Accelerating TFHE: Scalable Multiplication Algorithms and Efficient Carry Handling

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Fully Homomorphic Encryption (FHE) enables private data processing on untrusted servers. However, FHE performance remains a critical bottleneck for applications such as machine learning, which rely heavily on non-linear operations, such as comparisons, and numerous ciphertext-ciphertext (CxC) and ciphertext-plaintext (CxP) multiplications. While modern FHE schemes such as TFHE efficiently handle non-linear operations, multiplication remains a significant performance bottleneck. This paper introd