https://eureka.patsnap.com/resources/blog/rd-blog/tensor-network-contraction-algorithm-acceleration-patent-landscape/ · Patsnap · data cut-off 2026-10-15 · downloaded from the live page
Patent Landscape · Patent Landscape Snapshot

Tensor Network Contraction Algorithm Acceleration Patents

A 2-family dataset on tensor network contraction acceleration patents, with filer and filing data as a starting point for deeper search.

2
Published Records
2
Simple Patent Families
CA
Leading Jurisdiction
2025
Peak Filing Year

2 published records collapse into 2 simple (DOCDB) families; the difference is the same invention filed in more than one country.

  • Two simple patent families make up this entire dataset. Both are at or above the 50% share threshold on at least one IPC subclass tracked here.
  • RGT UNIV OF CALIFORNIA is named on one of the two families a 50.0% share of the families in scope, the only single-row figure the page shows.
  • Filings surface across two receiving offices Canada and WIPO (PCT) each account for one published record.
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Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview

What this dataset covers

This page reports the results of a single search for tensor network contraction algorithm acceleration, built around a search string requiring both a tensor-network contraction concept and a term for acceleration or hardware. The search string sets no date limit, so the records returned span whatever filing dates exist in the index for this exact term combination, not a chosen window of years. G06N (computing based on AI models) appears on both families in scope, with G06F and H03K each appearing on one.

Only 2 simple patent families and 2 published records matched this search string. That is a small pool by any measure, and the figures on this page describe only what this particular search returned, they are a starting point for a more targeted search rather than a map of a technology field.

Records in scope, by filing status
  1. RGT UNIV OF CALIFORNIA1

Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. Filings held by named individuals rather than organisations are removed where they can be identified (1 here); that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 1 of the 1 filers returned for this search; the data endpoint returns at most 100 entities, so even that 1 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.

Source: Patsnap Eureka. Assignee ranking and totals. Derived from one Patsnap search for Tensor Network Contraction Algorithm Acceleration Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Data

Filing activity and technology composition

The figures below cover every record this search string returned: 2 published records across 2 receiving offices, and 2 simple patent families split across three IPC subclasses.

Filing trend by earliest filing year

Published records by earliest filing year show 2 records in 2025 and 0 so far in 2026. Filings from 2022 onward are still filling in as later publications arrive, so recent years understate the eventual count and no trend judgement can be drawn from two data points.

Filing trend by earliest filing year0112222025020262022 onwards are shaded as still filling in: a filing is only visible once it publishes, up to 30 months after filing.

Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two.

IPC subclass composition

G06N (computing based on AI models) appears on both of the 2 simple patent families in scope (100.0%). G06F (electric digital data processing) and H03K (pulse technique & logic circuits) each appear on 1 of the 2 families (50.0%). Because a single family can carry more than one classification, these shares add up to more than 100%.

IPC subclass compositionG06N · Computing based on AI models2100.0%G06F · Electric digital data processi…150.0%H03K · Pulse technique & logic circui…150.0%

Shares are the percentage of the 2 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.

Source: Patsnap Eureka. Filing trend and technology composition. Derived from one Patsnap search for Tensor Network Contraction Algorithm Acceleration Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.

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Record on File

A record from the result set

From the result set
WO2026128915A12026-06-18

WO2026128915A1, Systems and methods for ultra memory-efficient on-FPGA training of transformers using tensor-compressed optimization

THE REGENTS OF THE UNIVERSITY OF CALIFORNIA

The abstract describes a method for training a transformer model on a resource-constrained device. It encodes input tokens into hidden representations using tensor-compressed embedding tables stored in tensor-train-matrix (TTM) format, performs forward propagation through tensor-compressed layers with tensor-train (TT) decomposed weight matrices without reconstructing dense weight matrices, computes gradients of loss from the model outputs, and backpropagates.This is the first record returned under the database's default ordering, not a ranking by citations, novelty or breadth. What the granted claims actually require has to be read from the claim set itself, not inferred from this abstract.

WO2026128915A1, patent drawing 1WO2026128915A1, patent drawing 2
View full record

Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.

Source: Patsnap Eureka. The first record the search returned, shown in full. Derived from one Patsnap search for Tensor Network Contraction Algorithm Acceleration Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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Insights

What the figures show

Three figures from this search, reported as counted, no ranking or market read should be drawn from a 2-family pool.

Scope
2 families / 2 records
simple patent families and published records in scope

A 2-family dataset

This search returned 2 simple patent families and 2 published records in total. Any share or count quoted elsewhere on this page is a fraction of that same small total, not of a wider field.

Counted across the full result set, no date limit applied.
Filer
50.0%
share held by the top single filer row

One filer named on one of two families

RGT UNIV OF CALIFORNIA is named on 1 of the 2 simple patent families in scope, a 50.0% share. The filer list returned by this search contains organisations only; filings held by named individuals are removed from the list but remain inside the total and share figures.

This is the only single-row share the page shows; rows are never added together.
Classification
100.0%
share of families carrying G06N

G06N on both families

G06N (computing based on AI models) appears on both of the 2 simple patent families in scope. G06F and H03K each appear on 1 of the 2 families. Because one family can carry several IPC subclasses, these shares add up to more than 100% and cannot be summed into a single figure.

Shares are each counted against the same 2-family denominator.
Offices
2 offices
receiving offices returned by this search

Two receiving offices, one record each

The search returned 2 receiving offices in total: Canada with 1 published record and WIPO (PCT) with 1 published record. This counts where applications were filed, not where any filer is based.

Counted in published records, which sum to the record total rather than the family total.
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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 tensor network contraction algorithm acceleration patent landscape, with the prior art for and against each one.

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Source: Patsnap Eureka. Derived observations on the same dataset. Derived from one Patsnap search for Tensor Network Contraction Algorithm Acceleration Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Next Steps

Where to take this from here

A 2-family result is a narrow starting point. Broadening or adjusting the search terms, and reading the full claim sets of any record of interest, is the next step before drawing conclusions.

Read the granted claims directly

An abstract and a family count cannot establish what a patent's claims cover. Pull the granted claim set for any record of interest before forming a view on scope or freedom to operate.

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Widen or adjust the search string

A 2-family result from this exact term combination likely misses adjacent phrasing used elsewhere in tensor-network or tensor-decomposition filings. Running variant terms is the way to test that.

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Source: Patsnap Eureka. Suggested next steps. No new data: every figure named here is one of those above. Derived from one Patsnap search for Tensor Network Contraction Algorithm Acceleration Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
FAQ

Common questions about this dataset

Answers are grounded in the same dataset. Derived from one Patsnap search for Tensor Network Contraction Algorithm Acceleration Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP

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Go past this page: query the whole tensor network contraction algorithm acceleration patent landscape corpus yourself, in your own scope.
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How this page was built, and what the numbers do and do not mean

Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:

TAC:(("tensor network" AND contraction) AND (algorithm OR computation) AND (accelerat* OR hardware))

Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field. One subclass (G06N) carries 100.0% of the patent families, so this search returned a classification-tight set.

What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 2 records and 2 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.

Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list (1 of them here). Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 1 of the 1 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 1 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included

Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in. The data behind this page was retrieved on 2026-10-15.

Legal status. Legal status was not available for this search, so no in-force figure is shown. Get the status breakdown in Eureka

Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level

Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.

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 limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. 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, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records 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.

The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.

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