⚡ Bolt: optimize unique random number generation

[babelman97]

💡 What

Implemented a hybrid sampling strategy in random.html for unique random number generation.

• Low density (< 50%): Uses rejection sampling with a Set.
• High density (>= 50%): Uses a Sparse Fisher-Yates shuffle algorithm with a Map.
• Switched DOM updates from innerText to textContent.
• Added CSS max-height and overflow-y: auto to the results container.
• Added range validation and a 10,000,000 limit safety cap.

🎯 Why

Rejection sampling suffers from the "coupon collector's problem" where collisions become extremely frequent as the sample count approaches the range size, leading to $O(N^2)$ or worse performance. This caused the browser to hang for several seconds when generating large unique sets.

📊 Impact

• Logic performance: Internal JS execution for 999,999 numbers in a 1,000,000 range improved by ~6.5x (from ~2600ms to ~400ms).
• Total performance: Total browser time (including DOM rendering) for 1M numbers reduced from ~14.5s to ~5.5s.
• UX: The UI no longer breaks or hangs when displaying millions of digits, thanks to CSS containment and scrollable results.

🔬 Measurement

Verified using a Playwright benchmarking script measuring performance.now() for internal logic and total time until the DOM reflects the results. Screenshot random_optimized.png shows the new scrollable UI.

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PR created automatically by Jules for task 2622278185721710192 started by @babelman97

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