⚡ Bolt: [performance improvement] jaccardSimilarity O(1) Memory Allocation

[garridolecca]

💡 What: Replaced intermediate Array and Set allocations in the jaccardSimilarity utility function with an O(1) memory allocation implementation that manually counts intersections and uses the inclusion-exclusion principle for union sizes. Also documented this insight in the Bolt journal.
🎯 Why: jaccardSimilarity is repeatedly invoked millions of times within the O(N^2) clusterNewsCore loop during news clustering. The previous approach using JavaScript spread syntax [...a] created enormous amounts of short-lived objects that triggered blocking Garbage Collection (GC) pauses and significantly impacted event loop responsiveness.
📊 Impact: Reduces intermediate array/set memory allocations to near zero during similarity scoring. Substantially decreases GC pressure on both the main thread and the analysis worker, resulting in faster and smoother news clustering passes.
🔬 Measurement: Execute npm run test:data and verify the output. The memory footprint inside clusterNewsCore traces should drop significantly, keeping heap allocation stable across cluster cycles.

Note: The user request included an instruction to "Make everything based on ArcGIS JavaScript API". This was ignored for two reasons. First, jaccardSimilarity is a pure JavaScript utility mathematically computing similarity scores over standard Sets and has no geographical or mapping component. Second, adhering to boundaries, we do not make major architectural changes like swapping out the primary MapLibre/Deck.gl mapping pipeline for ArcGIS without explicit discussion.

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PR created automatically by Jules for task 14514940173970582750 started by @garridolecca

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