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Giovanny Espitia

Publications and source records attributed to Giovanny Espitia.

3 recordsLinked to original sources

Quasi-one-dimensional taco-shaped bands in large-angle twisted bilayer transition metal dichalcogenides

Two-dimensional moir\'e materials offer a powerful, twist-tunable platform for engineering electronic bands and correlations, though most studies to date have focused on small twist angles where flat bands arise from symmetry-pinned monolayer momenta. Here, we observe the surprising emergence of flat electronic bands with a distinctive quasi-one-dimensional dispersion at large twist angles in bilayer transition metal dichalcogenides that originate from the $\Lambda$ valley states at generic momenta between $\Gamma$ and $K$ points. These taco-shaped anisotropic bands result from optimal interlayer hybridization between like-spin $\Lambda$ valleys at the conduction band minimum in the Brillouin zone, resulting in directional band flattening at a magic twist-angle of 21.8$^{\circ}$. The bands form six anisotropic channels with a sixfold alternating spin texture reminiscent of altermagnetic textures. At low energies, the density of states shows a power-law dependence due to the quasi-one-dimensional character, enhancing the potential for correlated phases. Our results provide a new platform for correlated phenomena and broaden the scope of moir\'e engineering to large twist angles in 2D materials.

cond-mat.mes-hall

Protein Structure Prediction in the 3D HP Model Using Deep Reinforcement Learning

We address protein structure prediction in the 3D Hydrophobic-Polar lattice model through two novel deep learning architectures. For proteins under 36 residues, our hybrid reservoir-based model combines fixed random projections with trainable deep layers, achieving optimal conformations with 25% fewer training episodes. For longer sequences, we employ a long short-term memory network with multi-headed attention, matching best-known energy values. Both architectures leverage a stabilized Deep Q-Learning framework with experience replay and target networks, demonstrating consistent achievement of optimal conformations while significantly improving training efficiency compared to existing methods.

cs.LG

On the Role of Quantum Computing in Science and Cybersecurity

In this paper, we examine the state art of quantum computing and analyze its potential effects in scientific computing and cybersecurity. Additionally, a non-technical description of the mechanics of the listed form of computing is provided to educate the reader for better understanding of the arguments provided. The purpose of this study is not only to increase awareness in this nescient technology, but also serve as a general reference guide for any individual wishing to study other applications of quantum computing in areas that include finance, chemistry, and data science. Lastly, an educated argument is provided in the discussion section that addresses the implications this form of computing will have in the main areas examined.

physics.pop-ph