Skip to main content

Ket quantum programming language interpreter and library

Project description

Ket Quantum Programming

PyPI Contributor Covenant REUSE status

[[TOC]]

Ket is an embedded programming language that introduces the ease of Python to quantum programming, letting anyone quickly prototype and test a quantum application.

Python is the most widely used programming language for machine learning and data science and has been the language of choice for quantum programming. Ket is a Python-embedded language, but many can use it as a Python library in most cases. So you can use Ket together with NumPy, ScyPy, Pandas, and other popular Python libraries.

Ket's goal is to streamline the development of hardware-independent classical quantum applications by providing transparent interaction of classical and quantum data. See https://quantumket.org to learn more about Ket.

Installation :arrow_down:

Ket requires Python 3.10 or newer and is available for Linux, Windows, and macOS (both Apple silicon and Intel). If you are using a non-x86_64 (Intel/AMD) CPU, such as ARM, on Linux or Windows, you will need to install Rust before installing Ket.

You can install Ket using pip. To do so, copy and paste the following command into your terminal:

pip install ket-lang

Documentation :scroll:

Documentation available at https://quantumket.org.

Examples :bulb:

Grover's Algorithm

from ket import *
from math import sqrt, pi


def grover(n: int, oracle) -> int:
    p = Process()
    qubits = H(p.alloc(n))
    steps = int((pi / 4) * sqrt(2**n))
    for _ in range(steps):
        oracle(qubits)
        with around(H, qubits):
            phase_oracle(0, qubits)
    return measure(qubits).value


n = 8
looking_for = 13
print(grover(n, phase_oracle(looking_for)))
# 13

Quantum Teleportation

from ket import *


def entangle(a: Quant, b: Quant):
    return CNOT(H(a), b)


def teleport(quantum_message: Quant, entangled_qubit: Quant):
    adj(entangle)(quantum_message, entangled_qubit)
    return measure(entangled_qubit).value, measure(quantum_message).value


def decode(classical_message: tuple[int, int], qubit: Quant):
    if classical_message[0] == 1:
        X(qubit)

    if classical_message[1] == 1:
        Z(qubit)


if __name__ == "__main__":
    from math import pi

    p = Process()

    alice_message = P(pi / 4, H(p.alloc()))

    alice_message_dump = dump(alice_message)

    alice_qubit, bob_qubit = entangle(*p.alloc(2))

    classical_message = teleport(
        quantum_message=alice_message, entangled_qubit=alice_qubit
    )

    decode(classical_message, bob_qubit)

    bob_qubit_dump = dump(bob_qubit)

    print("Alice Message:")
    print(alice_message_dump.show())

    print("Bob Qubit:")
    print(bob_qubit_dump.show())
# Alice Message:
# |0⟩     (50.00%)
#  0.707107               ≅      1/√2
# |1⟩     (50.00%)
#  0.500000+0.500000i     ≅  (1+i)/√4
# Bob Qubit:
# |0⟩     (50.00%)
#  0.707107               ≅      1/√2
# |1⟩     (50.00%)
#  0.500000+0.500000i     ≅  (1+i)/√4

Setup for Ket Development :hammer:

To get started with Ket development, follow these steps:

  1. Rust Installation

    Ensure that Rust is installed on your system. If not, follow the Rust install guide. After installation, set the Rust version to 1.88 using the following command:

    rustup default 1.88
    
  2. Clone and Compile

    Clone the Ket repository and compile the Rust libraries:

    git clone --recursive https://gitlab.com/quantum-ket/ket.git
    cd ket
    
    cargo build --manifest-path src/ket/clib/libs/libket/Cargo.toml
    cargo build --manifest-path src/ket/clib/libs/kbw/Cargo.toml
    
    ln -s libket/target/debug/libket.so src/ket/clib/libs
    ln -s kbw/target/debug/libkbw.so src/ket/clib/libs
    
  3. Set Up Virtual Environment

    Set up a virtual environment for Python:

    python3 -m venv venv
    source venv/bin/activate
    
  4. Install Dependencies

    Upgrade pip and install development requirements:

    pip install -U pip
    pip install -r requirements_dev.txt
    
  5. Install Ket

    Install Ket in editable mode:

    pip install -e .[full]
    
  6. Run Tests

    To ensure everything is correctly installed, run the tests:

    pytest
    

You're now set up for Ket development! Happy coding! 🚀

Cite Ket :book:

When using Ket for research projects, please cite:

Evandro Chagas Ribeiro da Rosa and Rafael de Santiago. 2021. Ket Quantum Programming. J. Emerg. Technol. Comput. Syst. 18, 1, Article 12 (January 2022), 25 pages. DOI: 10.1145/3474224

@article{ket,
   author = {Evandro Chagas Ribeiro da Rosa and Rafael de Santiago},
   title = {Ket Quantum Programming},
   year = {2021},
   issue_date = {January 2022},
   publisher = {Association for Computing Machinery},
   address = {New York, NY, USA},
   volume = {18},
   number = {1},
   issn = {1550-4832},
   url = {https://doi.org/10.1145/3474224},
   doi = {10.1145/3474224},
   journal = {J. Emerg. Technol. Comput. Syst.},
   month = oct,
   articleno = {12},
   numpages = {25},
   keywords = {Quantum programming, cloud quantum computation, qubit simulation}
}

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ket_lang-0.9.3.1.tar.gz (144.2 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

ket_lang-0.9.3.1-py3-none-win_amd64.whl (7.3 MB view details)

Uploaded Python 3Windows x86-64

ket_lang-0.9.3.1-py3-none-manylinux_2_28_x86_64.whl (4.1 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ x86-64

ket_lang-0.9.3.1-py3-none-macosx_14_0_universal2.whl (7.0 MB view details)

Uploaded Python 3macOS 14.0+ universal2 (ARM64, x86-64)

File details

Details for the file ket_lang-0.9.3.1.tar.gz.

File metadata

  • Download URL: ket_lang-0.9.3.1.tar.gz
  • Upload date:
  • Size: 144.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.20

File hashes

Hashes for ket_lang-0.9.3.1.tar.gz
Algorithm Hash digest
SHA256 1249149fc014021537ff5409ed13ec226ec5234acc9ec54310aeb762f6ce850c
MD5 ebf8c107e5f25daa790bdd17565b0215
BLAKE2b-256 6acec5967b5744322af307c668d6ca58217d9e9261cac1403d1f0ed855b01631

See more details on using hashes here.

File details

Details for the file ket_lang-0.9.3.1-py3-none-win_amd64.whl.

File metadata

  • Download URL: ket_lang-0.9.3.1-py3-none-win_amd64.whl
  • Upload date:
  • Size: 7.3 MB
  • Tags: Python 3, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.20

File hashes

Hashes for ket_lang-0.9.3.1-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 acf5c646c3fb1fd2429ffea0377b51ea781b6d9e7917d4b9d48f93ae43885c52
MD5 41c4cdf5cf7fb5c2e8d24810cd67c4e9
BLAKE2b-256 30f18335be84037709e02e5808da9e2633497f2e474ecd13e93bed0e87969016

See more details on using hashes here.

File details

Details for the file ket_lang-0.9.3.1-py3-none-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for ket_lang-0.9.3.1-py3-none-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 37609e75411fd31fc8af37efe4dd47c62391199dfa26aa614e9f8651308a42e9
MD5 5e3021ee0f3b76d17cca554427204153
BLAKE2b-256 efbaec9bf42dd691d56895913869481e4ea0ea51f51e008a75173fc32fb1743f

See more details on using hashes here.

File details

Details for the file ket_lang-0.9.3.1-py3-none-macosx_14_0_universal2.whl.

File metadata

File hashes

Hashes for ket_lang-0.9.3.1-py3-none-macosx_14_0_universal2.whl
Algorithm Hash digest
SHA256 b80cc8de3cd66bb41dadf06437872221198cb8544a8c5a0a6dcc60e50545a1bb
MD5 833c8ebe10d89d6b0f80b220d1bc4628
BLAKE2b-256 e0583d7c5505951dd1a15248515f2dd75790ceac4b68d901fd6859f4d3aa8588

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page