Paris, France, March 16, 2026 -- Pasqal, a global leader in neutral-atom quantum computing and member of the NVIDIA Inception program for startups, announced today the integration of the NVIDIA CUDA-Q platform (“CUDA-Q”) with its Quantum Resource Management Interface (QRMI) runtime. The integration enables CUDA-Q workloads to be scheduled and orchestrated on Pasqal quantum systems through standard Slurm-based high-performance computing (“HPC”) workflows via QRMI, making quantum processors native accelerators in heterogeneous HPC environments. This milestone follows Pasqal’s recently announced path to go public through a business combination with Bleichroeder Acquisition Corp. II.

HPC centers and enterprise compute teams rely on proven operational models to run large-scale workloads securely and efficiently. By integrating CUDA-Q with QRMI, Pasqal aims to reduce adoption friction for HPC users by enabling quantum workloads within familiar Slurm job submission, scheduling, and monitoring workflows.

CUDA-Q, NVIDIA’s open-source platform, provides a unified programming framework combining CPUs and GPUs with quantum processors (“QPUs”). CUDA-Q enables tight interleaving of GPU-accelerated classical kernels and quantum routines running on Pasqal’s neutral-atom processors.

QRMI exposes QPUs as schedulable resources within Slurm, enabling secure authentication, allocation, and monitoring alongside CPUs and GPUs. Users submit jobs through standard HPC interfaces, and QPUs are provisioned automatically as part of the Slurm workflow when quantum workloads are executed. Designed to be hardware-, modality-, and vendor-agnostic, QRMI integrates quantum processors into existing HPC infrastructures without requiring changes to core operating models.

QRMI originated from an initiative established by IBM with collaborative development from Pasqal, RPI, and STFC Hartree Centre. This integration represents Pasqal’s next step in enabling production-grade hybrid HPC–quantum workflows and provides the foundation for additional on-premises software components in Pasqal’s stack.

Pasqal’s on-premises stack is intended to be first deployed at CINECA, integrating Pasqal’s QPU with Leonardo (the EuroHPC pre-exascale supercomputer co-funded by the Italian Ministry of University and Research, MUR) to enable Slurm-native hybrid GPU–QPU workloads. The integration is already available using QPUs on Pasqal’s cloud platform.

“HPC users don’t want a new operational model to access quantum capabilities. By integrating CUDA-Q into our HPC-native environment with the QRMI, we’re enabling Pasqal quantum processors to be used within hybrid GPU-QPU workflows leveraging the existing resource management systems HPC teams already run in production. This is a practical step toward making quantum acceleration usable at scale, alongside CPUs and GPUs, for real applications in optimization, simulation, and AI,” said Wasiq Bokhari, Pasqal’s Chief Executive Officer.

“CUDA-Q is designed to make hybrid quantum-classical computing accessible to developers by unifying quantum and HPC resources,” said Sam Stanwyck, Director of Quantum Product at NVIDIA. “By integrating CUDA-Q with QRMI, Pasqal is enabling developers to explore new hybrid quantum-classical applications at supercomputing centers around the world ”.

“Leonardo will be among Europe’s first supercomputers supporting hybrid HPC–QPU workloads in our standard Slurm environment,” said Sara Marzella, Responsible of Quantum Computing group at CINECA.