feat: experimental data calibration pipeline with ROOT I/O

- Fix chi2 calculation bug in calibration.py (remove incorrect
  coeffs[::-1] reversal in np.polyval)
- Fix broken beta_spectrum/cli.py (remove orphaned detector response
  add_argument calls and unused imports)
- Add ExpSpectrum.apply_calibration() and EnergyCalibrator.from_am241_spectrum()
- Add LivetimeDetermination class for pulser-based livetime
- Add SpectrumPipeline orchestration (read→subtract→calibrate→livetime→validate)
- Add ROOT I/O with PyROOT primary + uproot fallback
- Add bs_exp CLI with process, livetime, export subcommands
- Add exp_calibration notebook with pre-calibration visualization
- Add comprehensive tests (73 passing)
- Add bs_exp console script and [root] extra to pyproject.toml
- Remove obsolete detector_response module and unused notebooks

tests/exp_data/conftest.py

@@ -0,0 +1,55 @@
+"""Shared fixtures for exp_data tests."""
+
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+from exp_data.spectrum import ExpSpectrum
+from exp_data.calibration import CalibrationResult
+
+
+@pytest.fixture
+def synthetic_spectrum():
+    """Create a synthetic ExpSpectrum (4096 channels)."""
+    n_channels = 4096
+    energies = np.arange(n_channels, dtype=np.float64)
+    counts = np.exp(-energies / 500) * 1000 + np.random.poisson(5, n_channels)
+    return ExpSpectrum(
+        energies=energies,
+        counts=counts,
+        source="Tc99",
+        run_id="synthetic",
+    )
+
+
+@pytest.fixture
+def calibration_result():
+    """Create a synthetic CalibrationResult (linear, E = 0.4 + 0.1*ch)."""
+    coeffs = np.array([0.1, 0.4])  # polyfit order: [slope, intercept]
+    cov = np.eye(2) * 1e-6
+    return CalibrationResult(
+        coefficients=coeffs,
+        order=1,
+        chi2_per_dof=0.5,
+        n_points=2,
+        covariance=cov,
+    )
+
+
+@pytest.fixture
+def full_spectrum():
+    """Create a full ExpSpectrum with all fields populated."""
+    return ExpSpectrum(
+        energies=np.arange(4096, dtype=np.float64),
+        counts=np.exp(-np.arange(4096) / 500) * 1000 + np.random.poisson(5, 4096),
+        source="Tc99",
+        run_id="run_042",
+        date="2025-01-15",
+        dead_time=0.05,
+        live_time=3420.0,
+        metadata={
+            "calibration": {"type": "linear", "coefficients": [0.1, 0.4]},
+            "livetime": {"fraction": 0.95, "method": "pulser"},
+        },
+    )