On September 14, 2026, researchers Wei-Hao Huang, Keisuke Sato, Hiromichi Matsuyama, Kuan-Cheng Chen, and Rosse Grassie will introduce Qamomile, a new tool designed to bridge the gap between estimating quantum resource needs and executing actual programs. JIJ developed Qamomile to support a single quantum program description for both stages, utilizing a typed programming model and integration with the OMMX optimization format.
The team reports this unified workflow is increasingly crucial as quantum algorithms become more complex, offering a path from algorithm design to executable implementations. JIJ is also the main organizer of QuBench 2026, a workshop focused on quantum benchmarking and resource estimation, held in conjunction with IEEE Quantum Week in Toronto.
Qamomile Tutorial: Symbolic Estimation and Concrete Execution Workflow
Recognizing the increasing complexity of quantum algorithms, JIJ developed Qamomile to address the need for practical methods to scale resource requirements alongside problem size while maintaining a clear path to executable code. The “Introduction to Qamomile: Estimating Symbolically and Executing Concretely” tutorial will instruct participants on writing quantum programs using the tool, estimating resource needs as functions of problem size, and transpiling programs for execution on supported software backends.
Attendees will also explore quantum optimization workflows leveraging OMMX. According to the tutorial description available online, participants will learn how to write quantum programs in Qamomile through a hands-on approach. JIJ intends to continue bridging research advances with practical tools for testing and application.
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