ISEARCH
ISEARCH = 0 | 1
Default: ISEARCH = 0
Description: Controls the line-search algorithm used during the direct minimization of the electronic structure (ALGO = All).
The line search determines the optimal step size along the conjugate gradient search direction. ISEARCH = 0 performs incremental steps along the search direction. It may lead to inconsistencies in total energy evaluations and slower convergence. ISEARCH = 1 introduces a more robust and consistent method for determining the optimal step size, leading to improved convergence behavior and more reliable energy minimization.
Important: We recommend ISEARCH = 1 when performing electronic minimizations with ALGO = All, as it generally improves convergence stability and reduces the total number of required SCF steps.
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Mind: ISEARCH = 0 should only be used for backward compatibility or benchmarking against legacy behavior.
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Improved line-search algorithm (ISEARCH = 1)
The improved algorithm introduces several technical enhancements over the legacy implementation to ensure more robust convergence:
- Absolute Reference: Each line search step is calculated from the origin of the search direction rather than progressing incrementally. This maintains energy consistency and reduces cumulative rounding errors.
- Intelligent Slot System: Trial steps are managed through a "slot-in" mechanism. This system avoids redundant evaluations and strategically places new probes near the predicted minimum to provide the curvature data needed for higher-order fits.
- Adaptive Fitting Logic: The algorithm scales complexity based on the data density:
- Low density (≤ 5 points): Uses a combined Harmonic (2nd-order) and 4th-order polynomial fit. The 4th-order result is only accepted if it is consistent with the harmonic direction.
- High density (> 5 points): Employs Cubic Spline interpolation, which is more robust against the oscillations often found in high-order polynomials.
- Hybrid Gradient-Energy Correction: While primarily using energy, the algorithm monitors the slope. If the slope at the new point suggests the minimum was missed, it applies a Harmonic Correction to rescale the step length before attempting a polynomial fit.
- Concave Safety Descent: If the second derivative of the fit is negative (indicating a "hill" rather than a "valley"), the algorithm ignores the fit and automatically reverts to the step that yielded the lowest energy evaluation recorded in the current search.