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Quantum Gate Device with Superconducting Qubit Technology

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Summary

USPTO published patent application US20260111776A1, filed September 13, 2023 as Application No. 19111598, covering a quantum gate device using superconducting qubit technology. The invention includes at least two data qubits and a coupler qubit, with a pulse irradiator that applies cross-Rabi transition and residual ZZ interaction elimination drive pulses to reduce quantum decoherence errors. Inventors are Atsushi Noguchi, Shotaro Shirai, Yuta Okubo, and Yasunobu Nakamura.

“A quantum gate device includes a qubit substrate that includes at least two data qubits, namely a first data qubit and a second data qubit, and a coupler qubit disposed between the first data qubit and the second data qubit and a pulse irradiator that irradiates drive pulses to the coupler qubit.”

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USPTO classification G06N covers computer systems based on specific computational models: neural networks, knowledge representation, fuzzy logic, expert systems, evolutionary algorithms. With the AI patent boom, this is one of the most-filed application classes in the office. Every newly published application in G06N lands in this feed, around 230 a month. Patent applications publish 18 months after filing, so this feed reveals what AI labs and companies were working on in the prior year and a half. Watch this if you compete in machine learning, file freedom-to-operate analyses, scout acquisition targets in AI infrastructure, or track which research groups are converting publications to patents. GovPing pulls each application with the filing number, title, applicant, and abstract.

What changed

USPTO published Application US20260111776A1 for a quantum gate device using superconducting qubit technology, describing a qubit substrate with at least two data qubits and a coupler qubit between them, with a pulse irradiator that applies cross-Rabi transition drive pulses and residual ZZ interaction elimination drive pulses shifted by a predetermined frequency. The invention targets reduction of residual ZZ interaction between data qubits in quantum computing systems.

Entities engaged in quantum computing research, superconducting circuit development, or quantum processor design should monitor this application for potential prior art or freedom-to-operate implications. The patent covers technical approaches to mitigating quantum decoherence — a key challenge in scalable quantum computing — and may be relevant to firms developing cryogenic quantum control systems or multi-qubit architectures.

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Apr 23, 2026

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← USPTO Patent Applications

QUANTUM GATE DEVICE, SUPERCONDUCTING QUANTUM GATE DEVICE, QUANTUM COMPUTER AND METHOD OF QUANTUM GATE OPERATION

Application US20260111776A1 Kind: A1 Apr 23, 2026

Inventors

Atsushi NOGUCHI, Shotaro SHIRAI, Yuta OKUBO, Yasunobu NAKAMURA

Abstract

A quantum gate device includes a qubit substrate that includes at least two data qubits, namely a first data qubit and a second data qubit, and a coupler qubit disposed between the first data qubit and the second data qubit and a pulse irradiator that irradiates drive pulses to the coupler qubit. The pulse irradiator irradiates a first cross-Rabi transition drive pulse and a residual ZZ interaction elimination drive pulse, which is shifted by a predetermined frequency from the first cross-Rabi transition drive pulse. The predetermined frequency shift is a value that eliminates the residual ZZ interaction between the first data qubit and the second data qubit.

CPC Classifications

G06N 10/20 G06N 10/40

Filing Date

2023-09-13

Application No.

19111598

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Last updated

Classification

Agency
USPTO
Published
April 23rd, 2026
Instrument
Notice
Branch
Executive
Legal weight
Non-binding
Stage
Final
Change scope
Minor
Document ID
US20260111776A1

Who this affects

Applies to
Technology companies Manufacturers
Industry sector
5112 Software & Technology
Activity scope
Patent application filing Quantum computing research
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Semiconductors

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