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Duplicate from phanerozoic/qiskit-calibration-drift
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metadata
license: cc-by-4.0
task_categories:
  - time-series-forecasting
  - tabular-classification
tags:
  - quantum-computing
  - IBM-Quantum
  - calibration
  - hardware-characterization
  - drift-analysis
  - qiskit
  - space-weather
  - cosmic-rays
pretty_name: IBM Quantum Calibration Drift
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: backend
      dtype: string
    - name: qubit
      dtype: int64
    - name: property
      dtype: string
    - name: value
      dtype: float64
    - name: calibrated_time
      dtype: string
    - name: observed_time
      dtype: string
    - name: location
      dtype: string
    - name: latitude
      dtype: float64
    - name: longitude
      dtype: float64
    - name: solar_zenith_deg
      dtype: float64
    - name: temperature_c
      dtype: float64
    - name: pressure_hpa
      dtype: float64
    - name: humidity_pct
      dtype: float64
    - name: kp_index
      dtype: float64
    - name: solar_flux_sfu
      dtype: float64
    - name: dst_nt
      dtype: float64
    - name: bz_gsm_nt
      dtype: float64
    - name: neutron_flux
      dtype: float64
  splits:
    - name: train
      num_bytes: 30865256
      num_examples: 155368
  download_size: 1065305
  dataset_size: 30865256

IBM Quantum Calibration Drift Dataset

Continuously-updated calibration data from IBM Quantum hardware with concurrent environmental measurements. Enables correlation analysis between qubit performance and atmospheric/space weather conditions.

Overview

Property Value
Update frequency Every 30 minutes
Backends ibm_fez (156 qubits), ibm_torino (133 qubits), ibm_marrakesh (156 qubits)
Total qubits 445
Collection method Automated polling via GitHub Actions
Calibration source IBM Quantum Runtime API
Weather source NWS API (NOAA)
Space weather source SWPC (NOAA)

Schema

Field Type Description
backend string Backend identifier
qubit int Qubit index (0 to N-1), or -1 for two-qubit gate data
property string Calibration property name
value float Measured value
calibrated_time string IBM calibration timestamp (UTC)
observed_time string Collection timestamp (UTC ISO)
location string Data center location identifier
latitude float Data center latitude
longitude float Data center longitude
solar_zenith_deg float Solar zenith angle (>90° = night)
temperature_c float Local temperature (°C)
pressure_hpa float Barometric pressure (hPa)
humidity_pct float Relative humidity (%)
kp_index float Planetary K-index (0-9, geomagnetic activity)
solar_flux_sfu float 10.7cm solar radio flux (SFU)
dst_nt float Dst index (nT, ring current strength)
bz_gsm_nt float IMF Bz component (nT, negative = geo-coupling)
neutron_flux float Cosmic ray proxy (Newark, DE monitor)

Important: Timestamp Interpretation

This dataset contains two timestamp fields with very different meanings:

  • calibrated_time — When IBM last calibrated that specific property. These timestamps can span months because IBM does not recalibrate all properties simultaneously. Some properties (like T1/T2) may retain calibration timestamps from weeks or months ago.

  • observed_time — When the poller actually collected the record. This reflects the true data collection period.

For time-series analysis, use observed_time. The calibrated_time span reflects IBM's stale cache, not the collection period.

Calibration Properties

Per-qubit:

  • T1 — Relaxation time (seconds)
  • T2 — Dephasing time (seconds)
  • readout_error — Measurement error probability
  • prob_meas0_prep1 — P(measure 0 | prepared 1)
  • prob_meas1_prep0 — P(measure 1 | prepared 0)
  • sx_error — SX gate error (native single-qubit gate)

Per-edge:

  • cz_error_{i}_{j} — Two-qubit CZ gate error for edge (i, j)

Environmental Fields

Solar position:

  • solar_zenith_deg — Sun angle from vertical (0°=overhead, 90°=horizon, >90°=night)

Weather (local to data center):

  • temperature_c — Ambient temperature
  • pressure_hpa — Barometric pressure (correlates with cosmic ray flux attenuation)
  • humidity_pct — Relative humidity

Space weather (global):

  • kp_index — Geomagnetic storm indicator (0=quiet, 9=severe storm)
  • solar_flux_sfu — Solar activity proxy (higher = more active sun)
  • dst_nt — Ring current strength (< -50 nT = storm, < -100 nT = severe)
  • bz_gsm_nt — Interplanetary magnetic field z-component (negative = geomagnetic coupling)
  • neutron_flux — Cosmic ray flux from Newark, DE monitor (pressure-corrected)

Data Center Locations

Location ID Coordinates Backends
yorktown_heights_ny 41.27°N, 73.78°W ibm_torino, ibm_fez, ibm_marrakesh

Usage

from datasets import load_dataset

ds = load_dataset("phanerozoic/qiskit-calibration-drift", split="train")

# Filter by backend
torino = ds.filter(lambda x: x["backend"] == "ibm_torino")

# Correlation analysis: T1 vs pressure
t1_data = ds.filter(lambda x: x["property"] == "T1")
df = t1_data.to_pandas()
correlation = df["value"].corr(df["pressure_hpa"])

# Filter by space weather conditions
storm_data = ds.filter(lambda x: x["kp_index"] >= 5)

Research Applications

  • Cosmic ray correlation: Barometric pressure modulates atmospheric shielding against cosmic rays, which cause quasiparticle poisoning in superconducting qubits.
  • Geomagnetic storm effects: Kp index tracks magnetospheric disturbances that may correlate with qubit coherence.
  • Solar cycle tracking: Dataset spans the declining phase of Solar Cycle 25 (peaked October 2024).
  • Seasonal/diurnal patterns: Long-term collection enables detection of periodic environmental effects.

Note: Environmental correlation studies require weeks to months of continuous observed_time coverage. Check the current observation window before attempting such analyses.

Collection Method

Data is collected via GitHub Actions every 30 minutes:

  1. Fetch space weather (NOAA SWPC)
  2. Fetch local weather (NWS API)
  3. Query IBM Quantum calibration data
  4. Deduplicate by (backend, qubit, property, calibrated_time)
  5. Append new records to dataset

Source: github.com/CharlesCNorton/qiskit-calibration-drift

Citation

@dataset{qiskit-calibration-drift,
  title={IBM Quantum Calibration Drift Dataset},
  author={Norton, Charles C.},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/phanerozoic/qiskit-calibration-drift}
}

Acknowledgments

We acknowledge the NMDB database (www.nmdb.eu), founded under the European Union's FP7 programme (contract no. 213007) for providing neutron monitor data.

License

CC-BY-4.0