Diraq says commercial quantum value should be measured by cost per logical operation

【Article Title】 Diraq says commercial quantum value should be measured by cost per logical operation 【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/diraq-logical-operation-cost-metric/) Diraq argues that judging the commercial value of quantum computers requires evaluating 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 the number of logical quantum operations per second and the cost per logical operation. The company also provides preliminary estimates of computation time and cost for materials-science and quantum-chemistry problems assuming future practical-scale systems. ✍️ Quantum Index Analysis We explain the technical and business implications behind the announcement and evaluation points that are not obvious from numbers or headlines alone. Read our exclusive analysis ↓ Announcement summary Under Diraq’s framework, the cost per logical quantum operation is calculated by dividing the system’s operational cost per second by the number of logical quantum operations the system can process in the same time. The number of logical operations required by a quantum algorithm is determined by the target problem and can only be reduced through algorithmic improvements. The company explains there are two conditions for commercializing quantum algorithms. First, the system must provide the required number of error-corrected logical qubitslogical qubitsLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. to represent the problem. Second, the computation must complete within a time and cost acceptable to the customer. Assuming the same type of quantum low-density parity-check (qLDPC) codes reported by partner Iceberg Quantum, Diraq performed preliminary calculations of logical-operation speeds for future practical-scale systems. Their estimates suggest that models for high-temperature superconductors and standard models for correlated electrons could be processed in under an hour at costs ranging from a few dollars to several thousand dollars. Quantum-chemistry simulations related to solar-cell improvements are estimated to take several hours at a cost of a few thousand dollars. A FeMoCo-class cluster is estimated to require 2.85×10^14 logical operations, taking several weeks and costing on the order of several million dollars to complete. The company notes that comparisons between platforms should consider not only operation speed but also operational expenses—including cooling, control, and supporting infrastructure—and the incremental cost of adding qubits. On that basis, Diraq suggests silicon spin qubits could be advantageous in terms of cost per logical operation. Key points • Proposes logical-operation throughputthroughputThroughput / ThroughputA metric indicating the amount of work that can be processed per unit time. In quantum computing, it represents how quickly circuits or jobs can be repeatedly executed, among other things.QI NoteThe definition and units of throughput vary between companies and systems. When comparing, check not only the raw number of executions but also conditions such as circuit size, accuracy, and wait times. and cost per logical operation as evaluation metrics for quantum computers. • Defines cost per logical operation as the system’s operational cost per second divided by the number of logical quantum operations per second. • Commercial viability requires both the necessary number of logical qubits and completion within acceptable time and cost for customers. • Provides preliminary estimates of computation time and cost for materials-science and quantum-chemistry tasks assuming qLDPC-coded, practical-scale future systems. • The per-use estimates are Diraq’s preliminary calculations for future systems; detailed assumptions and independent verification are not provided. Technical and business implications Technically, this shifts comparison metrics away from raw qubit counts toward an assessment that combines usable, error-corrected computational capacity and operating cost. Even with sufficient logical qubits, slow logical-operation speeds raise execution time and cost, so throughput becomes a key practical metric. From a business perspective, the framework offers a way to estimate the price of computation services by multiplying the required number of logical operations for an application by the cost per logical operation. However, the times and costs presented are Diraq’s preliminary estimates for future systems and do not reflect current device performance or third-party evaluations. What to watch next Going forward, attention will focus on how much the company discloses about the hardware configuration, error rates, and qLDPC implementation conditions used to derive logical-operation speeds and operating costs. It will be important to see whether equivalent throughput can be demonstrated on real hardware and whether the application-specific estimates for materials science and FeMoCo are reproducible in independent comparisons. Additionally, whether the assumed cost per logical operation can be maintained when scaling system size—including cooling and control costs—will be decisive for commercial viability. ✍️ Quantum Index Analysis Diraq’s argument is that the commercial value of quantum computers should be judged by the actual time and cost required to run computations, not 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 alone. That rationale is reasonable, but not new: in addition to logical qubitlogical qubitLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. counts, practitioners have long recognized that operation speed, error-correction overhead, and system-wide operating costs determine practical utility. However, cost per logical operation alone may not provide a fair basis for comparing different approaches. The types of gates, parallelization capability, and error-correction schemes change actual runtimes and required resources. Also, the application-specific times and costs Diraq presents are preliminary estimates for future systems and have not been validated on hardware. There is also a strategic element in proposing an evaluation axis that favors its own silicon-spin approach. Diraq emphasizes semiconductor manufacturing’s strengths in high integration and low cost, and attempts to link those advantages to competitiveness in cost per logical operation. But a low manufacturing cost per physical qubitphysical qubitPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. does not automatically imply a low total computational cost once error correction and system-level factors are included. It is important to separate the reasonableness of the metric from any claimed advantage for the company’s chosen platform. NETWORKSee Diraq’s industry network → (/qi-network/) Sources Read the original announcement (https://www.diraq.com/newsdesk/customers-dont-want-qubits-they-want-answers) 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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Diraq argues that judging the commercial value of quantum computers requires evaluating 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 the number of logical quantum operations per second and the cost per logical operation. The company also provides preliminary estimates of computation time and cost for materials-science and quantum-chemistry problems assuming future practical-scale systems.

Announcement summary

Under Diraq’s framework, the cost per logical quantum operation is calculated by dividing the system’s operational cost per second by the number of logical quantum operations the system can process in the same time. The number of logical operations required by a quantum algorithm is determined by the target problem and can only be reduced through algorithmic improvements. The company explains there are two conditions for commercializing quantum algorithms. First, the system must provide the required number of error-corrected logical qubitslogical qubitsLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. to represent the problem. Second, the computation must complete within a time and cost acceptable to the customer. Assuming the same type of quantum low-density parity-check (qLDPC) codes reported by partner Iceberg Quantum, Diraq performed preliminary calculations of logical-operation speeds for future practical-scale systems. Their estimates suggest that models for high-temperature superconductors and standard models for correlated electrons could be processed in under an hour at costs ranging from a few dollars to several thousand dollars. Quantum-chemistry simulations related to solar-cell improvements are estimated to take several hours at a cost of a few thousand dollars. A FeMoCo-class cluster is estimated to require 2.85×10^14 logical operations, taking several weeks and costing on the order of several million dollars to complete. The company notes that comparisons between platforms should consider not only operation speed but also operational expenses—including cooling, control, and supporting infrastructure—and the incremental cost of adding qubits. On that basis, Diraq suggests silicon spin qubits could be advantageous in terms of cost per logical operation.

Key points

• Proposes logical-operation throughputthroughputThroughput / ThroughputA metric indicating the amount of work that can be processed per unit time. In quantum computing, it represents how quickly circuits or jobs can be repeatedly executed, among other things.QI NoteThe definition and units of throughput vary between companies and systems. When comparing, check not only the raw number of executions but also conditions such as circuit size, accuracy, and wait times. and cost per logical operation as evaluation metrics for quantum computers.
• Defines cost per logical operation as the system’s operational cost per second divided by the number of logical quantum operations per second.
• Commercial viability requires both the necessary number of logical qubits and completion within acceptable time and cost for customers.
• Provides preliminary estimates of computation time and cost for materials-science and quantum-chemistry tasks assuming qLDPC-coded, practical-scale future systems.
• The per-use estimates are Diraq’s preliminary calculations for future systems; detailed assumptions and independent verification are not provided.

Technical and business implications

Technically, this shifts comparison metrics away from raw qubit counts toward an assessment that combines usable, error-corrected computational capacity and operating cost. Even with sufficient logical qubits, slow logical-operation speeds raise execution time and cost, so throughput becomes a key practical metric. From a business perspective, the framework offers a way to estimate the price of computation services by multiplying the required number of logical operations for an application by the cost per logical operation. However, the times and costs presented are Diraq’s preliminary estimates for future systems and do not reflect current device performance or third-party evaluations.

What to watch next

Going forward, attention will focus on how much the company discloses about the hardware configuration, error rates, and qLDPC implementation conditions used to derive logical-operation speeds and operating costs. It will be important to see whether equivalent throughput can be demonstrated on real hardware and whether the application-specific estimates for materials science and FeMoCo are reproducible in independent comparisons. Additionally, whether the assumed cost per logical operation can be maintained when scaling system size—including cooling and control costs—will be decisive for commercial viability.

✍️ Quantum Index Analysis

Diraq’s argument is that the commercial value of quantum computers should be judged by the actual time and cost required to run computations, not 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 alone. That rationale is reasonable, but not new: in addition to logical qubitlogical qubitLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. counts, practitioners have long recognized that operation speed, error-correction overhead, and system-wide operating costs determine practical utility.

However, cost per logical operation alone may not provide a fair basis for comparing different approaches. The types of gates, parallelization capability, and error-correction schemes change actual runtimes and required resources. Also, the application-specific times and costs Diraq presents are preliminary estimates for future systems and have not been validated on hardware.

There is also a strategic element in proposing an evaluation axis that favors its own silicon-spin approach. Diraq emphasizes semiconductor manufacturing’s strengths in high integration and low cost, and attempts to link those advantages to competitiveness in cost per logical operation. But a low manufacturing cost per physical qubitphysical qubitPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. does not automatically imply a low total computational cost once error correction and system-level factors are included. It is important to separate the reasonableness of the metric from any claimed advantage for the company’s chosen platform.

NETWORKSee Diraq’s industry network →

Sources

Read the original announcement