Sampling Noise and Optimized Measurement Distribution in Imaginary-Time Quantum Dynamics S

Simulation and analysis data for spin models with 6 and 8 sites, supporting a manuscript on quantum dynamics. The dataset includes raw data, Python scripts, and figure files. It was authored by Feng Zhang and last updated on 2026-05-19.

Use Cases

• Benchmarking quantum simulation algorithms based on spin model data
• Analyzing sampling noise in imaginary-time quantum dynamics based on the described simulation data
• Developing optimized measurement distribution strategies for quantum Monte Carlo methods based on the provided analysis

Strengths

• Includes data for two specific system sizes (6 and 8 sites), enabling comparative analysis
• Contains original Python scripts and Jupyter notebooks for reproducibility of the published figures
• All figures from the manuscript are provided in PDF format for reference

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• The dataset is relatively small at 13.9 MB, which may limit the scope of analysis

Provenance

Source

figshare

Collection Method

Likely generated from quantum Monte Carlo simulations as described in the associated manuscript.

Freshness

Last updated 2026-05-19 17:24:17