The environmental pollution, property losses and casualties caused by wildfires in California are getting worse by the year. To minimize the interference of wildfires on economic and social development, and formulate targeted mitigation strategies, it is imperative to understand the scale and extent of previous wildfire occurrences. In this study, we first investigated the temporal distributions of past wildfires in California divided by size and causes and analyzed the changes observed in the past two decades against the last century. The trend of wildfires in different time scales (yearly and monthly), as well as the distribution of wildfires across different spatial scales (administrative units, climate divisions in California from 2000 to 2019) were also studied. Furthermore, to extract the significant variables on the risk of wildfire occurrence, multivariate analyses of environmental and human-related variables with wildfire densities were carried out. The results show that the wildfire density distribution of the burned area in California conforms to the characteristics of the Pareto distribution. Over the past two decades, the frequency of small (< 500 acres), human-caused wildfires has increased most rapidly, and they are widely distributed in central and western California. The wildfire season has lengthened and the peak months have been advanced from August to July. In terms of the variables related to the risk of wildfire occurrence, the temperature, vapor pressure deficit, grass cover, and the distance to roads are crucial. This study reveals the relationship between environmental and social background conditions and the spatial-temporal distribution of wildfires, which can provide a reference for wildfire management, the formulation of future targeted wildfire emergency plans, and the planning of future land use in California.

Past studies reported a drastic growth in the wildland–urban interface (WUI), the location where man-made structures meet or overlap wildland vegetation. Fighting fire is difficult in the WUI due to the combination of wildland and structural fuels, and therefore, WUI areas are characterized by frequent damage and loss of structures from wildfires. Recent wildland fire policy has targeted fire prevention, evacuation planning, fuel treatment, and home hardening in WUI areas. Therefore, it is important to understand the occurrence of wildfire events relative to the location of the WUI. In this work, we have reported the occurrences of wildfires with respect to the WUI and quantified how much of the WUI is on complex topography in California, which intensifies fire behavior and complicates fire suppression. We have additionally analyzed the relative importance of WUI-related parameters, such as housing density, vegetation density, and distance to wildfires, as well as topographic factors, such as slope, elevation, aspect, and surface roughness, on the occurrence of large and small wildfires and the burned area of large wildfires near the WUI. We found that a very small percentage of wildfire ignition points and large wildfire-burned areas (>400 ha or 1000 acres) were located in the WUI areas. A small percentage of large wildfires were encountered in WUI (3%), and the WUI area accounted for only 4% of the area burned, which increased to 5% and 56%, respectively, outside WUI (5-km buffer from WUI). Similarly, 66% of fires ignited outside WUI, whereas only 3.6% ignited within WUI. Results from this study have implications for fuel management and infrastructure hardening, as well as for fire suppression and community response.

Due to the mixed distribution of buildings and vegetation, wildland-urban interface (WUI) areas are characterized by complex fuel distributions and geographical environments. The behavior of wildfires occurring in the WUI often leads to severe hazards and significant damage to man-made structures. Therefore, WUI areas warrant more attention during the wildfire season. Due to the ever-changing dynamic nature of California's population and housing, the update frequency and resolution of WUI maps that are currently used can no longer meet the needs and challenges of wildfire management and resource allocation for suppression and mitigation efforts. Recent developments in remote sensing technology and data analysis algorithms pose new opportunities for improving WUI mapping methods. WUI areas in California were directly mapped using building footprints extracted from remote sensing data by Microsoft along with the fuel vegetation cover from the LANDFIRE dataset in this study. To accommodate the new type of datasets, we developed a threshold criteria for mapping WUI based on statistical analysis, as opposed to using more ad-hoc criteria as used in previous mapping approaches. This method removes the reliance on census data in WUI mapping, and does not require the calculation of housing density. Moreover, this approach designates the adjacent areas of each building with large and dense parcels of vegetation as WUI, which can not only refine the scope and resolution of the WUI areas to individual buildings, but also avoids zoning issues and uncertainties in housing density calculation. Besides, the new method has the capability of updating the WUI map in real-time according to the operational needs. Therefore, this method is suitable for local governments to map local WUI areas, as well as formulating detailed wildfire emergency plans, evacuation routes, and management measures.

Accurate microscopic description of the charge-trapping process from semiconductor to defects in the dielectric-oxide layer is of paramount importance for understanding many microelectronic devices such as complementary metal-oxide-semiconductor (CMOS) transistors, as well as electrochemical reactions. Unfortunately, most current microscopic descriptions of such processes are based on empirical models with parameters fitted to experimental device performance results or simplified approximations like the Wentzel-Kramers-Brillouin (WKB) method. Some critical questions are still unanswered, including: What controls the charge-hopping rate, the coupling strength between the defect level to semiconductor level, or the energy difference? How does the hopping rate decay with defect-semiconductor distance? What is the fluctuation of the defect level, especially in amorphous dielectrics? Many of these questions can be answered by ab initio calculations. However, to date, there are few ab initio studies for this problem mainly due to technical challenges from atomic-structure construction to large-system calculations. Here, using the latest advances in calculation methods and codes, we study the carrier-trapping problem using density-functional theory (DFT) based on the Heyd-Scuseria-Ernzerhof (HSE) exchange correlation functional. The valence bond random-switching method is used to construct the crystalline-Si-amorphous-SiO2 (c-Si/a-SiO2) interfacial atomic structure, and the HSE yields a band offset that agrees well with experiments. The hopping rate is calculated with the Marcus theory, and the hopping-rate dependences on the gate potential and defect distances are revealed, as well as the range of fluctuation results from amorphous structural variation. We also analyze the result with the simple WKB model and find a major difference in the description of the coupling constant decay with the defect-semiconductor distance. Our results provide the ab initio simulation insights for this important carrier-trapping process for device operation.

Future electron-positron colliders will play a leading role in the precision measurement of Higgs boson couplings which is one of the central interests in particle physics. Aiming at maximizing the performance to measure the Higgs couplings to the bottom, charm and strange quarks, we develop machine learning methods to improve the selection of events with a Higgs decaying to dijets. Our methods are based on the Boosted Decision Tree (BDT), Fully-Connected Neural Network (FCNN) and Convolutional Neural Network (CNN). We find that the BDT and FCNN algorithms outperform the conventional cut-based method. With our improved selection of Higgs decaying to dijet events using the FCNN, the charm quark signal strength is measured with a 16% error, which is roughly a factor of two better than the 34% precision obtained by the cut-based analysis. Also, the strange quark signal strength is constrained as μss≲35 at the 95% C.L. with the FCNN, which is to be compared with μss≲70 obtained by the cut-based method.

Ultrafast photoexcitation can induce a nonequilibrium dynamic with electron-lattice interaction, offering an effective way to study photoinduced phase transitions (PIPTs) in solids. The issue that atomic displacements after photoexcitation belong to a coherent change or disordered process has become controversial in the PIPT community. Using real-time, time-dependent density functional theory (rt-TDDFT) simulations, we obtained both the coherent and the disordered PIPTs (dimer dissociation) in IrTe2 with different electronic occupations. More importantly, we found that in the disordered phase transition there exists a local correlation between different dimers regarding their dissociation status. We define these Ir-Ir dimers directly connected by Te atoms, including intralayer and vertically across the layers, as a group (group I). Other Ir-Ir dimers separated by five Ir atoms from Ir-Ir dimers in group I are divided into another group (group II). The dimers in the same group will dissociate in a correlated fashion; they either all dissociate or all do not dissociate. On the other hand, the dimers in neighboring groups will have an anticorrelation: If the dimers in one group dissociate, the dimers in the neighboring group tend not to be dissociated, and vice versa.

Charged-defect calculation using a periodic supercell is a significant class of problems in solid state physics. However, the finite supercell size induces an undesirable long-range image charge Coulomb interaction. Although a variety of methods have been proposed to eliminate such image Coulomb interaction, most of the previous schemes are based on a rough approximation of the defect charge screening. In this work, we present a rigorous derivation of the image charge interaction with a defect screening model where the use of a bulk macroscopic dielectric constant can be avoided. We have verified this approach in comparison with a widely used approach for 12 different defects. Our correction scheme offers a much faster convergence concerning the supercell size for cases with considerable image charge interactions. In those cases, we also found that the nonlinear dielectric screening might play an important role. Our proposed defect screening model will also shed new light on understanding the defect screening properties and can be applied to other defect systems.