Problems it solves: - RNG seed selection (parallel Monte Carlo, simulations) - Hash function parameters (collision avoidance in distributed systems) - NTT transform sizing (post-quantum cryptography) - Network timer intervals (protocol synchronization avoidance) - FPGA/ASIC parameter conflicts (multi-constraint hardware design)
How it differs from traditional approaches: - No simulation required (direct calculation) - Mathematical proof of correctness (not empirical) - Detects impossible constraint combinations at design time - 24-48 hour delivery vs weeks of trial-and-error
Example: 16-lane FPGA PHY with mixed AVOID/REQUIRE constraints across PRBS generators, scramblers, and NTT blocks. Identified a fundamental constraint conflict (p=5 depth-2 AVOID vs p=11 depth-2 REQUIRE both affecting same parameter). Would have cost $500K+ in respin if discovered during bring-up. Found it in less than 24 hours.
The method is based on peer-reviewed research in multiplicative order and p-adic depth theory. Essentially: translates "avoid synchronization at prime p to depth t" into exact modular arithmetic constraints, then combines via Chinese Remainder Theorem.
Validating demand: Offering free analysis for first 10 serious requests.
If you have: - Mysterious periodic bugs in distributed systems - Parameter selection problems with formal requirements - Hardware designs with conflicting constraints
Christopher W. Stevens
Email: cwstevens71@gmail.com with your system specs.
Will provide: - Constraint analysis - Provably correct parameters (or proof of impossibility) - Verification test cases
Looking for feedback on: - Is this valuable to practicing engineers? - What use cases am I missing? - Would you or your company pay for this? How much?