Build, simulate, transpile, and execute quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.
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name
qiskit
description
Build, simulate, transpile, and execute quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.
license
Apache-2.0
compatibility
Python 3.10+ on a supported 64-bit platform. Local SDK workflows need qiskit; noisy simulation needs qiskit-aer; IBM QPU access needs qiskit-ibm-runtime, network access, an IBM Quantum Platform account, and an API key.
metadata
{"version":"2.0","skill-author":"K-Dense Inc."}
Qiskit
Use current Qiskit 2.x APIs to build circuits, prepare hardware-compatible instruction set architecture (ISA) circuits, and execute them through V2 primitives.
This skill was verified on 2026-07-23 against the PyPI releases qiskit==2.5.0, qiskit-ibm-runtime==0.48.0, and qiskit-aer==0.17.2. Check references/sources.md before changing pins or documenting newly released behavior.
Choose the Right Path
Goal
Recommended interface
Exact local sampling
qiskit.primitives.StatevectorSampler
Exact local expectation values
qiskit.primitives.StatevectorEstimator
High-performance or noisy simulation
Qiskit Aer
IBM QPU sampling
qiskit_ibm_runtime.SamplerV2
IBM QPU expectation values and mitigation
qiskit_ibm_runtime.EstimatorV2
Backend without native primitives
BackendSamplerV2 or BackendEstimatorV2
Open-system or master-equation dynamics
Prefer QuTiP
Differentiable quantum machine learning
Prefer PennyLane unless Qiskit integration is required
Installation
Create an isolated environment and install only the components needed:
uv venv --python 3.13
source .venv/bin/activate
# Core SDK plus plotting support
uv pip install "qiskit[visualization]==2.5.0"# Add only when needed
uv pip install "qiskit-ibm-runtime==0.48.0"
uv pip install "qiskit-aer==0.17.2"
Do not install qiskit-terra; it was superseded by the qiskit distribution. Qiskit Runtime, Aer, Nature, Machine Learning, Optimization, and Algorithms are separate distributions.
For IBM account setup, CI-safe credential handling, optional packages, and environment repair, read references/setup.md.
Core Workflow
Follow this sequence for every hardware-oriented workload:
Map the problem to a circuit and, for Estimator, one or more observables.
Optimize the parameterized circuit once for the selected backend.
Apply the layout to every observable.
Execute ISA circuits through a V2 primitive using Primitive Unified Blocs (PUBs).
Analyze register-aware results, metadata, uncertainty, and resource usage.
Do not bind and retranspile a parameterized circuit inside every optimizer iteration. Transpile the parameterized circuit once, then pass parameter arrays in PUBs.
Quick Local Sampling
from qiskit import QuantumCircuit
from qiskit.primitives import StatevectorSampler
circuit = QuantumCircuit(2)
circuit.h(0)
circuit.cx(0, 1)
circuit.measure_all() # creates the classical register named "meas"
sampler = StatevectorSampler(seed=7)
pub_result = sampler.run([circuit], shots=1024).result()[0]
counts = pub_result.data.meas.get_counts()
print(counts)
Sampler V2 preserves shots and classical-register structure. Access the register by its actual name; measure_all() uses meas.
Error mitigation is not guaranteed to improve every workload and increases cost. Record the complete options and result metadata.
Non-Negotiable Qiskit 2.x Rules
Use V2 primitive interfaces and PUB inputs. Do not write new V1 Sampler, Estimator, or QuantumInstance code.
Runtime primitives accept ISA circuits; they do not perform layout, routing, and basis translation for you.
Apply the transpiler layout to Estimator observables with observable.apply_layout(isa_circuit.layout).
Use mode=backend, mode=session, or mode=batch for Runtime primitives.
Use EstimatorV2 for resilience levels and expectation-value mitigation. Sampler has different noise-management options and no Estimator-style resilience levels.
Treat BackendV2.target, backend.operation_names, backend.coupling_map, and direct backend attributes as the source of hardware constraints. Do not use backend.configuration() or BackendProperties.
Read Sampler output by classical register name. Bitstrings are displayed most-significant bit first; Qiskit qubit 0 is conventionally the least-significant bit.
Use a fixed seed_transpiler when comparing compilation settings. A simulator seed does not make QPU results deterministic.
qiskit.pulse was removed in Qiskit 2.0. Use supported fractional gates for IBM hardware or Qiskit Dynamics for pulse-model research.
QPY is the Qiskit-native circuit serialization format. Do not use Python pickle for untrusted circuit artifacts.
Job mode: one-off work; instantiate a primitive with mode=backend.
Batch mode: independent jobs submitted together; available on the Open Plan.
Session mode: iterative jobs that benefit from prioritized follow-on execution; unavailable on the Open Plan.
from qiskit_ibm_runtime import Batch, SamplerV2 as Sampler
with Batch(backend=backend, max_time="10m") as batch:
sampler = Sampler(mode=batch)
jobs = [sampler.run([circuit], shots=1024) for circuit in isa_circuits]
results = [job.result() for job in jobs]
Close sessions and batches after submission. Exiting their context stops new submissions but allows accepted jobs to finish, subject to service limits.
