Tutorials

Here is a list of notebooks that introduce the basics of the package. They are also available in the examples directory as plain .py files using the py:percent format.

• 1. Building circuits
• 2. Chemistry to qubit Hamiltonians
• 3. Textbook QPE
• 4. Trotter-Suzuki decomposition of \(U(t)\)
• 5. QPE with Trotterization
• 6. QPE with Linear Combination of Unitaries
• 7. Robust Phase Estimation
• 8. quimb - qiskit MPS benchmark
• 9. Hyperoptimization
• 10. Variational Circuit Preparation

Details

• building_circuits explains how to create, plot, record and load quantum circuits in quimb and qiskit.

• chemistry_to_qubit describes how to build the qubit Hamiltonian and perform the Density Matrix Renormalization Group (DMRG) algorithm for a given molecule.

• textbook_qpe introduces the textbook Quantum Phase Estimation algorithm assuming time evolution is implemented exactly.

• trotter_decomposition introduces the Trotter-Suzuki decomposition to implement a time evolution operator \(U\).

• qpe_with_trotter studies the Quantum Phase Estimation algorithm using Trotterization of the evolution operator, and provides resource estimates.

• qpe_with_lcu gives an introduction to Block Encoding via Linear Combination of Unitaries.

• robust_phase_estimation introduces the Robust Phase Estimation algorithm, based on the Hadamard test circuit.

• performance_mps compares the performance of quimb and qiskit when contracting and sampling circuits with Matrix Product States.

• hyperoptimization presents advanced contraction schemes provided by quimb.

• variational_circuit_preparation finds an initial guess state with variational circuit optimization.