Noise modeling and Quantum Error Mitigation (QEM) techniques
Quantum computing holds the potential to revolutionize fields such as optimization, artificial intelligence, and the simulation of complex molecules and materials. Yet, today’s quantum machines are highly sensitive to environmental disturbances, which introduce noise and disrupt their intended operations. To unlock their practical value, it is crucial to combine these imperfect devices with precise noise characterization, advanced simulation methods, and error mitigation techniques—software-driven strategies designed to minimize the effects of such noise.
Papers:
A novel approach to noisy gates for simulating quantum computers, 2023, Phys. Rev. Research 5, 043210
Simulating photonic devices with noisy optical elements, 2024, Phys. Rev. Research 6, 033337
Mitigating Coherent Errors through a Decoherence-Resistant Variational Framework employing Stabilizer States, 2025, arXiv:2510.20445
Quantum Algorithms
Quantum computing offers powerful tools for tackling complex problems in optimization, AI, and molecular simulation. Variational Quantum Algorithms (VQAs) provide a flexible framework that combines quantum circuits with classical optimization to efficiently solve these challenges. Moreover, in recent years, attention has turned to simulating open quantum systems—those interacting with external environments. Such systems, especially in biological and chemical contexts, exhibit dynamics that can reveal unique functionalities and reaction mechanisms. Quantum computers are suited to capture the exponential complexity of these processes.
Papers:
Efficient quantum algorithm to simulate open systems through a single environmental qubit, 2024, Phys. Rev. Research 6, 043321
Equivariant Variational Quantum Eigensolver to detect phase transitions through energy level crossings, 2024, Quantum Sci. Technol. 10, 015048