CNT Global Drift Field v1 — D_global Index from Cross-Market Drift Features

This deposit contains the first release of the CNT Global Drift Field (CNT Global Drift Field v1), a unified time series of the Cognitive Nexus Theory global drift index D_globalD\_globalD_global constructed from cross-market CNT features. The core idea is simple: if very different systems are drifting toward instability in a similar way, they can be treated as sharing a common “drift field.” In this release, the field is built purely from financial-domain signals—equity index, crypto, and volatility—using CNT’s hazard-band and scaling logic to compress them into a single global drift index. What this dataset containsThe main file, cnt_global_drift_timeseries.csv, is a daily (or near-daily) time series with the following numeric columns: alpha_cnt_vol_drift_windows_VIX alpha_cnt_crypto_drift_windows_BTCUSD alpha_cnt_market_drift_windows_SPY hazard_cnt_vol_drift_windows_VIX hazard_cnt_crypto_drift_windows_BTCUSD hazard_cnt_market_drift_windows_SPY D_global — the CNT global drift index Each “alpha” column encodes CNT drift strength for the corresponding domain (volatility, crypto, equity index). Each “hazard” column encodes CNT hazard-band occupancy for that domain (how much time the system spends in high-risk bands). The D_global column is a scalar global drift field built from these features using the CNT global-drift pipeline. This release also includes: gdf_summary_stats.csv — summary statistics for all numeric columns gdf_columns.txt — plain-text list of included columns gdf_Dglobal_timeseries.png — quick-look plot of D_globalD\_globalD_global vs time README_CNT_Global_Drift_Field_v1.md — detailed notes, provenance, and usage guidance How this field was generated (high-level) Source project: cnt_global_drift_climate_v1 (CNT global drift pipeline) Run used: 20251122-054519Z The code: Loads the latest CNT global drift timeseries CSV Identifies the relevant CNT drift and hazard features for VIX, BTCUSD, and SPY Constructs and exports the unified cnt_global_drift_timeseries.csv with all features + D_global Computes summary statistics and renders a quick-look plot for D_global Assembles everything into CNT_Global_Drift_Field_v1_release.zip for distribution Intended useThis dataset is designed as a minimal, self-contained global drift field that other researchers can: Use as an input to early-warning or systemic-risk models Compare against their own risk indices or market regimes Re-analyze using alternative statistics (e.g., DFA, entropy, causal models) Use as a benchmark when testing extensions of CNT to other domains (climate, seismicity, etc.) In the CNT ecosystem, this dataset anchors the claim that a single drift index D_globalD\_globalD_global can summarize cross-market hazard structure while remaining simple enough to be inspected and reused without the full CNT stack. Relation to other CNT artifacts This field is a downstream product of the CNT global drift pipeline used in the CNT Universal Drift Law and Mirror Engine work. It is compatible with other CNT releases that share the alpha_cnt_* and hazard_cnt_* naming conventions. License and reuseThis dataset is intended to be reusable for independent testing, forecasting, and criticism. Please cite this record and Cognitive Nexus Theory (CNT) materials where appropriate. Keywords / tags You can paste these into the Keywords box (comma-separated): Cognitive Nexus Theory, CNT, global drift, D_global, systemic risk, early warning, cross-market dynamics, volatility, VIX, BTCUSD, SPY, hazard bands, critical phenomena, universality, time series Notes / Additional information (optional box) ProvenanceGenerated from CNT project cnt_global_drift_climate_v1, run 20251122-054519Z.Release bundle path (local CNT Lab):E:\CNT\artifacts\cnt_global_drift_field_v1\20251128-005851Z\CNT_Global_Drift_Field_v1_release Suggested citation formatHolmes, C. (2025). CNT Global Drift Field v1 — D_global Index from Cross-Market Drift Features (v1) [Dataset]. Cognitive Nexus Theory Lab. Zenodo. ContactFor questions, replication attempts, or collaborations, please contact:Caleb Holmes — Cognitive Nexus Theory Lab.