Article by Two Academic Reserve Students from the Faculty of Engineering Published by Prestigious Journal

Alon Levi (23) and Ziv Ossi (22) had already completed their studies as academic reserve students in the computer engineering track of the Faculty of Engineering and enlisted in the IDF when they received the good news: an article they co-wrote about their final project was accepted for publication in the prestigious Quantum Science and Technology, one of the leading journals in the field of quantum science and technology. The article is co-authored with doctoral student Amit Te’eni, who supervised the two during the project, and academic supervisor Prof. Eli Cohen. As part of the project, the pair harnessed tools from information theory for the "Hamiltonian learning" process. "The dynamics of closed quantum systems are determined by a physical quantity called the Hamiltonian, which describes how the system changes over time," explains Te’eni. "The problem is that we often have a quantum system whose Hamiltonian is unknown to us, and we must discover it through a series of experiments and measurements. This process is called Hamiltonian learning, and it is important for applications such as simulation and control of quantum systems."

One of the promising tools for performing Hamiltonian learning is an algorithm called Quantum Likelihood Estimation, a hybrid method that combines quantum computing power with classical data analysis: the quantum computer performs an experiment, and the regular computer processes the results to update the guess about the Hamiltonian's identity. Then another quantum experiment is performed, and so on repeatedly, until the Hamiltonian can be guessed with high certainty. "As part of the project, Alon and Ziv harnessed tools from information theory to make this process much more efficient," says Te’eni. "Instead of performing predetermined experiments - they developed a smart strategy that plans the next experiment to yield the maximum possible amount of information. Using an optimization algorithm, the system selects precisely the initial state, evolution time, and ideal measurement for each stage."

The project’s results were dramatic: an improvement of more than tenfold to the learning process, bringing us a step closer to being able to diagnose and operate larger, more complex quantum systems with unprecedented precision. The impressive results were presented in the article Optimal quantum likelihood estimation, which was recently published in the prestigious journal. "This is a very exceptional achievement: two academic reserve students managed to publish an article very close to the completion of the project, shortly after enlisting in the IDF," says Te’eni.

The Key to Efficiency: Maximizing Information Flow

The informationtheoretic tools that Ziv and Alon used in the project rely on a theoretical framework developed in a previous article, Oracle problems as communication tasks and optimization of quantum algorithms. The article was authored by Te’eni and Prof. Cohen, together with Dr. Zohar Schwartzman-Nowik (doctoral graduate under joint supervision of Prof. Dorit Aharonov from the Hebrew University and Prof. Cohen), Prof. Marcin Nowakowski, and Prof. Paweł Horodecki from the Gdańsk University of Technology in Poland. The researchers proposed viewing quantum computations as a "communication task" – a conversation of sorts between the computer and the system being studied. The article shows how, using tools from information theory, it is possible to quantify and accurately calculate how much information passes in each "word" in this conversation. This insight proved that the key to efficiency is maximizing information flow in each individual step, a principle that became the foundation for the new optimization method.

The published article affirms the theoretical framework developed in the previous work and proves that it is not just a tool for retrospective analysis, but one that enables developing new quantum algorithms and improving existing ones. The potential is great since there is a fundamental need to find new quantum algorithms, and indeed Prof. Cohen's group aims to continue this research direction through funded projects in computing and encryption.