# How D-Wave Clears Magnetic Noise in Quantum Computers > A method for improving quantum computer accuracy by actively clearing out magnetic interference that builds up during calculations. - **Patent:** US 11295225 - **Original title:** Superconducting quantum processor and method of operating same - **Owner:** D Wave Systems Inc - **Granted:** 2022 - **Status:** Active - **Times cited:** 13 - **Field:** semiconductors, ai_ml, consumer_electronics ## What it does Quantum processors often suffer from 'spin-bath polarization,' which is essentially magnetic noise that builds up in the environment surrounding the qubits during a calculation. This patent describes a way to reset this environment by forcing the qubit into an opposite state after a calculation is finished. By raising a 'tunneling barrier'—which acts like a gate to lock the qubit's state—the system holds the qubit in this corrective position for a specific amount of time. This process effectively depolarizes the surrounding environment, allowing the quantum processor to start its next calculation without the lingering magnetic interference from the previous one. ## What it does NOT cover - Does not cover passive cooling techniques that do not involve active qubit state manipulation - Does not cover quantum gate-based processors that do not utilize quantum annealing cycles - Does not cover error correction methods that rely solely on software algorithms rather than physical qubit state latching - Does not cover systems that do not use superconducting qubits ## The clever bit Instead of trying to shield the qubit from noise, the system uses the qubit itself as a tool to 'flush' the noise out by intentionally flipping its state and holding it there to cancel out the accumulated magnetic polarization. ## Real-world examples 1. D-Wave Advantage quantum annealing processors 2. Superconducting quantum annealing hardware ## Why it matters Quantum computers are incredibly sensitive to noise. If the environment doesn't 'reset' between operations, the errors accumulate, making the final result useless. D-Wave Systems, a leader in quantum annealing, uses this technology to make their processors more reliable for complex optimization problems, such as logistics or financial modeling. ## Frequently asked questions ### What does How D-Wave Clears Magnetic Noise in Quantum Computers cover? A method for improving quantum computer accuracy by actively clearing out magnetic interference that builds up during calculations. ### Who owns patent US 11295225? D Wave Systems Inc owns this patent, granted in 2022. ### When does this patent expire? This patent is expected to expire on July 6, 2038, when the invention enters the public domain. ### What is patent US 11295225 cited by? This patent has been cited by 13 later patents that build on its ideas. ### What problem does this patent solve? Quantum computers are incredibly sensitive to noise. If the environment doesn't 'reset' between operations, the errors accumulate, making the final result useless. D-Wave Systems, a leader in quantum annealing, uses this technology to make their processors more reliable for complex optimization problems, such as logistics or financial modeling. ### What does this patent NOT cover? Does not cover passive cooling techniques that do not involve active qubit state manipulation **Full plain-English explainer:** https://patentbrief.org/patent/us/11295225/superconducting-quantum-processor-and-method-of-operating-same **Original patent:** https://patents.google.com/patent/US11295225 --- _Source: PatentBrief — https://patentbrief.org. Patent facts are from public records; the plain-English explanation is PatentBrief's._ ## Related patents Semantically similar inventions in the PatentBrief corpus: - [How to Fix Faulty Memory Cells in AI Chips](https://patentbrief.org/patent/us/10956815/killing-asymmetric-resistive-processing-units-for-neural-network-training) — This patent describes a system that tests individual memory cells in AI chips for uneven behavior and then permanently disables the faulty ones before the chip starts learning, making AI training more efficient. - [How a Single Electronic Component Can Learn and Process AI Data](https://patentbrief.org/patent/us/10248907/resistive-processing-unit) — This patent describes a tiny electronic component called a resistive processing unit (RPU) that acts like a brain cell in an artificial intelligence network, storing and processing information directly within its changing electrical resistance. - [How to Automatically Expand Neural Networks by Adding New Nodes](https://patentbrief.org/patent/us/10832138/gpt-language-model-pre-training) — A method for growing artificial intelligence models by identifying underperforming parts of a network and adding new nodes based on the behavior of existing ones. - [How Graphics Processors Switch Between Different Tasks Efficiently](https://patentbrief.org/patent/us/7512773/context-switching-using-halt-sequencing-protocol) — A method for graphics chips to pause and swap between different programs or tasks without waiting for every single part of the processor to finish its current job. - [Making AI Smarter by Focusing on Unsure 'Nodes'](https://patentbrief.org/patent/us/12423586/training-nodes-of-a-neural-network-to-be-decisive) — This 2025 patent from D5AI LLC describes a way to train AI models more effectively by boosting the learning signal for 'nodes' that aren't making clear decisions on data.