---
title: StatevectorSampler (latest version)
description: API reference for qiskit.primitives.StatevectorSampler in the latest version of qiskit
source: https://quantum.cloud.ibm.com/docs/en/api/qiskit/qiskit.primitives.StatevectorSampler
---

# StatevectorSampler

*class* `qiskit.primitives.StatevectorSampler(*, default_shots=1024, seed=None)`

[GitHub](https://github.com/Qiskit/qiskit/tree/stable/2.5/qiskit/primitives/statevector_sampler.py#L51-L204)

Bases: [`BaseSamplerV2`](/docs/api/qiskit/qiskit.primitives.BaseSamplerV2 "qiskit.primitives.base.base_sampler.BaseSamplerV2")

Simple implementation of [`BaseSamplerV2`](/docs/api/qiskit/qiskit.primitives.BaseSamplerV2 "qiskit.primitives.BaseSamplerV2") using full state vector simulation.

This class is implemented via [`Statevector`](/docs/api/qiskit/qiskit.quantum_info.Statevector "qiskit.quantum_info.Statevector") which turns provided circuits into pure state vectors, and is therefore incompatible with mid-circuit measurements (although other implementations may be).

As seen in the example below, this sampler supports providing arrays of parameter value sets to bind against a single circuit.

Each tuple of `(circuit, <optional> parameter values, <optional> shots)`, called a sampler primitive unified bloc (PUB), produces its own array-valued result. The [`run()`](#qiskit.primitives.StatevectorSampler.run "qiskit.primitives.StatevectorSampler.run") method can be given many pubs at once.

```python
from qiskit.circuit import (
    Parameter, QuantumCircuit, ClassicalRegister, QuantumRegister
)
from qiskit.primitives import StatevectorSampler

import matplotlib.pyplot as plt
import numpy as np

# Define our circuit registers, including classical registers
# called 'alpha' and 'beta'.
qreg = QuantumRegister(3)
alpha = ClassicalRegister(2, "alpha")
beta = ClassicalRegister(1, "beta")

# Define a quantum circuit with two parameters.
circuit = QuantumCircuit(qreg, alpha, beta)
circuit.h(0)
circuit.cx(0, 1)
circuit.cx(1, 2)
circuit.ry(Parameter("a"), 0)
circuit.rz(Parameter("b"), 0)
circuit.cx(1, 2)
circuit.cx(0, 1)
circuit.h(0)
circuit.measure([0, 1], alpha)
circuit.measure([2], beta)

# Define a sweep over parameter values, where the second axis is over
# the two parameters in the circuit.
params = np.vstack([
    np.linspace(-np.pi, np.pi, 100),
    np.linspace(-4 * np.pi, 4 * np.pi, 100)
]).T

# Instantiate a new statevector simulation based sampler object.
sampler = StatevectorSampler()

# Start a job that will return shots for all 100 parameter value sets.
pub = (circuit, params)
job = sampler.run([pub], shots=256)

# Extract the result for the 0th pub (this example only has one pub).
result = job.result()[0]

# There is one BitArray object for each ClassicalRegister in the
# circuit. Here, we can see that the BitArray for alpha contains data
# for all 100 sweep points, and that it is indeed storing data for 2
# bits over 256 shots.
assert result.data.alpha.shape == (100,)
assert result.data.alpha.num_bits == 2
assert result.data.alpha.num_shots == 256

# We can work directly with a binary array in performant applications.
raw = result.data.alpha.array

# For small registers where it is anticipated to have many counts
# associated with the same bitstrings, we can turn the data from,
# for example, the 22nd sweep index into a dictionary of counts.
counts = result.data.alpha.get_counts(22)

# Or, convert into a list of bitstrings that preserve shot order.
bitstrings = result.data.alpha.get_bitstrings(22)
print(bitstrings)
```

**Parameters**

- **default\_shots** ([*int*](https://docs.python.org/3/library/functions.html#int)) – The default shots for the sampler if not specified during run.
- **seed** (*np.random.Generator |* [*int*](https://docs.python.org/3/library/functions.html#int) *| None*) – The seed or Generator object for random number generation. If None, a random seeded default RNG will be used.

## Attributes

### default\_shots

Return the default shots

### seed

Return the seed or Generator object for random number generation.

## Methods

### run

`run(pubs, *, shots=None)`

[GitHub](https://github.com/Qiskit/qiskit/tree/stable/2.5/qiskit/primitives/statevector_sampler.py#L156-L171)

Run and collect samples from each pub.

**Parameters**

- **pubs** ([*Iterable*](https://docs.python.org/3/library/collections.abc.html#collections.abc.Iterable)*\[TypeAliasForwardRef('SamplerPubLike')]*) – An iterable of pub-like objects. For example, a list of circuits or tuples `(circuit, parameter_values)`.
- **shots** ([*int*](https://docs.python.org/3/library/functions.html#int) *| None*) – The total number of shots to sample for each sampler pub that does not specify its own shots. If `None`, the primitive’s default shots value will be used, which can vary by implementation.

**Returns**

The job object of Sampler’s result.

**Return type**

[*PrimitiveJob*](/docs/api/qiskit/qiskit.primitives.PrimitiveJob "qiskit.primitives.primitive_job.PrimitiveJob")\[[*PrimitiveResult*](/docs/api/qiskit/qiskit.primitives.PrimitiveResult "qiskit.primitives.containers.primitive_result.PrimitiveResult")\[[*SamplerPubResult*](/docs/api/qiskit/qiskit.primitives.SamplerPubResult "qiskit.primitives.containers.sampler_pub_result.SamplerPubResult")]]