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Run your analysis now →https://eureka.patsnap.com/resources/blog/rd-blog/quantum-approximate-optimization-algorithm-patent-landscape-patent-landscape/ · Patsnap · data cut-off 2026-08-31 · downloaded from the live page
Patent Landscape · Quantum ComputingQuantum Approximate Optimization Algorithm Patents: Who Leads and Where Filings Are Headed
A data-backed view of Quantum Approximate Optimization Algorithm patents: who holds the deepest filing positions, how the technology composition breaks down across IPC classes, and where filing activity is concentrated b
318
Published Records
26%
Top-5 Share of All Records
+31%
Filing Growth 2021→2024
US
Leading Jurisdiction
Filing growth = 2021 (32 records) → 2024 (42); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 318 records in scope (CR5), not the ranked leaders only.
Published byPatsnap Research··5 min readSourced from Patsnap Eureka
Overview
What the QAOA patent record shows
The Quantum Approximate Optimization Algorithm (QAOA) sits at the intersection of combinatorial optimization and near-term quantum hardware, and the patent record reflects that dual identity. Filings classified under G06N (AI-related computing models) touch every record in scope by definition of the search, but a large share also carries G06F digital-processing classes, showing that most claims describe classical-quantum hybrid execution rather than a pure quantum-only method. A smaller but consistent group of filings extends into B82Y nanotechnology and H04L/H04W communications classes, pointing to work on the physical qubit layer and on networked or distributed QAOA execution.
Filing activity has been rising since the first records appeared in 2017, with growth continuing through the most recent complete filing year. Because publication lags filing by roughly 18 months, the tail end of the trend in 2025 and 2026 will keep filling in and should not be read as a slowdown.
Filing activity by year
Source: Patsnap Eureka. Assignee ranking and totals. Derived from a Patsnap search on Quantum Approximate Optimization Algorithm Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
The Numbers
Filing trend and technology composition
Two views of the same 318-record dataset: how filing volume has moved year over year, and how those records distribute across IPC subclasses.
A decade of accelerating filings
Annual filings rose from 2 records in 2017 to a peak of 61 in 2022, with 2021 to 2024 alone showing 31% growth (32 to 42 records). Treat 2025 and 2026 figures as provisional, since publication lag means recent filings are still being disclosed.
Publication lags filing by roughly 18 months, so 2025 onwards are still filling in. Growth rates on this page therefore end at 2024; running them to the last bar would understate the field.
Where QAOA claims sit across the classification system
Every record in scope carries a G06N classification by construction of the search. Beyond that, 28.0% of records also carry G06F (classical-quantum hybrid processing), 8.8% carry G06Q (business and commerce applications such as portfolio or logistics optimization), and 7.2% carry B82Y (nanotechnology, largely qubit hardware). Communications-related classes (H04L, H04W) and power/pulse classes (H02J, H03K) each account for under 4% of records, marking them as the smaller, more specialized branches of the field.
Shares are the percentage of the 318 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from a Patsnap search on Quantum Approximate Optimization Algorithm Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.
Go deeper on Quantum Approximate Optimization Algorithm Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about quantum approximate optimization algorithm patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative Filing
A foundational parameter-selection patent
Representative Patent
Selecting parameters for a quantum approximate optimization algorithm (QAOA)
RIGETTI & CO, INC.
In a general aspect, values of input parameters for a quantum approximate optimization algorithm (QAOA) are selected by a Bayesian optimizer. The QAOA can be configured to solve a combinatorial optimization problem (COP), such as Maximum Cut. A hybrid classical-quantum computing system can be used to execute the QAOA and select the input parameters.Filed by Rigetti & Co, Inc.; published 2020-11-24.
Source: Patsnap Eureka. Citation counts and representative records. Derived from a Patsnap search on Quantum Approximate Optimization Algorithm Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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What the data means for filing strategy
Four figures from the dataset that matter more for decision-making than the headline counts.
Concentration
26.1%
of 318 records held by top 5 assignees
Leadership is real but not exclusive
The top 5 assignees combined hold 83 of the 318 records in scope, 26.1% of the field. That is a meaningful lead but far from a lock: nearly three-quarters of filings sit outside that group, spread across a ranked list that runs 100 companies deep.
Ranking basis: 318 records
Growth
+31%
growth 2021 to 2024
Filing momentum is still building
Annual filings grew from 32 in 2021 to 42 in 2024, a 31% rise over the last three-year span the data can treat as complete. Earlier peak-year activity in 2022 (61 records) suggests filing volume moves in bursts rather than a smooth curve.
2021-2024, complete years only
Composition
28.0%
of records also classified under G06F
Most claims describe hybrid execution, not pure quantum method
Beyond the universal G06N classification, the next-largest technical group is G06F (digital data processing), covering 28.0% of records. That signals most QAOA patents are written around the classical control and orchestration layer of hybrid classical-quantum systems, not the quantum circuit alone.
Classes overlap; shares exceed 100%
Geography
87
US-directed filings, the largest single office
Filing geography is broad, not single-jurisdiction
The United States leads with 87 filings, followed by China at 62 and India at 43, with WIPO (PCT) and EPO both in the mid-30s. That spread indicates applicants are pursuing multi-jurisdiction protection rather than concentrating on one home market.
By receiving office
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Looking for what nobody has claimed yet?
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to quantum approximate optimization algorithm patent landscape, with the prior art for and against each one.
Source: Patsnap Eureka. Derived observations on the same dataset. Derived from a Patsnap search on Quantum Approximate Optimization Algorithm Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Next Steps
Where to take this analysis
The figures above describe the field as a whole. Turning them into a filing or freedom-to-operate decision means drilling into specific claim language and specific assignees.
Map claim overlap against a specific hardware route
The IPC composition shows hybrid classical-quantum claims dominate, but which physical qubit modality a given filer targets is only visible at the claim level.
Explore claims in Eureka →Track the long tail of single-filing entrants
More than half of the 318 records sit outside the top 10 assignees; new entrants may be staking early positions in under-claimed branches before volume arrives.
Monitor new filers in Eureka →Check citation and continuation chains on foundational filings
Older parameter-selection and hybrid-execution patents accumulate citations simply by being early; verify which ones are still being actively cited by recent filings before treating them as blocking.
Run a citation check in Eureka →Source: Patsnap Eureka. Forward-looking reading of the same dataset. Derived from a Patsnap search on Quantum Approximate Optimization Algorithm Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
FAQ
Common questions about QAOA patents
The leading assignee in this dataset holds 24 of the 318 records in scope, with the fifth-ranked company at 14 and the tenth at 10. The ranking runs 100 companies deep, so while the leader has a clear edge, ownership of the field is far from concentrated in one hand. Reviewing the full ranked list is more useful than fixating on the single leader, since the top 10 combined only cover 43.4% of all records.
Filings rose from just 2 records in 2017 to a peak of 61 in 2022, and grew 31% from 32 records in 2021 to 42 in 2024, the most recent span that can be treated as complete. Figures for 2025 and 2026 will keep rising as publication catches up, since patent publication typically lags filing by around 18 months. Based on the 2021-2024 trend, the underlying filing rate has not slowed.
Every record in this dataset carries a G06N classification by design, but 28.0% also carry G06F, covering the classical digital-processing side of hybrid classical-quantum execution. Smaller but distinct clusters appear in G06Q (8.8%, business and optimization applications), B82Y (7.2%, nanotechnology and qubit hardware), and communications classes H04L and H04W (3.8% and 2.2% respectively). This spread shows QAOA patenting is not limited to algorithm design; it extends into hardware, orchestration software and application-specific use cases.
The United States receives the most filings at 87, ahead of China at 62 and India at 43. WIPO's PCT route accounts for 37 filings and the European Patent Office 36, with Canada at 14. The spread across these offices indicates that serious filers are pursuing protection in multiple major markets rather than relying on a single jurisdiction.
US10846366B1, filed by Rigetti & Co, Inc. and published in November 2020, claims a method for selecting input parameters for a QAOA circuit using a Bayesian optimizer, applied to combinatorial optimization problems such as Maximum Cut, executed on a hybrid classical-quantum system. It is a parameter-selection and execution-control claim rather than a claim over the QAOA algorithm itself. Anyone building a parameter-tuning layer for QAOA circuits should review this filing's specific claim scope before assuming freedom to operate.
Answers are grounded in the same dataset. Derived from a Patsnap search on Quantum Approximate Optimization Algorithm Patent Landscape covering 2015–2026, data cut-off 2026-08-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company's registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.