Curriculum Vitae CV | Google Scholar | arXiv | Orcid .
Publications
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J. Liu, F. Wilde, A. A. Mele, L. Jiang, J. Eisert. Noise can be helpful for variational quantum algorithms. ArXiv preprint, arXiv:2210.06723, 2022.
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A.A. Mele, G.B. Mbeng, G.E. Santoro, M. Collura, P. Torta. Avoiding barren plateaus via transferability of smooth solutions in Hamiltonian Variational Ansatz, 2022. PRA Letter.
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J.J. Meyer, M. Mularski, E. Gil-Fuster, A.A. Mele, F. Arzani, A. Wilms, J. Eisert. Exploiting symmetry in variational quantum machine learning. ArXiv preprint, arXiv:2206.01982, 2022.
Talks
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QTML conference, Avoiding barren plateaus via transferability of smooth solutions in Hamiltonian Variational Ansatz, 2022, Extended talk. Slides
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DPG conference, Avoiding barren plateaus via transferability of smooth solutions in Hamiltonian Variational Ansatz, 2022. Slides
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DPG conference, Exploiting symmetry in variational quantum machine learning, 2022. Slides
Schools and Workshops
- QMATH Masterclass on Entropy Inequalities in Quantum Information Science, University of Copenhagen, 2022.
Other projects
These are some of the projects I worked on during my master program:
- Variational Monte Carlo for a 2D semiconductor Quantum Dot. (PDF, code on GitHub)
- Alkali metal clusters by DFT. (PDF, code on GitHub)
- Mean-field methods for ultracold atoms trapped in an harmonic potential. (PDF, code on GitHub)
- Hydrogen Atom with a Gaussian Basis. (PDF, code on GitHub)
- Scattering of H atoms on a Kr atom. (PDF, code on GitHub)
- Some QFT exercises. (PDF)
- 2-sites Hubbard model. (PDF)
- Dielectric constants of wurtzite ZnS. (PDF, code on GitHub)