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MerLin Unveiled: The First Quantum Layer for Data Scientists, Optimized for NVIDIA Accelerated Computing 

Launching at GTC Paris, MerLin democratizes quantum machine learning by integrating with classical AI tools—backed by GPU-accelerated performance  Paris, France – June 11th – Today, Quandela announces MerLin, a groundbreaking […]

Launching at GTC Paris, MerLin democratizes quantum machine learning by integrating with classical AI tools—backed by GPU-accelerated performance 

Paris, France – June 11th – Today, Quandela announces MerLin, a groundbreaking quantum computing framework designed for and by AI data scientists. Set to debut at NVIDIA GTC Paris, MerLin redefines quantum machine learning (QML) with a GPU-first approach, enabling researchers to simulate and benchmark algorithms beyond the limits of today’s quantum hardware. 

Quantum Meets AI: A Collaborative Future 

MerLin positions itself as the “quantum layer for data scientists” – contrasting with other quantum machine learning tools that target quantum scientists. By abstracting quantum complexity into familiar workflows (e.g., PyTorch/scikit-learn integrations), MerLin empowers AI practitioners to prototype hybrid quantum-classical models in hours, not months. Early adopters – including teams from the Perceval Quest, and researchers from Mila, NYUAD’s QML Lab and Scaleway – are collaborating with us to leverage MerLin and bridge classical and quantum workflows. 

Quantum shouldn’t demand a PhD to use,” said Niccolo Somaschi, co-founder & CEO of Quandela. “MerLin gives data scientists a GPU-accelerated gateway to quantum advantage while ensuring their work remains compatible with real hardware today—and tomorrow. By integrating benchmarks and noise-aware validation, we’re addressing a critical gap: the lack of reproducible metrics in hybrid algorithm research.” 

Powerful simulation tools are essential to develop better algorithms and accelerate the path to broad quantum advantage”, said Sam Stanwyck, Group Product Manager for quantum computing at NVIDIA. “MerLin solves a critical ecosystem need by opening the door for the broader research community to develop with photonic quantum circuits.” 

Key Innovations 

  1. GPU-Optimized Simulators
  • Leveraging NVIDIA CUDA-Q, MerLin delivers high-performance simulation for photonic quantum circuits, enabling tests for hardware that doesn’t yet exist (e.g., 24+ qubit systems). 
  1. Benchmark-Driven Progress
  • MerLin establishes reproducible metrics for hybrid algorithms, addressing the “benchmarking gap” in QML research—where thousands of papers lack standardized comparisons. 
  • Integrated with Quandela Cloud, it enables immediate validation of GPU-optimized algorithms on real photonic hardware, studying noise impact and scalability. 
  • Targets pragmatic use cases like quantum-enhanced kNN, GANs, and variational algorithms—backed by hardware-aware compilation. 
  1. Photonic-First, Future-Proof
  • Designed for today’s photonic QPUs (e.g., Perceval-based systems) but architected to adapt to next-gen hardware. 
  • Features like dynamic circuit recompilation ensure code scalability across hardware generations. 

Who Uses MerLin? 

  • AI/ML Practitioners: Prototype quantum layers without rewriting classical pipelines. 
  • Quantum Researchers: Access photonic-specific tools (e.g., boson sampling) with GPU-accelerated simulation. 
  • Enterprises: Pilot hybrid quantum-AI workflows with clear ROI benchmarks. 

MerLin allowed us to adapt existing algorithms to a photonic-native format within a short timeframe. The platform offered useful comparative insights that contributed to our ongoing research and publication efforts”, said Dr. Louis Chen, an early user, Research Associate at the Quantum Centre of Imperial College London (Imperial QuEST) and participant in the most recent Perceval Quest.

Availability & Strategic Vision 

MerLin will be freely accessible to accelerate adoption, with enterprise tiers for advanced features. The roadmap includes: 

  • Q2 2025: Stable PyTorch/scikit-learn APIs. 
  • 2026+: Support for 24+ qubit photonic systems. 

Learn More: merlinquantum.ai 

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Quandela and OVHcloud join forces to democratize quantum machine learning with MerLin

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At the international Adopt AI event in Paris, Quandela and OVHcloud announce a strategic initiative to bring closer AI and quantum computing thanks to MerLin, Quandela’s quantum machine learning environment. This collaboration will enable researchers and companies to prototype and simulate hybrid models on NVIDIA GPUs before testing them on Quandela’s photonic quantum computers, directly accessible from OVHcloud’s cloud platform.

Paris, Roubaix (France), November 25, 2025 – Quandela, European leader in photonic quantum computing, and OVHcloud, a major European cloud provider, announce that MerLin – the first programming language and environment dedicated to quantum machine learning – will be made available on OVHcloud’s platform starting mid-2026. This unified approach will accelerate the development of hybrid applications within a sovereign cloud environment.

A bridge between AI and quantum

Unveiled in summer 2025, MerLin lays the groundwork for a new generation of Quantum Machine Learning (QML) tools, integrated into standard AI frameworks such as PyTorch and scikit-learn.
Now, thanks to its integration into the OVHcloud platform, users will be able to design, simulate, and test their hybrid AI-Quantum neural networks in a unified cloud environment powered by NVIDIA GPUs, a shared partner of both companies.

This approach will accelerate the development of industrial quantum applications: users will first be able to run their simulations on GPUs, then test and validate their models on Quandela’s photonic quantum computers, hosted and operated within OVHcloud.

A clear quantum roadmap

As part of this partnership, OVHcloud has published its quantum roadmap, announcing that Quandela’s quantum computers will become available on its cloud platform in mid-2026. The first systems to be offered will be BELENOS, a 12-qubit photonic processor, and CANOPUS, a 24-qubit photonic processor.

This deployment will be a major milestone in integrating quantum computing into the cloud, paving the way for democratized and sovereign access to European quantum power.

This partnership with OVHcloud perfectly embodies our vision: to make quantum accessible and useful for AI experts. With MerLin, we provide a seamless environment – from GPU to quantum processor – allowing the exploration of new hybrid algorithms and accelerating the journey from concept to real-world application,” says Jean Senellart, Chief Product Officer at Quandela.

With MerLin, data scientists finally have an accessible framework that does not require quantum computing skills – an actual tool that democratizes its use for the most innovative function in companies: data science,” says Fanny Bouton, Quantum Lead and Product Manager at OVHcloud.

Toward a sovereign European quantum cloud

By combining their expertise – photonics and hybrid algorithms for Quandela, cloud and sovereign infrastructure for OVHcloud, GPU acceleration for NVIDIA – the two partners are laying the foundations of a competitive and open European quantum ecosystem. An ecosystem expected to foster the emergence of hybrid applications in fields such as cybersecurity, finance, energy, healthcare, and logistics.

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Quandela Accelerates Quantum Spin-Photon Simulationby 20,000x with NVIDIA CUDA-Q

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Quandela and NVIDIA have achieved a transformative 20,000x acceleration in quantum photonics simulation using NVIDIA CUDA-Q the GPU-accelerated platform for hybrid quantum-classical computing. This breakthrough dramatically reduces development cycles for quantum optical hardware from months to hours, advancing Quandela’s Spin–Photonic Quantum Computing (SPOQC) architecture for fault-tolerant quantum computing while also creating new opportunities for hybrid quantum–classical computing approaches that combine the strengths of both paradigms.

The advance builds on Quandela’s Zero-Photon Generator (ZPG)method, which reformulates complex photon-mediated dynamics into parallelizable master equations, CUDA-Q’s master equation solver enhanced in v0.12 with support for custom superoperators andbatched Liouvillian evolution, make it possible to run hundreds of open-system simulations simultaneously on a single NVIDIA Hopper GPU, reaching an acceleration of four orders of magnitude compared to existing simulation tools. Together, these advances turn previously intractable light–matter simulations into a real-time engineering tool.

Dr. Jean Senellart, Chief Product Officer of Quandela, said: “This collaboration with NVIDIA represents a paradigm shift in how we approach quantum hardware development. What once took weeks of computation can now be done in minutes, enabling us to explore thousands of design variations and accelerate our roadmap to fault-tolerant photonic quantum processors.

The collaboration demonstrates how GPU acceleration is now redefining quantum research. CUDA-Q v0.12.0 introduces the new superoperator and batching features developed through this joint effort, now publicly available for researchers and developers.

Sam Stanwyck, Group Product Manager for quantum computing at NVIDIA, commented: “Development of larger and more performant quantum hardware requires increasingly more complex simulations. Quandela’s work with CUDA-Q shows how GPU-accelerated simulations are compressing months of quantum hardware development into hours, and accelerating the development of useful accelerated quantum supercomputers.

This milestone sets a new benchmark for simulating distributed spin–photon quantum gates, supporting Quandela’s broader mission to build fault-tolerant photonic quantum processors. Detailed benchmarks and implementation resources are available in the Quandela technical blog.

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Conclusions from the Franco-German Dialogue of Quantum Technology Players 2025

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Quantum Technologies hold great economic potential. That is why it is in Europe’s interest to secure a leading position in their development and industrial application.

The French German Dialogue of Quantum Technology Players on September 23, 2025 in Paris and Massy (France), was organized by the Quantum Technology and Application Consortium (QUTAC), Le lab Quantique, Quandela, CEA, Fraunhofer, with support from the French embassy in Germany and the German embassy in France. The dialogue brought together more than 60 experts, managers and decision-makers from innovation, corporates, research and public authorities from France and Germany.

Following the dialogue, participants identified the following key challenges for building Europe’s quantum future:

  1. Use Cases: A concrete, industry-driven pipeline of end-to-end use cases should be developed, aligned with realistic expectations and a clear definition of what constitutes a “quantum advantage”.
  2. Success Stories: Successful examples that translate scientific achievements into businesses cases with tangible return on investment and operational impact should act as references across sectors.
  3. Benchmarking and management of expectations: A focus should be given to benchmarking our progress toward error-corrected and fault-tolerant systems. These will determine the long-term viability and sovereignty of European quantum technologies.
  4. European champions: Champions at the European level should be nurtured to build scale and reduce fragmentation, all while connecting national strengths, particularly in strategic domains.
  5. Trust / Intellectual Property: Intellectual property rules in both countries should be clarified and harmonized, while patents should continue to be incentivized.
  6. European strategies: Joint roadmaps and funding strategies should be developed across countries to avoid duplicating efforts and promote shared projects with long-term impact.
  7. Funding: Investment funds and private capital should be mobilised to stimulate industrial co-development and adoption of quantum solutions. Public funding programs should expand, and public authorities and funding agencies should streamline cross-border funding through a single-entry point.
  8. Talents: Talent training should be prioritised, for example by developing shared talent platforms and joint doctoral schools and study schemes.
  9. Gathering of ecosystems among France and Germany: Creative formats of collaboration across countries should be developed, such as cross invitations at meetings, events, technology fairs, dedicated learning expeditions, and others.
  10. Dialogue governance: The Franco-German dialogue of quantum technology players should be followed up and expanded. Governance mechanisms should be supported jointly by France and Germany to ensure continuity, coordination, accountability, alignment with national strategies and dissemination of results and increased impact.

To master these challenges, participants have formulated concrete actions. You can find these in the complete version of our conclusion document, which you can download here