runtime.integrator settings
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Settings
bin_number_evolution
#runtime.integrator.bin_number_evolution
Optional per-iteration bin counts, overriding the fixed n_bins value as training proceeds.
- Type
array | null- Required
- no
- Default
- Not set
- Allowed values
- Any value accepted by the declared type
continuous_dim_learning_rate
#runtime.integrator.continuous_dim_learning_rate
Update rate for adaptive grids over continuous integration dimensions.
- Type
number- Required
- no
- Default
1.0- Allowed values
- Any value accepted by the declared type
discrete_dim_learning_rate
#runtime.integrator.discrete_dim_learning_rate
Update rate for learned probabilities over discrete sampling choices.
- Type
number- Required
- no
- Default
1.0- Allowed values
- Any value accepted by the declared type
integrated_phase
#runtime.integrator.integrated_phase
Complex component to integrate: real, imaginary, or both.
- Type
IntegratedPhase- Required
- no
- Default
"real"- Allowed values
both,imag,real
max_prob_ratio
#runtime.integrator.max_prob_ratio
Cap the ratio used when turning sampled weights into adaptive probabilities.
- Type
number- Required
- no
- Default
30.0- Allowed values
- Any value accepted by the declared type
min_samples_for_update
#runtime.integrator.min_samples_for_update
Minimum accumulated samples before an adaptive grid or discrete probability is updated.
- Type
integer- Required
- no
- Default
1000- Allowed values
- Any value accepted by the declared type
n_bins
#runtime.integrator.n_bins
Number of bins maintained along each continuous integration dimension.
- Type
integer- Required
- no
- Default
64- Allowed values
- Any value accepted by the declared type
n_increase
#runtime.integrator.n_increase
Samples added to each successive Monte Carlo iteration.
- Type
integer- Required
- no
- Default
10000- Allowed values
- Any value accepted by the declared type
n_max
#runtime.integrator.n_max
Hard upper bound on the total number of integrand evaluations.
- Type
integer- Required
- no
- Default
10000000000- Allowed values
- Any value accepted by the declared type
n_start
#runtime.integrator.n_start
Number of samples in the first Monte Carlo iteration.
- Type
integer- Required
- no
- Default
100000- Allowed values
- Any value accepted by the declared type
seed
#runtime.integrator.seed
Seed for deterministic initialization of Monte Carlo random-number streams.
- Type
integer- Required
- no
- Default
69- Allowed values
- Any value accepted by the declared type
show_max_wgt_info
#runtime.integrator.show_max_wgt_info
Include maximum-weight diagnostics in integration progress and result data.
- Type
boolean- Required
- no
- Default
true- Allowed values
- Any value accepted by the declared type
target_absolute_accuracy
#runtime.integrator.target_absolute_accuracy
Stop once the estimated absolute uncertainty reaches this value, if configured.
- Type
number | null- Required
- no
- Default
- Not set
- Allowed values
- Any value accepted by the declared type
target_relative_accuracy
#runtime.integrator.target_relative_accuracy
Stop once the estimated relative uncertainty reaches this value, if configured.
- Type
number | null- Required
- no
- Default
- Not set
- Allowed values
- Any value accepted by the declared type
train_on_avg
#runtime.integrator.train_on_avg
Train adaptive distributions on iteration averages instead of individual sample weights.
- Type
boolean- Required
- no
- Default
false- Allowed values
- Any value accepted by the declared type