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Researcher profile

Andrea Locatelli

Andrea Locatelli contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
cond-mat.mes-hallcond-mat.mtrl-sciMachine Learning

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Published work

7 published item(s)

preprint2026arXiv

Active multiple matrix completion with adaptive confidence sets

In this work, we formulate a new multi-task active learning setting in which the learner's goal is to solve multiple matrix completion problems simultaneously. At each round, the learner can choose from which matrix it receives a sample from an entry drawn uniformly at random. Our main practical motivation is market segmentation, where the matrices represent different regions with different preferences of the customers. The challenge in this setting is that each of the matrices can be of a different size and also of a different rank which is unknown. We provide and analyze a new algorithm, MAlocate that is able to adapt to the unknown ranks of the different matrices. We then give a lower-bound showing that our strategy is minimax-optimal and demonstrate its performance with synthetic experiments.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Boron nitride-graphene in-plane hexagonal heterostructure in oxygen environment

Aiming to improve fabrication protocols for boron nitride and graphene (h-BNG) lateral heterostructures, we studied the growth of h-BNG thin films on platinum and their behavior in an oxygen environment. We employed a surface science approach based on advanced spectroscopy and imaging techniques to investigate the evolution of surface stoichiometry and chemical intermediates at each reaction step. During oxygen exposure at increasing temperatures, we observed progressive and subsequent intercalation of oxygen, and selective etching of graphene accompanied by the oxidation of boron. Additionally, by exploiting the O2 etching selectivity towards graphene at 250°C and repeating growth cycles, we obtained in-plane h-BNG layers with controllable compositions and vertically stacked h-BN/Gr heterostructures without the use of consecutive transfer procedures. The growth using a single precursor molecule can be beneficial for the development of versatile atomically thin layers for electronic devices.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Moiré superlattice effects and band structure evolution in near-30-degree twisted bilayer graphene

In stacks of two-dimensional crystals, mismatch of their lattice constants and misalignment of crystallographic axes lead to formation of moiré patterns. We show that moiré superlattice effects persist in twisted bilayer graphene (tBLG) with large twists and short moiré periods. Using angle-resolved photoemission, we observe dramatic changes in valence band topology across large regions of the Brillouin zone, including the vicinity of the saddle point at $M$ and across 3 eV from the Dirac points. In this energy range, we resolve several moiré minibands and detect signatures of secondary Dirac points in the reconstructed dispersions. For twists $θ>21.8^{\circ}$, the low-energy minigaps are not due to cone anti-crossing as is the case at smaller twist angles but rather due to moiré scattering of electrons in one graphene layer on the potential of the other which generates intervalley coupling. Our work demonstrates robustness of mechanisms which enable engineering of electronic dispersions of stacks of two-dimensional crystals by tuning the interface twist angles. It also shows that large-angle tBLG hosts electronic minigaps and van Hove singularities of different origin which, given recent progress in extreme doping of graphene, could be explored experimentally.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Ghost anti-crossings caused by interlayer umklapp hybridization of bands in 2D heterostructures

In two-dimensional heterostructures, crystalline atomic layers with differing lattice parameters can stack directly one on another. The resultant close proximity of atomic lattices with differing periodicity can lead to new phenomena. For umklapp processes, this opens the possibility for interlayer umklapp scattering, where interactions are mediated by the transfer of momenta to or from the lattice in the neighbouring layer. Using angle-resolved photoemission spectroscopy to study a graphene on InSe heterostructure, we present evidence that interlayer umklapp processes can cause hybridization between bands from neighbouring layers in regions of the Brillouin zone where bands from only one layer are expected, despite no evidence for moir/'e-induced replica bands. This phenomenon manifests itself as 'ghost' anti-crossings in the InSe electronic dispersion. Applied to a range of suitable 2DM pairs, this phenomenon of interlayer umklapp hybridization can be used to create strong mixing of their electronic states, giving a new tool for twist-controlled band structure engineering.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Anisotropic skyrmion bubbles in ultra-thin epitaxial Au$_{0.67}$Pt$_{0.33}$/Co/W films

We studied the symmetry of magnetic properties and the resulting magnetic textures in ultra-thin epitaxial Au$_{0.67}$Pt$_{0.33}$/Co/W, a model system exhibiting perpendicular magnetic anisotropy and interface Dzyaloshinskii-Moriya interaction (DMI). As a peculiar feature, the C$_\mathrm{2v}$ crystal symmetry induced by the Co/W interface results in an additional uniaxial in-plane magnetic anisotropy in the cobalt layer. Photoemission electron microscopy with magnetic sensitivity reveals the formation of self-organized magnetic stripe domains oriented parallel to the hard in-plane magnetization axis. We attribute this behavior to the lower domain wall energy when oriented along this axis, where both the DMI and the in-plane magnetic anisotropy favor a Néel domain wall configuration. The anisotropic domain wall energy also leads to the formation of elliptical skyrmion bubbles in a weak out-of-plane magnetic field.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

In-plane magnetic domains and Néel-like domain walls in thin flakes of the room temperature CrTe$_2$ van der Waals ferromagnet

The recent discovery of magnetic van der Waals materials has triggered a wealth of investigations in materials science, and now offers genuinely new prospects for both fundamental and applied research. Although the catalogue of van der Waals ferromagnets is rapidly expanding, most of them have a Curie temperature below 300 K, a notable disadvantage for potential applications. Combining element-selective x-ray magnetic imaging and magnetic force microscopy, we resolve at room temperature the magnetic domains and domains walls in micron-sized flakes of the CrTe$_2$ van der Waals ferromagnet. Flux-closure magnetic patterns suggesting in-plane six-fold symmetry are observed. Upon annealing the material above its Curie point (315 K), the magnetic domains disappear. By cooling back down the sample, a different magnetic domain distribution is obtained, indicating material stability and lack of magnetic memory upon thermal cycling. The domain walls presumably have Néel texture, are preferentially oriented along directions separated by 120 degrees, and have a width of several tens of nanometers. Besides microscopic mapping of magnetic domains and domain walls, the coercivity of the material is found to be of a few mT only, showing that the CrTe$_2$ compound is magnetically soft. The coercivity is found to increase as the volume of the material decreases.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Rotting bandits are not harder than stochastic ones

In stochastic multi-armed bandits, the reward distribution of each arm is assumed to be stationary. This assumption is often violated in practice (e.g., in recommendation systems), where the reward of an arm may change whenever is selected, i.e., rested bandit setting. In this paper, we consider the non-parametric rotting bandit setting, where rewards can only decrease. We introduce the filtering on expanding window average (FEWA) algorithm that constructs moving averages of increasing windows to identify arms that are more likely to return high rewards when pulled once more. We prove that for an unknown horizon $T$, and without any knowledge on the decreasing behavior of the $K$ arms, FEWA achieves problem-dependent regret bound of $\widetilde{\mathcal{O}}(\log{(KT)}),$ and a problem-independent one of $\widetilde{\mathcal{O}}(\sqrt{KT})$. Our result substantially improves over the algorithm of Levine et al. (2017), which suffers regret $\widetilde{\mathcal{O}}(K^{1/3}T^{2/3})$. FEWA also matches known bounds for the stochastic bandit setting, thus showing that the rotting bandits are not harder. Finally, we report simulations confirming the theoretical improvements of FEWA.

0 citations0 reviewsNo code linkedOpen access