QuantumAccel – Symbolic Quantum Logic Gates for Efficient Computation

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.

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.

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