High-precision Monte Carlo study of directed percolation in (d+1) dimensions

We present a Monte Carlo study of the bond and site directed (oriented) percolation models in $(d+1)$ dimensions on simple-cubic and body-centered-cubic lattices, with $2 \leq d \leq 7$. A dimensionless ratio is defined, and an analysis of its finite-size scaling produces improved estimates of percolation thresholds. We also report improved estimates for the standard critical exponents. In addition, we study the probability distributions of the number of wet sites and radius of gyration, for $1 \leq d \leq 7$.Comment: 11 pages, 21 figure

Worm Monte Carlo study of the honeycomb-lattice loop model

We present a Markov-chain Monte Carlo algorithm of "worm"type that correctly simulates the O(n) loop model on any (finite and connected) bipartite cubic graph, for any real n>0, and any edge weight, including the fully-packed limit of infinite edge weight. Furthermore, we prove rigorously that the algorithm is ergodic and has the correct stationary distribution. We emphasize that by using known exact mappings when n=2, this algorithm can be used to simulate a number of zero-temperature Potts antiferromagnets for which the Wang-Swendsen-Kotecky cluster algorithm is non-ergodic, including the 3-state model on the kagome-lattice and the 4-state model on the triangular-lattice. We then use this worm algorithm to perform a systematic study of the honeycomb-lattice loop model as a function of n<2, on the critical line and in the densely-packed and fully-packed phases. By comparing our numerical results with Coulomb gas theory, we identify the exact scaling exponents governing some fundamental geometric and dynamic observables. In particular, we show that for all n<2, the scaling of a certain return time in the worm dynamics is governed by the magnetic dimension of the loop model, thus providing a concrete dynamical interpretation of this exponent. The case n>2 is also considered, and we confirm the existence of a phase transition in the 3-state Potts universality class that was recently observed via numerical transfer matrix calculations.Comment: 33 pages, 12 figure

Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification

Failure to recognize samples from the classes unseen during training is a major limit of artificial intelligence (AI) in real-world implementation of retinal anomaly classification. To resolve this obstacle, we propose an uncertainty-inspired open-set (UIOS) model which was trained with fundus images of 9 common retinal conditions. Besides the probability of each category, UIOS also calculates an uncertainty score to express its confidence. Our UIOS model with thresholding strategy achieved an F1 score of 99.55%, 97.01% and 91.91% for the internal testing set, external testing set and non-typical testing set, respectively, compared to the F1 score of 92.20%, 80.69% and 64.74% by the standard AI model. Furthermore, UIOS correctly predicted high uncertainty scores, which prompted the need for a manual check, in the datasets of rare retinal diseases, low-quality fundus images, and non-fundus images. This work provides a robust method for real-world screening of retinal anomalies

Improving Inversion Quality of IP-Affected TEM Data Using Dual Source

The induced polarization (IP) effects in transient electromagnetic (TEM) responses pose difficulties to the TEM data interpretation and inversion. The IP effects break the monotony in TEM decay curves and can even cause sign reversals and lead to the singularity and non-monotony of inversion. The singularity problem is still urgent to be solved. In this paper, the forward modeling method of IP-affected TEM responses is developed using the Cole&ndash;Cole model and a frequency-time domain transformation. A TEM data acquisition scheme using a dual-source method without a significant increase in field work is proposed to weaken the singularity and improve the inversion quality finally. Based on the modeling and analysis, the dual-source scheme is designed to guarantee all stations be measured twice with different loops. The joint inversion of dual-source datasets is realized by using an objective combing function and the particle swarm optimization (PSO) algorithm. The synthetic data test proved the validity of the algorithm and illustrated that the joint dual-source method greatly weakened the singularity and stabilized the inversion. The field example of the Baiyun golden deposit showed well consistency with resistivity logging and TEM logging results and predicted the gold mineralization below 2000 m

Joint Inversion with Borehole and Semi-Airborne TEM Data Based on Equivalent Filament Approximation

The borehole transient electromagnetic (TEM) method can be useful in deep mineral exploration to detect blind ore bodies beside or below the borehole, and is especially adapted to finding small-scale, deep, rich ore bodies. In this method a transmitting loop is deployed on the top surface of the Earth, while a receiving coil is moved down the borehole. As the borehole TEM method is limited by the borehole’s location and depth, so its exploration scope is limited. The surface to airborne TEM method is a semi-airborne TEM configuration that transmits on the surface and receives TEM response in air. The two systems are combined into one system in this study, sharing the transmission loop deployed on the surface. With this combined system, the TEM response in the borehole and in the air can be observed at the same time. This paper employs a joint interpretation method based on the equivalent filament, which is introduced to obtain more reliable geometric information for the target with both borehole and aerial TEM data. The eddy currents induced in a thin confined conductor can be represented by equivalent current filaments, and the distribution of filaments can reflect the position and geometry of the conductor. Therefore, geometric parameters of targets can be obtained by filament inversion, and the joint inversion can be more accurate with both borehole and aerial response. Numerical modeling results show that the joint inversion based on the equivalent filament results can reliably obtain the geometric parameters of the thin conductive plate embedded in half space

Joint Inversion with Borehole and Semi-Airborne TEM Data Based on Equivalent Filament Approximation

The borehole transient electromagnetic (TEM) method can be useful in deep mineral exploration to detect blind ore bodies beside or below the borehole, and is especially adapted to finding small-scale, deep, rich ore bodies. In this method a transmitting loop is deployed on the top surface of the Earth, while a receiving coil is moved down the borehole. As the borehole TEM method is limited by the borehole’s location and depth, so its exploration scope is limited. The surface to airborne TEM method is a semi-airborne TEM configuration that transmits on the surface and receives TEM response in air. The two systems are combined into one system in this study, sharing the transmission loop deployed on the surface. With this combined system, the TEM response in the borehole and in the air can be observed at the same time. This paper employs a joint interpretation method based on the equivalent filament, which is introduced to obtain more reliable geometric information for the target with both borehole and aerial TEM data. The eddy currents induced in a thin confined conductor can be represented by equivalent current filaments, and the distribution of filaments can reflect the position and geometry of the conductor. Therefore, geometric parameters of targets can be obtained by filament inversion, and the joint inversion can be more accurate with both borehole and aerial response. Numerical modeling results show that the joint inversion based on the equivalent filament results can reliably obtain the geometric parameters of the thin conductive plate embedded in half space