Overview

This page summarizes the guides that are available in addition to the extensive API documentation of this package.

Note

These guides might refer to specific Python modules when explaining core concepts. Unless otherwise stated, the C API provides matching functionality, although it is not structured into modules. However, the function names correspond naturally and should be easy to navigate.

Operators and their structure

Fermionic operators can be represented in different forms and you can map between these forms as well as qubit operators using different mappers. Start here if you are building a Hamiltonian.

• Design principles of operator representations
• Group operator terms: use the operator structure
• Map operator representations

Fermionic circuits

You can express circuits directly on the fermionic level rather than mapping to qubits first.

• Work with fermionic circuits
• VQE optimization at the fermionic level

Circuit examples

These guides provide you with concrete examples for different specific use cases:

Chemistry

• Build an LUCJ ansatz
• Generate SqDRIFT circuits

Lattice models

• Generate Krylov time-evolution circuits (SKQD)

Transpiling fermionic circuits

Guides explaining how a FermionicCircuit becomes a QuantumCircuit.

• Transpile fermionic circuits
• Optimize Slater determinant preparation

Workflow examples

• Simulate 1D Fermi-Hubbard dynamics with flow sets
• Simulate 2D Fermi-Hubbard dynamics with flow sets

Workflow validation

• The ffsim simulation backend