US quantum computing company D-Wave Quantum announced its July–September results and business progress on November 10, 2026. It also disclosed that it has reached a final agreement to receive up to $100 million in conditional support from the US Department of Commerce. The funds will be paid in stages as D-Wave meets set development goals and conditions, so receipt of the full amount is not yet assured. The support is an important source of funding for a company working to scale up its quantum computers, but it will also need to show concrete technical results.
In addition to quantum annealing, which solves combinatorial optimization problems, D-Wave is developing gate-model quantum computers that compute using circuits of quantum gates. The announcement covered NTT Docomo's commercial deployment, a gate-model simulator for developers, and technical targets for future large-scale systems. These achievements are not all at the same stage. Docomo's case is in use on a real telecommunications network, the gate-model development environment is an invitation-only simulator, and the large-scale systems covered by the government support are future development goals.
This information can be confirmed in D-Wave's earnings release, Docomo's official technical explanation, D-Wave's developer documentation, and similar sources. It is not a research result from a new peer-reviewed paper or preprint. The expansion of commercial contracts and the question of whether quantum computers outperform conventional methods must be judged on different evidence.
How quantum technology is used in Docomo's commercially deployed base-station optimization
NTT Docomo uses quantum technology to optimize how base stations in its mobile network are grouped. To manage device locations, mobile networks use "tracking areas (TAs)", which are groups of base stations, and "TA-Lists", which combine multiple TAs. When a device moves out of its managed range, it must register its location with the network. When a call comes in, base stations in the target area send out a call signal known as "paging" to find the device.
This system involves two conflicting loads. Making a TA-List smaller means devices leave its range more often, which increases the signaling for location registration. Making it larger reduces the number of registrations but increases the number of base stations that must send paging signals when a call arrives. Reducing both location registration and paging therefore requires designing the combinations of base stations appropriately.
According to Docomo's official technical explanation, the company determines the optimal TA-List combinations using statistics on device movement and incoming calls, along with operational constraints such as routes where people's movement is concentrated. The system converts this problem into QUBO (Quadratic Unconstrained Binary Optimization) form, which quantum annealing can handle, and solves it. QUBO is a mathematical problem format that represents multiple choices as 0-and-1 variables and searches for the combination that minimizes an objective function. Because optimization algorithms on classical computers can also handle QUBO, adopting it does not in itself imply a quantum computational advantage.
In its earnings release, D-Wave described this system as its second commercial application for Docomo. It uses a hybrid approach combining quantum technology with classical computing, and in a representative problem covering 333 base stations, it reportedly completed optimization in about five minutes. However, that five-minute figure describes the whole problem and does not represent only the time the quantum computer spent computing. Nor do results for 333 base stations necessarily apply as they are to a large-scale problem covering base stations nationwide.
Docomo reports that, comparing before and after deployment in a specific area, signaling volume fell for both location registration and paging. This is a result showing operational improvement on a real communications network, but the published technical explanation alone does not give enough detail on the number of devices compared, the observation period, or the absolute signaling volumes before and after deployment. The comparison was also not a randomized controlled trial, and it did not isolate the effect of the quantum portion of the hybrid method. It is therefore not possible to attribute the entire reduction in signaling to the quantum computer.
Docomo's technical explanation is current as of February 13, 2026, and is not a new research result released alongside this earnings announcement. For D-Wave, it is an example showing commercial use is advancing, but verifying any advantage in computation speed or solution quality over conventional classical optimization methods would require comparisons using the same input data, constraints, and computing environment.
The gate-model quantum computer is at the invitation-only simulator stage
In addition to quantum annealing, D-Wave is developing gate-model quantum computers. However, the developer environment introduced this time is not a service that uses an actual quantum processor but a simulator that mimics the behavior of quantum circuits. According to D-Wave's developer documentation, the gate-model simulator on its cloud service Leap is offered to invited beta users and can be accessed through the company's Ocean SDK. It is an environment for designing and verifying quantum circuits that correspond to the operation of a dual-rail quantum processing unit the company plans to develop.
The dual-rail approach encodes one logical quantum state across two physical modes or similar components. Its characteristic is that it can be given a structure in which certain errors are easier to detect, and D-Wave has adopted it for developing its gate-model quantum computers. However, being able to detect errors is not the same as being able to correct all of them.
The developer documentation describes operations that detect errors partway through a quantum circuit, and a "postselection" mechanism that excludes trials in which errors were detected from the results. Postselection improves the quality of the adopted results by keeping only trials in which no errors were detected. On the other hand, the more trials are discarded, the more runs are needed to obtain valid results. There are also limits to the types of errors that can be detected, so not all errors can be identified.
Being able to try these mechanisms in a simulator is meaningful for advancing software development for future quantum hardware. But writing and running quantum circuits in a simulated environment is a separate matter from running the same circuits on real hardware with a high success rate. The developer documentation does not show the error rates of a large-scale gate-model machine, the number of physical qubits required for error correction, or measured results from stably running long quantum circuits. The launch of the simulator should therefore not be read as the completion of a large-scale, error-corrected quantum computer.
Up to $100 million in US government support, with 100,000 qubits and 100 logical qubits as development goals
Another notable development in this announcement is the final agreement with the US Department of Commerce on up to $100 million in conditional support. D-Wave's development goals include a quantum annealing system on the scale of 100,000 qubits and a gate-model quantum computer on the scale of 10,000 qubits. For the gate model, the company also aims for a system that forms 100 logical qubits through quantum error correction and can stably execute more than one million quantum operations.
The key point here is the difference between physical and logical qubits. Physical qubits are the individual qubits that make up a quantum processor. Logical qubits, in contrast, use multiple physical qubits combined with error detection and correction to handle quantum information more reliably. The number of physical qubits needed for error correction varies with the method and the hardware's error rates, so the performance of 100 logical qubits cannot be assessed from the 10,000-physical-qubit target alone.
The goal of stably executing more than one million quantum operations is likewise not an experimental result confirmed as achieved. A real assessment would require checking the error rate of each operation, the reduction in logical error rates through error correction, and the success rate when running long circuits. The government support is meant to back this development, but the funds are paid in stages as set conditions and milestones are achieved. The figure of up to $100 million cannot be treated as funds already received or as confirmed revenue.
Revenue rose 21%, but R&D spending more than doubled
While D-Wave's technical development advances, the burden of its R&D investment has grown on the financial side. According to the unaudited results the company published, revenue for July–September 2026 was $4.513 million, up about 21% from $3.739 million a year earlier. R&D expenses, however, more than doubled from $14.075 million a year earlier to $31.543 million. Even with revenue growing, R&D expenses alone amount to about seven times quarterly revenue.
Gross profit, an indicator of profitability, fell from $2.669 million a year earlier to $2.386 million. Gross margin also dropped 18.5 percentage points from 71.4% to 52.9%, so the revenue increase has not translated directly into improved profitability. The quarterly net loss narrowed from $139.986 million a year earlier to $48.197 million. However, the prior-year period included expenses from the fair-value remeasurement of warrants, whereas no similar expense arose this quarter, which also contributed. The narrower net loss should not be read as a result of core profitability improving by the same margin.
Order trends also need to be checked separately from revenue. Bookings for July–September 2026 were about $1.9 million, down from about $2.3 million a year earlier; the company's announcement puts this at roughly 19% lower year over year. Cumulative bookings for January–September rose sharply from about $5.3 million a year earlier to $37.4 million, but that figure includes $2.3 million in orders that Quantum Circuits, which D-Wave acquired earlier in the year, received just before the acquisition. The increase in cumulative bookings therefore cannot be attributed entirely to growth in D-Wave's existing business.
Remaining performance obligations, which indicate the backlog of contracts that will lead to future revenue, grew from $2.9 million at the end of the prior-year period to $38.3 million. Remaining performance obligations are the transaction price allocated to products, services, and the like that are under contract but not yet delivered. This figure covers non-cancelable contracts and excludes items such as renewal options customers have not yet exercised. The company expects to recognize about 59% of the $38.3 million as revenue within the next 12 months and about 71% within the next 24 months.
These numbers show that contracts leading to future revenue are increasing, but they are not amounts already recognized as revenue. Bookings, remaining performance obligations, and actual revenue each mean something different, so it will be necessary to keep checking how much the expansion of contracts translates into revenue growth.
How to evaluate commercial deployment, the simulator, and scale-up goals
D-Wave's announcement contains several developments toward the practical use of quantum computers, but the strength of the evidence behind them is not uniform. Docomo's network optimization is a case used in a real commercial environment, and the gate-model simulator is a development environment for future quantum hardware. The large-scale systems covered by the government support are technical goals yet to be achieved.
Based on Docomo's technical explanation, D-Wave's developer documentation, and the November 10, 2026 earnings release, the stage reached and the unverified items for each can be summarized as follows.
| Item | Stage currently confirmed | Remaining verification issues |
|---|---|---|
| Docomo TA-List optimization | Commercial network deployment and a reported reduction in signaling in a specific area | Comparison with classical computing under identical conditions; verification of the quantum portion's contribution |
| Gate-model development environment | Invitation-only beta simulator | Error rates on real hardware, circuit execution success rates, demonstration of quantum error correction |
| Scaling up quantum annealing | Development plan targeting the 100,000-qubit scale | Development of real hardware at the target scale and performance evaluation |
| Scaling up the gate model | Development goals such as 10,000 physical qubits and 100 logical qubits | Demonstration of logical qubits and stable execution of more than one million quantum operations |
This table compares different quantum computing approaches and development stages and does not indicate which is superior in qubit count or practicality. In particular, quantum annealing and gate-model quantum computers compute differently, so their computational power cannot be directly compared by physical qubit count alone.
Docomo's commercial deployment is an important example of a system incorporating quantum technology being used on a real communications network and leading to operational improvements. However, that alone does not prove that a quantum computer can obtain faster or higher-quality solutions than classical algorithms under identical conditions. For the gate model as well, building a simulator-based development environment must be clearly distinguished from completing real hardware with quantum error correction.
The materials reviewed do not show independent third-party performance comparisons under identical conditions, or demonstrations of logical qubits operating on large-scale gate-model hardware. Going forward, the results of comparisons with classical computing in commercial optimization, the error rates and quantum error correction performance of gate-model hardware, and progress toward the development goals tied to the US government's support conditions will serve as the basis for judging D-Wave's technical progress. It is important to evaluate the expansion of commercial use and improvements in quantum computing performance itself on separate, independent evidence.