Optimal Quantum Likelihood Estimation – New EC2 Scientific Publication

Advancing hybrid quantum-classical algorithms through smarter learning strategies

European City² supports cutting-edge scientific research in quantum computing and computational modelling. A new open access paper, Optimal quantum likelihood estimation, presents an important step forward in improving hybrid quantum-classical algorithms.

The publication focuses on quantum likelihood estimation, a method used to learn how quantum systems behave. This research was partially supported by the European Union’s Horizon Europe programme under Grant Agreement No. 101178170, which funds the European City² project.

What is optimal quantum likelihood estimation?

The paper introduces an improved version of Quantum Likelihood Estimation (QLE), a hybrid quantum-classical algorithm used for Hamiltonian learning. In simple terms, this means identifying the hidden rules that determine how a quantum system evolves over time.

This type of learning is essential for applications such as quantum simulation, device calibration and quantum control. However, standard approaches can be inefficient, especially in today’s early-stage quantum technologies where computational resources remain limited.

The authors address this challenge by optimising how the algorithm selects key parameters at each step. Instead of using fixed settings, the method dynamically chooses the most informative configuration, including the initial quantum state, measurement basis and evolution time.

Smarter learning through information theory

These choices are guided by mutual information, allowing the algorithm to prioritise measurements that provide the most valuable insights. As a result, the optimised version significantly reduces the number of iterations required to reach reliable conclusions.

This makes quantum learning processes faster, more efficient and better suited for real-world applications, where every measurement and computational step matters.

Why this research matters for European City²

While the publication focuses on quantum physics, it strongly aligns with the broader scientific foundation of European City². The project explores how quantum and classical computational approaches can be used to model complex systems, including social dynamics and democratic decision-making.

Although this specific research does not directly address voting systems, it contributes to the quantum knowledge base that EC2 builds upon. Improving quantum learning algorithms strengthens the tools that can later support more advanced modelling and simulation frameworks.

In this sense, the paper represents an important example of how EC2 supports both applied and fundamental research, laying the groundwork for future innovation at the intersection of quantum science and computational social systems.

Supporting high-quality scientific publications

Scientific publications are a key part of the European City² dissemination strategy. The project aims to produce and promote high-quality, open-access research that is visible to both the scientific community and wider audiences.

The publication Optimal quantum likelihood estimation clearly reflects this goal, combining theoretical insight with practical optimisation methods and demonstrating how information theory can improve real quantum algorithms.