English | 简体中文

TenCirChem is an efficient and versatile quantum computation package for molecular properties. TenCirChem is based on TensorCircuit and is optimized for chemistry applications.

Getting started with TenCirChem is a breeze. Simply install the package via pip:

pip install tencirchem

TenCirChem is written in pure Python, and its use is straightforward. Here's an example of calculating UCCSD:

from tencirchem import UCCSD, M d = 0.8 # distance unit is angstrom h4 = M(atom=[["H", 0, 0, d * i] for i in range(4)]) # setup uccsd = UCCSD(h4) # calculate uccsd.kernel() # analyze result uccsd.print_summary(include_circuit=True)

Running uccsd.kernel() in the above code determines the optimized circuit ansatz parameters and VQE energy.
TenCirChem also allows the user to supply custom parameters. Here's an example:

import numpy as np from tencirchem import UCCSD from tencirchem.molecule import h4 uccsd = UCCSD(h4) # evaluate various properties based on custom parameters params = np.zeros(uccsd.n_params) print(uccsd.statevector(params)) print(uccsd.energy(params)) print(uccsd.energy_and_grad(params))

For more examples and customization, please refer to the documentation

TenCirChem's features include:

• Statics module
  • UCC calculation with UCCSD, kUpCCGSD, pUCCD at an extremely fast speed
  • Noisy circuit simulation via TensorCircuit
  • Custom integrals, active space approximation, RDMs, GPU support, etc.
• Dynamics module
  • Transformation from renormalizer models to qubit representation
  • VQA algorithm based on JAX
  • Built-in models: spin-boson model, pyrazine S1/S2 internal conversion dynamics

TenCirChem is designed to be:

• Fast
  • UCC speed is 10000x faster than other packages
    • Example: H8 with 16 qubits in 2s (CPU). H10 with 20 qubits in 14s (GPU)
    • Achieved by analytical expansion of UCC factors and exploitation of symmetry
• Easy to hack
  • Avoid defining new classes and wrappers when possible
    • Example: Excitation operators are represented as tuple of int. An operator pool is simply a list of tuple
  • Minimal class inheritance hierarchy: at most two levels
  • Expose internal variables through class attributes

TenCirChem is released under Academic Public License. See the LICENSE file for details. In short, you can use TenCirChem freely for non-commercial/academic purpose and commercial use requires a commercial license.

If this project helps in your research, please cite our software whitepaper:

TenCirChem: An Efficient Quantum Computational Chemistry Package for the NISQ Era

which is also a good introduction to the software.