QuanTorch

QuanTorch is an educational library based on Pytorch to build quantum systems, the library is designed to be simple, self-contained and easy to use.

Current Features:

• Dirac Notation
  • Basis Vectors & States
  • Basic Operations
  • Checkers
  • Density Matrix
  • Finding Probabilities
• Quantum Gates
  • Single Qubit Gates
  • Multi Qubit Gates
  • Visualization (#TODO)
• Quantum Circuits (#TODO)

Dirac Notation:

Gates

Getting Started

For now, the library is not available on PyPI, so you have to clone the repo and install it locally.

git clone https://github.com/0ssamaak0/QuanTorch.git

Check QuanTorch_final notebook for detailed examples and use cases.

Dirac Notation

from QuanTorch.states import qstate, density_matrix
import QuanTorch.basis as qbasis
import QuanTorch.operations as qoperations
import QuanTorch.checkers as qcheckers

# define some basis vectors
zero = qbasis.zero
one = qbasis.one

# perform operations on them
inner = qoperations.inner_product(zero, one)
tensor = qoperations.tensor_product(zero, one)

# Check if they are valid basis vectors
print(qcheckers.check_basis([zero, one]))  # Should be True

# define set of states
psi1 = qstate([0.5, 0])
psi2 = qstate([0.5j, 0])

# check if this state is normalized
print(qcheckers.check_normalized(psi1))  # Should be False

# check if they can be used as basis vectors
print(qcheckers.check_basis([psi1, psi2]))  # Should be False

Quantum Gates

from QuanTorch.states import qstate, density_matrix
import QuanTorch.basis as qbasis
import QuanTorch.gates as qgates

# define some basis vectors
zero = qbasis.zero
one = qbasis.one

# Apply gates on the basis vectors
print(qgates.X(zero))  # should be | 1 >
print(qgates.H(one))  # should be | - >
print(qgates.CNOT(zero, one))  # should be | 0 1 >
print(qgates.BellStateGate(zero, one))  # should be | Ψ + >

Note

QuanTorch is an educational library, it is not meant to be in building real quantum systems that run on either simulators or quantum computers, it is just a very simple library to help you understand the concepts of quantum computing.