We are delighted to offer a tutorial on Qamomile at IEEE Quantum Week 2026! The tutorial will be held across two time slots, as follows:
| Tutorial | Time |
|---|---|
| 1. Introduction to Qamomile: Estimating Symbolically and Executing Concretely | 10:00 AM – 11:30 AM |
| 2. Introduction to Qamomile: Estimating Symbolically and Executing Concretely | 1:00 PM – 2:30 PM |
What Is Qamomile¶
Qamomile is a typed quantum programming language for describing quantum programs in Python, symbolically estimating their resource requirements, and transpiling and executing them. Qamomile currently supports transpiling programs to Qiskit, CUDA-Q, QURI Parts, HUGR, and Quration and executing the transpiled programs. Programs transpiled to Qiskit can additionally be executed through Qamomile on the qBraid platform. Qamomile also provides built-in algorithms and common patterns, so users do not need to reimplement them. It also provides quantum optimization functionality. This functionality supports the OMMX data format. Because the same OMMX data can also be used with classical solvers, users can easily compare quantum optimization algorithms with classical solvers.
Qamomile GitHub: https://
github .com /Jij -Inc /Qamomile Qamomile Docs: https://
jij -inc -qamomile .readthedocs -hosted .com /latest /en/ Qamomile Tutorial GitHub for IEEE Quantum Week 2026: https://
github .com /Jij -Inc /Qamomile -QCE2026 -Tutorial
About This Tutorial¶
In this tutorial, attendees will learn the basics of Qamomile, including how to write quantum programs, estimate their resource requirements symbolically, and transpile and execute them. The tutorial will also introduce Qamomile’s quantum optimization functionality.
No prior experience with Qamomile is required.
Agenda¶
The tutorial will cover the following topics:
understanding the motivation behind Qamomile and its core concepts,
writing quantum programs in Qamomile,
using built-in algorithms,
using a single quantum program for both symbolic resource estimation and execution, and
applying Qamomile to quantum optimization workflows.
Materials¶
The tutorial materials will be made available on this site.