GIS-based landslide susceptibility modeling using data mining techniques

Introduction: Landslide is one of the most widespread geohazards around the world. Therefore, it is necessary and meaningful to map regional landslide susceptibility for landslide mitigation. In this research, landslide susceptibility maps were produced by four models, namely, certainty factors (CF), naive Bayes (NB), J48 decision tree (J48), and multilayer perceptron (MLP) models.Methods: In the first step, 328 landslides were identified via historical data, interpretation of remote sensing images, and field investigation, and they were divided into two subsets that were assigned different uses: 70% subset for training and 30% subset for validating. Then, twelve conditioning factors were employed, namely, altitude, slope angle, slope aspect, plan curvature, profile curvature, TWI, NDVI, distance to rivers, distance to roads, land use, soil, and lithology. Later, the importance of each conditioning factor was analyzed by average merit (AM) values, and the relationship between landslide occurrence and various factors was evaluated using the certainty factor (CF) approach. In the next step, the landslide susceptibility maps were produced based on four models, and the effect of the four models were quantitatively compared by receiver operating characteristic (ROC) curves, area under curve (AUC) values, and non-parametric tests.Results: The results demonstrated that all the four models can reasonably assess landslide susceptibility. Of these four models, the CF model has the best predictive performance for the training (AUC=0.901) and validating data (AUC=0.892).Discussion: The proposed approach is an innovative method that may also help other scientists to develop landslide susceptibility maps in other areas and that could be used for geo-environmental problems besides natural hazard assessments

Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models

Exploring the application of powerful large language models (LLMs) on the fundamental named entity recognition (NER) task has drawn much attention recently. This work aims to investigate the possibilities of pushing the boundary of zero-shot NER with LLM via a training-free self-improving strategy. We propose a self-improving framework, which utilize an unlabeled corpus to stimulate the self-learning ability of LLMs on NER. First, we use LLM to make predictions on the unlabeled corpus and obtain the self-annotated data. Second, we explore various strategies to select reliable samples from the self-annotated dataset as demonstrations, considering the similarity, diversity and reliability of demonstrations. Finally, we conduct inference for the test query via in-context learning with the selected self-annotated demonstrations. Through comprehensive experimental analysis, our study yielded the following findings: (1) The self-improving framework further pushes the boundary of zero-shot NER with LLMs, and achieves an obvious performance improvement; (2) Iterative self-improving or naively increasing the size of unlabeled corpus does not guarantee improvements; (3) There might still be space for improvement via more advanced strategy for reliable entity selection

Dominant Andreev Reflection through Nonlinear Radio-Frequency Transport

We theoretically propose the laser-induced Andreev reflection between two-component Fermi superfluid and normal states via spatially-uniform Rabi couplings. By analyzing the tunneling current between the superfluid and normal states up to the fourth order in the Rabi couplings, we find that the Andreev current exhibits unconventional non-Ohmic transport at zero temperature. Remarkably, the Andreev current gives the only contribution in the synthetic junction system at zero detunings regardless of the ratio of the chemical potential bias to the superfluid gap, which is in sharp contrast to that in the conventional superconductor-normal metal junction. Our result may also pave a way for understanding the black hole information paradox through the Andreev reflection as a quantum-information mirror.Comment: 6 pages, 4 figure

Spin transport between polarized Fermi gases near the ferromagnetic phase transition

We theoretically study the spin current between two polarized Fermi gases with repulsive interactions near the itinerant ferromagnetic phase transition. We consider a two-terminal model where the left reservoir is fixed to be fully polarized while the polarization of the right reservoir is tuned through a fictitious magnetic field defined by the chemical-potential difference between different atomic hyperfine states. We calculate the spectra of the spin-flip susceptibility function, which displays a magnon dispersion emerging from the Stoner continuum at low momentum in the ferromagnetic phase. Based on the spin-flip susceptibility and using Keldysh Green's function formalism, we investigate the spin current induced by quasiparticle and spin-flip tunneling processes, respectively, and show their dependence on the polarization bias between two reservoirs. The one-body (quasiparticle) tunneling demonstrates a linear dependence with respect to the polarization bias. In contrast, the spin-flip process manifests a predominantly cubic dependence on the bias. While indicating an enhanced magnon tunneling in the strong-coupling regime, our results also demonstrate a characteristic behavior around the critical repulsive strength for ferromagnetic phase transition at low temperatures.Comment: 9 pages, 6 figure

Experimental observation of three-photon interference between a two-photon state and a weak coherent state on a beam splitter

We experimentally demonstrated a three-photon interference on a beam splitter between a weak coherent state and a two-photon state produced by a spontaneous parametric down conversion. It indicates that a combined three-photon probability amplitude, which is formed by the two-photon state and one-photon from the coherent state, can be used to interfere with another three-photon probability amplitude from the coherent state. The observed three-photon coincidence rate showed that the interference depended on not only the relative phase between the two interference field but also the amplitude of the weak coherent state. This may introduce another free parameter for preparing quantum state, such as high N00N state, with quantum interference

Controlling quantum interference in phase space with amplitude

We experimentally show a quantum interference in phase space by interrogating photon number probabilities (n = 2, 3, and 4) of a displaced squeezed state, which is generated by an optical parametric amplifier and whose displacement is controlled by amplitude of injected coherent light. It is found that the probabilities exhibit oscillations of interference effect depending upon the amplitude of the controlling light field. This phenomenon is attributed to quantum interference in phase space and indicates the capability of controlling quantum interference using amplitude. This remarkably contrasts with the oscillations of interference effects being usually controlled by relative phase in classical optics

Characterizing current noise of commercial constant-current sources by using of an optically-pumped rubidium atomic magnetometer

This paper introduces a method for characterizing the current noise of commercial constant-current sources(CCSs) using a free-induction-decay(FID) type optically-pumped rubidium atomic magnetometer driven by a radio-frequency(RF) magnetic field. We convert the sensitivity of the atomic magnetometer into the current noise of CCS by calibrating the coil constant. At the same time, the current noise characteristics of six typical commercial low-noise CCSs are compared. The current noise level of the KeySight Model B2961A is the lowest among the six tested CCSs, which is 36.233 0.022 nA / Hz1/2 at 1-25 Hz and 133.905 0.080 nA / Hz1/2 at 1-100 Hz respectively. The sensitivity of atomic magnetometer is dependent on the current noise level of the CCS. The CCS with low noise is of great significance for high-sensitivity atomic magnetometer. The research provides an important reference for promoting the development of high precision CCS, metrology and basic physics research.Comment: 7pages,7figure