Imagine a light switch that doesn't just go on or off, but has a dimmer with multiple levels. Most quantum computers only use two states, but this project uses many more levels to pack more information into the same space. It's like upgrading from a simple yes/no system to a rich vocabulary, making it much faster to solve giant puzzles.
Current quantum computers are limited by binary qubits, leading to high encoding overheads and scalability issues. This makes it difficult to solve real-world industrial problems, such as EV charging optimization, efficiently.
A full-stack qudit processing system including hardware firmware, design automation software, and specific algorithms for gauge theories and industrial optimization.
If you are a charging network operator dealing with the growing number of electric vehicles and grid congestion — this project developed qudit-based optimization algorithms that manage multi-level variables to improve charging efficiency.
If you are a software vendor dealing with the extreme complexity of quantum hardware control — this project developed user-friendly software and design automation tools that allow non-specialists to operate qudit hardware.
If you are a research lab dealing with the lack of efficient classical algorithms to compute particle behavior — this project developed quantum simulators for gauge theories to model electrons, positrons, and quarks.
Based on available project data, no specific pricing or commercial cost models are provided; the project is funded by an EU contribution of EUR 3,207,671.
The project specifically aims to overcome scalability difficulties by using qudits to compact information and developing design automation tools similar to those used in classical computing.
Based on available project data, specific licensing terms are not listed, though the project includes a detailed exploitation strategy for its results.
It targets the full stack, including firmware for trapped-ion hardware and high-level control software to make the hardware more accessible to end-users.
The project period runs from 2022-11-01 to 2026-02-28, suggesting that final results and certification tools will be available by early 2026.
The consortium is heavily weighted toward research and academia, with 3 universities and 4 research institutes. Only 1 industry partner is involved, representing a 12% industry ratio, which indicates the project is primarily focused on technical breakthroughs rather than immediate commercial productization.
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