CharlesCNorton
demos: standalone per-machine programs that put each machine to work
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# demos
Standalone programs that put each machine in the family to work on a named
task. Every script is self-contained (`python demos/<name>.py`), loads the
shipped weights, and cross-checks its result against an independent reference.
| Demo | Machine | What it does |
|------|---------|--------------|
| `neural_computer8_self_modifying_sieve.py` | `neural_computer8` | Sieve of Eratosthenes; with no indexed addressing, the program rewrites the address bytes of its own LOAD/STORE. Finds all 54 primes < 256. |
| `neural_computer8_euclid_gcd.py` | `neural_computer8` | Euclid's GCD, with `a mod b` built from the DIV/MUL/SUB opcodes and an XOR register swap. |
| `neural_computer8_collatz.py` | `neural_computer8` | Collatz step counts; exact for every seed whose trajectory stays inside the 8-bit range. |
| `neural_rv32_machin_pi.py` | `neural_rv32` | pi to nine digits by Machin's 1706 arctangent formula, printed to the console. |
| `neural_rv32_neural_nets_via_neur.py` | `neural_rv32` | Ternary neural nets run as NEUR software: one learned by gradient descent, one (XOR) compiled by construction. |
| `neural_matrix8_gpu_cpu_fleet.py` | `neural_matrix8` | 65,536 CPUs stepped in lockstep on the GPU as one batched matrix product. |
| `neural_attractor_factoring.py` | `neural_attractor` | Factors semiprimes by relaxing an 8x8 multiplier's energy backward; also divides. |
| `neural_attractor_nqueens.py` | `neural_attractor` | Solves 6- and 8-queens by relaxing toward zero unsatisfied clauses. |
| `neural_subleq8io_universal_constructor.py` | `neural_subleq8io` | The universal constructor fabricates a sibling machine byte-for-byte, which then boots. |
| `neural_reflect_self_modifying_stack.py` | `neural_reflect` | Self-modifying SUBLEQ code, on a stored machine, on the fixed interpreter: three levels in one tensor. |
| `neural_reversible_counterfactual.py` | `neural_reversible` | Bijective mixing, exact reverse recovery, and the counterfactual when a digest bit is flipped. |
| `neural_ca_loschmidt_echo.py` | `neural_ca` | A ~2,000-particle gas mixed 500 steps and un-mixed exactly; one flipped cell corrupts half the past. |
| `neural_ca_reversible_cipher.py` | `neural_ca` | The reversible automaton as a block cipher: exact decryption with the right key, noise with a wrong one. |
| `neural_tile_pascal_lucas.py` | `neural_tile` | Self-assembly grows Pascal's triangle mod 2; every cell verified against Lucas' theorem. |