Shared Quantum Decoder Pipeline for Scalable Logical Qubits
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Solution Overview
Problem
Current quantum error correction decoders face challenges in scalability and resource efficiency, as they require multiple dedicated decoders for each logical qubit, limiting the size and scale of quantum computing devices and incurring high resource overheads.
Innovation Solution
A 3-stage pipelined micro-architecture for a hardware implementation of the Union-Find decoder is designed, allowing resource sharing across multiple logical qubits to reduce hardware costs and enable scalable fault-tolerant quantum computation, with data compression techniques to manage memory and bandwidth requirements in a cryogenic environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If one or more dedicated decoders are provided for each logical qubit, then error correction capability is improved, but device size and scale are limited
Solution Approach 1:
The patent implements a shared decoder architecture where a single decoder block serves multiple logical qubits through time-multiplexed operation. The decoder processes syndromes from different logical qubits sequentially, with each logical qubit having its own syndrome buffer but sharing the same decoding logic and processing resources. This universal approach allows one decoder to perform error correction for L logical qubits, reducing the total decoder count from L to 1 while maintaining full error correction capability across all qubits.
Solution Approach 2:
The patent segments the decoder functionality into modular components: syndrome buffers for each logical qubit, a shared decoding engine, and a correction output stage. This segmentation allows independent buffering of syndromes from different qubits while sharing the computationally intensive decoding operations, enabling scalable architecture where the number of buffers scales with L but the decoding resources remain constant.
2Measurement precision
If multiple dedicated decoders are provided for each logical qubit, then decoding accuracy is improved, but hardware cost increases
Solution Approach 1:
The patent implements a shared decoder architecture where a single decoder block serves multiple logical qubits through time-multiplexed operation. The decoder processes syndromes from different logical qubits sequentially, with each logical qubit having its own syndrome buffer but sharing the same decoding logic and processing resources. This universal approach allows one decoder to perform error correction for L logical qubits, reducing the total decoder count from L to 1 while maintaining full error correction capability across all qubits.
Solution Approach 2:
The patent segments the decoder functionality into modular components: syndrome buffers for each logical qubit, a shared decoding engine, and a correction output stage. This segmentation allows independent buffering of syndromes from different qubits while sharing the computationally intensive decoding operations, enabling scalable architecture where the number of buffers scales with L but the decoding resources remain constant.
3Reliability
If dedicated decoders are provided for each logical qubit, then error correction performance is improved, but resource overhead increases
Solution Approach 1:
The patent implements a shared decoder architecture where a single decoder block serves multiple logical qubits through time-multiplexed operation. The decoder processes syndromes from different logical qubits sequentially, with each logical qubit having its own syndrome buffer but sharing the same decoding logic and processing resources. This universal approach allows one decoder to perform error correction for L logical qubits, reducing the total decoder count from L to 1 while maintaining full error correction capability across all qubits.
Solution Approach 2:
The patent segments the decoder functionality into modular components: syndrome buffers for each logical qubit, a shared decoding engine, and a correction output stage. This segmentation allows independent buffering of syndromes from different qubits while sharing the computationally intensive decoding operations, enabling scalable architecture where the number of buffers scales with L but the decoding resources remain constant.
Data Source
AI summary
A quantum computing device comprises at least one quantum register including l logical qubits, where l is a positive integer. The quantum computing device further includes a set of d decoder blocks coupled to the at least one quantum register, where d<2*l. In this way, the decoder blocks may share decoding requests generated by the logical qubits.


