Update defaults for max overhead and layers to learn (#1535)

* update defaults * fix docstring
Qiskit · Mar 19, 2024 · 5625e98 · 5625e98
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diff --git a/qiskit_ibm_runtime/options/layer_noise_learning_options.py b/qiskit_ibm_runtime/options/layer_noise_learning_options.py
@@ -39,7 +39,7 @@ class LayerNoiseLearningOptions:
             If there are more unique layers present, then some layers will not be learned or
             mitigated. The learned layers are prioritized based on the number of times they
             occur in a set of run estimator PUBs, and for equally occurring layers are
-            further sorted by the number of two-qubit gates in the layer.
+            further sorted by the number of two-qubit gates in the layer. Default: 4.
 
         shots_per_randomization: The total number of shots to use per random learning circuit.
             A learning circuit is a random circuit at a specific learning depth with a specific

diff --git a/qiskit_ibm_runtime/options/pec_options.py b/qiskit_ibm_runtime/options/pec_options.py
@@ -23,7 +23,7 @@ class PecOptions:
 
     Args:
         max_overhead: The maximum circuit sampling overhead allowed, or
-            ``None`` for no maximum.
+            ``None`` for no maximum. Default: 100.
 
         noise_gain: The amount by which to scale the noise, where:
 

diff --git a/qiskit_ibm_runtime/sampler.py b/qiskit_ibm_runtime/sampler.py
@@ -94,7 +94,7 @@ def __init__(
             raise NotImplementedError("SamplerV2 is not supported with q-ctrl channel strategy.")
 
     def run(self, pubs: Iterable[SamplerPubLike], *, shots: int | None = None) -> RuntimeJobV2:
-        """Submit a request to the estimator primitive.
+        """Submit a request to the sampler primitive.
 
         Args:
             pubs: An iterable of pub-like objects. For example, a list of circuits