|
|
---
|
|
|
license: mit
|
|
|
tags:
|
|
|
- formal-verification
|
|
|
- coq
|
|
|
- threshold-logic
|
|
|
- neuromorphic
|
|
|
- modular-arithmetic
|
|
|
---
|
|
|
|
|
|
# tiny-mod12-verified
|
|
|
|
|
|
Formally verified MOD-12 circuit. Single-layer threshold network computing modulo-12 arithmetic with 100% accuracy.
|
|
|
|
|
|
## Architecture
|
|
|
|
|
|
| Component | Value |
|
|
|
|-----------|-------|
|
|
|
| Inputs | 8 |
|
|
|
| Outputs | 1 (per residue class) |
|
|
|
| Neurons | 12 (one per residue 0-11) |
|
|
|
| Parameters | 108 (12 × 9) |
|
|
|
| Weights | [1, 1, 1, 1, 1, 1, 1, 1] |
|
|
|
| Bias | 0 |
|
|
|
| Activation | Heaviside step |
|
|
|
|
|
|
## Key Properties
|
|
|
|
|
|
- 100% accuracy (256/256 inputs correct)
|
|
|
- Coq-proven correctness
|
|
|
- All-ones weight pattern (m > input width)
|
|
|
- Computes Hamming weight mod 12
|
|
|
- Compatible with neuromorphic hardware
|
|
|
|
|
|
## Algebraic Pattern
|
|
|
|
|
|
MOD-12 uses all-ones weights because the reset position (position 12) is beyond the 8-bit input width:
|
|
|
- All positions 1-8: weight = 1
|
|
|
- Position 12 (beyond input): would be weight = 1-12 = -11
|
|
|
|
|
|
The circuit tracks cumulative sum mod 12 using the Hamming weight directly.
|
|
|
|
|
|
## Usage
|
|
|
|
|
|
```python
|
|
|
import torch
|
|
|
from safetensors.torch import load_file
|
|
|
|
|
|
weights = load_file('mod12.safetensors')
|
|
|
|
|
|
def mod12_circuit(bits):
|
|
|
# bits: list of 8 binary values
|
|
|
inputs = torch.tensor([float(b) for b in bits])
|
|
|
weighted_sum = (inputs * weights['weight']).sum() + weights['bias']
|
|
|
return int(weighted_sum.item()) % 12
|
|
|
|
|
|
# Test
|
|
|
print(mod12_circuit([1,1,1,1,1,1,1,1])) # 8 mod 12 = 8
|
|
|
print(mod12_circuit([1,1,1,1,0,0,0,0])) # 4 mod 12 = 4
|
|
|
```
|
|
|
|
|
|
## Verification
|
|
|
|
|
|
**Coq Theorem**:
|
|
|
```coq
|
|
|
Theorem mod12_correct_residue_0 : forall x0 x1 x2 x3 x4 x5 x6 x7,
|
|
|
mod12_is_zero [x0; x1; x2; x3; x4; x5; x6; x7] =
|
|
|
Z.eqb ((Z.of_nat (hamming_weight [x0; x1; x2; x3; x4; x5; x6; x7])) mod 12) 0.
|
|
|
```
|
|
|
|
|
|
Proven axiom-free using algebraic weight patterns.
|
|
|
|
|
|
Full proof: [coq-circuits/Modular/Mod12.v](https://github.com/CharlesCNorton/coq-circuits/blob/main/coq/Modular/Mod12.v)
|
|
|
|
|
|
## Residue Distribution
|
|
|
|
|
|
For 8-bit inputs (256 total), limited to residues 0-8:
|
|
|
- Residue 0: 1 inputs
|
|
|
- Residue 1: 8 inputs
|
|
|
- Residue 2: 28 inputs
|
|
|
- Residue 3: 56 inputs
|
|
|
- Residue 4: 70 inputs
|
|
|
- Residue 5: 56 inputs
|
|
|
- Residue 6: 28 inputs
|
|
|
- Residue 7: 8 inputs
|
|
|
- Residue 8: 1 inputs
|
|
|
- Residues 9-11: 0 inputs (unreachable with 8-bit input)
|
|
|
|
|
|
## Citation
|
|
|
|
|
|
```bibtex
|
|
|
@software{tiny_mod12_verified_2025,
|
|
|
title={tiny-mod12-verified: Formally Verified MOD-12 Circuit},
|
|
|
author={Norton, Charles},
|
|
|
url={https://huggingface.co/phanerozoic/tiny-mod12-verified},
|
|
|
year={2025}
|
|
|
}
|
|
|
```
|
|
|
|