Ket Quantum Programming¶
Ket is a quantum programming platform that enables the development and execution of quantum-accelerated software. The platform consists of three main components:
Ket: Brings the simplicity of Python programming to quantum computing by providing only the necessary types, functions, and constructs for efficient quantum development. (Ket repository)
Libket: The runtime library for the platform, used by Ket in the background, but also accessible directly through C or Rust APIs. (Libket repository)
Ket Bitwise Simulator (KBW): A noise-free quantum computer simulator that allows testing of quantum applications on classical computers. KBW supports two simulation methods: Dense simulation (state vector simulation) and Sparse simulation based on the Bitwise representation. (KBW repository)
Getting Started with Ket¶
Installation¶
Ket requires Python 3.8 or newer and is supported on 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 proceeding with the Ket installation.
Ket is available on the Python Package Index (PyPI) and can be installed using pip. To install Ket, simply copy and paste the following command into your terminal:
python3 -m pip install ket-lang
Usage¶
You can execute a quantum application using Python interpreter. For example:
# bell.py
from ket import *
p = Process()
a, b = p.alloc(2)
CNOT(H(a), b)
print(dump(a+b).show())
To run the code above, use the command python3 bell.py.
$ python3 bell.py
|00⟩ (50.00%)
0.707107 ≅ 1/√2
|11⟩ (50.00%)
0.707107 ≅ 1/√2
Example: Quantum Teleportation¶
With the quantum teleportation protocol, quantum information can be transfered from one qubit to another using a pair of entangled qubits and quantum measurements.
# teleport.py
import ket
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__":
p = ket.Process(execution="live")
alice_message = p.alloc() # alice_message = |0⟩
ket.H(alice_message) # alice_message = |+⟩
ket.Z(alice_message) # 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)
ket.H(bob_qubit) # bob_qubit = |1⟩
bob_m = ket.measure(bob_qubit)
print("Expected measure 1, result =", bob_m.value)
$ python teleport.py
Expected measure 1, result = 1
Used by¶
Otto M. Pires, Rafael de Santiago and Jerusa Marchi, “Two Stage Quantum Optimization for the School Timetabling Problem”, 2021 IEEE Congress on Evolutionary Computation (CEC), 2021, pp. 2347-2353, doi: 10.1109/CEC45853.2021.9504701.
Portable GPU-Accelerated Quantum Computer Simulator QuBOX at Universidade Federal de Santa Catarina (Brazil).
Cite Ket¶
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. https://doi.org/10.1145/3474224
@article{ket2021,
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}
}
Download the original article that proposes the Ket language: pdf
Ket API Documentation¶
Ket Quantum Programming Platform. |
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