i%lSrSSKJrJrJr SSKJrJr SSKJ r J r J r J r \Sr \ "SS55rg ) z-Zero noise extrapolation mitigation options..)UnionSequenceLiteral)field_validatormodel_validator)Unset UnsetTypeprimitive_dataclassskip_unset_validation) linear exponentialdouble_exponentialpolynomial_degree_1polynomial_degree_2polynomial_degree_3polynomial_degree_4polynomial_degree_5polynomial_degree_6polynomial_degree_7fallbackc2\rSrSr%Sr\r\\\ S4\ S'\r \\\ \ 4\ S'\r\\\\ \4\ S'\r\\\ \ 4\ S'S\ \ 4S jr\S\ \4S j5r\"S5\\S \ \ S\ \ 4S j555r\"S S9SSj5rSrg) ZneOptions$a Zero noise extrapolation mitigation options. This is only used by the V2 Estimator. .. note:: Any V2 estimator is guaranteed to return data fields called ``evs`` and ``stds`` that report the desired expectation value estimates and errors, respectively. When ZNE options are enabled in the runtime estimator, additional data is returned. In particular, suppose an input pub has observable array shape ``obs_shape`` and parameter values shape ``par_shape``, with corresponding pub shape ``shape=np.broadcast_shapes(obs_shape, par_shape)``. Then the corresponding pub result will additionally contain: 1. `pub_result.data.evs_extrapolated` and `pub_result.data.stds_extrapolated`, both with shape ``(*shape, num_extrapolators, num_evaluation_points)``, where ``num_extrapolators`` is the length of the list of ``options.resilience.zne.extrapolators``, and ``num_evaluation_points`` is the length of the list ``options.resilience.extrapolated_noise_factors``. These values provide evaluations of every extrapolator at every specified noise extrapolation value. 2. ``pub_result.data.evs_noise_factors``, ``pub_result.data.stds_noise_factors``, and ``ensemble_stds_noise_factors`` all have shape ``(*shape, num_noise_factors)`` where ``num_noise_factors`` is the length of ``options.resilience.zne.noise_factors``. These values provide raw expectation values, averaged over twirling if applicable, at each of the noise amplifications; you can base your own fitting routines off of these values. In the case of no twirling, both ``*stds*`` arrays will be equal, otherwise, ``stds_noise_factors`` is derived from the spread over twirling samples, whereas ``ensemble_stds_noise_factors`` assumes only shot noise and no drift. Technical note: for single observables with multiple basis terms it might turn out that multiple extrapolation methods are used in *the same* expectation value, for example, ``XX`` gets linearly extrapolated but ``XY`` gets exponentially extrapolated in the observable ``{"XX": 0.5, "XY": 0.5}``. Let's call this a *heterogeneous fit*. The data from (2) is evaluated from heterogeneous fits by selecting the best fit for every individual distinct term, whereas data from (1) is evaluated from forced homogenous fits, one for each provided extrapolator. If your work requires a nuanced distinction in this regard, we presently recommend that you use single-term observables in addition to your multi-term observables. References: 1. Z. Cai, *Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications*, `npj Quantum Inf 7, 80 (2021) `_ ) gate_foldinggate_folding_frontgate_folding_backpea amplifier noise_factors extrapolatorextrapolated_noise_factorsreturnc*URS:XaS$S$)Nr)rg?g@)rr&)r)selfs `/home/james-whalen/.local/lib/python3.13/site-packages/qiskit_ibm_runtime/options/zne_options.py_default_noise_factors!ZneOptions._default_noise_factorss&*nn&="L9Lcg)N)rr )clss r)_default_extrapolator ZneOptions._default_extrapolators(r,factorscJ[SU55(a [S5eU$)zValidate noise_factors.c3*# UH oS:v M g7f)rNr.).0is r) 9ZneOptions._validate_zne_noise_factors..s&g1ugsz,noise_factors` option value must all be >= 1)any ValueError)r/r2s r)_validate_zne_noise_factors&ZneOptions._validate_zne_noise_factorss& &g& & &KL Lr,after)modecUR[:wa UROUR5nUR[:wa UROUR 5nSSSSS.n[ SS5HnUS-USU3'M [ U[5(aU/OUnUH'n[U5X6:dM[USX6S35e U$) z@Check that there are enough noise factors for all extrapolators.r%r)r rrrpolynomial_degree_z requires at least z noise_factors) r r r*r!r0range isinstancestrlenr:)r(r r!required_factorsidx extrapolatorsextraps r)_validate_optionsZneOptions._validate_optionss#'"4"4"=D  4C^C^C` "&!2!2e!;D  A[A[A]  "#   A;C;>7 1#7 8 ,,,N  $F=!$4$<< h12B2J1K>Z$  r,r.N)r#r)__name__ __module__ __qualname____firstlineno____doc__r rrr r__annotations__r rfloatr!ExtrapolatorTyper"r* classmethodr0rr r;rrK__static_attributes__r.r,r)rr$s#)Z u7[\\.8=M5HUO34<TYL% #3X>N5OOPX*EJi%&@ AIMM)h/?&@))_%(5/huo& '"#r,rN)rQtypingrrrpydanticrrutilsr r r r rTrr.r,r)rZsE4++5OO  WWWr,