# HPE brings quantum computing to real-world use cases with HPC and AI > Source: > Published: 2026-08-04 19:16:33+00:00 ### HPE brings quantum computing to real-world use cases with HPC and AI Quantum hybrid computing is moving from a hardware race to an integration challenge — and Hewlett Packard Enterprise Co. is positioning itself around the infrastructure layer that connects quantum with HPC and AI. During [HPE’s World Quantum Day](https://siliconangle.com/tag/hpeworldquantumday26eventpage/) event, researchers, national laboratory representatives and analysts reached a similar conclusion: Quantum will not replace today’s systems. Instead, it will become another important capability inside HPC, AI, networking and software environments. The challenge is no longer just building better quantum processors. It is connecting quantum systems to the classical infrastructure around them. “Quantum computing will not be defined by replacing classical computing, but by extending it,” said [Dave Vellante](https://www.linkedin.com/in/dvellante), chief analyst at theCUBE Research. [Paul Gillin](https://www.linkedin.com/in/paulgillin), enterprise editor at SiliconANGLE Media, reached a similar conclusion after conversations with quantum researchers: “The industry’s focus has shifted from building general-purpose quantum computers to integrating quantum technology with high-performance computing,” he said. It makes sense that HPE would be highly invested in this evolving space; the shift aligns with the company’s core strengths. Quantum’s next phase will depend less on standalone processors and more on the infrastructure, orchestration and hybrid environments that make quantum useful. *This feature is part of SiliconANGLE Media’s exploration of quantum computing’s shift from research to real-world use. Be sure to check out SiliconANGLE’s exclusive coverage of the HPE World Quantum Day event, an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. (* Disclosure below.)* ### Quantum expectations are maturing from hype to disciplined progress Quantum computing has spent years caught between revolutionary promises and engineering reality. HPE has focused on integrating quantum into the HPC and AI environments researchers already use. Early forecasts suggested quantum computers would move quickly out of research laboratories and into widespread commercial use. The industry’s progress has followed a much slower and more measured path, Gillin explained. “Those predictions proved to be wildly over-optimistic,” he said. Near-term applications are instead becoming more focused, including molecular simulation, materials discovery, optimization and scientific workloads where quantum effects matter. “Practical applications will emerge slowly and in niches,” Gillin added. That outlook echoed across HPE’s research ecosystem. Oak Ridge National Laboratory’s [Tom Beck](https://www.linkedin.com/in/tom-beck-675950234) emphasized hybrid workflows over standalone quantum systems. Meanwhile, [Amir Shehata](https://www.linkedin.com/in/amir-shehata-6998b747), a high-performance computing systems engineer in the Quantum-HPC Group at Oak Ridge National Laboratory, identified software integration as a central challenge: “Your software stack that you’re developing has to handle all these different types of requirements that are being thrown at you from the hardware side.” The industry is now focused on engineering problems — error correction, fault tolerance, software integration and workflow design — rather than waiting for a single breakthrough machine. Quantum adoption depends on building systems in which quantum works alongside classical computing. ### HPE’s quantum hybrid computing argument: Quantum works with HPC and AI This year’s World Quantum Day’s central theme was that quantum will not replace HPC and AI. It will become [another capability](https://www.forbes.com/sites/gilpress/2025/04/08/the-coming-convergence-of-ai-and-quantum-computing/) inside existing systems. “We believe the practical path forward is hybrid,” Vellante said. “In other words, bringing CPUs, GPUs and QPUs together through HPC and AI workflows so researchers and enterprises can apply quantum selectively to problems that are beyond the reach of today’s systems.” The approach mirrors modern supercomputing, where heterogeneous architectures are standard.[ Oak Ridge National Laboratory’s Frontier supercomputer](https://www.olcf.ornl.gov/frontier/) combines CPUs and GPUs for exascale scientific computing. Quantum systems could become another accelerator, not a replacement. The industry’s view has shifted, according to Gillin. “We’re no longer looking at quantum as being a replacement for conventional traditional computer architectures, but really a complement to them,” he said. Researchers now focus on integrating quantum into existing supercomputing environments. The challenge is seamless integration, according to Shehata. The goal is a unified system where different architectures work together. “You want to be able to make it as seamless as possible for the user,” he said. ### Quantum hybrid computing architecture: Middleware, orchestration and workflows Quantum adoption depends on integrating quantum systems into existing computing environments. Shehata described a full-stack challenge. A key initiative addressing it is the [Open Quantum-HPC Software Ecosystem, or openQSE](https://www.openqse.org/). “You have to start at the top of the stack and go all the way down to the bottom of the stack,” he said. “Your software stack that you’re developing has to handle all these different types of requirements that are being thrown at you from the hardware side.” Different quantum technologies create different constraints. Middleware must accommodate those differences within existing HPC workflows. “You want to be able to make it as seamless as possible for the user,” Shehata added. [Dieter Kranzlmüller](https://de.linkedin.com/in/dieter-kranzlmueller), chairman of the board at the Leibniz Supercomputing Centre, described quantum as [another HPC accelerator](https://siliconangle.com/2026/04/15/hybrid-quantum-hpc-computing-reshapes-infrastructure-hpeworldquantumday/). “The supercomputers will still be used for most of those things that it is excellent in,” he said. “But in addition to that, we will be utilizing quantum computers for those things where we already know today that the quantum computer is superior.” That requires new workflows. Shehata described systems where workloads move between classical and quantum resources: “You can do your classical preprocessing, you can collect some data from there, then you free your HPC resources, then you move towards quantum resources where you run your circuits.” Gillin identified software accessibility as a major barrier: “We need a Python for quantum. Higher-level tools must emerge before quantum programming expands beyond specialists.” That software challenge is becoming a research focus. An [April 2026 survey](https://arxiv.org/abs/2601.20247) of quantum-HPC software stacks found that existing systems remain fragmented and often lack common interfaces across runtime, resource management, orchestration and execution layers. The researchers proposed the openQSE reference architecture as a step toward more interoperable hybrid systems. For HPE’s hybrid computing vision, the processor is only one part of the system. Orchestration across compute, networking, storage and software will determine whether quantum becomes practical for scientific and industrial workloads. ### Early applications are emerging where quantum mechanics matters most Quantum computing is not aimed at everyday workloads. Its early value is expected in problems shaped by quantum mechanics, including chemistry, materials science and optimization. Researchers hope quantum systems can eventually simulate molecules, chemical reactions and materials more accurately than classical systems, potentially accelerating drug discovery and the development of batteries and advanced materials. [Mikael Johansson](https://fi.linkedin.com/in/mikael-p-johansson), manager of quantum technologies at CSC – IT Center for Science, identified [materials science, energy, pharmaceuticals, telecommunications and logistics](https://siliconangle.com/2026/04/15/quantum-technologies-eu-hybrid-computing-strategy-hpeworldquantumday/) as key areas. “Pharmaceuticals will benefit greatly from quantum computing,” he said. Kranzlmüller pointed to personalized medicine as another potential application. “We want to model the patient as a digital twin in the supercomputer and test how certain treatments work with that,” he said. Quantum is unlikely to have a sudden “ChatGPT moment,” according to Gillin. Instead, value will emerge in targeted areas such as “molecular modeling, complex drug interactions [and] advanced logistics.” The industry is focused on finding where quantum provides measurable advantages and integrating it into existing HPC and AI workflows, Vellante added. ### Hybrid quantum computing’s hard problems have not gone away Quantum computing still faces fundamental engineering challenges. Qubits are fragile, and environmental noise can disrupt calculations before they are complete. The path to quantum adoption is becoming less about replacing classical computing and more about building systems where quantum can work alongside it, reflecting [HPE’s hybrid quantum-classical supercomputing vision](https://siliconangle.com/2026/04/15/hybrid-quantum-hpc-computing-reshapes-infrastructure-hpeworldquantumday/). “The challenges are still real, from error correction and cooling to fragmented architectures and immature developer tools,” Vellante said. “But quantum has momentum and will become another powerful engine in the modern computing stack, not a standalone destination.” Error correction remains the key milestone, Shehata emphasized. “Error correction is key,” he said. Without it, quantum systems cannot run the deep circuits required for meaningful scientific applications. The challenge is not simply adding more qubits. It is creating reliable systems that can execute useful workloads. Superconducting systems also require complex cooling infrastructure, while different quantum architectures create distinct software and hardware requirements. The industry must solve hardware and integration challenges in parallel, according to Shehata. “You can’t focus on error correction only,” he said. “You have to look at everything at the same time.” Software remains another barrier. As Gillin noted, the industry still lacks “a Python for quantum” — accessible tools that allow more developers to build applications without programming directly at the qubit level. For HPE and the broader HPC ecosystem, the challenge is making quantum usable within existing computing environments. The focus is not replacing today’s infrastructure, but building the orchestration, networking and software layers needed to connect quantum processors with classical HPC and AI systems. ### HPE’s opportunity: Building the quantum-ready infrastructure layer Quantum computing’s next phase may not be won by the company with the largest processor, but by the companies that make quantum usable. That requires orchestration, middleware, networking, storage and integration with HPC and AI. “Companies like HPE and its ecosystem can play a critical role — helping make quantum part of a broader computing fabric,” Vellante said. That fabric will connect quantum processors with classical systems that prepare workloads, manage operations and analyze results. AI may assist with optimization and error correction, while HPC provides the surrounding compute infrastructure. The challenge is integration, according to Shehata. The objective is to make the interaction among those systems largely invisible to users, he noted. Kranzlmüller described quantum as an accelerator within larger computing environments. “The supercomputers will still be used for most of those things that it is excellent in,” he said, while quantum handles workloads where it has an advantage. “Quantum will become part of the computing landscape but won’t create a new frontier,” Gillin added. HPE’s opportunity is the integration layer: infrastructure that lets quantum, classical computing and AI operate together. [HPE’s hybrid quantum-classical approach](https://siliconangle.com/2026/04/14/quantum-computing-hpc-co-processor-hpeworldquantumday/) illustrates how that vision is beginning to take shape. The breakthrough may not be a standalone quantum machine, but the systems that make quantum accessible to researchers and enterprises. *(* Disclosure: TheCUBE is a paid media partner for the HPE World Quantum Day event. 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