🌐 SSM-ClockKe — A tiny 15 KB Symbolic Engine for Transparent Time Stability — Full Source Code Uploaded

🌟 Deterministic. Tamper-evident. Universal.


From “what time is it?” to “how honest has time been?”

A small, open-standard timing kernel that reveals how stable or stressed time has been, running quietly beside your existing clock.

No content profiling.
No telemetry.
No hidden analytics.
Only symbolic clarity. 

⚡ Quick Proof SSM-ClockKe Is Real — Try This in 5 Seconds

Below is a tiny, self-contained demo that produces a deterministic alignment lane and a tamper-evident stamp chain.
No installation, no dependencies — just copy, run, and observe.

# --- Minimal SSM-ClockKe Demo ---
# Deterministic alignment lane + tamper-evident stamp chain

from math import tanh, log1p
import hashlib, time, datetime

U = 0.0
W = 0.0
prev = ""

def atanh(x):  # stable formulation
    return 0.5 * (log1p(x) - log1p(-x))

def make_stamp(prev, payload, t):
    h = hashlib.sha256(payload.encode()).hexdigest()
    raw = (prev + h + t).encode()
    return hashlib.sha256(raw).hexdigest()

for tick in range(1, 6):
    t_utc = datetime.datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
    a_raw = 0.02  # baseline stability (full ClockKe uses jitter/noise)
    a_c   = max(min(a_raw, 0.999999), -0.999999)
    u     = atanh(a_c)
    U    += u
    W    += 1.0
    a_out = tanh(U / W)

    payload = f"{t_utc}|{a_out:+.6f}"
    stamp   = make_stamp(prev, payload, t_utc)
    prev    = stamp

    print(f"{tick:02d}  time={t_utc}  align={a_out:+.6f}  stamp={stamp[:16]}...")
    time.sleep(0.5)

Typical output:

01  time=2025-03-05T12:18:11Z  align=+0.01999  stamp=19bd4e3c82c7...
02  time=2025-03-05T12:18:12Z  align=+0.03997  stamp=51a12c8b5d9e...
03  time=2025-03-05T12:18:12Z  align=+0.05994  stamp=ad3ef114bc27...
...

Alignment rises smoothly.
Each stamp links to the previous one.
Any edit or reordering breaks the chain immediately.

⏱️ Why SSM-ClockKe Matters

Modern systems record timestamps, but never explain:

  • Did time behave smoothly?

  • Were there micro-freezes or jitter?

  • Was the system paused or throttled?

  • Is this timing record trustworthy?

SSM-ClockKe adds a symbolic truth-layer that answers these questions without altering the underlying clock.

Each tick becomes a transparent record of:

  • stability

  • drift

  • band classification

  • tamper-evident continuity

A clean, deterministic companion to real time.

🧠 What SSM-ClockKe Computes

Every tick produces a compact, reproducible structure:

time_utc      – timestamp for the tick
dt_ms         – actual milliseconds since the previous tick
a_out         – bounded alignment in (-1 .. +1)
band          – A+, A, B, C, D
stamp         – tamper-evident continuity hash

This structure is identical across browser, desktop, and CLI builds.

🔧 The Alignment Kernel (ASCII Formula)

SSM-ClockKe takes real-world jitter, freeze behavior, and micro-noise, and transforms them into a bounded symbolic signal.

Stability source:

a_src = baseline_a
a_src += user_stress
a_src -= jitter_gain * ((dt_ms - tick_ms) / tick_ms)
if dt_ms > freeze_mult * tick_ms: a_src -= freeze_penalty

Bounded alignment and accumulation:

a_c   = clamp(a_src, -1 + eps_a, +1 - eps_a)
u     = atanh(a_c)
U     = DECAY_W * U + u
W     = DECAY_W * W + 1
a_out = tanh(U / max(W, eps_w))

  • Stable ticks push a_out upward

  • Unstable ticks push a_out downward

This creates a consistent indicator of time behavior.

🎨 Readable Band Classification

Based on the final alignment:

  • A+ / A — highly stable

  • B — mild drift

  • C — visible drift

  • D — noticeable instability

Bands make the symbolic signal easy to interpret in research, diagnostics, and monitoring.

🔐 Tamper-Evident Stamp Chain

Each tick is cryptographically linked to the previous one:

stamp_k = SHA256(prev_stamp || SHA256(payload) || time_utc_k)

  • Removing a tick breaks the chain

  • Editing a tick breaks the chain

  • Reordering ticks breaks the chain

Verification requires only the CSV log and the reference algorithm.

This ensures append-only integrity with no central authority.

💻 Three Ways to Run SSM-ClockKe

1. Browser Edition

  • Live drift history

  • Stability bar

  • Stamp tail

  • Direct CSV export

  • Adjust tick rate and stress

2. Desktop Edition

  • Simple, clean graphical window

  • One tick per second

  • Drift, band, and alignment display

  • CSV export and basic controls

3. CLI Edition

  • Headless operation

  • ASCII sparkline of recent drift

  • Tick cadence control

  • Fast CSV generation

All three editions follow the exact same symbolic rules.

⚙️ One-Minute Usage Flow

Run the kernel

Browser: open the HTML file
Desktop: run the Python script
CLI:

python clockke_run_v2_1.py --tick-sec 1.0 --ticks 30

Export

CSV output is available in all editions.

Verify

python clockke_verify_v2_1.py exported.csv

Expected output:

ALL CHECKS PASSED

🧩 Key Advantages of SSM-ClockKe

✔️ Open-standard

Anyone may implement or adapt the kernel.

✔️ Zero telemetry

No identity, no profiling, no behavior tracking.

✔️ Deterministic and reproducible

Two devices observing identical timing patterns produce identical alignment paths.

✔️ Suitable for research and observation

Ideal for drift analysis, teaching, diagnostics, and reproducible experiments.

✔️ Small and clear

The entire logic is transparent and easily inspectable.

🌱 What You Can Do With Symbolic Time

  • Observe background jitter

  • Compare different timing sources

  • Detect throttling or freeze patterns

  • Provide integrity for time-based logs

  • Teach system behavior using alignment bands

  • Bundle evidence for reproducible studies

Symbolic time adds a second, independent dimension to the way systems represent temporal behavior — one that focuses on truth of motion rather than absolute timestamps.

🔗 Official Repository and Links

SSM-ClockKe (Open Standard): Full Source Code, Browser Edition, Python Scripts, and Documents
https://github.com/OMPSHUNYAYA/Symbolic-Mathematical-Clock-Kernel

Shunyaya Symbolic Mathematics — Project Index:
https://github.com/OMPSHUNYAYA/Shunyaya-Symbolic-Mathematics-Master-Docs

Blogs:
https://shunyaya.blogspot.com
https://shunyaya.blog

🌈 Closing Thought

Time is continuous, but its behavior is not always smooth.
SSM-ClockKe offers a clear symbolic signal that reflects this behavior —
a quiet, transparent companion to real time.

It does not judge, predict, or interfere.
It simply reveals the structure that was always there.

Disclaimer: Observation Only

OMP

Comments

Post a Comment

Popular posts from this blog

🌟 SSM-AIM — A Tiny 108 KB Verifiable Personal AI With a Big Promise

Image
🧩 Dictionary-Optional, Manifest-First — A Lightweight Personal AI That Understands Without Words. ⚠️ Important: SSM-AIM is not a talking assistant or a universal question-answering system. It will not chat, write emails, or generate stories for you. SSM-AIM does one thing, but does it with proof: it takes the numbers you choose to give it, and tells you whether things are stable or drifting — with a stamped receipt you can trust. ✨ In the future, the same manifest-first framework can support richer layers of symbolic intelligence, and  larger, general-purpose AI systems can easily plug into AIM as their integrity core  — but AIM’s identity will always be this: a small, verifiable companion that you fully control. 🌱 Imagine a personal AI that doesn’t live in giant data centers, but quietly on your own laptop… inside just 108 KB. No heavy downloads, no hidden cloud, no secret training on your life. Just a tiny, honest companion running in a simple folder you ca...
Read more

🌟 SSM-AIM Mini — A 23 KB Transparent Personal AI Built for Every Human — Full Source Code Uploaded

Image
A tiny, fully offline symbolic intelligence tool — open, inspectable, and completely under your control. The world’s simplest personal AI console, now in just 23 KB. 🌱 A New Kind of AI for the World The world is full of massive AI systems — gigabytes of weights, billions of parameters, opaque pipelines, and unreadable inner workings. But intelligence does not need to be heavy to be meaningful. Somewhere inside that vast landscape, something small was born. Tiny. Transparent. Human-sized. AIM stands for " Artificial Intelligence Manifest"   — a fully transparent, rule-based, manifest-driven form of intelligence built on Shunyaya Symbolic Mathematics. SSM-AIM Mini is a personal AI that fits inside 13 KB + 7 KB + 3 KB …just 23 KB total . Not a chatbot. Not a predictor. Not a decision-maker. Not a model trained on your life. Just a calm symbolic mirror. It listens. It computes a symbolic alignment value. It speaks back in simple sentences. It keeps a ti...
Read more