Flexible Spatio-Temporal Hawkes Process Models for Earthquake Occurrences

Hawkes process is one of the most commonly used models for investigating the self-exciting nature of earthquake occurrences. However, seismicity patterns have complicated characteristics due to heterogeneous geology and stresses, for which existing methods with Hawkes process cannot fully capture. This study introduces novel nonparametric Hawkes process models that are flexible in three distinct ways. First, we incorporate the spatial inhomogeneity of the self-excitation earthquake productivity. Second, we consider the anisotropy in aftershock occurrences. Third, we reflect the space-time interactions between aftershocks with a non-separable spatio-temporal triggering structure. For model estimation, we extend the model-independent stochastic declustering (MISD) algorithm and suggest substituting its histogram-based estimators with kernel methods. We demonstrate the utility of the proposed methods by applying them to the seismicity data in regions with active seismic activities.Comment: 53 page

Gate-dependent spin Hall induced nonlocal resistance and the symmetry of spin-orbit scattering in Au-clustered graphene

Engineering the electron dispersion of graphene to be spin-dependent is crucial for the realization of spin-based logic devices. Enhancing spin-orbit coupling in graphene can induce spin Hall effect, which can be adapted to generate or detect a spin current without a ferromagnet. Recently, both chemically and physically decorated graphenes have shown to exhibit large nonlocal resistance via the spin Hall and its inverse effects. However, these nonlocal transport results have raised critical debates due to the absence of field dependent Hanle curve in subsequent studies. Here, we introduce Au clusters on graphene to enhance spin-orbit coupling and employ a nonlocal geometry to study the spin Hall induced nonlocal resistance. Our results show that the nonlocal resistance highly depends on the applied gate voltage due to various current channels. However, the spin Hall induced nonlocal resistance becomes dominant at a particular carrier concentration, which is further confirmed through Hanle curves. The obtained spin Hall angle is as high as similar to 0.09 at 2 K. Temperature dependence of spin relaxation time is governed by the symmetry of spin-orbit coupling, which also depends on the gate voltage: asymmetric near the charge neutral point and symmetric at high carrier concentration. These results inspire an effective method for generating spin currents in graphene and provide important insights for the spin Hall effect as well as the symmetry of spin scattering in physically decorated graphene

Dynamic principal component analysis with missing values

Dynamic principal component analysis (DPCA), also known as frequency domain principal component analysis, has been developed by Brillinger [Time Series: Data Analysis and Theory, Vol. 36, SIAM, 1981] to decompose multivariate time-series data into a few principal component series. A primary advantage of DPCA is its capability of extracting essential components from the data by reflecting the serial dependence of them. It is also used to estimate the common component in a dynamic factor model, which is frequently used in econometrics. However, its beneficial property cannot be utilized when missing values are present, which should not be simply ignored when estimating the spectral density matrix in the DPCA procedure. Based on a novel combination of conventional DPCA and self-consistency concept, we propose a DPCA method when missing values are present. We demonstrate the advantage of the proposed method over some existing imputation methods through the Monte Carlo experiments and real data analysis.N

Estimation of spatio-temporal extreme distribution using a quantile factor model

This paper describes the estimation of the extreme spatio-temporal sea surface temperature data based on the quantile factor model implemented by the SNU multiscale team. The proposed method was developed for the EVA2019 Data Challenge. Various attempts have been conducted to use factor models in spatio-temporal data analysis to find hidden factors in high-dimensional data. Factor models represent high-dimensional data as a linear combination of several factors, and hence, can describe spatially and temporally correlated data in a simple form. Meanwhile, unlike ordinary factor models, there are asymmetric norm-based factor models, such as quantile factor models or expectile dynamic semiparametric factor models, that can help understand the quantitative behavior of data beyond their mean structure. For this purpose, we apply a quantile factor model to the data to obtain significant factors explaining the quantile response of the temperatures and find quantile estimates. We develop a new method for inference of quantiles of extremal levels by extrapolating quantile estimates from the factor model with extreme value theory. The proposed method provides better performance than the benchmark, gives some interpretable insights, and shows the potential to expand the factor model with various data.N

Gate dependent of nonlocal spin resistance in hydrogenated graphene

Graphene has been perceived as a promising spin channel material for spin field effect transistor and spin logic device because of long spin diffusion length arising from weak intrinsic spin-orbit interaction (SOI). Further, incorporation of SOI into graphene can lead to many interesting spin related phenomena; such as spin Hall effect, topological quantum spin Hall effect. The partial hydrogenation of the graphene has been suggested to induce local enhancement of SOI in graphene. The chemisorbed hydrogen can produce local magnetic moments and enhance SOI of graphene due to a change in orbital hybridization of the carbon network from sp2 into sp3. In this study, we introduce hydrogenated graphene by the dissociation of a hydrogen silsesquioxane (HSQ) resist. The ratio of hydrogenated carbon in graphene was determined to be 0.01~0.05 % for irradiation does of range 1~3 mC/cm2 which is determined by ID/IG ratio of Raman peak. We employed an H-bar type device to probe the nonlocal spin signal induced by spin Hall and inverse spin Hall effect. The geometry of the studied H-bar devices fabricated by E-beam lithography has channels of 1 mm width and 2, 3, 4 mm length. Detailed study or non-local spin signal in hydrogenated graphene will be discussed further

Gate dependent non-local spin resistance in an Au-patched graphene

Enhanced spin-orbit coupling in grapheme can induce spin Hall effect, which can be adapted to electrically generate or detect a spin current in the spin logic device without a ferromagnet. Recently, spin Hall effect in decorated graphenes has been experimentally observed by non-local transport studies. However, results on the non-local measurements in graphene hall bar devices exploiting spin Hall effect have been under controversy. In this study, we introduced an ultra-thin Au-patch on a graphene surface to enhance the spin-orbit coupling, and employed an H-bar type device to probe the nonlocal spin signal induced by spin Hall effect. The geometry of the studied H-bar devices has channels of 1 ??m width and 5.6 ??m length. An ultra-thin Au patch (\textasciitilde 1 nm) was deposited by a thermal evaporation. And in-plane field dependent spin precession signature can be observed at particular gate voltage. At that point, the spin hall angle and the spin relaxation length of the Au-patch graphene device were ?? \textasciitilde 8.8 {\%} and ??s \textasciitilde 2.2 ??m at 2 K, respectively. The estimated spin relaxation rates were proportional to square of temperature, suggesting an Elliott-Yafet spin relaxation mechanism

Observation of spin-polarized Anderson state around charge neutral point in graphene with Fe-clusters

The pristine graphene described with massless Dirac fermion could bear topological insulator state and ferromagnetism via the band structure engineering with various adatoms and proximity effects from heterostructures. In particular, topological Anderson insulator state was theoretically predicted in tight-binding honeycomb lattice with Anderson disorder term. Here, we introduced physi-absorbed Fe-clusters/adatoms on graphene to impose exchange interaction and random lattice disorder, and we observed Anderson insulator state accompanying with Kondo effect and field-induced conducting state upon applying the magnetic field at around a charge neutral point. Furthermore, the emergence of the double peak of resistivity at nu = 0 state indicates spin-splitted edge state with high effective exchange field (>70T). These phenomena suggest the appearance of topological Anderson insulator state triggered by the induced exchange field and disorder