QuantumAccel – Symbolic Quantum Logic Gates for Efficient Computation

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Hi everyone, I’ve released an open-source project called QuantumAccel which is built around a symbolic logic engine that transforms traditional logic gates like AND, XOR, and Toffoli into optimised quantum-inspired operations, all within a constrained mathematical space.

Features:

  • Ultra-fast logic compression using sparse attention
  • Evolving symbolic gates that simulate Hadamard, CNOT, XNOR
  • Memory-efficient operation (as low as 4 KB for massive input)
  • Reversible logic operations for feature extraction, pattern recognition, and error detection

Use Cases:

  • Quantum simulation
  • Edge AI with kilobytes of RAM
  • Memory compression & logic acceleration
  • NLP/vision feature extraction without neural nets
    Link to the repo: GitHub - fikayoAy/quantum_accel
    This is part of a larger symbolic AI framework I’m building. Would love your feedback or contributions! Let me know if you’re interested in symbolic computation, quantum logic, or memory-efficient learning.

Demo benchmarks and documentation are available in the repo. Apache Licensed.

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Impressive project. The logic compression and reversible gate operations are especially relevant for edge AI and efficient memory-bound workloads. If you’re interested in collaborating on symbolic AI frameworks or benchmarking against deterministic AI systems, let me know.

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Hi, thank you and sure how can i contact you?