GaN Playback Workbook

Re-Analyze. Refine. Improve.

The sister to GaN Live.

Same data.
Different objective.

Why It Matters

Growth happens once.

Understanding can happen forever.

Most labs treat experiments as static history:

A saved video
A plotted intensity trace
A few notes

Playback turns experiments into a reusable, evolving dataset.

Automatically Captured

GaN Live automatically generates:

RHEED video
Intensity profiles
Structured metadata
Linked ProcessID
Surface regime labels
Growth context

Nothing is lost.

Everything is reconstructable.

Replay Any Experiment

With GaN Playback you can:

Replay full experiments
Scrub frame-by-frame
Overlay intensity envelopes
Inspect regime transitions

But more importantly—

You can re-analyze them.

Turbo Re-Analysis

Playback processes data as fast as frames can be handled.

Typically:

~10 seconds to re-analyze a 5-minute growth video.

No re-growth required.

No new wafer.

Just compute.

Try Different AI Models On The Fly

Swap model versions instantly:

Old vs new classifiers
Different hyperparameters
Alternative fitting approaches

Compare outputs side-by-side.

You are no longer locked into one AI decision.

You can iterate safely.

Generate Training Data Automatically

Playback allows you to:

Auto-annotate existing experiments
Generate structured training datasets
Extract envelope features
Label transitions
Store clean datasets

In minutes.

AI adoption becomes incremental, not disruptive.

Controlled Experimentation

You can:

Add synthetic noise
Smooth signals
Compare deterministic vs stochastic fitting models
Stress-test classification logic

Before deploying new logic to live systems.

Playback becomes the sandbox for improvement.

The Strategic Advantage

AI systems degrade when:

Data is messy
Upgrades are risky
Retraining is painful

Playback solves this.

It:

Preserves experiments
Makes re-analysis trivial
Enables painless model iteration
Keeps improvements safe

AI becomes an evolving tool.

Not a frozen dependency.

The Philosophy

GaN Live executes.

GaN Playback learns.

Together, they create a loop:

Experiment → Capture → Re-analyze → Improve → Deploy

That loop compounds.

And over time, your system becomes smarter without adding risk.