Silicon Quantum Photonics Patent Snapshot 2026
The silicon quantum photonics patent corpus is small and heavily concentrated, with Massachusetts Institute of Technology holding a commanding share of all ranked patent records. Filing activity peaked in 2019 and has eased since, leaving this a specialist field where a handful of academic-led innovators set the technical agenda.
MIT dominates a compact, academically driven field
Massachusetts Institute of Technology leads the applicant ranking with 9 patent records, followed distantly by University of Southern California with 2 patent records. The remaining ranked filers — Harris Nicholas C, Carolan Jacques Johannes, and several individual inventors — each hold 1 patent record.
The top five filers account for 88% of the combined total across the ranked applicants visible in this query, an exceptionally high concentration that signals MIT’s near-exclusive control of the formal IP evidence snapshot. There is no meaningful second tier; the gap between MIT and all other applicants is stark.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | Massachusetts Institute of Technology | 9 | |
| 2 | University of Southern California | 2 | |
| 3 | HARRIS NICHOLAS C | 1 | |
| 4 | CAROLAN JACQUES JOHANNES | 1 | |
| 5 | DR SAMANVITA N | 1 | |
| 6 | DR AMRUTH RAMESH THELKAR | 1 | |
| 7 | ENGLUND DIRK ROBERT | 1 |
MIT’s dominance, reinforced by co-inventor collaboration patterns, means that any new entrant seeking freedom-to-operate must navigate a portfolio shaped almost entirely by a single institution. University of Southern California is the only other organizational filer of note, and its position is nascent.
Patent publication typically lags filing by 18–24 months, so the most recent activity window may be under-represented in the current data. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
A 2019 filing spike, a quiet aftermath, and a photonics-AI technology core
The annual filing trend reveals a field that surged briefly in 2019 and has since settled into low single-digit activity. The technology composition shows that AI-computing frameworks and nanotechnology classifications sit alongside classical photonics branches, reflecting the programmable-circuit nature of the work.
Annual filing trend
Filings peaked at 5 records in 2019, dropped to zero for several years, and recorded 3 in 2023 followed by 1 in 2025. Years 2024–2026 should be treated as under-counted due to publication lag, so the apparent recent quietness does not necessarily confirm a sustained decline.
↗ Hover for values · click a bar to ask EurekaTechnology composition
G06N (Computing based on AI models) and B82Y (Nanotechnology applications) and G02B (Optical elements and systems) each appear in 6–9 patent records, confirming that programmable photonic processing for quantum computation is the visible technical theme. G02F (Optical control and modulation), H01S (Lasers and stimulated emission), and H04B (Transmission) occupy smaller but technically adjacent shares.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Scalable Feedback Control of Single-Photon Sources…
Typically, quantum systems are very sensitive to environmental fluctuations, and diagnosing errors via measurements causes unavoidable perturbations. Here, an in situ frequency-locking technique monitors and corrects frequency variations in single-photon sources based on resonators. By using the classical laser fields used for photon generation as probes to… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Methods, systems, and apparatus for programmable q… | 86 |
| 2 | Methods, systems, and apparatus for programmable q… | 82 |
| 3 | Programmable photonic processing | 70 |
| 4 | High Density Fiber Optic Packaging for Cryogenic A… | 41 |
| 5 | Scalable Feedback Control of Single-Photon Sources… | 14 |
| 6 | Methods, systems, and apparatus for programmable q… | 14 |
| 7 | Programmable photonic processing | 8 |
| 8 | Scalable feedback control of single-photon sources… | 7 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
Massachusetts Institute of Technology
MIT holds 9 patent records, anchored in B82Y nanotechnology, G01B optical measurement, and G06N AI-computing classifications — consistent with programmable photonic quantum processors. Its co-inventor network (Harris, Pant, Englund, Chakraborty, Carolan) shows deep team-based IP generation. Momentum data registers MIT as a new entrant in the most recent filing window, reflecting a single recent record against a prior-period base.
patent records: 9University of Southern California
University of Southern California holds 2 patent records, emphasizing G02B optical elements and G06N AI-computing classifications. Its applicant momentum also registers as a new entrant in the recent window, indicating an early-stage position. With a focus on optical system integration rather than the device-physics layer that MIT occupies, USC represents a differentiated but still nascent challenger.
patent records: 2Frequently asked questions
The corpus covers 11 patent families in scope, providing a focused but limited view of formal IP activity in silicon quantum photonics.
Massachusetts Institute of Technology leads with 9 patent records, accounting for the large majority of the top-100 ranked filers’ combined total.
No. The lifecycle evidence indicates that annual filings peaked in 2019 and have eased since. The field is classified as Decline, though the most recent 18–24 months may be under-counted due to publication lag.
Nine patent records are filed in the United States, 2 through WIPO PCT, and 1 in India. Major jurisdictions including Europe, China, Japan, and South Korea are not represented in this corpus.
G06N (Computing based on AI models) appears in 9 patent records, followed by B82Y (Nanotechnology applications) and G02B (Optical elements and systems) each in 6 records, and G01B (Measuring length and dimensions) in 5 records.
H01S (Lasers and stimulated emission) and H04B (Transmission, general) each appear in only 2 patent records, representing the sparsest branches in the current corpus and potential areas for differentiated IP development.
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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.
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