenged them to write some code that could be run on IBM’s free-to-access quantum computer. “The organizers and lecturers from the QSL worked hard to develop material that would make sense to the students, and the attendees really grabbed the opportunity to come and learn,” Doosti explained. “From the questions they were asking and the way they tackled the games and challenges, we could see that they were interested and that they had learnt something.”

From the outset the QSL team were also keen for the Quantum Fringe to become a focal point for quantum-inspired activities that were being planned by other organizations. Starting from a baseline of four pillar events that had been organized by the NQCC and the QSL in previous years, the programme eventually swelled to 16 separate gatherings with different aims and outcomes. That included a public lecture organized by the new QCi3 Hub – a research consortium focused on interconnected quantum technologies – which attracted around 200 people who wanted to know more about the evolution of quantum science and its likely impact across technology, industry, and society. An open discussion forum hosted by Quantinuum, one of the main sponsors of the festival, also brought together academic researchers, industry experts and members of the public to identify strategies for ensuring that quantum computing benefits everyone in society, not just a privileged few.

Quantum researchers also had plenty of technical events to choose from. The regular AIMday Quantum Computing, now in its third year, enabled academics to work alongside industry experts to explore a number of business-led challenges. More focused scientific meetings allowed researchers to share their latest results in quantum cryptography and cybersecurity, algorithms and complexity, and error correction in neutral atoms. For her part, Doosti co-led the third edition of Foundations in Quantum Computing, a workshop that combines invited talks with dedicated time for focused discussion. “The speakers are briefed to cover the evolution of a particular field and to highlight open challenges, and then we use the discussion sessions to brainstorm ideas around a specific question,” she explained.

Those scientific meetings were complemented by a workshop on responsible quantum innovation, again hosted by the QCi3 Hub, and a week-long summer school on the Isle of Skye that was run by Heriot-Watt University and the London School of Mathematics. “All of our partners ran their events in the way they wanted, but we helped them with local support and some marketing and promotion,” said Ramin Jafarzadegan, the QSL’s operations manager and the chair of the Quantum Fringe festival. “Bringing all of these activities together delivered real value because visitors to Edinburgh could take part in multiple events.”

Indeed, one clear benefit of this approach was that some of the visiting scientists stayed for longer, which also enabled them to work alongside the QSL team. That has inspired a new scheme, called QSL Visiting Scholars, that aims to encourage scientists from other institutions to spend a month or so in Edinburgh to pursue collaborative projects.

As a whole, the Quantum Fringe has helped both the NQCC and the QSL in their ambitions to bring diverse stakeholders together to create new connections and to grow the ecosystem for quantum computing in the UK. “The NQCC should have patented the ‘quantum hackathon’ name,” joked Sir Peter. “Similar events are popping up everywhere these days, but the NQCC’s was among the first.”

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