trotter

Decompose Hamiltonians into Pauli terms and generate Trotter-Suzuki circuits.

30|2|Updated Apr 16, 2026
One-click install
npx skills add https://github.com/unitarylab/quantum-skills --skill trotter
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: trotter
Source: https://github.com/unitarylab/quantum-skills/tree/main/algorithms/hamiltonian-simulation/trotter
Command: npx skills add https://github.com/unitarylab/quantum-skills --skill trotter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Trotter-Suzuki Hamiltonian simulation converts the challenge of simulating quantum time evolution e^{-iHt} into structured, controllable short-time exponentials by decomposing the Hamiltonian into Pauli terms.

Core Features & Use Cases

  • Supports first and higher even Suzuki orders, enabling a trade-off between accuracy and circuit depth.
  • Decomposes Hamiltonians into grouped Pauli terms and builds reusable SuzukiTrotterAlgorithm workflows for benchmarking, teaching, and research.
  • Serves as a reliable baseline for digital quantum simulation in spin models, lattice systems, and chemistry-inspired Hamiltonians; suitable for benchmarking against QDrift, Taylor-LCU, and QSP.

Quick Start

Experiment with a 2-qubit Hamiltonian to compare order-1, order-2, and order-4 Suzuki decompositions using the SuzukiTrotterAlgorithm.

Frequently Asked Questions about trotter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I simulate quantum time evolution e^{-iHt} using a Trotter-Suzuki product formula?

First-order and higher even-order Suzuki formulas enable a trade-off between simulation accuracy and circuit depth. Higher even Suzuki orders reduce Trotter error but increase the number of circuit steps required for the Hamiltonian simulation.

Can I use this for large-scale quantum dynamics or chemistry Hamiltonians?

This Trotter-Suzuki simulation is designed for small-to-medium-scale quantum dynamics tasks, including spin models, lattice Hamiltonians, and chemistry-style Hamiltonians. It is not intended for large-scale quantum simulations beyond these benchmarking and teaching contexts.

What is the best way to benchmark digital quantum simulation against QDrift or Taylor-LCU?

Using Trotter-Suzuki product formulas provides a reliable baseline for benchmarking digital quantum simulation against QDrift, Taylor-LCU, and QSP. You can compare different Suzuki orders and step counts to evaluate accuracy and circuit depth trade-offs.

How do I convert a spin model or lattice Hamiltonian into Pauli terms for circuit simulation?

Converting spin models or lattice Hamiltonians into Pauli terms is required before Trotter-Suzuki simulation. The Skill accepts Hamiltonians already decomposed into Pauli terms and builds reusable SuzukiTrotterAlgorithm workflows for circuit simulation and benchmarking.