FiniteDiffSamplerGradient

class FiniteDiffSamplerGradient(sampler, epsilon, options=None, *, method='central')

Bases: BaseSamplerGradient

Compute the gradients of the sampling probability by finite difference method [1].

Reference: [1] Finite difference method

Parameters

• sampler (BaseSampler) – The sampler used to compute the gradients.

• epsilon (float) – The offset size for the finite difference gradients.

• options (Options | None) – Primitive backend runtime options used for circuit execution. The order of priority is: options in run method > gradient’s default options > primitive’s default setting. Higher priority setting overrides lower priority setting

• method (Literal[('central', 'forward', 'backward')]) –

  The computation method of the gradients.

  • central computes \(\frac{f(x+e)-f(x-e)}{2e}\),

  • forward computes \(\frac{f(x+e) - f(x)}{e}\),

  • backward computes \(\frac{f(x)-f(x-e)}{e}\)

  where \(e\) is epsilon.

Raises

• ValueError – If epsilon is not positive.

• TypeError – If method is invalid.

Methods

run	Run the job of the sampler gradient on the given circuits.
update_default_options	Update the gradient's default options setting.

Attributes

options

Return the union of sampler options setting and gradient default options, where, if the same field is set in both, the gradient’s default options override the primitive’s default setting.

Returns

The gradient default + sampler options.