Paddle Quantum 2.1.2

Release Note

New Modules

Quantum chemistry module

Add the quantum chemistry module paddle_quantum.qchem. This module, depending on Psi4 and OpenFermion, can construct Hamiltonian applicable to quantum computers from chemical molecular structure and supports most platforms. To use the qchem module, please refer to the README file.

Time evolution simulation module

Add the module paddle_quantum.trotter for constructing circuits that simulate the time evolution of quantum systems. Arbitrarily high order Trotter-Suzuki circuits are provided as a built-in function construct_trotter_circuit(). Additionally, users can design custom time evolution circuits with user-specified permutation and coefficients. For more detailed usage, please refer to our tutorials on Hamiltonian simulation.

Measurement-based quantum computation module

Add the measurement-based quantum computation (MBQC) module paddle_quantum.mbqc. It supports the simulation of universal quantum computing with the MBQC model. Unlike the conventional quantum circuit model, MBQC has its unique way of computing and thus common circuit simulation tools cannot be directly used for the simulation of this model.

Along with this new module, we also provide some examples and tutorials. The provided examples are QAOA (Quantum Approximate Optimization Algorithm), VQSVD (Variational Quantum Singular Value Decomposition), and QKernel.

New Tutorials

Quantum chemistry

• Add the tutorial Building Molecular Hamiltonian under the quantum_simulation folder, which explains how to obtain a Hamiltonian from a molecular structure.

Classical shadow

• Add the tutorial The Classical Shadow of Unknown Quantum States under the quantum_simulation folder, which introduces the concept of classical shadow and its application.
• Add the tutorial Estimation of Quantum State Properties Based on the Classical Shadow under the quantum_simulation folder, which shows how to estimate the expectation value of an observable using classical shadow.

Hamiltonian simulation

• Add the tutorial Hamiltonian Simulation with Product Formula under the quantum_simulation folder, which shows how to perform digital quantum simulations based on Suzuki product formula.
• Add the tutorial Simulate the Spin Dynamics on a Heisenberg Chain under the quantum_simulation folder, which demonstrates how to simulate the time evolution of a one-dimensional Heisenberg chain using both the built-in Trotter-Suzuki circuit and the custom time evolution circuits in Paddle Quantum.

QNN expressibility

• Add the tutorial Expressibility of Quantum Neural Network under the qun_research folder, which introduces a method for quantitatively analyzing the expressibility of quantum neural networks and evaluates the expressibility of quantum neural network templates provided by Paddle Quantum at different depths.

Quantum compiling

• Add the tutorial Variational Quantum Circuit Compiling under the qnn_research folder, which shows a process of simulating an unknown unitary operator by optimizing a parameterized quantum circuit.

Measurement-based quantum computation

• Add the tutorial MBQC Quick Start Guide under the mbqc folder, which explains the basic concepts of MBQC.
• Add the tutorial Measurement-based Quantum Approximate Optimization Algorithm under the mbqc folder, which shows how to implement the QAOA algorithm in the MBQC mode.
• Add the tutorial Polynomial Unconstrained Boolean Optimization Problem in MBQC under the mbqc folder, which shows how to solve the max-cut problem and a specific PUBO problem using the QAOA algorithm in the MBQC mode.

In addition to these new tutorials, we update the Quick Start manual to include how to draw and display a Bloch sphere using functions plot_state_in_bloch_sphere() and plot_rotation_in_bloch_sphere() from the module paddle_quantum.utils. The tutorial Variational Quantum Eigensolver is also updated to making use of the new paddle_quantum.qchem module.