Extract physical observables with error estimates from completed DQMC simulations. Use when computing density, double occupancy, spin correlations, structure factors, or any measured quantity from simulation data.
bin_*.h5 files (completed simulations)(mean, stderr) tuples for each observableBasic analysis:
from dqmc_util import analyze_hub
data = analyze_hub.get("data/run/", "sign", "den", "zzr")
print(f"sign = {data['sign'][0]:.4f} +/- {data['sign'][1]:.4f}")
print(f"density = {data['den'][0]:.4f} +/- {data['den'][1]:.4f}")
Available observables:
| Name | Description |
|---|
| Requires |
|---|
sign | Fermion sign | - |
den | Density <n> | - |
docc | Double occupancy <n_up n_down> | - |
gr, gk | Green's function (real/k-space) | - |
nnr, nnq | Density correlator / structure factor | - |
zzr, zzq | Spin-z correlator / structure factor | - |
xxr | Spin-x correlator | - |
swq0 | S-wave pair structure factor | - |
nnrw0, zzrw0 | Zero-freq susceptibilities | period_uneqlt > 0 |
dwq0t | D-wave pair susceptibility | period_uneqlt > 0 |
Collect from multiple directories:
import os
def collect_results(base_dir, observables):
results = []
for subdir in sorted(os.listdir(base_dir)):
path = os.path.join(base_dir, subdir)
if os.path.isdir(path):
try:
results.append(analyze_hub.get(path + "/", *observables))
except Exception as e:
print(f"Skipping {path}: {e}")
return results
Compute derived quantities:
# Magnetic moment squared from spin correlator
path = "data/run/"
data = analyze_hub.get(path, "zzr")
mz2 = 4 * data["zzr"][0][0, 0] # [0] = mean, shape (Ny, Nx)
mz2_err = 4 * data["zzr"][1][0, 0] # [1] = stderr
| Symptom | Cause | Recovery |
|---|---|---|
| KeyError for observable | Observable not computed | Check period_uneqlt setting |
| "No files found" | Wrong path or no bin_*.h5 | Verify directory structure |
| Large error bars | Insufficient statistics | Run more sweeps or bins |