Alice & Bob and Hyperion Research outline HPC–quantum–AI integration requirements, shifting competition from QPU to system integration

【Article Title】 Alice & Bob and Hyperion Research outline HPC–quantum–AI integration requirements, shifting competition from QPU to system integration 【Article Body】 AI TRANSLATION This article is an AI-generated translation of the original Japanese article. For the authoritative version, please refer to the original. Read the original Japanese article → (https://quantumindex.jp/alice-bob-hpc-quantum-ai-full-stack-report/) Alice & Bob and Hyperion Research have published a report summarizing requirements for integrating HPC, quantum, and AI. Based on interviews with 15 officials and engineers from major supercomputing organizations, the report argues that a quantum processorquantum processorQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together.’s value is determined not only by qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. count but by the overall system that includes software, hybrid workflows, and operational capability. ✍️ Quantum Index Analysis We explain the technical and business implications behind the announcement and the evaluation points that aren’t obvious from headlines or numbers. Read our analysis ↓ Report overview The report, “HPC-Quantum-AI: Shaping the Next Compute Era,” was compiled from interviews with leaders and engineers at supercomputing organizations in Europe, the Asia-Pacific region, and the United States. Interviewees included representatives from Argonne National Laboratory, Lawrence Berkeley National Laboratory/NERSC, Oak Ridge National Laboratory, and RIKEN. As priorities, the report recommends empirically measuring how tightly quantum, classical, and AI computing should be connected; establishing open standards in a software layer that are independent of qubit modality; and co-designing workflows between HPC/AI experts and quantum vendors. For connection approaches, it states that measurements of the latency tolerable for each workload should serve as a basis for decisions. On the software side, the report proposes standardization for device management and job submission while advocating that compilers and programming models remain competitive. It also discusses the importance of on-premises deployments that allow centers to operate quantum machines themselves and accumulate integration experience. Key points • The report is based on interviews with 15 leaders, quantum program managers, and engineers at major supercomputing organizations. • It recommended measuring workload latency tolerance to determine appropriate coupling methods between quantum, classical, and AI computing. • It proposed open standards for device management and job submission while keeping competition in compilers and programming models. • As a co-design example, it introduced a quantum chemistry workflow aiming for a 10,000× speedup. • It warned that early deployment of immature stacks could undermine trust in quantum computing within the HPC community. Technical and business implications On the technical side, the report organizes the view that evaluation should consider not only the performance of fault-tolerant quantum hardware but also connection latency, job management, software standards, and application design as an integrated whole. On the business side, it suggests that HPC centers that have accumulated operational experience through testbeds and on-premises environments will have an advantage when adopting early fault-tolerant quantum machines. However, the report does not provide commercialization timelines, cost estimates, or verified performance results, so its recommendations should be distinguished from demonstrated outcomes. Points to watch Going forward, the focus will be whether latency between quantum, classical, and AI components can be measured on real workloads so that connection approaches can be compared. It will also be important to see whether common specifications for device management and job submission are concretized, whether comparative results support the speedup goals of the jointly designed quantum chemistry workflow, and whether on-premises deployment examples and business information such as costs and availability dates are disclosed. ✍️ Quantum Index Analysis The important point of this report is not that it defines a new metric for quantum computers, but that it organizes the conditions under which a QPUQPUQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together. is “usable” from the perspective of HPC. The argument is that evaluation should include not only qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. count but also connection latency, job management, software standards, on-premises operation, and application design. That said, even though the report is based on interviews with 15 HPC stakeholders, one should not treat the results as the unanimous view of the entire industry. The selection of whom to interview, how responses are framed, and which recommendations are emphasized all reflect the compilers’ judgments. In particular, conclusions that emphasize “tight integration with HPC,” “on-premises operational experience,” and “hybrid workflows” align with Alice & Bob’s own strategy of pursuing QPU adoption in HPC environments; reading this as evidence that the 15 experts fully endorse that company’s strategy would be an overstatement. Conversely, it would also be inappropriate to dismiss this direction as merely Alice & Bob’s position. IBM has been pursuing a concept of “Quantum-Centric Supercomputing” that operates QPUs, CPUs, and GPUs together, and RIKEN has been building a quantum–HPC integration platform connecting ROQUO, Fugaku, IBM Quantum System Two “ibm_kobe,” and Quantinuum’s “Reimei.” In the Cleveland Clinic–RIKEN–IBM chemical computation project, they combined QPUs with multiple supercomputers to handle a 12,635-atom protein system and advanced workflow automation across multiple quantum and classical compute resources on ROQUO. Read about the Cleveland Clinic, RIKEN, and IBM chemical computation (https://en.quantumindex.jp/cleveland-clinic-riken-ibm-gordon-bell-finalists-2026/). In other words, this report is less a presentation of a new market vision than an organization of the requirements that have already started to emerge: treating QPUs not as standalone computers but as heterogeneous accelerators within HPC. In addition to competition over quantum-hardware performance, a new axis of competition will be how low-latency and easy-to-integrate QPUs can be made within existing CPU/GPU environments and how much value they can deliver in real scientific computing workflows. For Alice & Bob, the question is therefore less about making the report’s recommendations and more about how far they can implement them in their own systems. Future evaluation will focus on concrete HPC integration performance including connection latency and job management, actual deployments at supercomputing centers, and what differentiations they can demonstrate against other vendors such as IBM and Quantinuum that have already begun building integration track records. NETWORKSee the industry network around Alice & Bob → (/qi-network/) Related • Cleveland Clinic, RIKEN, and IBM: quantum–HPC chemistry computation shortlisted for the Gordon Bell Prize (12,635-atom system) (https://en.quantumindex.jp/cleveland-clinic-riken-ibm-gordon-bell-finalists-2026/) • Ranking and outlook for 29 quantum computing companies (Summer 2026) (https://en.quantumindex.jp/top-29-quantum-companies-ranking-summer-2026/) • Alice & Bob joins QuBriC, an EU doctoral network focused on quantum error correction (https://en.quantumindex.jp/alice-bob-joins-qubric-qec-doctoral-network/) • Alice & Bob announces Helium, an 18-cat qubit on-premises quantum system (https://en.quantumindex.jp/alice-bob-helium-quantum-system/) Source Read the original announcement (https://alice-bob.com/newsroom/hpc-quantum-report/) If you found this article useful, please consider sharing it. ──────────────────── 【AI Evaluation Request】 Evaluate the following article critically, not based on the quality of its writing, but on its **original informational value as a specialist publication**. Do not give a high rating to summaries, paraphrases, explanations of technical terms, or generic observations such as "this will be worth watching" or "the timeline remains uncertain" if they could easily be produced by a general-purpose generative AI, even if they are well written. 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However, do not give an S rating merely because the article contains a large amount of information, covers many subjects, or uses extensive technical terminology. In particular, consider the following points. * Does the article contain information or perspectives that would be difficult to obtain simply by reading the original announcement? * Does it contain comparisons, reasoning, verification, or evaluation specific to the subject? * Does it integrate multiple pieces of information to provide a new understanding or broader picture? * Could the content easily be produced by a general-purpose generative AI? * Are you avoiding giving a high rating merely because the article uses technical terminology or headings such as "Analysis" or "Key Points"? In your response, first briefly show the **S–D rating scale above**, and then clearly indicate **where this article falls within that scale**. 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Alice & Bob and Hyperion Research have published a report summarizing requirements for integrating HPC, quantum, and AI. Based on interviews with 15 officials and engineers from major supercomputing organizations, the report argues that a quantum processorquantum processorQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together.’s value is determined not only by qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. count but by the overall system that includes software, hybrid workflows, and operational capability.

Report overview

The report, “HPC-Quantum-AI: Shaping the Next Compute Era,” was compiled from interviews with leaders and engineers at supercomputing organizations in Europe, the Asia-Pacific region, and the United States. Interviewees included representatives from Argonne National Laboratory, Lawrence Berkeley National Laboratory/NERSC, Oak Ridge National Laboratory, and RIKEN. As priorities, the report recommends empirically measuring how tightly quantum, classical, and AI computing should be connected; establishing open standards in a software layer that are independent of qubit modality; and co-designing workflows between HPC/AI experts and quantum vendors. For connection approaches, it states that measurements of the latency tolerable for each workload should serve as a basis for decisions. On the software side, the report proposes standardization for device management and job submission while advocating that compilers and programming models remain competitive. It also discusses the importance of on-premises deployments that allow centers to operate quantum machines themselves and accumulate integration experience.

Key points

• The report is based on interviews with 15 leaders, quantum program managers, and engineers at major supercomputing organizations.
• It recommended measuring workload latency tolerance to determine appropriate coupling methods between quantum, classical, and AI computing.
• It proposed open standards for device management and job submission while keeping competition in compilers and programming models.
• As a co-design example, it introduced a quantum chemistry workflow aiming for a 10,000× speedup.
• It warned that early deployment of immature stacks could undermine trust in quantum computing within the HPC community.

Technical and business implications

On the technical side, the report organizes the view that evaluation should consider not only the performance of fault-tolerant quantum hardware but also connection latency, job management, software standards, and application design as an integrated whole. On the business side, it suggests that HPC centers that have accumulated operational experience through testbeds and on-premises environments will have an advantage when adopting early fault-tolerant quantum machines. However, the report does not provide commercialization timelines, cost estimates, or verified performance results, so its recommendations should be distinguished from demonstrated outcomes.

Points to watch

Going forward, the focus will be whether latency between quantum, classical, and AI components can be measured on real workloads so that connection approaches can be compared. It will also be important to see whether common specifications for device management and job submission are concretized, whether comparative results support the speedup goals of the jointly designed quantum chemistry workflow, and whether on-premises deployment examples and business information such as costs and availability dates are disclosed.

✍️ Quantum Index Analysis

The important point of this report is not that it defines a new metric for quantum computers, but that it organizes the conditions under which a QPUQPUQuantum Processor / Quantum Processor / Quantum Processing Unit / QPUThe central part of the hardware that houses qubits and performs quantum computational operations such as quantum gates and measurements.QI NoteThe performance of a QPU cannot be judged by the number of qubits alone. Gate fidelity, connectivity, speed, error rates, and other factors must be considered together. is “usable” from the perspective of HPC. The argument is that evaluation should include not only qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. count but also connection latency, job management, software standards, on-premises operation, and application design.

That said, even though the report is based on interviews with 15 HPC stakeholders, one should not treat the results as the unanimous view of the entire industry. The selection of whom to interview, how responses are framed, and which recommendations are emphasized all reflect the compilers’ judgments. In particular, conclusions that emphasize “tight integration with HPC,” “on-premises operational experience,” and “hybrid workflows” align with Alice & Bob’s own strategy of pursuing QPU adoption in HPC environments; reading this as evidence that the 15 experts fully endorse that company’s strategy would be an overstatement.

Conversely, it would also be inappropriate to dismiss this direction as merely Alice & Bob’s position. IBM has been pursuing a concept of “Quantum-Centric Supercomputing” that operates QPUs, CPUs, and GPUs together, and RIKEN has been building a quantum–HPC integration platform connecting ROQUO, Fugaku, IBM Quantum System Two “ibm_kobe,” and Quantinuum’s “Reimei.” In the Cleveland Clinic–RIKEN–IBM chemical computation project, they combined QPUs with multiple supercomputers to handle a 12,635-atom protein system and advanced workflow automation across multiple quantum and classical compute resources on ROQUO. Read about the Cleveland Clinic, RIKEN, and IBM chemical computation.

In other words, this report is less a presentation of a new market vision than an organization of the requirements that have already started to emerge: treating QPUs not as standalone computers but as heterogeneous accelerators within HPC. In addition to competition over quantum-hardware performance, a new axis of competition will be how low-latency and easy-to-integrate QPUs can be made within existing CPU/GPU environments and how much value they can deliver in real scientific computing workflows.

For Alice & Bob, the question is therefore less about making the report’s recommendations and more about how far they can implement them in their own systems. Future evaluation will focus on concrete HPC integration performance including connection latency and job management, actual deployments at supercomputing centers, and what differentiations they can demonstrate against other vendors such as IBM and Quantinuum that have already begun building integration track records.

NETWORKSee the industry network around Alice & Bob →

Related

• Cleveland Clinic, RIKEN, and IBM: quantum–HPC chemistry computation shortlisted for the Gordon Bell Prize (12,635-atom system)
• Ranking and outlook for 29 quantum computing companies (Summer 2026)
• Alice & Bob joins QuBriC, an EU doctoral network focused on quantum error correction
• Alice & Bob announces Helium, an 18-cat qubit on-premises quantum system

Source

Read the original announcement