Coherent Map Research Articles

Sensitivity of Bayesian 21 cm power spectrum estimation to foreground model errors

Abstract Power spectrum estimators are an important tool in efforts to detect the 21 cm brightness temperature fluctuations from neutral hydrogen at early times. An initial detection will likely be statistical in nature, meaning that it will not be possible to make a coherent map of the brightness temperature fluctuations; instead, only their variance will be measured against a background of noise and residual systematic effects. Optimal Quadratic Estimator (OQE)-based methods often apply an inverse covariance weighting to the data. However, inaccurate covariance modelling can lead to reduced sensitivity and, in some cases, severe signal loss. We recently proposed a Bayesian method to jointly estimate the 21 cm fluctuations, their power spectrum, and foreground emission. Instead of requiring a fixed a priori estimate of the covariance, we estimate the covariance as part of the inference. Choices of parametrization, particularly of the foregrounds, are subject to model errors and could lead to biases and other ill effects if not properly controlled. In this paper, we investigate the effects of inaccurate foreground models on 21 cm power spectrum recovery. Using simulated visibilities, we find that, even in the most extreme scenarios tested, our approach is capable of recovering 21 cm delay power spectrum estimates consistent with a known input signal for delays ≳ 300 ns (∼88% of the available Fourier modes). This is true even when using foreground models derived from modified foreground catalogs containing spatial and spectral perturbations at the quoted level of uncertainty on our foreground catalogs.

An air quality and boundary layer dynamics analysis of the Los Angeles basin area during the Southwest Urban NOx and VOCs Experiment (SUNVEx)

Abstract. The NOAA Chemical Sciences Laboratory (CSL) conducted the Southwest Urban NOx and VOCs Experiment (SUNVEx) to study emissions and the role of boundary layer (BL) dynamics and sea-breeze (SB) transitions in the evolution of coastal air quality. The study presented utilizes remote sensing and in situ observations in Pasadena, California. Separate analyses are conducted on the synoptic conditions during ozone (O3) exceedance (>70 ppb) and non-exceedance (<70 ppb) days, as well as the fine-structure variability of in situ chemistry measurements during BL growth and SB transitions. Diurnal analyses spanning August 2021 revealed a markedly different wind direction during evenings preceding O3 exceedance (northerly) versus non-exceedance (easterly) days. Increased O3 occurred simultaneously with warmer and drier conditions, a reduction in winds, and an increase in volatile organic compounds (VOCs) and fine particulate matter (PM2.5). While the average BL height was lower and surface pressure was higher, the day-to-day variability of these quantities led to an overall weak statistical relationship. Investigations focused on the fine-structure variability of in situ chemistry measurements superimposed on background trends were conducted using a novel multivariate spectral coherence mapping (MSCM) technique that combined the spectral structure of two or more independent measurements through a wavelet analysis as reported by maximum-normalized scaleograms. A case study was chosen to illustrate the MSCM technique, where the dominant peaks in scaleograms were identified and compared to BL height during the growth phase. The temporal widths of peaks (τmax) derived from VOC and nitrogen oxide (NOx) scaleograms, as well as scaleograms combining VOCs, NOx, and variations in BL height, indicated a broadening with respect to time as the BL increased in depth. A separate section focused on comparisons between τmax and BL height during August 2021 revealed uncorrelated or weakly correlated scatter, except in the case of VOCs when really large τmax and relatively deep BL heights were ignored. Instances of large τmax and relatively deep BL heights occurred near sunrise and as onshore flow entered Pasadena, respectively. Wind transitions likely influenced both the dynamical evolution of the BL and tracer advection and thus offer additional challenges when separating factors contributing to the fine structure. Other insights gained from this work include observations of descending wind jets from the San Gabriel Mountains that were not resolved by the High-Resolution Rapid Refresh (HRRR) model and the derivation of intrinsic properties of oscillations observed in NOx and O3 during the interaction between an SB and enhanced winds above the BL that flowed in opposition to the SB.

A Priori Estimation of Radar Satellite Interferometry’s Sensitivity for Landslide Monitoring in the Italian Emilia-Romagna Region

The InSAR technique is known to be a powerful tool for precise monitoring of wide areas in terms of displacements. It is conceivable to also use this technique to monitor landslide areas, but geometrical distortions due to ground morphology and land cover could make InSAR processing ineffective for such applications. Because of the computational burden of InSAR processing, it is important to have preliminary knowledge about the possible suitability of the technique for the inspected area before acquiring and processing the data. This paper aims to perform a preliminary analysis of the InSAR sensitivity for the specific case of landslide monitoring. A new approach is proposed considering aspects specific to landslide displacements, which are basically tangent to the slope direction. Pre-processed coherence maps were used to account for the impact of land cover. The whole analysis can be carried out without acquiring cumbersome SAR datasets and can be used as a preliminary step. The Italian Emilia-Romagna region has been considered as the study area, with landslide areas accounting for more than 12% of its territory. The outcomes show that the inspected area has favourable morphological conditions, mainly thanks to its mild slopes and the limited number of landslides facing north, but the land cover has a strong negative impact on the InSAR sensitivity. Nevertheless, 7.5% of the landslide areas have promising conditions for monitoring using radar interferometry.

The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks

Thin pancake-like neuronal networks cultured on top of a planar microelectrode array have been extensively tried out in neuroengineering, as a substrate for the mobile robot’s control unit, i.e., as a cyborg’s brain. Most of these attempts failed due to intricate self-organizing dynamics in the neuronal systems. In particular, the networks may exhibit an emergent spatial map of steady nucleation sites (“n-sites”) of spontaneous population spikes. Being unpredictable and independent of the surface electrode locations, the n-sites drastically change local ability of the network to generate spikes. Here, using a spiking neuronal network model with generative spatially-embedded connectome, we systematically show in simulations that the number, location, and relative activity of spontaneously formed n-sites (“the vitals”) crucially depend on the samplings of three distributions: (1) the network distribution of neuronal excitability, (2) the distribution of connections between neurons of the network, and (3) the distribution of maximal amplitudes of a single synaptic current pulse. Moreover, blocking the dynamics of a small fraction (about 4%) of non-pacemaker neurons having the highest excitability was enough to completely suppress the occurrence of population spikes and their n-sites. This key result is explained theoretically. Remarkably, the n-sites occur taking into account only short-term synaptic plasticity, i.e., without a Hebbian-type plasticity. As the spiking network model used in this study is strictly deterministic, all simulation results can be accurately reproduced. The model, which has already demonstrated a very high richness-to-complexity ratio, can also be directly extended into the three-dimensional case, e.g., for targeting peculiarities of spiking dynamics in cerebral (or brain) organoids. We recommend the model as an excellent illustrative tool for teaching network-level computational neuroscience, complementing a few benchmark models.

Integration of Large Multielement Geochemical, Aeromagnetic, and Gravity Data to Geologically Map a Largely Covered Area: A Case Study from the Central African Copperbelt in Northern Zambia

Abstract This study provides a method to map lithology, stratigraphy, and structures in areas with limited outcrop using mineral exploration data from multielement soil geochemical surveys, airborne and ground geophysical surveys, and drill hole data sourced from multiple exploration companies and campaigns. The 45- by 50-km study area is located in the southern portion of the Congolese Copperbelt, where the regional geology, structure, and overall basin architecture were not well understood, partly due to thick saprolite cover. The results demonstrate that the integration of such data sets allows the creation of a geologically coherent map, which can then be used to investigate basin architecture and identify basin-forming structures.

Regional wood chip quality parameters decomposition and price linkage with impact on Polish energy sustainability: Time frequency analysis between 2013 and 2019

The study aims to analyze and decompose the qualitative parameters of wood chips in Poland. The European Green Deal brings the new framework to support sustainability and elimination of emissions. The Wavelet coherence and Wavelet Discrete Decomposition are used for determination of relations among significant qualitative parameters. Thus, the possible uses are discussed. For the obvious relationship between moisture and calorific value there is evidence of strong correlation. The behaviour of these interrelations are different at frequencies in the long and short time. The wood chip price is inter-transmitter from moisture parameter to calorific value in a positive (in-phase) relationship. At both low and high frequencies there is evidence that the variables of moisture and calorific value are highly correlated. The transient effect of linkage is presented at values between 0.1 and 0.3 in coherence map. The empirical findings provide implication for local producers and policymakers.

The value of ripple mapping in the age of coherent mapping in scar-related atrial tachycardia.

An accurate display of scar-related atrial tachycardia (ATs) is a key determinant of ablation success. The efficacy of ripple mapping (RM) in identifying the mechanism and critical isthmus of scar-related ATs during coherent mapping is unknown. A total of 97 patients with complex ATs who underwent radiofrequency catheter ablation at our center between October 2018 and September 2022 were included. ATs was mapped using a multielectrode mapping catheter on the CARTO3v7 CONFIDENCE module. Coherent and RM were used to identify the reentrant circuit. The mechanisms of 128 ATs were analyzed retrospectively (84 anatomic-reentrant ATs and 44 non-anatomic reentrant ATs). The median AT cycle length was 264±25ms. The correct diagnosis was achieved in 83 ATs (68%) using only coherent mapping. Through coherent mapping plus RM, 114 ATs (84.2%) were correctly diagnosed (68% vs. 89%, p=.019). In non-anatomical reentrant ATs, 81% of the diagnostic rate was achieved by reviewing both coherent and ripple mapping compared to reviewing coherent mapping alone (81% vs. 52%, p=.03). Reviewing coherent mapping and ripple mapping showed a higher diagnostic rate in patients who underwent cardiac surgery than those with Coherent mapping alone (64% vs. 88%, p=.04). Coherent mapping combined with RM was superior to coherent mapping alone in identifying the mechanism of scar-related ATs post-cardiac surgery and non-anatomic reentrant ATs.

Sentinel Lymph Node Mapping by Retroperitoneal vNOTES for Uterus-Confined Malignancies: A Standardized 10-Step Approach.

(1) Background: Sentinel lymph node (SLN) mapping represents an accurate and feasible technique for the surgical staging of endometrial and cervical cancer. This is commonly performed by conventional laparoscopy or robotic-assisted laparoscopy, but in recent years, a new retroperitoneal transvaginal natural orifice transluminal endoscopic surgery (vNOTES) approach has been described and developed by Jan Baekelandt. This technique provides easy visualization of lymphatic afferent vessels and pelvic lymph nodes, early SLN assessment, and a coherent mapping methodology following the lymphatic flow from caudal to cranial. However, only a few publications have reported it. Following the IDEAL (Idea Development Exploration Assessment Long-term follow-up) framework, research concerning this technique is in Stage 2a, with only small case series as evidence of its feasibility. Its standardized description appears necessary to provide the surgical homogeneity required to move further. (2) Methods: Description of a standardized approach for retroperitoneal pelvic SLN mapping by vNOTES. (3) Results: We describe a 10-step approach to successfully perform retroperitoneal vNOTES SLN mapping, including pre-, intra-, and postoperative management. (4) Conclusions: This IDEAL Stage 2a study could help other surgeons approach this new technique, and it proposes a common methodology necessary for evolving through future IDEAL Stage 2b (multi-center studies) and Stage 3 (randomized controlled trials) studies.

Significance of Coherent Mapping in unveiling slow conduction zones of ventricular tachycardia substrate in ischemic cardiomyopathy

Abstract Introduction Ventricular tachycardia (VT) presents a formidable challenge, particularly in cases with extensive myocardial scar tissue, complicating critical ablation site identification. Prolonged interventions not only extend procedural durations but also heighten the risk of complications. This study aimed to assess the efficacy of coherent mapping techniques in precisely locating regions of slow conduction within scar tissue and explored potential correlations with electrophysiological markers in scar-related VT. Methods Seventeen patients (mean age: 61.6 ± 9.2 years, mean EF: 28 ± 9%) with ischemic cardiomyopathy (ICM) and frequent implantable cardioverter-defibrillator (ICD) shocks underwent high-density (>2000 points) left ventricular (LV) substrate mapping (15 endo, 2 epicardial) during sinus or right ventricular (RV) pacing and ablation. Coherent mapping tool was utilized for the identification of slow conduction, demonstrated by vector thickening. Bipolar low voltage areas (LVAs) below 0.5 mV were defined as dense scar, and bipolar voltage between 0.5 and 1.5 mV was defined as the border zone (Figure, panel A). Late potentials (LPs) and local abnormal ventricular activities (LAVA) were manually identified and tagged. Isochronal late activation mapping (ILAM) was also performed to elucidate the functional properties of the substrate (Figure, Panel B). Results LPs and LAVA were identified in all cases, with a mean number of LPs being 10.0 ± 7.1. Of these, 14/17 cases had LPs located in dense scar, while 4/17 cases had LPs in the border zone. The mean area of LAVA was 9.9 ± 7.7 mm², located in dense scar in 6/17 cases and in the border zone in 15/17 cases. Average deceleration zones (DZ, >3 isochrones in 1 cm radius) identified by ILAM was 2 ± 1. Coherent mapping consistently identified slow conduction zones adjacent to LVA in all cases, with these coherent map-based slow conduction zones (CM-SCZ) located in dense scar in 3/17 cases and in the border zone in 14/17 cases. The distance of CM-SCZ to LPs was 12.6 ± 13.9 mm (in 4 cases, LPs were recorded on the spot), and the distance to LAVAs was 18.8 ± 13.7 mm (in 2 cases, LAVAs were recorded on the spot). CM-SCZ was colocalized with DZ in 14/17 of the patients. Ablation lesions covered CM-SCZ in 10/17 cases. Over a mean follow-up duration of 11 ± 6.5 months, 4 patients experienced VT recurrence, with 3 having no ablation lesions covering CM-SCZ, and 2 patients died due to pump failure. Conclusion This study underscores the significance of coherent mapping in refining the understanding of VT substrate in ICM. Identifying and ablating CM-SCZ during substrate-based mapping may provide a potential additional benefit for VT ablation. Nevertheless, larger studies are needed to clarify the prognostic significance and validate the clinical benefits of this approach.Figure 1

D.5 Low density scalp electrical source imaging of the ictal onset zone network using source coherence maps

Background: This study investigates the utility of low-density scalp electrical source imaging (LD-ESI) of the Ictal Onset Zone (IOZ) and interictal spike ripple high frequency oscillation (ISRHFO) networks using Source Coherence Maps (SCM) in the surgical evaluation of children with medically refractory epilepsy. Invasive intracranial monitoring, the gold standard for determining epileptogenic zones, has limited spatial sampling. SCM presents a promising new non-invasive diagnostic technique. Methods: This was a retrospective review of 11 patients who underwent focal resections. SCMs were generated using Standardized Low Resolution Electromagnetic Tomography (sLORETA). SCM concordance to resection margins was assessed, noting outcomes at 3 years. Results: For 7/11 cases, ictal SCMs included the resection, and 5/7 achieved seizure freedom, indicating inclusion of the epileptogenic zone. For the 2/7 not seizure-free, the IOZ networks on the SCMs extended beyond resection margins, suggesting the epileptogenic zone also extended beyond the resection. Interictal spike ripple ESI and ISRHFO SCM were performed for 7/11, with 3/7 included in the resection and all 3 seizure-free. Conclusions: These findings may support LD-ESI of the IOZ and ISRHFO network using SCM as promising methods complementary to ictal and interictal ESI in pediatric epilepsy surgical workup, guiding electrode placement for intracranial monitoring to identify the epileptogenic zone.

All-optical spin access via a cavity-broadened optical transition in on-chip hybrid quantum photonics

Hybrid quantum photonic systems connect classical photonics to the quantum world and promise to deliver efficient light-matter quantum interfaces while leveraging the advantages of both, the classical and the quantum, subsystems. However, combining efficient, scalable photonics and solid-state quantum systems with desirable optical and spin properties remains a formidable challenge. In particular, the access to individual spin states and coherent mapping to photons remains unsolved for hybrid systems. In this paper, we demonstrate all-optical initialization and readout of the electron spin of a negatively charged silicon-vacancy center in a nanodiamond coupled to a silicon nitride photonic crystal cavity. We characterize relevant parameters of the coupled emitter-cavity system and determine the silicon-vacancy center’s spin-relaxation and spin-decoherence rate. Our results mark a key step towards the realization of a hybrid spin-photon interface based on silicon nitride photonics and the silicon-vacancy center’s electron spin in nanodiamonds with potential use for quantum networks, quantum communication, and distributed quantum computation. Published by the American Physical Society 2024

Detecting and Monitoring Artisanal Mining Operations in Semi-Arid Terrain Using Multitemporal SAR Data for InSAR Coherence Estimation and Unsupervised Classification

Abstract. The impact of artisanal mining in sub-Saharan Africa and other developing countries are often huge as they leave trails of environmental and socio-economic effects on the people and the environment. 123 Multi-temporal SAR data acquired between 2019 and 2023 was used. SARPROZ was used to co-register the images and other preprocessing steps like radiometric and geometric correction to transform the images from SAR coordinates to geographic coordinates after generating all the interferograms. A stack of the 122 coherence map was created. Unsupervised classification was implemented on the stack. Principal component analysis of dimensionality reductions method yielded a far better result than the other unsupervised cluster methods attempted, it showed a very high classification accuracy of the terrain. The principal component analysis worked by computing the covariance matrix of the stacked coherence map then performed eigen-decomposition on it to yield eigenvectors and eigenvalues, The eigenvectors corresponding to the largest eigenvalues represent the principal components. These principal components capture the directions of maximum variance, and the eigenvectors provides a reduced-dimensional representation of the image stack which is then used to reconstruct an approximation of the original image that captures the essential features of the original SAR data. Backscatter intensity of the SAR images processed for this study period for unsupervised change detection and land cover classification, delineated the different features and classes based on long term coherence values.

Coherence mapping to identify the intermediates of multi-channel dissociative ionization

Identifying the short-lived intermediates and reaction mechanisms of multi-channel radical cation fragmentation processes remains a current and important challenge to understanding and predicting mass spectra. We find that coherent oscillations in the femtosecond time-dependent yields of several product ions following ultrafast strong-field ionization represent spectroscopic signatures that elucidate their mechanism of formation and identify the intermediate(s) they originate from. Experiments on endo-dicyclopentadiene show that vibrational frequencies from various intermediates are mapped onto their resulting products. Aided by ab initio methods, we identify the vibrational modes of both the cleaved and intact molecular ion intermediates. These results confirm stepwise and concerted fragmentation pathways of the dicyclopentadiene ion. This study highlights the power of tracking the femtosecond dynamics of all product ions simultaneously and sheds further light onto one of the fundamental reaction mechanisms in mass spectrometry, the retro-Diels Alder reaction.

Learning Ground Displacement Signals Directly from InSAR-Wrapped Interferograms.

Monitoring ground displacements identifies potential geohazard risks early before they cause critical damage. Interferometric synthetic aperture radar (InSAR) is one of the techniques that can monitor these displacements with sub-millimeter accuracy. However, using the InSAR technique is challenging due to the need for high expertise, large data volumes, and other complexities. Accordingly, the development of an automated system to indicate ground displacements directly from the wrapped interferograms and coherence maps could be highly advantageous. Here, we compare different machine learning algorithms to evaluate the feasibility of achieving this objective. The inputs for the implemented machine learning models were pixels selected from the filtered-wrapped interferograms of Sentinel-1, using a coherence threshold. The outputs were the same pixels labeled as fast positive, positive, fast negative, negative, and undefined movements. These labels were assigned based on the velocity values of the measurement points located within the pixels. We used the Parallel Small Baseline Subset service of the European Space Agency's GeoHazards Exploitation Platform to create the necessary interferograms, coherence, and deformation velocity maps. Subsequently, we applied a high-pass filter to the wrapped interferograms to separate the displacement signal from the atmospheric errors. We successfully identified the patterns associated with slow and fast movements by discerning the unique distributions within the matrices representing each movement class. The experiments included three case studies (from Italy, Portugal, and the United States), noted for their high sensitivity to landslides. We found that the Cosine K-nearest neighbor model achieved the best test accuracy. It is important to note that the test sets were not merely hidden parts of the training set within the same region but also included adjacent areas. We further improved the performance with pseudo-labeling, an approach aimed at evaluating the generalizability and robustness of the trained model beyond its immediate training environment. The lowest test accuracy achieved by the implemented algorithm was 80.1%. Furthermore, we used ArcGIS Pro 3.3 to compare the ground truth with the predictions to visualize the results better. The comparison aimed to explore indications of displacements affecting the main roads in the studied area.

Towards a more robust non-invasive assessment of functional connectivity

Abstract Non-invasive evaluation of functional connectivity, based on source-reconstructed estimates of phase-difference-based metrics, is notoriously non-robust. This is due to a combination of factors, ranging from a misspecification of seed regions to suboptimal baseline assumptions, and residual signal leakage. In this work, we propose a new analysis scheme of source-level phase-difference-based connectivity, which is aimed at optimizing the detection of interacting brain regions. Our approach is based on the combined use of sensor subsampling and dual-source beamformer estimation of all-to-all connectivity on a prespecified dipolar grid. First, a pairwise two-dipole model, to account for reciprocal leakage in the estimation of the localized signals, allows for a usable approximation of the pairwise bias in connectivity due to residual leakage of “third party” noise. Secondly, using sensor array subsampling, the recreation of multiple connectivity maps using different subsets of sensors allows for the identification of consistent spatially localized peaks in the 6-dimensional connectivity maps, indicative of true brain region interactions. These steps are combined with the subtraction of null coherence estimates to obtain the final coherence maps. With extensive simulations, we compared different analysis schemes for their detection rate of connected dipoles, as a function of signal-to-noise ratio, phase difference, and connection strength. We demonstrate superiority of the proposed analysis scheme in comparison to single-dipole models, or an approach that discards the zero phase difference component of the connectivity. We conclude that the proposed pipeline allows for a more robust identification of functional connectivity in experimental data, opening up new possibilities to study brain networks with mechanistically inspired connectivity measures in cognition and in the clinic.

Model of Coupled Quantum Memristors Based on a Single Trapped 171Yb+ Ion

A method for the joint application of two coupled quantum memristors on a single 171Yb+ ion by using optical and radio-frequency transitions induced by resonant laser fields is proposed. As a result, coherent mapping of the input quantum state to the output state is created. The proposed method makes it possible to use only one ion to control statistical weights in two-layer perceptrons.

Mapping Subcortico-Cortical Coupling-A Comparison of Thalamic and Subthalamic Oscillations.

The ventral intermediate nucleus of the thalamus (VIM) is an effective target for deep brain stimulation in tremor patients. Despite its therapeutic importance, its oscillatory coupling to cortical areas has rarely been investigated in humans. The objective of this study was to identify the cortical areas coupled to the VIM in patients with essential tremor. We combined resting-state magnetoencephalography with local field potential recordings from the VIM of 19 essential tremor patients. Whole-brain maps of VIM-cortex coherence in several frequency bands were constructed using beamforming and compared with corresponding maps of subthalamic nucleus (STN) coherence based on data from 19 patients with Parkinson's disease. In addition, we computed spectral Granger causality. The topographies of VIM-cortex and STN-cortex coherence were very similar overall but differed quantitatively. Both nuclei were coupled to the ipsilateral sensorimotor cortex in the high-beta band; to the sensorimotor cortex, brainstem, and cerebellum in the low-beta band; and to the temporal cortex, brainstem, and cerebellum in the alpha band. High-beta coherence to sensorimotor cortex was stronger for the STN (P = 0.014), whereas low-beta coherence to the brainstem was stronger for the VIM (P = 0.017). Although the STN was driven by cortical activity in the high-beta band, the VIM led thesensorimotor cortex in the alpha band. Thalamo-cortical coupling is spatially and spectrally organized. The overall similar topographies of VIM-cortex and STN-cortex coherence suggest that functional connections are not necessarily unique to one subcortical structure but might reflect larger frequency-specific networks involving VIM and STN to a different degree. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A Comprehensive Stress Drop Map From Trench to Depth in the Northern Chilean Subduction Zone

AbstractWe compute stress drops for earthquakes in Northern Chile recorded between 2007 and 2021. By applying two analysis techniques, (a) the spectral ratio (SR) method and (b) the spectral decomposition (SDC) method, a stress drop map for the subduction zone consisting of 51,510 stress drop values is produced. We build an extended set of empirical Green’s functions (EGF) for the SR method by systematic template matching. Outputs are used to compare with results from the SDC approach, where we apply cell‐wise obtained global EGF's to compensate for the structural heterogeneity of the subduction zone. We find a good consistency of results of the two methods. The increased spatial coverage and quantity of stress drop estimates from the SDC method facilitate a consistent stress drop mapping of the different seismotectonic domains. Albeit only small differences of median stress drop, strike‐perpendicular depth sections clearly reveal systematic variations, with earthquakes at different seismotectonic locations exhibiting distinct values. In particular, interface seismicity is characterized by the lowest observed median value, whereas upper plate earthquakes show noticeably higher stress drop values. Intermediate depth earthquakes show comparatively high average stress drop and a rather strong depth‐dependent increase of median stress drop. Additionally, we observe spatio‐temporal variability of stress drops related to the occurrence of the two megathrust earthquakes in the study region. The presented study is the first coherent large scale 3D stress drop mapping of the Northern Chilean subduction zone. It provides an important component for further detailed analysis of the physics of earthquake ruptures.

Wobbling motion for a triaxial rotor plus a single quasiparticle*

Abstract Wobbling motion in a system comprising a triaxial rotor and a single quasiparticle is studied employing the particle-rotor model. The energy spectra, wobbling frequencies, electromagnetic transition probabilities, g-factors, angular momentum components, spin coherent state maps, and static quadrupole moments are investigated. These investigations were conducted with regard to the Fermi surface transitioning from the lowest orbit to the highest one. As the Fermi surface increases, notable transformations occur in the wobbling mode. Initially, the mode exhibits a transverse revolution around the short axis of the nucleus. However, as the Fermi surface continues to increase, the mode gradually shifts to a longitudinal revolution around the intermediate axis. Eventually, it transitions to a transverse revolution around the long axis. Notably, the stability of the long axis transverse mode diminishes relative to its counterpart along the short axis as the total angular momentum increases at .

Myeloarchitectonic maps of the human cerebral cortex registered to surface and sections of a standard atlas brain.

C. and O. Vogt had set up a research program with the aim of establishing a detailed cartography of the medullary fiber distribution of the human brain. As part of this program, around 200 cortical fields were differentiated based on their myeloarchitectural characteristics and mapped with regard to their exact location in the isocortex. The typical features were graphically documented and classified by a sophisticated linguistic coding. Their results have only recently received adequate attention and applications. The reasons for the revival of this spectrum of their research include interest in the myeloarchitecture of the cortex as a differentiating feature of the cortex architecture and function, as well as the importance for advanced imaging methodologies, particularly tractography and molecular imaging. Here, we describe our approach to exploit the original work of the Vogts and their co-workers to construct a myeloarchitectonic map that is referenced to the Atlas of the Human Brain (AHB) in standard space. We developed a semi-automatic pipeline for processing and integrating the various original maps into a single coherent map. To optimize the precision of the registration between the published maps and the AHB, we augmented the maps with topographic landmarks of the brains that were originally analyzed. Registration of all maps into the AHB opened several possibilities. First, for the majority of the fields, multiple maps from different authors are available, which allows for sophisticated statistical integration, for example, unification with a label-fusion technique. Second, each field in the myeloarchitectonic surface map can be visualized on the myelin-stained cross-section of the AHB at the best possible correspondence. The features of each field can be correlated with the fiber-stained cross-sections in the AHB and with the extensive published materials from the Vogt school and, if necessary, corrected. Third, mapping to the AHB allows the relationship between fiber characteristics of the cortex and the subcortex to be examined. Fourth, the cytoarchitectonic maps from Brodmann and von Economo and Koskinas, which are also registered to the AHB, can be compared. This option allows the study of the correspondence between cyto- and myeloarchitecture in each field. Finally, by using our "stripe" technology - where any other feature registered to the same space can be directly compared owing to the linear and parallel representation of the correlated cortex segments - this map becomes part of a multidimensional co-registration platform.