Temporal Phase Coherence Research Articles

Challenges and Opportunities of Sentinel-1 InSAR for Transport Infrastructure Monitoring

Monitoring displacement at transport infrastructure using Sentinel‑1 Interferometric Synthetic Aperture Radar (InSAR) faces challenges due to the sensor’s medium spatial resolution, which limits the pixel coverage over the infrastructure. Therefore, carefully selecting coherent pixels is crucial to achieve a high density of reliable measurement points and to minimize noisy observations. This study evaluates the effectiveness of various pixel selection methods for displacement monitoring within transport infrastructures. We employ a two-step InSAR time series processing approach. First, high-quality first-order pixels are selected using temporal phase coherence (TPC) to estimate and correct atmospheric contributions. Then, a combination of different pixel selection methods is applied to identify coherent second-order pixels for displacement analysis. These methods include amplitude dispersion index (ADI), TPC, phase linking coherence (PLC), and top eigenvalue percentage (TEP), targeting both point-like scatterer (PS) and distributed scatterer (DS) pixels. Experiments are conducted in two case studies: one in Germany, characterized by dense vegetation, and one in Spain, with sparse vegetation. In Germany, the density of measurement points was approximately 30 points/km², with the longest segment of the infrastructure without any coherent pixels being 2.8 km. In Spain, the density of measurement points exceeded 500 points/km², with the longest section without coherent pixels being 700 meters. The results indicate that despite the challenges posed by medium-resolution data, the sensor is capable of providing adequate measurement points when suitable pixel selection methods are employed. However, careful consideration is necessary to exclude noisy pixels from the analysis. The findings highlight the importance of choosing a proper method tailored to infrastructure characteristics. Specifically, combining TPC and PLC methods offers a complementary set of pixels suitable for displacement measurements, whereas ADI and TEP are less effective in this context. This study demonstrates the potential of Sentinel‑1 InSAR for capturing both regional-scale and localized displacements at transport infrastructure.

Conditional Dynamics in Heterodyne Detection of Superradiant Lasing with Incoherently Pumped Atoms.

In this Letter, we use quantum trajectory theory to simulate heterodyne detection of narrow bandwidth superradiant lasing from an incoherently excited atomic ensemble. To this end, we describe the system dynamics and account for stochastic measurement backaction by second-order mean-field theory. Our simulations show how heterodyne measurements break the phase symmetry, and initiate the atomic coherence with a random phase and a long temporal phase coherence. More importantly, our theory allows direct simulation of experimental procedures for extraction of spectral information which do not lend themselves to evaluation with the quantum regression theorem.

Enhancing Landslide Prediction Through Advanced Transformer-Based Models: Integrating SAR Imagery and Environmental Data

Landslides, a significant natural hazard driven predominantly by rainfall infiltration, pose a continuous threat to the terrain, buildings, and ecosystem of Caiazzo, located in southern Italy (Caserta). This research undertakes a novel approach to predict and understand the complex patterns of landslide deformations in this region. Our study leverages the advanced capabilities of COSMO-SkyMed satellite imagery, integrating a comprehensive dataset that includes factors such as elevation, slope, Topographic Wetness Index, Stream Power Index, geology, flow direction, curvature, Normalized Difference Vegetation Index, and several other relevant indices. We employ Transformer-based models, renowned for their effectiveness in capturing long-range dependencies within sequential data. The Transformer models in our study are adept at analyzing the temporal sequences of environmental factors and their intricate interactions, thereby offering a more nuanced understanding of the temporal patterns leading to landslides. These Transformer models are designed to process the entire sequence of satellite data obtained by the Coherent Pixels - Temporal Phase Coherence within the SUBSOFT package to ensure data integrity and precision, encompassing 132 images in ascending geometry and 143 in descending geometry, spanning from 2013 to 2021. By doing so, they efficiently identify critical patterns and dependencies over time, such as the interplay between rainfall events and subsequent soil and vegetation changes. The models are fine-tuned to our specific dataset, ensuring high precision and accuracy in landslide deformation prediction. Our evaluation metrics, including Mean Absolute Error, Root Mean Square Error, and R^2 score, demonstrate the superior performance of the Transformer-based approach, with significant improvements over the conventional Deep Learning model. The visual correlation of our predictions with actual landslide occurrences further corroborates the effectiveness of this method. This transformative approach not only enhances our understanding and predictive capability for landslides in Caiazzo but also sets a benchmark for landslide prediction in geologically vulnerable regions worldwide.

High-Quality Pixel Selection Applied for Natural Scenes in GB-SAR Interferometry

Phase analysis based on high-quality pixel (HQP) is crucial to ensure the measurement accuracy of ground-based SAR (GB-SAR). The amplitude dispersion (ADI) criterion has been widely applied to identify pixels with high amplitude stability, i.e., permanent scatterers (PSs), which typically are point-wise scatterers such as stones or man-made structures. However, the PS number in natural scenes is few and limits the GB-SAR applications. This paper proposes an improved method to take HQP selection applied for natural scenes in GB-SAR interferometry. In order to increase the spatial density of HQP for phase measurement, three types of HQPs including PS, quasi-permanent scatter (QPS), and distributed scatter (DS), are selected with different criteria. The ADI method is firstly utilized to take PS selection. To select those pixels with high phase stability but moderate amplitude stability, the temporal phase coherence (TPC) is defined. Those pixels with moderate ADI values and high TPC are selected as QPSs. Then the feasibility of the DS technique is explored. To validate the feasibility of the proposed method, 2370 GB-SAR images of a natural slope are processed. Experimental results prove that the HQP number could be significantly increased while slightly sacrificing phase quality.

Model-Free Characterization of SAR MTI Time Series

Multitemporal interferometric synthetic aperture radar (MTI) displacement time series are usually characterized by the model-dependent temporal phase coherence as a quality measure. Additional tests have to be performed to recognize other “interesting” but nonmodeled trends, and several automated approaches to this task have been proposed to date. We introduce here the fuzzy entropy ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_{E}$ </tex-math></inline-formula> ), a measure introduced in medical data analysis, as a viable parameter to characterize MTI time series. Being a measure of disorder in a time series, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_{E}$ </tex-math></inline-formula> exhibits homogeneously low values for a large class of displacement models, such as seasonal, parabolic, or piecewise linear signals, while increasing for more chaotic trends, dominated by noise. It appears therefore suited as a discriminative parameter to isolate meaningful MTI time series within large data sets, without specifying a predefined model. The calculation of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_{E}$ </tex-math></inline-formula> has low computational cost and can thus be easily performed as a prescreening filter. In this letter, results over simulated data and some examples on a real data set are shown with interesting performances which hint to possible large-scale implementations.

Individual Differences in Multisensory Interactions:The Influence of Temporal Phase Coherence and Auditory Salience on Visual Contrast Sensitivity.

While previous research has investigated key factors contributing to multisensory integration in isolation, relatively little is known regarding how these factors interact, especially when considering the enhancement of visual contrast sensitivity by a task-irrelevant sound. Here we explored how auditory stimulus properties, namely salience and temporal phase coherence in relation to the visual target, jointly affect the extent to which a sound can enhance visual contrast sensitivity. Visual contrast sensitivity was measured by a psychophysical task, where human adult participants reported the location of a visual Gabor pattern presented at various contrast levels. We expected the most enhanced contrast sensitivity, the lowest contrast threshold, when the visual stimulus was accompanied by a task-irrelevant sound, weak in auditory salience, modulated in-phase with the visual stimulus (strong temporal phase coherence). Our expectations were confirmed, but only if we accounted for individual differences in optimal auditory salience level to induce maximal multisensory enhancement effects. Our findings highlight the importance of interactions between temporal phase coherence and stimulus effectiveness in determining the strength of multisensory enhancement of visual contrast as well as highlighting the importance of accounting for individual differences.

A Temporal Phase Coherence Estimation Algorithm and Its Application on DInSAR Pixel Selection

Pixel selection is a crucial step of all advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques that have a direct impact on the quality of the final DInSAR products. In this paper, a full-resolution phase quality estimator, i.e., the temporal phase coherence (TPC), is proposed for DInSAR pixel selection. The method is able to work with both distributed scatterers (DSs) and permanent scatterers (PSs). The influence of different neighboring window sizes and types of interferograms combinations [both the single-master (SM) and the multi-master (MM)] on TPC has been studied. The relationship between TPC and phase standard deviation (STD) of the selected pixels has also been derived. Together with the classical coherence and amplitude dispersion methods, the TPC pixel selection algorithm has been tested on 37 VV polarization Radarsat-2 images of Barcelona Airport. Results show the feasibility and effectiveness of TPC pixel selection algorithm. Besides obvious improvements in the number of selected pixels, the new method shows some other advantages comparing with the other classical two. The proposed pixel selection algorithm, which presents an affordable computational cost, is easy to be implemented and incorporated into any advanced DInSAR processing chain for high-quality pixels' identification.

Power and phase coherence in sensorimotor mu and temporal lobe alpha components during covert and overt syllable production.

The sensorimotor dorsal stream is known to activate in both overt and covert speech production. However, overt production produces sensory consequences that are absent during covert production. Thus, the purpose of the current study is to investigate differences in dorsal stream activity between these two production conditions across the time course of utterances. Electroencephalography (EEG) was recorded from 68 channels while 23 participants overtly (Op) and covertly (Cp) produced orthographically cued bisyllabic targets. Sensorimotor mu and auditory alpha components (from anterior and posterior aspects of the dorsal stream) were identified using independent component analysis (ICA). Event-related spectral perturbation (ERSP) analyses identified changes in mu and alpha oscillatory power over time, while intercomponent phase coherence (IPC) measured anterior-posterior connectivity in the two conditions. Results showed greater beta (15-25Hz) suppression during speech planning across left and right hemisphere sensorimotor and temporal ICs for Op relative to Cp. By contrast, greater intrahemispheric beta coherence was observed for Cp compared to Op during speech planning. During execution, greater beta suppression was observed along with greater low frequency (< 10Hz) power enhancement and intrahemispheric phase coherence in Op compared to Cp. The findings implicate low frequency sensorimotor and posterior temporal phase coherence in the integration of somatosensory and acoustic feedback in overt relative to covert execution. Findings are consistent with early frontal-temporal forward models involved in planning and execution with modulations depending on whether the task goal is internal or overt syllable production.

Landslide Monitoring Using Multi-Temporal SAR Interferometry with Advanced Persistent Scatterers Identification Methods and Super High-Spatial Resolution TerraSAR-X Images

Landslides are one of the most common and dangerous threats in the world that generate considerable damage and economic losses. An efficient landslide monitoring tool is the Differential Synthetic Aperture Radar Interferometry (DInSAR) or Persistent Scatter Interferometry (PSI). However, landslides are usually located in mountainous areas and the area of interest can be partially or even heavily vegetated. The inherent temporal decorrelation that dramatically reduces the number of Persistent Scatters (PSs) of the scene limits in practice the application of this technique. Thus, it is crucial to be able to detect as much PSs as possible that can be usually embedded in decorrelated areas. High resolution imagery combined with efficient pixel selection methods can make possible the application of DInSAR techniques in landslide monitoring. In this paper, different strategies to identify PS Candidates (PSCs) have been employed together with 32 super high-spatial resolution (SHR) TerraSAR-X (TSX) images, staring-spotlight mode, to monitor the Canillo landslide (Andorra). The results show that advanced PSI strategies (i.e., the temporal sub-look coherence (TSC) and temporal phase coherence (TPC) methods) are able to obtain much more valid PSs than the classical amplitude dispersion (DA) method. In addition, the TPC method presents the best performance among all three full-resolution strategies employed. The SHR TSX data allows for obtaining much higher densities of PSs compared with a lower-spatial resolution SAR data set (Sentinel-1A in this study). Thanks to the huge amount of valid PSs obtained by the TPC method with SHR TSX images, the complexity of the structure of the Canillo landslide has been highlighted and three different slide units have been identified. The results of this study indicate that the TPC approach together with SHR SAR images can be a powerful tool to characterize displacement rates and extension of complex landslides in challenging areas.

Emergence of long-range phase coherence in nonlocal fluids of light

The emergence of long-range phase coherence among random nonlinear waves is a fascinating effect that characterizes fundamental phenomena such as the condensation of nonlinear waves and the related manifestation of superfluidity of certain turbulent flows. Here we report a previously unrecognized phenomenon of spontaneous emergence of long-range phase coherence among incoherent waves interacting through a nonlocal nonlinearity. The theory reveals that the establishment of long-range phase coherence constitutes a generic property of a conservative (Hamiltonian) system of highly nonlocal random waves that evolve in the strongly nonlinear regime. Aside from phase coherence, the field exhibits intensity fluctuations whose coherence length is shown to increase in a dramatic way during the evolution of the system. The analysis can be transposed to the temporal domain, revealing the emergence of temporal phase coherence among incoherent waves propagating in nonlinear materials featured by a noninstantaneous nonlinear response.

Spaceborne Spotlight SAR Interferometry With TerraSAR-X

Recently, synthetic aperture radar (SAR) data with 1-m resolution acquired by satellites in spotlight mode became available to the public. In this paper, we elucidate the differences between interferometric processing of strip map and of spotlight SAR data, and we outline adequate algorithms for key processing steps such as azimuth Doppler filtering. We further present first TerraSAR-X spotlight interferograms, together with an evaluation of the paraeters that are critical for interferometry. Our results indicate a very good geometric accuracy, stability, and phase fidelity of the TerraSAR-X sensor and its products. From the interferograms, we are able to determine the heights of larger buildings and millimeter-scale structural deformation in several examples. The high detail level of imaged buildings and the good temporal phase coherence of urban areas in X-band make spotlight interferometry an exciting processing technique that enables new applications such as surveying individual buildings.

Temporal interferometry: A mechanism for controlling qubit transitions during twisted rapid passage with possible application to quantum computing

In an adiabatic rapid passage experiment, the Bloch vector of a two-level system (qubit) is inverted by slowly inverting an external field to which it is coupled, and along which it is initially aligned. In twisted rapid passage, the external field is allowed to twist around its initial direction with azimuthal angle $\ensuremath{\varphi}(t)$ at the same time that it is inverted. For polynomial twist, $\ensuremath{\varphi}(t)\ensuremath{\sim}{\mathrm{Bt}}^{n}.$ We show that for $n&gt;~3,$ multiple avoided crossings can occur during the inversion of the external field, and that these crossings give rise to strong interference effects in the qubit transition probability. The transition probability is found to be a function of the twist strength B, which can be used to control the time separation of the avoided crossings, and hence the character of the interference. Constructive and destructive interference are possible. The interference effects are a consequence of the temporal phase coherence of the wave function. The ability to vary this coherence by varying the temporal separation of the avoided crossings renders twisted rapid passage with adjustable twist strength into a temporal interferometer through which qubit transitions can be greatly enhanced or suppressed. Possible application of this interference mechanism to construction of fast fault-tolerant quantum controlled-NOT and NOT gates is discussed.

ENSO as a forewarning tool of regional fire occurrence in northern Patagonia, Argentina

Composite series of ENSO indices recorded over 36 months preceding major fire years in four National Parks in northern Patagonia were compared with series of these indices for individual years over the period 1950–1996 by means of an additive temporal phase coherence index. Logistic regressions of the dichotomous variable high vs low regional fire occurrence against the coherence index gained highest significant classificatory power using an index based on SST anomaly data between January of year –3 to August of year –1. Thus, warnings of extreme fire seasons could be declared as early as 3 months before the full fire season starts (i.e. early September). A regional fire season readiness index is proposed based on the periodicity of the Southern Oscillation, strong links with climate at particular regions of the globe, and empirically derived climatic controls on fine fuel buildup and coarse fuel desiccation. This long-range alerting tool could help decision-makers prepare preventative measures to mitigate the effects of large, high intensity wildfire seasons. However, it should be used with caution given that differences in timing in the onset of ENSO events and instability in teleconnection patterns could change climatic sequences, differentially affecting fire susceptibility.

Birefringent beam splitter for intracavity mode selection in high-power multimirror lasers

The design and application of an uncoated sapphire plate that acts as both the beam splitter and the output coupler of an interferometric laser resonator are described. Output coupling is provided at one of the surfaces by p-polarized (TM) reflection near the Brewster angle, and axial-mode selection is enforced at the other surface by s-polarized (TE) reflection at the same angle of incidence. The design is discussed in the context of the phase-locked, rf linac free-electron laser, in which the coupling of adjacent optical pulses at the beam splitter induces temporal phase coherence among all the pulses in the output beam; this coherence is manifested in the frequency domain as a reduction in the number of axial modes per rf frequency interval. The Michelson and Fox-Smith resonator designs are compared, and applications to cavity dumping are discussed.

Time-dependent transport through a mesoscopic structure.

We present a general formulation of the nonlinear, time-dependent current through a small interacting region, where electron energies are changed by time-dependent voltages. An exact solution is obtained for the non-interacting case when the elastic coupling to the leads is independent of energy. Temporal phase coherence in a double-barrier tunneling structure produces ``ringing" in the response of the current to a voltage pulse, which can be observed experimentally in the dc-current by varying the pulse length in a train of voltage pulses. The nonlinear current due to an ac-bias also shows complex time-dependence.