samplomatic
Serving all of your circuit sampling needs since 2025.
Decision gist · record as of 2026-08-14
Yes, if you work with Qiskit and need systematic circuit randomization for error mitigation or noise studies. The low install friction, active maintenance, and permissive license make it a reasonable choice. However, expect breaking changes between minor versions (beta stage), so pin your dependency. No known security vulnerabilities as of 2026-08-14.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python ≥3.10 and qiskit runtime dependency; quantum circuit construction knowledge assumed.
- Low friction install with a pure-Python wheel.
- Active maintenance as of 2026-08-12.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
last release 2026-06-23 (52 days) · last repo commit 2026-08-12 · 24 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 306,696 downloads/mo, #7,785 on PyPI
Alternatives
Verify before relying
pip install samplomatic
from samplomatic import build, Twirl
from qiskit.circuit import QuantumCircuit
circuit = QuantumCircuit(2)
with circuit.box([Twirl()]):
circuit.sx(0)
circuit.cx(0, 1)
template, samplex = build(circuit)
samples = samplex.sample({"parameter_values": []}, num_randomizations=5)- Scope and maturity of the extensible randomization group system beyond Pauli twirling.
- Performance characteristics for large circuits or high-volume sampling.
- Whether visualization dependencies (samplomatic[vis]) are commonly needed.
What it is and what it does
Samplomatic is a library for generating randomized variants of quantum circuits with explicit, declarative intent. It works by annotating sections of a Qiskit quantum circuit with randomization instructions (like Twirl for Pauli twirling), then using a build process to generate a template circuit and a sampling engine (samplex) that encodes the randomization logic as a directed acyclic graph. The samplex can then produce many randomized circuit arguments without regenerating circuits, making it efficient for tasks like error mitigation through circuit randomization.
The library is designed for quantum researchers and engineers who need to systematically apply randomization patterns to circuits—whether for Pauli twirling, noise injection, or custom group-based transformations. It depends on qiskit, numpy, rustworkx, pybase64, and orjson. As a beta-stage project (version 0.20.0), it is actively maintained but subject to breaking changes between minor versions; the project may also relocate from its current GitHub home.
Use it for
- Apply Pauli twirling to quantum circuits for error mitigation in near-term quantum processors.
- Generate multiple randomized circuit variants from a single template for statistical noise characterization.
- Inject sampling-based noise into quantum circuits to study robustness under realistic error models.
- Parametrize quantum circuits with randomization intent for transpiler-based circuit optimization.
- Extend circuit randomization with custom group-based transformations for specialized quantum protocols.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with Qiskit and need systematic circuit randomization for error mitigation or noise studies.
The low install friction, active maintenance, and permissive license make it a reasonable choice. However, expect breaking changes between minor versions (beta stage), so pin your dependency. No known security vulnerabilities as of 2026-08-14.
Install
samplomatic on PyPI
Before you install
Low friction install with a pure-Python wheel. Active maintenance as of 2026-08-12. Beta-stage library (version 0.20.0) with documented breaking changes between minor versions—pin dependencies accordingly. Requires Python ≥3.10.
Requires Python ≥3.10 and qiskit runtime dependency; quantum circuit construction knowledge assumed.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
Quickstart
pip install samplomatic
from samplomatic import build, Twirl
from qiskit.circuit import QuantumCircuit
circuit = QuantumCircuit(2)
with circuit.box([Twirl()]):
circuit.sx(0)
circuit.cx(0, 1)
template, samplex = build(circuit)
samples = samplex.sample({"parameter_values": []}, num_randomizations=5)Verify before relying
- Scope and maturity of the extensible randomization group system beyond Pauli twirling.
- Performance characteristics for large circuits or high-volume sampling.
- Whether visualization dependencies (samplomatic[vis]) are commonly needed.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesqiskitnumpyrustworkxpybase64orjson |
| Maintenance | Actively maintained 52 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 306,696 / month, #7,785 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.11 |
Evidence: samplomatic-0.20.0-py3-none-any.whl
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