Tensor Codes are a class of error-correcting codes used in information theory and computer science to detect and correct errors that occur during data transmission or storage. They are constructed by combining simpler codes using a mathematical operation called a tensor product. In the context of blockchain and distributed systems, tensor codes can be applied to improve data availability and resilience against data corruption. They enhance the robustness of data stored or transmitted across unreliable networks.
Context
Tensor codes are relevant in advanced research for data availability layers and decentralized storage solutions, occasionally appearing in news related to these infrastructure improvements. Their application aims to make blockchain data more robust and efficiently verifiable, even if some parts of the data are lost or corrupted. The development of efficient tensor code implementations is crucial for scaling data-intensive decentralized applications.
ZODA introduces a tensor code-based proof of encoding that eliminates sampler communication overhead, fundamentally democratizing data availability verification for light nodes.
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