HPE aims to position quantum computing within real supercomputing infrastructure, not as an isolated lab technology. The company announced at HPE Discover Las Vegas 2026 the expansion of its partnerships with eight companies in the quantum sector to advance hybrid platforms combining classical computing, supercomputing, artificial intelligence, and quantum processors.
These collaborations include Intel, IQM, Qblox, Quantinuum, QuEra Computing, Quantum Machines, Rigetti, and Riverlane. The list is no coincidence: it brings together manufacturers of quantum units, control specialists, error correction experts, and various qubit technologies. HPE’s goal is to build integrated testbeds where hybrid algorithms can be validated, software interoperability assessed, and the performance of quantum systems connected to HPC environments evaluated.
This news reflects an increasingly accepted idea in the industry: quantum computing will not replace classical supercomputers in the short term. If it becomes useful at an industrial scale, it will do so integrated with HPC and AI infrastructures, where each technology solves a different part of the problem.
A hybrid strategy, not a race for a single qubit type
HPE approaches its collaborations from a “full-stack hybrid quantum supercomputing” perspective. Practically, this means working across the entire stack: quantum hardware, control, error correction, software, interconnection, workflows, and performance evaluation.
The company does not rely on a single quantum modality. Instead, it explores multiple technologies in parallel: neutral atoms, ion traps, superconducting qubits, and spin qubits in silicon. Each has its own advantages and limitations regarding scalability, fidelity, control, temperature, manufacturability, or connectivity.
| Partner | Main area within the announcement |
|---|---|
| Intel | Silicon spin qubits and manufacturing capacity |
| IQM | Superconducting quantum systems |
| Quantinuum | Trapped ion quantum computing and software |
| QuEra Computing | Neutral atom-based quantum computing |
| Rigetti | Superconducting quantum processors |
| Qblox | Quantum control electronics and systems |
| Quantum Machines | Control and orchestration of quantum systems |
| Riverlane | Quantum error correction |
Technological diversity is important because the quantum market is still far from a definitive consensus. Some architectures excel in fidelity, others promise faster scalability, and some better suit industrial manufacturing processes. HPE is not trying to pick a winner now but aims to create an integration layer that can coexist with different approaches.
This approach aligns with its stance in supercomputing. With the HPE Cray platform, the company already supplies infrastructure to research centers, national laboratories, and major scientific facilities. If quantum computing needs to connect to classical systems for data preprocessing, algorithm execution, error correction, or result validation, HPE wants to be that integration layer.
Why supercomputing remains essential
Quantum computing is often presented as a technology capable of solving problems impossible for classical computers. That promise exists, but it still coexists with huge technical challenges. Current systems remain noise-sensitive, face scalability limitations, and require error correction to approach reliable applications.
This is where supercomputing plays a role. A hybrid flow can use a classical supercomputer to prepare data, split tasks, run complementary simulations, optimize circuits, interpret results, or coordinate multiple quantum resources. In some cases, the quantum component would act as a specialized accelerator within a broader workflow.
| Component | Role in a hybrid architecture |
| Classical supercomputer | Simulation, preprocessing, optimization, coordination |
| Quantum processor | Solving specific parts of the problem |
| Artificial intelligence | Search, parameter tuning, result analysis |
| Quantum control | Precise signal management and operation execution on qubits |
| Error correction | Noise reduction and reliability improvement |
| Orchestration software | Unifying resources in a common flow |
This integration will be necessary in fields such as computational chemistry, materials science, optimization, energy, pharmaceutical research, post-quantum cryptography, defense, and physical modeling. Not all applications will arrive simultaneously or with the same maturity, but they share a need: systems capable of combining classical and quantum resources without forcing researchers to work with disconnected platforms.
Trish Damkroger, senior vice president and general manager of HPC & AI Infrastructure Solutions at HPE, argued that integrating supercomputing and quantum technologies within a hybrid platform can accelerate the transition from research to real-world deployment. The phrase encapsulates the ambition well: to move quantum computing out of isolated demonstrations and into operational environments where it can be measured against scientific and industrial workloads.
From the lab to an integrated testbed
HPE’s new collaborations do not announce a single commercial quantum product nor a specific date for practical quantum advantage. The focus is on creating testbeds—integrated testing environments for evaluating algorithms, software, and architectures.
This nuance is important. Quantum computing still requires significant engineering work before becoming a routine business tool. HPE is operating in an intermediate phase: building infrastructure to test what works, how components connect, what performance levels are achievable, and which technologies can scale.
| Testbed goals | What they enable evaluating |
| Co-design of hybrid algorithms | Determining which parts run on classical vs. quantum hardware |
| Software interoperability | Ensuring compatibility between stacks, tools, and drivers |
| Performance benchmarking | Real measurements against HPC and AI workloads |
| Workflow validation | End-to-end execution of tasks |
| Modalities comparison | Strengths and limitations of each qubit type |
| Integration with AI factories | Using quantum alongside AI infrastructure |
HPE also mentions the relationship with AI environments. This does not mean quantum will replace GPUs. Rather, there is interest in how quantum systems could be part of broader infrastructures where HPC, AI models, simulations, and complex scientific workflows coexist.
In this context, “scaling” does not only mean more qubits. Scaling also involves stable control, error correction, interconnection, cooling, software, reliability, maintenance, security, and user-friendliness. A useful quantum system is not just a chip with many qubits but a complete platform that can be integrated into real operations.
Error correction and control: two decisive pieces
Two areas within HPE’s strategy deserve special attention: quantum error correction and control systems. Without them, transitioning to practical applications will be very difficult.
Qubits are extremely fragile. Any unintended environmental interaction can degrade the calculation. Error correction aims to detect and fix these faults but requires additional resources and precise coordination between hardware and software. Riverlane appears in the announcement precisely for its role in this area.
Quantum control, in turn, is the layer that enables precise operation of qubits. Companies like Qblox and Quantum Machines are developing the electronics, signals, and orchestration necessary to perform reliable quantum operations. Without quality control, a promising quantum processor cannot become a useful system.
| Technical challenge | Why it matters |
| Qubit noise | Reduces the reliability of calculations |
| Error correction | Allows closer to stable executions |
| Signal control | Enables precise operation of qubits |
| Hybrid orchestration | Coordinates classical, AI, and quantum resources |
| Benchmarks | Allow technology comparisons under real loads |
| Standards | Avoids closed systems that are hard to integrate |
For HPE, bringing together experts in these layers is as important as working with quantum processor manufacturers. Industry history shows that winning platforms depend not only on the chip but on the complete system surrounding it.
An ongoing industrial race
HPE’s announcement adds to a broader trend. Tech giants, national laboratories, supercomputing centers, and startups are trying to connect their advances with classical infrastructure. IBM, Google, Microsoft, Quantinuum, IonQ, Rigetti, IQM, QuEra, and others are pursuing different paths, while US, European, and Asian governments fund strategic programs.
Europe is also progressing in hybrid systems linked to supercomputing, with projects driven by EuroHPC and national centers. For the public sector, quantum computing is associated with technological sovereignty, security, materials, energy, and defense. For private companies, the focus is on applications where a small but tangible advantage could justify significant investments.
HPE seeks a cross-cutting position: not just a provider of classical hardware nor solely an integrator, but a platform connecting various quantum technologies with supercomputing and AI. This is a reasonable bet because it reduces dependency on a single quantum architecture and leverages its installed HPC base.
The challenge will be transforming research collaborations into operational, measurable, and useful systems. The quantum industry has promised a lot for years, and timelines remain uncertain. The key difference now is that the debate has shifted from scientific headlines to engineering details: system connectivity, programming, error correction, and how to measure value against a classical supercomputer.
HPE is not claiming that practical quantum computing has arrived. Instead, it’s laying the groundwork so that when it becomes useful, it won’t be an isolated technological island. The most important takeaway may be that quantum will have greater potential if it’s born integrated into the supercomputing environments already in use by researchers, governments, and industries.
FAQs
What did HPE announce at HPE Discover 2026?
HPE expanded collaborations with Intel, IQM, Qblox, Quantinuum, QuEra Computing, Quantum Machines, Rigetti, and Riverlane to develop hybrid platforms integrating supercomputing, AI, and quantum computing.
What does hybrid classical-quantum computing mean?
It refers to a system where classical supercomputers and quantum processors work together. The classical system manages coordination, preprocessing, and analysis tasks, while the quantum processor handles specific problem parts.
Why is HPE working with multiple qubit technologies?
Because the quantum industry has not yet chosen a dominant architecture. HPE aims to explore neutral atoms, ion traps, superconductors, and silicon spin qubits to compare their advantages and limitations.
What roles do error correction and quantum control play?
They are essential for making quantum systems reliable. Error correction detects and fixes faults, while control systems enable precise operation of qubits.
via: hpe
