University of Strasbourg’s QPerfect aQCess Targets Over 400 Qubits

The University of Strasbourg’s aQCess platform is targeting more than 400 qubits as France’s first publicly accessible neutral-atom quantum computing platform, and QPerfect, a subsidiary of BTQ Technologies, is building a crucial tool to accelerate its development. QPerfect will create a hardware-accurate digital twin of the aQCess processor using its MIMIQ simulation platform, allowing researchers to design and test quantum workloads before running them on the physical system. This collaboration places QPerfect’s software directly alongside a sovereign European quantum computing initiative backed by the French National Strategy for Quantum Technologies and part of the Quantum Sciences and Technologies priority programme for research. “QPerfect’s collaboration with the University of Strasbourg reflects why BTQ moved to bring this team and technology into our platform,” said Olivier Roussy Newton, Chief Executive Officer of BTQ Technologies, emphasizing the company’s strategy of developing technologies across quantum software, hardware, and secure network infrastructure.

aQCess Platform Targets 400+ Qubit Neutral Atom Quantum Computing

The ambition to build practical quantum computers depends on scaling qubit counts while maintaining control and fidelity; the aQCess platform, spearheaded by the University of Strasbourg, directly addresses this challenge with a target exceeding 400 qubits. Co-coordinators Shannon Whitlock and Guido Pupillo lead the effort at the Centre Européen de Sciences Quantiques (“CESQ”) building a full-stack platform for multidisciplinary research spanning chemistry, materials science, and computer science. Central to accelerating development is a novel approach to software validation. “Every major shift in computing is won or lost at the interface between hardware and the software that makes it usable,” notes Philippe Blot, Chief Executive Officer of QPerfect. This close collaboration, with QPerfect’s team co-located with the aQCess hardware, provides a unique opportunity to refine software tools against a real, scaling quantum system.

Guido Pupillo explains that a trustworthy digital twin is essential to this mission, allowing users to begin work immediately and enabling validation of the machine as it scales. The platform, supported as part of the Quantum Sciences and Technologies priority programme for research (PEPR-Quantique: pepr-quantique.fr/projet/aqcess ), involves 18 partners and aims to make quantum computing more accessible on both national and international levels.

Every major shift in computing is won or lost at the interface between hardware and the software that makes it usable. I lived that with the transition to public key cryptography, and we are at exactly that point in quantum computing today.

Philippe Blot, Chief Executive Officer of QPerfect

The pursuit of practical quantum computers increasingly focuses on bridging the gap between theoretical potential and real-world implementation. While qubit counts steadily rise, validating software and optimizing performance on nascent hardware remains a significant challenge. MIMIQ aims to replicate the physical machine at the circuit level, encompassing the native gate set, instruction set architecture, and even experimentally characterized noise; this is more than standard simulation. This detailed mirroring, deployed both on premises at CESQ and as a cloud accessible service, allows researchers to design, test, and validate quantum workloads against a realistic model before running them on the actual hardware. The aQCess platform is based on a processor with more than 400 qubits.

aQCess is built to give France and Europe open access to leading neutral atom quantum hardware. A trustworthy digital twin is essential to that mission. It lets users get productive on day one and lets us validate the machine as it scales.

Guido Pupillo, Co-Coordinator of aQCess

This co-location of QPerfect’s software and CESQ’s hardware is intended to provide a hardware-accurate view of a scaling quantum system, supporting BTQ’s goal of developing trustworthy quantum technologies. Guido Masella of QPerfect and Stanimir Kondov of CESQ are leading the scientific effort.

BTQ builds trusted quantum technologies across silicon, blockchain and quantum networks. MIMIQ sits directly within that deployment layer, helping users run, validate and control quantum systems before and alongside real hardware. By placing QPerfect’s software stack alongside one of Europe’s leading neutral atom quantum computing initiatives, we are strengthening the tools needed to make quantum systems more usable, more reliable and more accessible as they scale.

The drive to build practical quantum computers increasingly focuses on the critical link between hardware and software, and a new collaboration between QPerfect and the University of Strasbourg’s aQCess platform exemplifies this trend. “Working closely with the aQCess team gives us something rare: a hardware accurate view of a real, scaling neutral atom machine,” said Guido Pupillo, Co-Coordinator of aQCess. Central to QPerfect’s approach is the Quantum Logic Unit, or QLU, a multi-layered framework designed to accelerate quantum development. The company’s flagship product, MIMIQ, forms the first layer of the QLU and is intended to offer a platform executing quantum algorithms with speed and accuracy. The aQCess platform itself is based on a processor with more than 400 qubits, aiming to provide open access to advanced neutral atom hardware.

Working shoulder to shoulder with the aQCess team gives us something rare: a hardware accurate view of a real, scaling neutral atom machine. That is how we make MIMIQ a faithful digital twin, and how we sharpen the compilation and error correction software, including our Quantum Logic Unit, QLU, that we are building for neutral atom systems as they scale toward 400 qubits and beyond.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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