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  • 🔵 The Quantum Insider Weekly | AI For Quantum. Horizon's Hardware. And More News in Quantum

🔵 The Quantum Insider Weekly | AI For Quantum. Horizon's Hardware. And More News in Quantum

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FROM THE EDITOR.

Welcome back, everyone — and for U.S. readers, I hope you had a restful Thanksgiving break. If your inbox looked anything like mine this week, you already know the quantum sector wasted no time getting back to work. December tends to be a holiday-shortened month, but it’s shaping up to be a busy one, rounding out what will likely go down as a historic year for quantum research, investment, and industrial momentum.

One of the most important developments came out of Singapore, where Horizon Quantum announced that it has completed and activated its first in-house quantum computer. The company is describing itself as the first quantum-software firm to stand up and operate its own hardware — a notable signal of how quickly the software–hardware divide is starting to blur.

It was also a strong week on the funding front. Delft Circuits extended its financing round by €8 million as demand grows for its cryogenic cabling systems, and Niobium secured more than US $23 million in a follow-on round to accelerate its superconducting tech platform. Both moves underscore how capital is continuing to cluster around enabling technologies rather than single-bet architectures.

On the research side, a new NVIDIA-led study argued that quantum computing will require AI not just for error correction, but for pretty much the whole dang stack. The paper stops short of spelling it out, but it points toward a deeper — and increasingly unavoidable — idea: if quantum needs AI to scale, AI may eventually need quantum to keep advancing.

And in a sign of how mainstream the conversation has become, top executives at Google and Intel publicly offered bullish timelines for when quantum systems could begin solving commercially relevant problems. Their comments won’t settle any debates, but they do reflect a shift in tone: quantum is moving from “if” to “when,” and industry leaders are confident enough to say so on the record.

Links to all these stories — and more — are below.

Have a great weekend, and thanks as always for reading.

— Matt, Chief Content Officer at The Quantum Insider

INSIDER BRIEF.

The Noteworthy & Nuanced

The Quantum Insider’s team aren’t the only ones who love “quantum” wordplay. Germany has launched INQUBATOR, a four-year Fraunhofer-led programme aimed at helping companies adopt quantum computing and build early, real-world use cases. Supported by the Federal Ministry of Research, Technology and Space, the initiative provides low-cost access to quantum hardware, training, and joint R&D opportunities.

The UK’s Autumn 2025 Budget left the quantum community wanting for more. No dedicated quantum funding was introduced, while instead the broader landscape in which the sector operates was reshaped. Instead of standalone programs, quantum is positioned as a horizontal capability underpinning national priorities such as AI, sovereign compute, and advanced manufacturing.

Japan plans to build a 600-kilometer quantum-encrypted fiber network linking Tokyo, Nagoya, Osaka, and Kobe by 2027, with full deployment targeted for 2030. Operated by the National Institute of Information and Communications Technology and developed with Toshiba, NEC, and major telecom carriers, the project aims to secure finance, diplomacy, and medical-genomics communications before quantum computers threaten current encryption. — Alan Kanapin, Analyst at The Quantum Insider

The Research Rundown

Check out this week’s handpicked quantum research. These are studies headed for real-world impact: improving accuracy, reducing latency, using fewer resources, or solving problems that classical methods struggle with. These are early developments, but they hint at where quantum might earn its keep.

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➡️ A new research review published in Nature Communications argues that artificial intelligence is becoming essential for solving quantum computing’s most difficult engineering challenges.
➡️ The 28-author team — led by NVIDIA with contributors from Oxford, Toronto, Perimeter Institute, Waterloo, NASA Ames and others — reports that AI methods are now outperforming traditional techniques across nearly every layer of the quantum-computing stack.
➡️ Speculative, but quantum processors may be necessary for training and sustaining future trillion-parameter AI models as classical energy constraints tighten.
➡️ The review outlines how AI is accelerating hardware design, system identification, calibration, algorithm compilation, readout, error correction and noise mitigation.
➡️ The researchers conclude that AI and quantum computing may need to coevolve into a tightly integrated hybrid ecosystem, where each field compensates for the other’s scaling limits.

Analyst Commentary

An interesting technical review by a NVIDIA-led team of scientists makes a clear case that AI is no longer just an optional accelerator for quantum computing — it is becoming a requirement.

Across hardware design, system control, error correction and algorithm development, AI techniques are beginning to replace or outperform traditional engineering approaches. At the same time, the study points to an equally important strategic shift: as AI systems scale toward trillion-parameter regimes and energy constraints harden, quantum hardware may become essential to keep future AI models computationally sustainable. What began as two adjacent scientific communities are starting to show signs of interdependence.

The research team spans multiple institutions across North America and Europe, and they converge on a shared conclusion: AI will be central to lifting quantum computing out of its noisy era. Today’s devices are fragile, finicky and governed by complex dynamics that require constant recalibration and control. According to the review, deep-learning models and reinforcement-learning agents are already proposing qubit geometries, optimizing multi-qubit gates, reconstructing Hamiltonians and Lindbladians from sparse data, and mapping out fluctuating noise sources that degrade coherence. These models operate in design spaces far too large for human inspection, giving researchers a tool to navigate complexity in a field defined by it.

The review also points to a trend that has emerged steadily but quietly: AI is beginning to automate tasks once thought to require human intuition. Calibration workflows, charge-sensor tuning, drift compensation and pulse optimization — jobs that typically consume days or weeks of laboratory effort — are now being handled by reinforcement-learning agents, Bayesian optimizers and even multimodal language-vision systems. These systems are not yet capable of running without oversight. As datasets expand and models improve, quantum-device operation will shift toward semi-autonomous management. For companies working toward commercial-scale quantum processors, this automation will become one of the primary levers for scaling.

On the software side, AI-driven circuit generation and compilation represent another important shift. The team highlights transformer-based models that learn to generate compact chemistry circuits, reinforcement-learning systems that discover gate decompositions classical methods fail to find, and graph-based architectures that transfer optimization parameters across related problem instances. These tools shrink circuit depth and gate counts — critical steps for running algorithms on noisy machines — but they come with a catch: training them often requires simulations that scale exponentially. This is one of the first places where the researchers suggest that quantum hardware itself may need to enter the training loop.

Error correction remains arguably Job 1 in quantum. The authors argue that AI may ultimately be the only viable path to scalable decoding. Classical decoders struggle with realistic noise and become computationally unwieldy as code distances grow. AI-based decoders — including convolutional networks, transformers and graph neural networks — have shown that they can adapt to complex noise and identify error patterns more efficiently. Yet even these systems face barriers: training data requirements rise exponentially. Without new methods for generating synthetic data or running training loops directly on quantum hardware, progress will hit practical ceilings.

There are limitations, according to the study. AI models remain fundamentally classical and cannot escape the overhead of simulating large quantum systems. Many ML-trained controllers work well in simulation but degrade under hardware drift. Calibration agents still miss edge cases that human researchers catch. Error-mitigation networks lack rigorous guarantees for precision-sensitive workloads. These constraints reinforce an important point: AI will accelerate progress, but it will not eliminate the need for scalable qubit architectures, robust codes and high-performance classical infrastructure.

Pay close attention to the paper’s closing section. The authors describe an inevitable architecture: AI supercomputers tightly coupled to quantum accelerators through high-bandwidth, low-latency interconnects. In this model, AI would optimize quantum hardware, quantum systems would generate data and subroutines for AI training loops, and classical accelerators would orchestrate both. The researchers refer to this as an “accelerated quantum supercomputing system” — a future in which AI and quantum evolve together, each enabling the other’s progress.

If that ecosystem emerges, it would redefine how national laboratories, hyperscalers, semiconductor companies and quantum startups plan their roadmaps. It would also signal a transition that has been building slowly in the background: the shift from quantum computing as a standalone discipline to quantum computing as a foundational component of the global compute stack.

DATA SPOTLIGHT.

PacketLight Networks and NEC demonstrated quantum key distribution over a 400G dense wavelength division multiplexing (DWDM) network using a dual-fiber setup. They integrated NEC’s QKD system with PacketLight’s PL-4000M 600G Muxponder, achieving 100% data throughput and low latency, verified via a 100GbE tester. The QKD ran over a dedicated parallel fiber, maintaining quantum signal integrity. The result: a cost-effective, scalable quantum-safe model with zero performance tradeoffs on existing high-capacity infrastructure.

INDUSTRY HIGHLIGHTS.

💰️ SEALSQ made a strategic investment in U.S.-based quantum chip designer EeroQ, advancing its “Quantum Made in USA” strategy and expanding its integrated ecosystem for scalable, sovereign quantum and post-quantum technologies.

🗾 Japanese researchers demonstrated what may be Japan’s first cloud-operated trapped-ion qubit system, integrating an automated ytterbium ion trap, precision lasers, and the OQTOPUS software stack to run single-qubit operations remotely.

💸 Horizon Quantum Computing secured $110 million in PIPE financing to support its planned merger with dMY Squared, with participation from IonQ and major institutional investors.

🤝 The UK and Germany announced new joint initiatives to deepen quantum-technology collaboration, including a £6 million bilateral R&D call in 2026, an £8 million investment in Fraunhofer UK’s applied photonics centre, and a metrology agreement to advance shared quantum standards.

🇮🇪 Ireland’s Walton Institute at SETU is leading Q-FENCE, a €5.3 million Horizon Europe project to develop and deploy EU-mandated quantum-resistant security for critical sectors. The effort unites 12 European partners and will run real-world demonstrations across finance, healthcare, government, manufacturing, and utilities.

💶 Sparrow Quantum raised €27.5 million in Series A funding to scale production of its industrial photonic quantum chips and advance next-generation designs. Its Sparrow Core chip, already used by European tech firms, generates highly stable single photons at room temperature.

🤝 IonQ and the Centre for Commercialization of Regenerative Medicine formed an investment partnership to accelerate next-generation therapeutic development using hybrid quantum and quantum-AI technologies, with initial projects launching in Canada and Sweden in 2026.

🛰️ WISeKey and its subsidiaries SEALSQ and WISeSat.Space successfully launched a new WISeSat satellite on SpaceX’s Falcon 9 Transporter-16 mission, expanding their secure IoT and cybersecurity-focused constellation with higher data rates, SDR capabilities, and improved resilience.

🇺🇸 D-Wave created a dedicated U.S. government business unit, led by Jack Sears Jr., to accelerate federal adoption of its quantum technologies and develop applications tailored to national security and defense needs.

🖥️ Horizon Quantum activated its first in-house quantum computer, becoming the first quantum software company to assemble and operate its own system. Built from modular components across multiple vendors, the testbed gives Horizon full hardware–software control to advance its hardware-agnostic tools.

💻️ QM Inc. and the Israeli Quantum Computing Center deployed Qolab’s next-generation superconducting qubit device winning qubit physics into a scalable, noise-reduced processor. The collaboration enables global cloud access to Qolab’s devices through the IQCC’s hybrid quantum-classical infrastructure.

🎲 The Hartree Centre and Quantum Dice formalized a strategic partnership to expand industrial use cases for quantum-grade randomness and probabilistic computing, beginning with deploying QRNG technology across materials science, manufacturing, product design, and logistics.

🇩🇪 Germany’s DLR Quantum Computing Initiative and ParityQC launched QCMobility, a federally funded project to apply quantum, hybrid, and classical computing to complex transportation and logistics optimization.

🌴 Florida launched Florida Quantum, a privately led statewide initiative to position the state as a major quantum-technology hub by coordinating public–private partners, attracting companies, and accelerating commercialization.

🇮🇳 India released a national roadmap to become a top-three quantum power by 2035, outlining plans to scale hardware, lead global quantum software markets, and deploy the technology across strategic sectors. The report sets ambitious targets including quantum startups generating over $100M each and capturing half the global software market.

🇨🇳 China unveiled UnitaryLab 1.0, a quantum scientific computing platform built on new “Schrödingerization” algorithms to accelerate complex scientific and engineering computations.

EVENTS.

Nov. 15- 18 -- BIG Quantum Hackathon, Qatar 2025, Minaretein, Education City,. Doha, Qatar.

Nov. 16-21 -- SuperComputing 2025 (SC25) will be held n St. Louis, USA. SC25 is an international conference for high performance computing, networking, storage and analysis.

Nov. 24-25 -- World Strategic Forum is an international conference organized by the International Economic Forum of the Americas (IEFA). The 14th edition of the World Strategic Forum will be held at the Loews Coral Gables Hotel in Miami, Florida, presented by Integra Capital.

Dec. 1-4 -- QUEST-IS 2025 Quantum Engineering Sciences and Technologies for Industry and Services From Quantum Engineering to Applications for Citizens. EDF Lab, Paris-Saclay, France.

Dec. 3-5 -- Quantum Education Summit 2025 will advance accessible, inclusive quantum education through keynotes, workshops, and a collaborative white paper on workforce development and policy alignment.

Dec. 9-11 -- Q2B 2025 Silicon Valley Q2B is back for the eighth year in a row, connecting the international quantum community computing ecosystems. The event will feature top academics, industry end users, government representatives and quantum computing vendors from all over the world.

Dec. 17-18 -- Science Diplomacy - Bridging divides in a fragmented world will be held in Copenhagen, Denmark. The conference explores how science diplomacy can bridge divides and promote innovation, competitiveness, and international cooperation.

January 27 and 28, 2026 -- Qubits 2026 D-Wave is bringing its annual user conference, Qubits, to Boca Raton, Florida. The event will be held at The Boca Raton resort.

March 24 -- The QSECDEF World Symposium will be held on 24 March 2026 from 12:00–18:00 CET at the Palais des Congrès de Paris (Auditorium Havana), gathering global leaders from industry, government, and research to advance quantum-secure communication and infrastructure.

April 27-30 -- The Quantum Matter International Conference & Expo (QUANTUMatter2026) will take place at the Barceló Sants Hotel in Barcelona. The conference to foster the incubation of new ideas & collaborations at the forefront of quantum technologies, emerging quantum materials and novel generations of quantum communication protocols, quantum sensing and quantum simulation.

June 22-24 -- IQT Nordics: Oslo, Norway

June 24-26 -- Quantum. Tech World: Boston, Mass