Growth Rate in the Dynamical Dark Energy Models

Dark Energy models with slowly-rolling cosmological scalar field provide a popular alternative to the standard, time-independent cosmological constant model. We study simultaneous evolution of background expansion and growth in the scalar field model with the Ratra-Peebles self-interaction potential. We use recent measurements of the linear growth rate and the baryon acoustic oscillation peak positions to constrain the model parameter $\alpha$ that describes the steepness of the scalar field potential.Comment: 7 pages, 6 figures, discussions and references added; conclusions unchange

Topological features of hydrogenated graphene

Hydrogen adatoms are one of the most the promising proposals for the functionalization of graphene. Hydrogen induces narrow resonances near the Dirac energy, which lead to the formation of magnetic moments. Furthermore, they also create local lattice distortions which enhance the spin-orbit coupling. The combination of magnetism and spin-orbit coupling allows for a rich variety of phases, some of which have non trivial topological features. We analyze the interplay between magnetism and spin-orbit coupling in ordered arrays of hydrogen on graphene monolayers, and classify the different phases that may arise. We extend our model to consider arrays of adsorbates in graphene-like crystals with stronger intrinsic spin-orbit couplings.Comment: 6 pages, 4 figure

Quantum spin Hall phase in multilayer graphene

The so called quantum spin Hall phase is a topologically non trivial insulating phase that is predicted to appear in graphene and graphene-like systems. In this work we address the question of whether this topological property persists in multilayered systems. We consider two situations: purely multilayer graphene and heterostructures where graphene is encapsulated by trivial insulators with a strong spin-orbit coupling. We use a four orbital tight-binding model that includes the full atomic spin-orbit coupling and we calculate the $Z_{2}$ topological invariant of the bulk states as well as the edge states of semi-infinite crystals with armchair termination. For homogeneous multilayers we find that even when the spin-orbit interaction opens a gap for all the possible stackings, only those with odd number of layers host gapless edge states while those with even number of layers are trivial insulators. For the heterostructures where graphene is encapsulated by trivial insulators, it turns out that the interlayer coupling is able to induce a topological gap whose size is controlled by the spin-orbit coupling of the encapsulating materials, indicating that the quantum spin Hall phase can be induced by proximity to trivial insulators.Comment: 7 pages, 6 figure

Controlled complete suppression of single-atom inelastic spin and orbital cotunnelling

The inelastic portion of the tunnel current through an individual magnetic atom grants unique access to read out and change the atom's spin state, but it also provides a path for spontaneous relaxation and decoherence. Controlled closure of the inelastic channel would allow for the latter to be switched off at will, paving the way to coherent spin manipulation in single atoms. Here we demonstrate complete closure of the inelastic channels for both spin and orbital transitions due to a controlled geometric modification of the atom's environment, using scanning tunnelling microscopy (STM). The observed suppression of the excitation signal, which occurs for Co atoms assembled into chain on a Cu$_2$N substrate, indicates a structural transition affecting the d$_z$$^2$ orbital, effectively cutting off the STM tip from the spin-flip cotunnelling path.Comment: 4 figures plus 4 supplementary figure

Cosmological Constraints from Hubble Parameter versus Redshift Data

We use the Simon, Verde, & Jimenez (2005) determination of the redshift dependence of the Hubble parameter to constrain cosmological parameters in three dark energy cosmological models. We consider the standard $\Lambda$CDM model, the XCDM parameterization of the dark energy equation of state, and a slowly rolling dark energy scalar field with an inverse power-law potential. The constraints are restrictive, consistent with those derived from Type Ia supernova redshift-magnitude data, and complement those from galaxy cluster gas mass fraction versus redshift data.Comment: Minor changes, including an estimate for H_0. ApJL, in pres

Chemical weathering of the volcanic soils of Isla Santa Cruz (Galápagos Islands, Ecuador)

We present a study on weathering of volcanic soils using 43 profiles (131 horizons) sampled in Santa Cruz Island (Galapagos Islands). Several weathering indices, based on chemical composition, are used. Since the geological material is highly homogeneous the intensity of weathering is mostly related to climatic conditions controlled by topography. There is a gradient of increasing weathering from the arid conditions predominant in the coast to elevations of 400-500 m a.s.l. where much more humid conditions prevail

Electrically controllable magnetism in twisted bilayer graphene

Twisted graphene bilayers develop highly localised states around AA-stacked regions for small twist angles. We show that interaction effects may induce either an antiferromagnetic (AF) and a ferromagnetic (F) polarization of said regions, depending on the electrical bias between layers. Remarkably, F-polarised AA regions under bias develop spiral magnetic ordering, with a relative $120^\circ$ misalignment between neighbouring regions due to a frustrated antiferromagnetic exchange. This remarkable spiral magnetism emerges naturally without the need of spin-orbit coupling, and competes with the more conventional lattice-antiferromagnetic instability, which interestingly develops at smaller bias under weaker interactions than in monolayer graphene, due to Fermi velocity suppression. This rich and electrically controllable magnetism could turn twisted bilayer graphene into an ideal system to study frustrated magnetism in two dimensions, with interesting potential also for a range of applications.Comment: 7 pages, 3 figures. Minor correction

Real space mapping of topological invariants using artificial neural networks

Topological invariants allow to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wavefunctions under twisted boundary conditions. However, those procedures do not allow to calculate a topological invariant by evaluating the system locally, and thus require information about the wavefunctions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a 1-D topological superconductor and a 2-D quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the Kernel Polynomial Method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.Comment: 9 pages, 6 figure

STB-VMM: Swin Transformer Based Video Motion Magnification

The goal of video motion magnification techniques is to magnify small motions in a video to reveal previously invisible or unseen movement. Its uses extend from bio-medical applications and deepfake detection to structural modal analysis and predictive maintenance. However, discerning small motion from noise is a complex task, especially when attempting to magnify very subtle, often sub-pixel movement. As a result, motion magnification techniques generally suffer from noisy and blurry outputs. This work presents a new state-of-the-art model based on the Swin Transformer, which offers better tolerance to noisy inputs as well as higher-quality outputs that exhibit less noise, blurriness, and artifacts than prior-art. Improvements in output image quality will enable more precise measurements for any application reliant on magnified video sequences, and may enable further development of video motion magnification techniques in new technical fields.Comment: Code available at: https://github.com/RLado/STB-VM