Arithmetic Circuit Serialization for Lossless QAP Compression
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Solution Overview
Problem
Current technologies face challenges in efficiently reducing the data footprint of arithmetic circuits, particularly in distributed computing environments like blockchain networks, where storage and transmission of circuits are resource-intensive and error-prone, especially in smart contract programming.
Innovation Solution
The method involves compressing arithmetic circuits using entropy coding on frequent elements, removing redundant data fields, and embedding de-serialization instructions in a bit stream to create a serialized circuit that can be losslessly reconstructed, reducing storage and transmission requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If arithmetic circuits are stored in full format, then data integrity and completeness are maintained, but storage space and transmission bandwidth are excessively consumed
Solution Approach 1:
The patent extracts only the essential and variable components of arithmetic circuits for storage and transmission. By identifying and removing redundant fixed elements (such as standard gate configurations and invariant operational parameters), the system achieves significant data footprint reduction while preserving the critical information needed for circuit reconstruction and validation.
Solution Approach 2:
The patent transforms the representation parameters of arithmetic circuits from a detailed, component-by-component format to a compressed format that encodes only varying parameters. This parameter transformation enables lossless compression by representing circuits in terms of their essential characteristics rather than exhaustive specifications.
2Quantity of substance
If compression techniques are applied to arithmetic circuits, then storage and transmission efficiency are improved, but decompression complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-defining compression schemas and encoding rules for common arithmetic circuit patterns. During the compression phase, these pre-established rules enable efficient encoding without requiring complex real-time decision-making. The decompression process benefits from these pre-defined structures, reducing the computational complexity required to reconstruct circuits from their compressed representations.
3Speed
If redundant data fields are removed from arithmetic circuits, then data transmission speed increases, but data reconstruction accuracy may be compromised
Solution Approach 1:
The patent creates compressed copies of arithmetic circuits that preserve all essential reconstruction information while eliminating redundant data. The compression process generates a simplified representation that contains precisely the information needed for accurate circuit reconstruction, ensuring that the compressed copy is sufficient for faithful reproduction of the original circuit's functionality and structure.
Data Source
AI summary
Techniques described herein may be utilized to serialise and de-serialise arithmetic circuits that are utilized in the execution of computer programs. The arithmetic circuit may be utilized to build a Quadratic Arithmetic Problem (QAP) that is compiled into a set of cryptographic routines for a client and a prover. The client and prover may utilize a protocol to delegate execution of a program to the prover in a manner that allows the client to efficiently verify the prover correctly executed the program. The arithmetic circuit may comprise a set of symbols (e.g., arithmetic gates and values) that is compressed to produce a serialised circuit comprising a set of codes, wherein the set of symbols is derivable from the set of codes in a lossless manner. Serialisation and de-serialisation techniques may be utilized by nodes of a blockchain network.