File size: 1,617 Bytes
6045388
 
 
 
68d0c70
 
 
6045388
 
 
 
 
 
 
b4f0dea
2082b20
 
6045388
2082b20
 
6045388
2082b20
 
6045388
2082b20
6045388
 
 
 
 
b4f0dea
6045388
 
b4f0dea
 
 
6045388
 
 
b4f0dea
 
 
6045388
 
 
 
 
b4f0dea
6045388
 
 
b4f0dea
1f98d07
6045388
 
b4f0dea
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6045388
8204b29
6045388
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
---
license: mit
tags:
  - syf
  - reference-implementation
  - specification
  - verification
  - deterministic
  - invariant
---

# SYF‑Minimal

Minimal, non‑canonical reference implementation of the Systemic Fire (SYF) invariant.

## Related Repositories

- **SYF‑Core — Canonical law (immutable)**  
  https://github.com/AnathemaOfficial/SYF-Core

- **SYF‑Lab — Experimental and observational framework**  
  https://github.com/AnathemaOfficial/SYF-Lab

## Status

- Non‑canonical  
- Non‑normative  
- Reference / verification only  
- Not a machine learning model  
- Not intended for deployment or inference  

This repository does **not** define, modify, or extend the SYF law.  
Any discrepancy with SYF‑Core must be treated as an implementation error.

## Purpose

- Demonstrate deterministic computation of the invariant  
- Provide minimal reference code and test vectors  
- Enable blind analysis and external verification  

## Law

\[
R = \frac{F \times E}{K}
\]

### Constraints enforced by the reference implementations

- \(F \ge 0\)  
- \(0 \le E \le 1\)  
- \(K > 0\)  

Inputs outside this domain must be rejected (error/exception).  
No clamping.  
Numerical tolerance, if any, is implementation‑defined.

## Layout

```
syf-minimal/
├── README.md
├── python/
│   └── syf_core.py
├── rust/
│   └── lib.rs
├── notebook/
│   └── syf_demo.ipynb
├── HOW_TO_DERIVE_F_E.md
└── TEST_VECTORS.md
```

## Machine‑Facing Only

This project is intended for machines, not humans.  
No governance. No optimization. No feedback.