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Pre-release

This release is a pre-release and may not be stable for production use.

Stim

Stim is a fast simulator for quantum stabilizer circuits.

API references are available on the stim github wiki: https://github.com/quantumlib/stim/wiki

Stim can be installed into a python 3 environment using pip:

pip install stim

Once stim is installed, you can import stim and use it. There are three supported use cases:

  1. Interactive simulation with stim.TableauSimulator.
  2. High speed sampling with samplers compiled from stim.Circuit.
  3. Independent exploration using stim.Tableau and stim.PauliString.

Interactive Simulation

Use stim.TableauSimulator to simulate operations one by one while inspecting the results:

import stim

s = stim.TableauSimulator()

# Create a GHZ state.
s.h(0)
s.cnot(0, 1)
s.cnot(0, 2)

# Look at the simulator state re-inverted to be forwards:
t = s.current_inverse_tableau()
print(t**-1)
# prints:
# +-xz-xz-xz-
# | ++ ++ ++
# | ZX _Z _Z
# | _X XZ __
# | _X __ XZ

# Measure the GHZ state.
print(s.measure_many(0, 1, 2))
# prints one of:
# [True, True, True]
# or:
# [False, False, False]

High Speed Sampling

By creating a stim.Circuit and compiling it into a sampler, samples can be generated very quickly:

import stim

# Create a circuit that measures a large GHZ state.
c = stim.Circuit()
c.append("H", [0])
for k in range(1, 30):
    c.append("CNOT", [0, k])
c.append("M", range(30))

# Compile the circuit into a high performance sampler.
sampler = c.compile_sampler()

# Collect a batch of samples.
# Note: the ideal batch size, in terms of speed per sample, is roughly 1024.
# Smaller batches are slower because they are not sufficiently vectorized.
# Bigger batches are slower because they use more memory.
batch = sampler.sample(1024)
print(type(batch))  # numpy.ndarray
print(batch.dtype)  # numpy.uint8
print(batch.shape)  # (1024, 30)
print(batch)
# Prints something like:
# [[1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
#  [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
#  [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
#  ...
#  [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
#  [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
#  [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
#  [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]]

This also works on circuits that include noise:

import stim
import numpy as np

c = stim.Circuit("""
    X_ERROR(0.1) 0
    Y_ERROR(0.2) 1
    Z_ERROR(0.3) 2
    DEPOLARIZE1(0.4) 3
    DEPOLARIZE2(0.5) 4 5
    M 0 1 2 3 4 5
""")
batch = c.compile_sampler().sample(2**20)
print(np.mean(batch, axis=0).round(3))
# Prints something like:
# [0.1   0.2   0.    0.267 0.267 0.266]

You can also sample annotated detection events using stim.Circuit.compile_detector_sampler.

For a list of gates that can appear in a stim.Circuit, see the latest readme on github.

Independent Exploration

Stim provides data types stim.PauliString and stim.Tableau, which support a variety of fast operations.

import stim

xx = stim.PauliString("XX")
yy = stim.PauliString("YY")
assert xx * yy == -stim.PauliString("ZZ")

s = stim.Tableau.from_named_gate("S")
print(repr(s))
# prints:
# stim.Tableau.from_conjugated_generators(
#     xs=[
#         stim.PauliString("+Y"),
#     ],
#     zs=[
#         stim.PauliString("+Z"),
#     ],
# )

s_dag = stim.Tableau.from_named_gate("S_DAG")
assert s**-1 == s_dag
assert s**1000000003 == s_dag

cnot = stim.Tableau.from_named_gate("CNOT")
cz = stim.Tableau.from_named_gate("CZ")
h = stim.Tableau.from_named_gate("H")
t = stim.Tableau(5)
t.append(cnot, [1, 4])
t.append(h, [4])
t.append(cz, [1, 4])
t.prepend(h, [4])
assert t == stim.Tableau(5)

Metadata

Release files for stim 1.16.dev1758926350

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for stim 1.16.dev1758926350
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stim-1.16.dev1758926350-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
stim-1.16.dev1758926350-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp313-cp313-macosx_11_0_arm64.whl CPython 3.13 CPython 3.13 macOS 11.0+ ARM64 Details
stim-1.16.dev1758926350-cp313-cp313-macosx_10_13_x86_64.whl CPython 3.13 CPython 3.13 macOS 10.13+ x86-64 Details
stim-1.16.dev1758926350-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
stim-1.16.dev1758926350-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp312-cp312-macosx_11_0_arm64.whl CPython 3.12 CPython 3.12 macOS 11.0+ ARM64 Details
stim-1.16.dev1758926350-cp312-cp312-macosx_10_13_x86_64.whl CPython 3.12 CPython 3.12 macOS 10.13+ x86-64 Details
stim-1.16.dev1758926350-cp311-cp311-win_amd64.whl CPython 3.11 CPython 3.11 Windows x86-64 Details
stim-1.16.dev1758926350-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp311-cp311-macosx_11_0_arm64.whl CPython 3.11 CPython 3.11 macOS 11.0+ ARM64 Details
stim-1.16.dev1758926350-cp311-cp311-macosx_10_9_x86_64.whl CPython 3.11 CPython 3.11 macOS 10.9+ x86-64 Details
stim-1.16.dev1758926350-cp310-cp310-win_amd64.whl CPython 3.10 CPython 3.10 Windows x86-64 Details
stim-1.16.dev1758926350-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp310-cp310-macosx_11_0_arm64.whl CPython 3.10 CPython 3.10 macOS 11.0+ ARM64 Details
stim-1.16.dev1758926350-cp310-cp310-macosx_10_9_x86_64.whl CPython 3.10 CPython 3.10 macOS 10.9+ x86-64 Details
stim-1.16.dev1758926350-cp39-cp39-win_amd64.whl CPython 3.9 CPython 3.9 Windows x86-64 Details
stim-1.16.dev1758926350-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp39-cp39-macosx_11_0_arm64.whl CPython 3.9 CPython 3.9 macOS 11.0+ ARM64 Details
stim-1.16.dev1758926350-cp39-cp39-macosx_10_9_x86_64.whl CPython 3.9 CPython 3.9 macOS 10.9+ x86-64 Details
stim-1.16.dev1758926350-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details
stim-1.16.dev1758926350-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp38-cp38-macosx_11_0_arm64.whl CPython 3.8 CPython 3.8 macOS 11.0+ ARM64 Details
stim-1.16.dev1758926350-cp38-cp38-macosx_10_9_x86_64.whl CPython 3.8 CPython 3.8 macOS 10.9+ x86-64 Details
stim-1.16.dev1758926350-cp37-cp37m-win_amd64.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-64 Details
stim-1.16.dev1758926350-cp37-cp37m-win32.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-32 Details
stim-1.16.dev1758926350-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.17+ x86-32 Details
stim-1.16.dev1758926350-cp37-cp37m-macosx_10_9_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64 Details
stim-1.16.dev1758926350-cp36-cp36m-win_amd64.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-64 Details
stim-1.16.dev1758926350-cp36-cp36m-win32.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-32 Details
stim-1.16.dev1758926350-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.17+ x86-64 Details
stim-1.16.dev1758926350-cp36-cp36m-manylinux_2_17_i686.manylinux2014_i686.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.17+ x86-32 Details
stim-1.16.dev1758926350-cp36-cp36m-macosx_10_9_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.9+ x86-64 Details

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Release files / stim-1.16.dev1758926350-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

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1.9.0

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1.8.0

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1.7.1

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1.7.0

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1.6.0

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1.4.0

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1.3.0

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1.2.1

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1.2

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1.0

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