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Run your analysis now →A data-backed view of dynamical decoupling patents in quantum error correction: who holds the filings, where classes concentrate, and where white space remains through 2026.
Filing growth = 2021 (19 records) → 2024 (18); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 78 records in scope (CR5), not the ranked leaders only.
Dynamical decoupling sits at the intersection of pulse-sequence engineering and quantum error correction: patterns of control pulses applied to a qubit to average out unwanted noise coupling without adding the overhead of full error-correcting codes. The 78 records in scope, spanning 2015 through the 2026 cut-off, cluster heavily around software and algorithmic framing of the technique rather than pure hardware pulse generation. That skew toward computing-based classification is itself a signal: the commercially contested ground is less about generating a clean pulse and more about deciding which sequence to apply, when, and how to verify it worked.
Publication lags filing by roughly 18 months, so the most recent one to two years in any trend understate real filing activity. Read the 2021 peak and the 2024 comparison as the most reliable recent signal, and treat 2025-2026 counts as still filling in rather than as evidence of a slowdown.
Pick a task. Every answer cites the patents behind it.
Two views of the same 78-record dataset: how filings moved year over year, and which IPC subclasses carry the claims.
Filings rose from zero in 2017 to a peak of 19 in 2021, then held near that level — 18 by 2024, a -5% change over the three-year span rather than a decline. 2025 and 2026 figures will rise as publication catches up with filing.
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.
G06N (computing based on AI models) appears in 92.3% of the 78 records, far ahead of H03M coding (11.5%), H04B transmission (9.0%) and G06F data processing (7.7%). Because records can carry multiple classes, these shares sum past 100% — the takeaway is that decoupling claims are overwhelmingly framed as computational methods, not as standalone pulse-generation hardware.
Shares are the percentage of the 78 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
This page is one run against one query. Ask Eureka your own question about quantum control & error correction: dynamical decoupling patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaThe method trains a genetic algorithm on an equivalent circuit structure to the target quantum circuit, generating and evolving populations of candidate dynamical decoupling sequences through reproduction and mutation to empirically identify sequences that suppress error on real hardware rather than relying on analytically derived pulse patterns.Filed by IBM, this record frames sequence selection as a search problem rather than a physics-first derivation — a distinct approach from the analytically-derived sequences in the earlier most-cited records.


| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20150324705A1 | Long-time low-latency quantum memory by dynamical decoupling | 29 |
| 2 | US20090241013A1 | Efficient decoupling schemes for quantum systems using soft pulses | 27 |
| 3 | CN109407690A | 一种飞行器稳定控制方法 | 25 |
| 4 | US20210258079A1 | Target qubit decoupling in an echoed cross-resonance gate | 21 |
| 5 | US11748652B1 | Heralding of amplitude damping decay noise for quantum error correction | 9 |
| 6 | WO2009117003A1 | Efficient decoupling schemes for quantum systems using soft pulses | 8 |
| 7 | US20230359923A1 | Characterization of time-correlated quantum errors through entanglement | 6 |
| 8 | US9946973B2 | Long-time low-latency quantum memory by dynamical decoupling | 6 |
| 9 | US8219871B2 | Efficient decoupling schemes for quantum systems using soft pulses | 6 |
| 10 | WO2021165108A1 | Target qubit decoupling in an echoed cross-resonance gate | 5 |
Ranked by citation count within the corpus; older records accumulate more citations by nature of tenure, so treat this as a signal of influence rather than of current commercial weight.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Each row carries its publication number; clicking a row searches Eureka by that number.
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →Three figures from this dataset carry direct implications for where a new filing would land and who would contest it.
Five assignees hold 73.1% of the 78 records in scope, and the leader alone holds 23. A new entrant is not filing into open ground at the algorithmic level — it is filing adjacent to a small number of well-resourced holders.
With 92.3% of records in G06N against single-digit shares for coding, transmission and pulse-technique classes, most contested claim space concerns sequence selection, optimisation and verification methods rather than the underlying pulse electronics.
Filings peaked at 19 in 2021 and stood at 18 in 2024, a -5% change across that span. That reads as a mature but still-active field holding its filing rate, not one that is cooling off.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to quantum control & error correction: dynamical decoupling patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| The University of Sydney | Dartmouth College | 4 |
| International Business Machines Corporation (IBM) | IBM DEUTSCHLAND GMBH | 3 |
Only two co-assignee pairs appear in the dataset, the strongest linking a university and a research institute on four shared records — collaboration is the exception here, not the norm.
The filing record answers who holds ground and where classes concentrate. Turning that into a filing or freedom-to-operate decision takes a closer read of specific claims.
Run the specific pulse sequence or verification method you plan to file against the claim language in the top-cited records to see how close the overlap actually sits.
Explore claim analysis in EurekaThe top assignee's share of 23 records is worth watching directly, since a single well-resourced filer shifting strategy changes the shape of this field faster than the aggregate trend shows.
Set up assignee monitoring in EurekaThe assignee ranking for this dataset returns 21 companies across the 78 records in scope, and it is not a top-50 or top-100 cut — it is the full ranked list the data endpoint returns. Within that list, concentration is steep: the top 5 combined hold 73.1% of all 78 records, and the top 10 combined hold 94.9%. That leaves a thin tail of single or low-count filers beyond the tenth-ranked assignee, which held 2 records.
Filing activity peaked at 19 records in 2021 and stood at 18 in 2024, a -5% change over that span — essentially a plateau rather than growth or decline. Because publication lags filing by roughly 18 months, the 2025 and 2026 figures in any trend chart are still incomplete and will revise upward. The safest read is that the field held its filing rate through the last fully-reported year rather than accelerating or cooling.
92.3% of the 78 records carry a G06N classification, covering computing based on AI models, which signals that most claims are framed around sequence selection, optimisation or verification methods rather than pulse-generation hardware itself. Coding and code conversion (H03M) and general transmission (H04B) each appear in under 12% of records, and hardware-adjacent classes like pulse technique (H03K) or nanotechnology applications (B82Y) barely register. A filer targeting hardware-level pulse generation is working in a much less crowded class than one targeting algorithmic sequence selection.
Rarely, based on this dataset. Only two co-assignee pairs appear across all 78 records, the strongest being a university paired with a research institute on four shared records, and a second pair linking a corporate parent with its national subsidiary on three records. Most filings in this space are single-assignee, which suggests the technique is being developed and filed largely in-house rather than through joint ventures or shared research grants.
The class-level data points to hardware-adjacent branches as the least crowded: pulse technique and logic circuits (H03K) appear in only 2.6% of records, and nanotechnology applications (B82Y), geophysics-linked sensing (G01V) and optical control (G02F) each appear in a single record. These are not proven-safe white space — a single record can still block a narrow claim — but they carry far less filing density than the dominant G06N computing class, where 92.3% of records and a concentrated top-5 assignee group make new claims harder to clear.
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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.