Publications
A complete list with all my scientific contributions can be found here.
Published in AVS Quantum Science, 2025
In this article we investigate the Maximum Cut (MaxCut) problem on different graph classes with the quantum approximate optimization algorithm (QAOA) using symmetries. In particular, heuristics on the relationship between graph symmetries and the approximation ratio achieved by a QAOA simulation are considered Read more
Recommended citation: L. Lavagna, S. Piperno, A. Ceschini and M. Panella, "On the Effects of Small Graph Perturbations in the MaxCut Problem by QAOA ," 2025 AVS Quantum Science 7(4), doi: 10.1116/5.0253160. https://www.researchgate.net/publication/396483291_Small_graph_perturbations_QAOA_and_the_MaxCut_problem
Published in Physica Scripta, 2025
This review presents time-independent perturbative methods for solving the one-dimensional Schrödinger equation, highlighting representative cases that reveal key aspects of the theory. The focus is on their relevance to quantum computing applications, particularly in systems with finite-dimensional state spaces. Blog post here and code here. There is also an app in the Applets page. Read more
Recommended citation: L. Lavagna, S. Carillo and M. Panella, "A topical review on time-independent perturbation theory in one-dimensional quantum systems," 2025 Phys. Scr. 100 102001. https://iopscience.iop.org/article/10.1088/1402-4896/ae0a8f
Published in 2025 IEEE International Symposium on Circuits and Systems (ISCAS), 2025
This work explores the impact of NISQ devices on encryption-decryption schemes and has its companion blog post here and code in this repository. Read more
Recommended citation: L. Lavagna, F. De Falco, A. Ceschini, A. Rosato and M. Panella, "Trade-offs in Cryptosystems by Boolean and Quantum Circuits," 2025 IEEE International Symposium on Circuits and Systems (ISCAS), London, UK, pp. 1-5. https://ieeexplore.ieee.org/document/11043205
Published in 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP), 2024
This paper is about an hybrid quantum-classical Gated Recurrent Unit used to infer information about multidimensional time series and has its companion blog post here. Read more
Recommended citation: Francesca De Falco, Leonardo Lavagna, Andrea Ceschini, Antonello Rosato, Massimo Panella: Evolving Hybrid Quantum-Classical GRU Architectures for Multivariate Time Series, in the 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP). https://inspirehep.net/literature/2849278
Published in 2024 International Joint Conference on Neural Networks (IJCNN), 2024
This work was the natural development of my master thesis on quantum optimization and has its companion blog post here. Read more
Recommended citation: L. Lavagna, A. Ceschini, A. Rosato and M. Panella, "A Layerwise-Multi-Angle Approach to Fine-Tuning the Quantum Approximate Optimization Algorithm," 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 2024, pp. 1-8. https://ieeexplore.ieee.org/document/10650075
Published in Arxiv preprint 2408.15413, 2024
This paper is about symmetries and QAOA and has its companion blog post here and companion code available here. Read more
Recommended citation: Leonardo Lavagna, Simone Piperno, Andrea Ceschini, Massimo Panella: On the Effects of Small Graph Perturbations in the MaxCut Problem by QAOA. Arxiv preprint 2408.15413 (2024). https://www.arxiv.org/abs/2408.15413
