Local Time Research Articles

Characteristic Analysis of the MS6.0 Ma'erkang Earthquake Sequence on Jun. 10, 2022

On June 10, 2022, the MS6.0 Ma'erkang earthquake sequence occurred in the Bayan Har block. In this paper, the temporal and spatial distribution and attenuation characteristics of earthquake sequence is analyzed based on the regional structure, the temporal and spatial distribution of earthquake sequence, the focal mechanism solution, and the parameters of earthquake sequence, using the data of Sichuan Seismic Network and the temporary stations incorporated into the network. The results show that: (1) The MS6.0 Ma'erkang earthquake sequence is generally distributed in NW-SE direction, and the long axis of this series is basically consistent with the nearby Songgang fault. (2) As the earthquake sequence is formed by three large events with MS ≥5.0, the frequency of small earthquakes in the earthquake sequence area generally attenuates relatively slowly, while the activity level (magnitude) of aftershocks attenuates rapidly. (3) After the MS5.2 earthquake, the sequence parameters obtained show that the h-value is 1.09 and the p-value is stable at 1.02, indicating that the intensity and frequency attenuation of the earthquake sequence are gradually stable and tend to be normal. The b-value is 0.95, indicating that the maximum aftershock magnitude of the series is estimated to be ML5.1, and the b-value gradually tended to be stable, indicating that the stress in the region gradually tended to be balanced after the MS5.2 earthquake. The MS4.4 (ML5.0) earthquake that occurred at 4:37 on June 10 (local time) is the largest aftershock after the MS5.2 earthquake in the sequence. (4) The Songgang fault with NW-SE trend is presumed to be the main seismogenic tectonics, but the migration of three earthquakes with MS≥5.0 may also indicate that the Songgang fault is not a single seismogenic tectonics, which requires further field scientific investigation and analysis.

Lunar South Polar Water Cycle and Water Resources: Diurnal and Spatial Variations in Surficial Hydration From Repeated Moon Mineralogy Mapper Observations

AbstractThe diurnal variation and distribution of lunar surficial hydration (OH/H2O) is of great significance for understanding the solar wind implantation and water cycle on the Moon. Lunar south pole is an ideal place to study the diurnal variation of surficial hydration due to the large number of repeat observations of the same region, which is very limited in mid‐ or low‐latitudes. Here we showed clear 0.5‐hr interval diurnal variation of surficial hydration at lunar south pole. The variation of hydration band depth with local time is exactly the opposite to the variation of temperature, indicating that lunar surficial hydration changes sufficiently with temperature. This relationship indicates that both the diurnal variation and hydration content are latitude dependent. Our observations support the hypothesis that the diurnal variation of hydration on the Moon is due to the formation of metastable hydroxyl.

Multipath Attention and Adaptive Gating Network for Video Action Recognition

3D CNN networks can model existing large action recognition datasets well in temporal modeling and have made extremely great progress in the field of RGB-based video action recognition. However, the previous 3D CNN models also face many troubles. For video feature extraction convolutional kernels are often designed and fixed in each layer of the network, which may not be suitable for the diversity of data in action recognition tasks. In this paper, a new model called Multipath Attention and Adaptive Gating Network (MAAGN) is proposed. The core idea of MAAGN is to use the spatial difference module (SDM) and the multi-angle temporal attention module (MTAM) in parallel at each layer of the multipath network to obtain spatial and temporal features, respectively, and then dynamically fuses the spatial-temporal features by the adaptive gating module (AGM). SDM explores the action video spatial domain using difference operators based on the attention mechanism, while MTAM tends to explore the action video temporal domain in terms of both global timing and local timing. AGM is built on an adaptive gate unit, the value of which is determined by the input of each layer, and it is unique in each layer, dynamically fusing the spatial and temporal features in the paths of each layer in the multipath network. We construct the temporal network MAAGN, which has a competitive or better performance than state-of-the-art methods in video action recognition, and we provide exhaustive experiments on several large datasets to demonstrate the effectiveness of our approach.

Nanoscale visualization of fast carrier dynamics in organic thin-film transistors by time-resolved electrostatic force microscopy

Fast carrier dynamics in organic thin-film transistors (OTFTs) was investigated by time-resolved electrostatic force microscopy (tr-EFM). We found that the carrier diffusion in the OTFTs proceeded in two stages: fast diffusion and slow diffusion. By applying the instantaneous frequency method to EFM, the temporal evolution of the spatial distribution of fast carriers in the channel region of the OTFTs, which took place on the timescale of several hundreds of nanoseconds, was evaluated. The inhomogeneous distribution of the local decay time constant showed that the carrier diffusion of the OTFTs was limited by the grain boundaries between each crystalline region. The quantitative capability of the method was verified by comparing the values of the carrier mobility estimated by the tr-EFM measurement and a numerical simulation. The mobility estimated from the experiment and the simulation showed good agreement, showing the possibility of the tr-EFM to evaluate the time evolution of dynamic phenomena in semiconductor devices.

Semidiurnal Non‐Migrating Tides in the Middle Thermosphere From Far Ultraviolet Observations

AbstractMuch of the longitude/local time dependence of the thermosphere is controlled by non‐migrating tides. Observations of semidiurnal (12‐hr) tides between 120 and 200 km altitude, that is, the middle thermosphere, are rare owing to the lack of systematic measurements in this region. Since late 2018, the Global‐scale Observations of the Limb and Disk (GOLD) Mission has provided unique measurements of thermospheric disk temperature and the column density ratio of atomic oxygen to molecular nitrogen ratio (ΣO/N2) from geostationary orbit. In this paper, we present an approach to deduce the strongest semidiurnal non‐migrating tides in the middle thermosphere by adapting the method of Krier et al. (2021, https://doi.org/10.1029/2021ja029563) that deduces diurnal non‐migrating tides in simultaneous observations of temperature and ΣO/N2 made by GOLD. Testing of this approach suggests that the principal sources of uncertainties in the derived semidiurnal non‐migrating tides are the limitation on the longitudes sampled, such that uncertainties are higher for tides with longer horizontal wavelength, and contamination of the local time sums by stationary planetary waves, which causes amplitudes to be overestimated. Our approach is applied to GOLD data during solstice conditions in 2019–2021. Comparison to models yield disagreements which are likely due to uncertainties intrinsic to the method and/or misrepresentation of tidal dynamics in the models. These results are the first observations of semidiurnal non‐migrating tides in the middle thermosphere from a geostationary observational platform.

Evaluation of the Empirical Scaling Factor of Joule Heating Rates in TIE‐GCM With EISCAT Measurements

AbstractJoule heating is one of the main energy inputs into the thermosphere‐ionosphere system. Precise modeling of this process is essential for any space weather application. Existing thermosphere‐ionosphere models tend to underestimate the actual Joule heating rate quite significantly. The Thermosphere‐Ionosphere‐Electrodynamics General‐Circulation‐Model applies an empirical scaling factor of 1.5 for compensation. We calculate vertical profiles of Joule heating rates from approximately 2,220 hr of measurements with the EISCAT incoherent scatter radar and the corresponding model runs. We investigate model runs with the plasma convection driven by both the Heelis and the Weimer model. The required scaling of the Joule heating profiles is determined with respect to the Kp index, the Kan‐Lee merging electric field EKL, and the magnetic local time. Though the default scaling factor of 1.5 appears to be adequate on average, we find that the required scaling varies strongly with all three parameters ranging from 0.46 to ∼20 at geomagnetically disturbed and quiet times, respectively. Furthermore, the required scaling is significantly different in runs driven by the Heelis and Weimer model. Adjusting the scaling factor with respect to the Kp index, EKL, the magnetic local time, and the choice of convection model would reduce the difference between Joule heating rates calculated from measurement and model plasma parameters.

Solar FTIR measurements of NOx vertical distributions – Part 1: First observational evidence of a seasonal variation in the diurnal increasing rates of stratospheric NO2 and NO

Abstract. Observations of nitrogen dioxide (NO2) and nitrogen oxide (NO) in the stratosphere are relevant to understand long-term changes and variabilities in stratospheric nitrogen oxide (NOx) and ozone (O3) concentrations. Due to the versatile role of NO2 and NO in stratospheric O3 photochemistry, they are important for recovery and build-up of O3 holes in the stratosphere and therefore can indirectly affect human life. Thus, we present in this work the evaluation of NO2 and NO stratospheric partial columns (> 16 km altitude) retrieved from ground-based Fourier-transform infrared (FTIR) measurements of over 25 years at Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.) and 18 years at Garmisch (47.47° N, 11.06° E; 745 m a.s.l.), Germany. The obtained stratospheric columns are only weakly influenced by tropospheric pollution and show only a very small bias of 2.5 ± 0.2 % when comparing NO2 above Zugspitze and Garmisch. Stratospheric columns of both NO2 and NO show a diurnal increase that depends on local solar time (LST). We quantified this behavior by calculating diurnal increasing rates. Here, we find mean values for the NO2 diurnal increasing rate of (0.89 ± 0.14) × 1014 and (0.94 ± 0.14) × 1014 cm−2 h−1 at Zugspitze and Garmisch, respectively. The mean NO morning diurnal increasing rate above Zugspitze is found to be (1.42 ± 0.12) × 1014 cm−2 h−1. Regarding the seasonal dependency of these increasing rates, for the first time, we were able to experimentally detect a significant seasonal variation in both NO2 diurnal increasing rates and NO morning diurnal increasing rates with a maximum of (1.13 ± 0.04) × 1014 cm−1 h−1 for NO2 and (1.76 ± 0.25) × 1014 cm−1 h−1 for NO in September and a minimum of (0.71 ± 0.18) × 1014 cm−1 h−1 in December for NO2 and a minimum of (1.18 ± 0.41) × 1014 cm−1 h−1 in November for NO. This similar behavior may be explained by the interconnection of both species in stratospheric photochemistry. The outcome of this work is a retrieval and analysis strategy of FTIR data for NOx stratospheric columns, which can help to further validate photochemical models or improve satellite validations. The first use of this data set is shown in the companion paper (Nürnberg et al., 2023) wherein experiment-based NOx scaling factors describing the diurnal increase in the retrieved partial columns are extracted and recently published model-based scaling factors are validated.

Analysis of Moving Bodies with a Direct Finite Difference Time Domain Method

This paper proposes an original and thorough analysis of the behavior of electromagnetic waves in the presence of moving bodies by using the finite difference time domain (FDTD) method. Movements are implemented by changing positions of the objects at each time step, through the classical FDTD time loop. This technique is suitable for non-relativistic speeds, thus for most encountered problems in antennas and propagation domain. The numerical aspects that need to be considered are studied. Then, different bodies in motion are examined: plane wave source with matching resistors, observation point, inclined partially reflecting surface (PRS), line source, and metallic cylinder illuminated by a plane wave. The results are compared with those of special relativity which are considered as the references. Some aspects of special relativity are present in the direct FDTD approach, such as the independence of the velocity of electromagnetic wave propagation with the speed of the source and Lorentz local time (with a different physical interpretation). It is shown that the amplitude of the electric field for a moving plane wave source does not increase with the speed of motion, if the impedance of the source is small. Moreover, for a moving scattering metallic wire, one can observe a phenomenon similar to shock waves.

Image rectangling network based on reparameterized transformer and assisted learning

Stitched images can offer a broader field of view, but their boundaries can be irregular and unpleasant. To address this issue, current methods for rectangling images start by distorting local grids multiple times to obtain rectangular images with regular boundaries. However, these methods can result in content distortion and missing boundary information. We have developed an image rectangling solution using the reparameterized transformer structure, focusing on single distortion. Additionally, we have designed an assisted learning network to aid in the process of the image rectangling network. To improve the network’s parallel efficiency, we have introduced a local thin-plate spline Transform strategy to achieve efficient local deformation. Ultimately, the proposed method achieves state-of-the-art performance in stitched image rectangling with a low number of parameters while maintaining high content fidelity. The code is available at https://github.com/MelodYanglc/TransRectangling.

PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell Modeling

Pre-routing timing prediction has been recently studied for evaluating the quality of a candidate cell placement in chip design. It involves directly estimating the timing metrics for both pin-level (slack, slew) and edge-level (net delay, cell delay), without time-consuming routing. However, it often suffers from signal decay and error accumulation due to the long timing paths in large-scale industrial circuits. To address these challenges, we propose a two-stage approach. First, we propose global circuit training to pre-train a graph auto-encoder that learns the global graph embedding from circuit netlist. Second, we use a novel node updating scheme for message passing on GCN, following the topological sorting sequence of the learned graph embedding and circuit graph. This scheme residually models the local time delay between two adjacent pins in the updating sequence, and extracts the lookup table information inside each cell via a new attention mechanism. To handle large-scale circuits efficiently, we introduce an order preserving partition scheme that reduces memory consumption while maintaining the topological dependencies. Experiments on 21 real world circuits achieve a new SOTA R2 of 0.93 for slack prediction, which is significantly surpasses 0.59 by previous SOTA method. Code will be available at: https://github.com/Thinklab-SJTU/EDA-AI.

Skin Cancer Recognition Using Unified Deep Convolutional Neural Networks.

The incidence of skin cancer is rising globally, posing a significant public health threat. An early and accurate diagnosis is crucial for patient prognoses. However, discriminating between malignant melanoma and benign lesions, such as nevi and keratoses, remains a challenging task due to their visual similarities. Image-based recognition systems offer a promising solution to aid dermatologists and potentially reduce unnecessary biopsies. This research investigated the performance of four unified convolutional neural networks, namely, YOLOv3, YOLOv4, YOLOv5, and YOLOv7, in classifying skin lesions. Each model was trained on a benchmark dataset, and the obtained performances were compared based on lesion localization, classification accuracy, and inference time. In particular, YOLOv7 achieved superior performance with an Intersection over Union (IoU) of 86.3%, a mean Average Precision (mAP) of 75.4%, an F1-measure of 80%, and an inference time of 0.32 s per image. These findings demonstrated the potential of YOLOv7 as a valuable tool for aiding dermatologists in early skin cancer diagnosis and potentially reducing unnecessary biopsies.

Exploration of low-frequency allelic variants of SARS-CoV-2 genomes reveals coinfections in Mexico occurred during periods of VOCs turnover.

A total of 14 973 alleles in 29 661 sequenced samples collected between March 2021 and January 2023 by the Mexican Consortium for Genomic Surveillance (CoViGen-Mex) and collaborators were used to construct a thorough map of mutations of the Mexican SARS-CoV-2 genomic landscape containing Intra-Patient Minor Allelic Variants (IPMAVs), which are low-frequency alleles not ordinarily present in a genomic consensus sequence. This additional information proved critical in identifying putative coinfecting variants included alongside the most common variants, B.1.1.222, B.1.1.519, and variants of concern (VOCs) Alpha, Gamma, Delta, and Omicron. A total of 379 coinfection events were recorded in the dataset (a rate of 1.28 %), resulting in the first such catalogue in Mexico. The most common putative coinfections occurred during the spread of Delta or after the introduction of Omicron BA.2 and its descendants. Coinfections occurred constantly during periods of variant turnover when more than one variant shared the same niche and high infection rate was observed, which was dependent on the local variants and time. Coinfections might occur at a higher frequency than customarily reported, but they are often ignored as only the consensus sequence is reported for lineage identification.

The Gauge Picture of Quantum Dynamics

Although local Hamiltonians exhibit local time dynamics, this locality is not explicit in the Schrödinger picture in the sense that the wavefunction amplitudes do not obey a local equation of motion. We show that geometric locality can be achieved explicitly in the equations of motion by "gauging" the global unitary invariance of quantum mechanics into a local gauge invariance. That is, expectation values ⟨ψ|A|ψ⟩ are invariant under a global unitary transformation acting on the wavefunction |ψ⟩→U|ψ⟩ and operators A→UAU†, and we show that it is possible to gauge this global invariance into a local gauge invariance. To do this, we replace the wavefunction with a collection of local wavefunctions |ψJ⟩, one for each patch of space J. The collection of spatial patches is chosen to cover the space; e.g. we could choose the patches to be single qubits or nearest-neighbor sites on a lattice. Local wavefunctions associated with neighboring pairs of spatial patches I and J are related to each other by dynamical unitary transformations UIJ. The local wavefunctions are local in the sense that their dynamics are local. That is, the equations of motion for the local wavefunctions |ψJ⟩ and connections UIJ are explicitly local in space and only depend on nearby Hamiltonian terms. (The local wavefunctions are many-body wavefunctions and have the same Hilbert space dimension as the usual wavefunction.) We call this picture of quantum dynamics the gauge picture since it exhibits a local gauge invariance. The local dynamics of a single spatial patch is related to the interaction picture, where the interaction Hamiltonian consists of only nearby Hamiltonian terms. We can also generalize the explicit locality to include locality in local charge and energy densities.

Pulmonary Evaluation of Earthquake Victims Followed Up in the Intensive Care Unit After the 2023 Turkey Kahramanmaras Earthquakes.

In Turkey, a total of 269 earthquakes took place from 1900 through 2023. The most devastating earthquakes in terms of casualties and extensive destruction occurred at 4:17am and 1:24pm local time on February 6, 2023 with the epicenters located in Pazarcik (Kahramanmaras) and Ekinozu (Kahramanmaras) and magnitudes of 7.7Mw and 7.6Mw, respectively. The aim of this study was to define the frequency of lung complications that occurred directly and/or developed during the intensive care follow-up of individuals affected by the Kahramanmaras earthquakes. A retrospective evaluation was conducted on the files of 69 patients who were rescued from the debris of collapsed buildings after the Kahramanmaras earthquakes and followed up in the intensive care unit in terms of the time under the debris, demographic data, vital signs, and lung complications that were present at the time of admission and developed during follow-up. SPSS for Windows v. 20.0 was used for data analysis. The study included a total of 69 patients, of whom 29 (42%) were female and 40 (58%) were male. The mean age was 39.9 (SD = 16.9) years. The mean time under the debris was 53.9 (SD = 52) hours, and the mean time from rescue to the intensive care unit admission was 18.7 (SD = 12.8) hours. One or more pulmonary complications were detected in 52.2% (n = 36) of the patients at the time of admission. During the follow-up, 30.4% (n = 21) of the patients developed pulmonary congestion, 13.0% (n = 9) pneumonia, 1.5% (n = 1) alveolar hemorrhage, and 1.5% (n = 1) atelectasis, while no additional lung complications developed in the remaining 37 patients (53.6%). Severe cases of individuals recovered from the debris can have a high prevalence of earthquake-related lung disorders and chest trauma, which may be associated with high mortality. The timely identification and effective intervention of pulmonary complications that may develop during follow-up can reduce mortality.

Political Budget Cycles and Mayoral Influence in Latvian Municipalities: An Examination of Revenue, Expenditure, and Electoral Dynamics

Budget allocation and budget planning can be used in different ways. In addition, it can be part of a political budget cycle. Previous research has highlighted the political budget cycle's existence in European countries, demonstrating its impact on public revenue and expenditure near elections. However, citizens often lack awareness of this phenomenon, underscoring the need for vigilant scrutiny. In addition, elected politicians increasingly rely on voters for support, targeting them during budget allocation and election campaigns. In Latvia, the mayors have a role in budget planning because they work full-time and are the head of the financial commission. In Latvia, despite a lack of trust in local politicians, there is a tendency for most of the mayors to be re-elected. The article aims to examine what kind of role the council’s chairperson has in the local government's budget allocation process and what factors affect the budget allocation process in Latvia. The article’s scope encompasses the years 2009 to 2017, spanning two election terms (2009-2013; 2013-2017), and focuses on eight state cities in Latvia, excluding the capital city, Riga. Notably, local governments with a higher percentage of council members from the mayor's party tend to exhibit higher expenditure levels. The findings of this study suggest that various socio-economic and political factors impact the financial performance of local governments in Latvia. These results underscore the significance of population and unemployment in shaping local government expenditures. Simultaneously, this research has highlighted the importance of political factors such as the majority in the local government and time spent in the mayor’s position. Moreover, it reveals that long-serving mayors and a majority in the council also influence budget allocation decisions. This article's implications can guide policymakers in making informed decisions regarding municipal budget expenditures and revenues.

Impaired long-range excitatory time scale predicts abnormal neural oscillations and cognitive deficits in Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is the most common form of dementia, progressively impairing cognitive abilities. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. Using magnetoencephalography imaging we documented abnormal local neural synchrony patterns in patients with AD. To identify global abnormal biophysical mechanisms underlying the spatial and spectral electrophysiological patterns in AD, we estimated the parameters of a biophysical spectral graph model (SGM).MethodsSGM is an analytic neural mass model that describes how long-range fiber projections in the brain mediate the excitatory and inhibitory activity of local neuronal subpopulations. Unlike other coupled neuronal mass models, the SGM is linear, available in closed-form, and parameterized by a small set of biophysical interpretable global parameters. This facilitates their rapid and unambiguous inference which we performed here on a well-characterized clinical population of patients with AD (N = 88, age = 62.73 +/- 8.64 years) and a cohort of age-matched controls (N = 88, age = 65.07 +/- 9.92 years).ResultsPatients with AD showed significantly elevated long-range excitatory neuronal time scales, local excitatory neuronal time scales and local inhibitory neural synaptic strength. The long-range excitatory time scale had a larger effect size, compared to local excitatory time scale and inhibitory synaptic strength and contributed highest for the accurate classification of patients with AD from controls. Furthermore, increased long-range time scale was associated with greater deficits in global cognition.ConclusionsThese results demonstrate that long-range excitatory time scale of neuronal activity, despite being a global measure, is a key determinant in the local spectral signatures and cognition in the human brain, and how it might be a parsimonious factor underlying altered neuronal activity in AD. Our findings provide new insights into mechanistic links between abnormal local spectral signatures and global connectivity measures in AD.

The Soliton Solutions for Nonlocal Multi-Component Higher-Order Gerdjikov–Ivanov Equation via Riemann–Hilbert Problem

The Lax pairs of the higher-order Gerdjikov–Ivanov (HOGI) equation are extended to the multi-component formula. Then, we first derive four different types of nonlocal group reductions to this new system. To construct the solution of these four nonlocal equations, we utilize the Riemann–Hilbert method. Compared to the local HOGI equation, the solutions of nonlocal equations not only depend on the local spatial and time variables, but also the nonlocal variables. To exhibit the dynamic behavior, we consider the reverse-spacetime multi-component HOGI equation and its Riemann–Hilbert problem. When the Riemann–Hilbert problem is regular, the integral form solution can be given. Conversely, the exact solutions can be obtained explicitly. Finally, as concrete examples, the periodic solutions of the two-component nonlocal HOGI equation are given, which is different from the local equation.

Effects of solar radiation and tree planting on photochemical reaction kinetics in urban street canyon

The investigation of the impact of tree planting on photochemical reaction kinetics and dispersion characteristics of reactive pollutants in street canyons under actual solar radiation remains a pertinent subject for research. The numerical models were employed and validated through wind-tunnel experiments to investigate the dynamic and thermodynamic effects of tree planting (LAD = 4.77) on turbulent flow, heat transfer, and NOx-O3 photochemical reaction in urban street canyons. The effects of solar radiation at three local solar times (LST0900, LST1200 and LST1500) and three background O3 concentrations (20 ppb, 100 ppb and 200 ppb) were considered. The ozone depletion rate (dO3) was defined to measure the photochemical reaction equilibrium. The results show that the presence of trees can offset the impact of varying LST solar radiation and promote greater stability in flow structures within street canyons. Specifically, a stable clockwise main vortex is observed in the upper part, while multiple smaller vortices form more regularly in the lower part. Compared with no trees, planting trees can effectively reduce the temperature by about 5 K in the lower part of street canyon through the shading and transpiration cooling effects. In conjunction with its dynamic effects, the tree planting can also effectively reduce the average concentration of pollutants before the reaction. It results in a predominant accumulation of NOx near the pollution source at the bottom center, thereby mitigating their detrimental impacts on both windward and leeward sides. Additionally, under the same background O3 concentration, tree planting can also influence the equilibrium process of photochemical reactions and enhance their reverse reaction leading to ozone depletion. The findings of this study contribute to a deeper understanding of the impact of tree greening on the local microclimate within urban street canyons.

Global Magnetic Reconnection During Sustained Sub‐Alfvénic Solar Wind Driving

AbstractWhen the solar wind speed falls below the local Alfvén speed, the magnetotail transforms into an Alfvén wing configuration. A Grid Agnostic Magnetohydrodynamics for Extended Research Applications (GAMERA) simulation of Earth's magnetosphere using solar wind parameters from the 24 April 2023 sub‐Alfvénic interval is examined to reveal modifications of Dungey‐type magnetotail reconnection during sustained sub‐Alfvénic solar wind. The simulation shows new magnetospheric flux is generated via reconnection between polar cap field lines from the northern and southern hemisphere, similar to Dungey‐type magnetotail reconnection between lobe field lines mapping to opposite hemispheres. The key feature setting the Alfvén wing reconnection apart from the typical Dungey‐type is that the majority of new magnetospheric flux is added to the polar cap at local times 1–3 (21‐23) in the northern (southern) hemisphere. During most of the sub‐Alfvénic interval, reconnection mapping to midnight in the polar cap generates relatively little new magnetospheric flux.

A multivariate extension of the Erdős–Taylor theorem

AbstractThe Erdős–Taylor theorem (Acta Math Acad Sci Hungar, 1960) states that if $$\textsf{L}_N$$ L N is the local time at zero, up to time 2N, of a two-dimensional simple, symmetric random walk, then $$\tfrac{\pi }{\log N} \,\textsf{L}_N$$ π log N L N converges in distribution to an exponential random variable with parameter one. This can be equivalently stated in terms of the total collision time of two independent simple random walks on the plane. More precisely, if $$\textsf{L}_N^{(1,2)}=\sum _{n=1}^N \mathbb {1}_{\{S_n^{(1)}= S_n^{(2)}\}}$$ L N ( 1 , 2 ) = ∑ n = 1 N 1 { S n ( 1 ) = S n ( 2 ) } , then $$\tfrac{\pi }{\log N}\, \textsf{L}^{(1,2)}_N$$ π log N L N ( 1 , 2 ) converges in distribution to an exponential random variable of parameter one. We prove that for every $$h \geqslant 3$$ h ⩾ 3 , the family $$ \big \{ \frac{\pi }{\log N} \,\textsf{L}_N^{(i,j)} \big \}_{1\leqslant i<j\leqslant h}$$ { π log N L N ( i , j ) } 1 ⩽ i < j ⩽ h , of logarithmically rescaled, two-body collision local times between h independent simple, symmetric random walks on the plane converges jointly to a vector of independent exponential random variables with parameter one, thus providing a multivariate version of the Erdős–Taylor theorem. We also discuss connections to directed polymers in random environments.