X-40 ResearchCore — Accelerate Discovery with Quantum Attention^™

Run physics-grade Φ-Anchors and entropy analytics on your own datasets — in milliseconds and with NVML-audited energy use near zero. Powered by QEIv15^™, the quantum-entropy core of X-40.

Testbed & API Version

GPU: NVIDIA H100 80GB HBM3 (Runpod)
CUDA: 12.1 · Torch: bf16 where applicable
API: X-40 ResearchCore v0.6 (Anchors, Audit, ZIP Batch)
Audit: NVML-based (avg_W, energy_Wh), measured per batch

How it works

You send one or more timeseries (e.g., an EEG channel, a climate station, a returns series). The API returns:

indices — anchor points (events/outliers/turns)
values — values at those indices
phi — compact entropy/structure score for the series
latency_ms — per-series processing time
_audit — { elapsed_ms, avg_W, energy_Wh } (always on in this demo)

JSON Batch (always audit=1)

Paste your items array and run. Response includes anchors, Φ, per-series latency, and batch energy.

[
  {
    "id": "series_1",
    "method": "zscore",
    "window": 64,
    "zscore": 2,
    "top_k": 32,
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