Simultaneous Phase Research Articles

Quantitative demodulation of distributed low-frequency vibration based on phase-shifted dual-pulse phase-sensitive OTDR with direct detection.

Phase-sensitive optical time-domain reflectometry (Φ-OTDR) has been proposed for distributed vibration sensing purpose over recent years. Emerging applications, including seismic and hydroacoustic wave detection, demand accurate low-frequency vibration reconstruction capability. We propose to use the direct-detection Φ-OTDR configuration to achieve quantitative demodulation of external low-frequency vibrations by phase-shifted dual-pulse probes. Simultaneous pulsing and phase shifting modulation is realized with a single acousto-optic modulator to generate such probes, relaxing the need for an additional optical phase modulator. In the experiments, vibrations with frequency as low as 0.5 Hz are successfully reconstructed with 10 m spatial resolution and 35 dB signal-to-noise ratio. Excellent linearity and repeatability are demonstrated between the optical phase demodulation results and the applied vibration amplitudes. The proposed method is capable of quantitative demodulation of low-frequency vibrations with a cost-effective system configuration and high computation efficiency, showing potential for commercial applications of distributed seismic or hydroacoustic wave acquisition.

A theoretical study on the simultaneous vapor-liquid and chemical equilibria in a highly restricted system

In this work, the isomerization reaction of n-butane (C4(2)) to isobutane (iC4(1)) in the absence of other components is studied with the help of a model, in a relatively wide pressure range, both, under single fluid phase conditions and under vapor-liquid equilibrium conditions. In this last case the phase and chemical equilibrium are solved simultaneously. This binary system was chosen, among other considerations, because of the low number of degrees of freedom that it has, according to the phase rule for reactive systems. Such high level of restriction leads to a peculiar behavior that provides interesting insights, in particular on the simultaneous chemical and phase equilibrium. The C4(2) + iC4(1) system is represented in this work by the Soave-Redlich-Kwong equation of state coupled to quadratic mixing rules with binary interaction parameters set to zero. The required computation algorithms were developed in this work. The computed fluid phase equilibrium of this reactive system is a single univariant vapor-liquid equilibrium line. Such line ends at the only reactive vapor-liquid critical point that the system has. Some reactive isochores (or isotherms) were also computed. The obtained computation results show that for this system the conversion can be changed, under certain conditions, just by modifying the overall density, while keeping the temperature and the pressure at constant values.

Positron Annihilation Spectroscopy Study of Metallic Materials after High-Speed Cutting.

During high-speed cutting, a white layer is often produced on the machined surfaces after mechanical machining, seriously affecting the mechanical properties. These properties are related to the material structure and the defects induced by cutting. However, there is a lack of research on the atomic-scale defects of the white layer. This paper studied the influence of cutting parameters, namely the feed rate, cutting speed and cutting depth, on atomic-scale defects induced by high-speed cutting in GCr15 steel. Positron annihilation studies showed typical plastically deformed or tempered carbon steel defects with additional vacancy cluster components. The quantity of these clusters changed with cutting parameters. Furthermore, significant changes were observed in the subsurface region up to 1 µm, occurring as a result of simultaneous phase transformations, deformation and thermal impacts. The predominant accumulation of only one type of atomic-scale defect was not observed.

Amplitude and phase locking of mechanical oscillation driven by radiation pressure

Cavity optomechanical systems have been widely studied for many of their interesting properties, which can be interpreted with their linearized dynamics. Previously, the genuine nonlinear dynamics of optomechanical systems was only considered for very few phenomena such as self-induced oscillation and optomechanical chaos. Beyond the scope of those previous studies, a phenomenon of frozen mechanical oscillation irrespective of the intensity variation on the driving fields was recently discovered for an optomechanical system under two pump fields having their frequencies properly matched [He et al., Phys. Rev. A 102, 011503(R) (2020)]. Here we significantly advance the study by showing that similar phenomena can manifest under more general conditions for the external driving fields. The mechanical oscillation in such doubly driven optomechanical systems can be locked in either its amplitude or both amplitude and phase. Simultaneous amplitude and phase locking is possible under a specific condition for the difference of the drive frequencies, whenever the drive intensity is sufficiently high. The variations of the phenomena also exist in two coupled cavities containing one mechanical breathing mode.

Interlayer exchange interaction driven topological phase transition in antiferromagnetic electride Gd2O

Based on first-principles calculations, we discover a two-dimensional layered antiferromagnetic (AFM) electride Gd$_2$O, where anionic excess electrons exist in the interstitial spaces between positively charged cationic layers. It is revealed that each cationic layer composed of three-atom-thick Gd$-$O$-$Gd stacks has in-plane ferromagnetic and out-of-plane AFM superexchange interactions between the localized Gd 4$f$ spins through O 2$p$ orbitals. Furthermore, the interlayer superexchange mediated by the hybridized Gd-5$d$ and interstitial-$s$-like states involves intimate couplings between the spin, lattice, and charge degrees of freedom, thereby inducing simultaneous magnetic, structural, and electronic phase transitions. The resulting ground state with the simple hexagonal lattice hosts massless Dirac fermions protected by nonsymmorphic magnetic symmetry, as well as massive Dirac fermions. We thus demonstrate that the anionic excess electrons in Gd$_2$O play a crucial role in the emergence of magnetic Dirac semimetal states, therefore offering an intriguing interplay between 2D magnetic electrides and topological physics.

Tri-wavelength simultaneous ESPI for 3D micro-deformation field measurement.

Electronic speckle pattern interferometry (ESPI), a well-established technique for micro-deformation measurement, can be used to determine both in-plane and out-of-plane displacement components. Although many works in ESPI have been reported for three-dimensional (3D) displacement measurement, few works have focused on the simultaneous measurement of 3D deformation fields. Here we present an ESPI system that consists of three sub-interferometers for simultaneous measurement of all three displacement components and in-plane strain fields. A 3CCD color camera, a specially designed shifting stage, and three lasers with optimal wavelengths are used in this system. The lasers and 3CCD camera provide independent interferograms with different color signals, while the shifting stage allows the sub-interferometers to achieve simultaneous phase shifting. The results of color separation and experimental measurement demonstrate the utility of the system.

Multi-phase locking value: A generalized method for determining instantaneous multi-frequency phase coupling

BackgroundMany physical, biological and neural systems behave as coupled oscillators, with characteristic phase coupling across different frequencies. Methods such as n:m phase locking value (where two coupling frequencies are linked as: mf1=nf2) and bi-phase locking value have previously been proposed to quantify phase coupling between two resonant frequencies (e.g. f,2f/3) and across three frequencies (e.g. f1,f2,f1+f2), respectively. However, the existing phase coupling metrics have their limitations and limited applications. They cannot be used to detect or quantify phase coupling across multiple frequencies (e.g. f1,f2,f3,f4,f1+f2+f3-f4), or coupling that involves non-integer multiples of the frequencies (e.g. f1,f2,2f1/3+f2/3). New methodsTo address the gap, this paper proposes a generalized approach, named multi-phase locking value (M-PLV), for the quantification of various types of instantaneous multi-frequency phase coupling. Different from most instantaneous phase coupling metrics that measure the simultaneous phase coupling, the proposed M-PLV method also allows the detection of delayed phase coupling and the associated time lag between coupled oscillators. ResultsThe M-PLV has been tested on cases where synthetic coupled signals are generated using white Gaussian signals, and a system comprised of multiple coupled Rössler oscillators, as well as a human subject dataset. Results indicate that the M-PLV can provide a reliable estimation of the time window and frequency combination where the phase coupling is significant, as well as a precise determination of time lag in the case of delayed coupling. This method has the potential to become a powerful new tool for exploring phase coupling in complex nonlinear dynamic systems.

High-accuracy simultaneous phase extraction and unwrapping method for single interferogram based on convolutional neural network

The high-precision dynamic measurement of optical surfaces in unstable environments is a critical problem in the process of fabrication and application. In order to solve this problem, a high-precision ultra-fast phase demodulation method based on convolutional neural network is proposed in this paper. The wrapped phase and corresponding wrap count map can be obtained from one interferogram at the same time, so the phase extraction and unwrapping are performed simultaneously. It only takes 0.02 seconds to demodulate single-frame interferogram. Simulation and experimental results show that the root-mean-square error between this algorithm and phase-shifting algorithm is better than 0.01λ (λ=632.8nm). It indicates that the proposed method has excellent performance in measurement accuracy and efficiency.

Reflection-Type Phase Shifter Integrated With Tunable Power Attenuation Mechanism for Sub-6 GHz Wireless Applications

An integrated configuration of the reflection-type phase shifter (RTPS) and attenuator with simultaneous phase and amplitude control is presented for a phased-array front-end beamforming. The phase shift function of the RTPS adopts a quadrature coupler with high/low pass lumped elements and the corresponding π-type C–L–C loads. An RF tuner is subsequently incorporated into the 90° coupler to provide an energy reduction path and applied at the intermediate inductor of the coupler, thereby enabling a tunable transmission power. The merged coupler/RF-tuner realizes a matched and symmetrical structure with less impact on the load impedance variation, which can be regarded as part of the RTPS that performs RF signal degradation and maintains phase shift tuning. Furthermore, the π-type attenuator is incorporated into the RTPS to obtain an adequate power control range for the side-lobe suppression of the beamforming network. The simulated and measured results demonstrate the feasibility and suitability of the network for the proposed merged configuration applied to the phased-array system.

Absorption Attenuation Compensation Using an End-to-End Deep Neural Network

Absorption attenuation compensation is an important part of seismic data processing. It enhances the resolution of non-stationary seismic data by compensating the amplitude energy and correcting phase distortion. The stabilized inverse <i>Q</i> -filter method, a widely used attenuation compensation method, constructs compensation operators based on stratigraphy-related assumptions and compensates seismic data using time-window analysis, which is computationally complex and sensitive to noise. The essence of attenuation compensation lies in the establishment of a nonlinear mapping relationship between attenuated and non-attenuated seismic traces, which strongly benefits from deep learning. This paper proposes a new method for attenuation compensation based on an end-to-end deep neural network to reduce the hand-crafted step of time-window analysis. Instead, the convolutional blocks of the network automatically learn and process seismic data features to achieve simultaneous amplitude and phase compensation. We have constructed two end-to-end network architectures for attenuation compensation: a fully convolutional network (FCN) and a U-Net. As an effective spectrum-broadening method, the compensation method based on the U-Net is shown to enhance vertical resolution with good lateral continuity, to provide reliable compensation results without complex calculations, and to exhibit high noise robustness. Synthetic data tests indicate that the compensation results from the U-Net are better than those from either the FCN or the stabilized inverse <i>Q</i> -filter method at different noise levels. Moreover, the correlation coefficient between the U-Net compensation results of the synthetic profile and the reference non-attenuated profile is higher than that of the FCN and the stabilized inverse <i>Q</i> -filter method. A field data application further verifies the effectiveness of this method.

CCFE: A Few-Shot Learning Model for Earthquake Detection and Phase Identification

Earthquake detection and phase identification are fundamental and challenging tasks in observational seismology. Deep learning has achieved many achievements in these two tasks. To overcome the limitations of existing methods, mainly becauseof the lack oflarge labeled seismic datasets and the separation of detection and identification tasks, we introducedthe CWT-CNN Few-shot learning Earthquake model (CCFE), a deep learning model for simultaneous earthquake detection and phase identification. CCFE can performfew-shot learning with minimal labeled seismic data by utilizing continuous wavelet transform and lightweight convolutional neural networks with fewer layers. We tested our model in the Huoshan area of southern Chinaand foundthat CCFE outperformed both traditional and published representative deep learning models for detection and identification in this area and that combining detection and identification tasks enhances the performance of each task separately. We found 76% more earthquakes using CCFE than the manual catalog across 15 days of continuous data from the Huoshan region. In regions with low seismicity, CCFE can aid in enhancing earthquake monitoring capacity.

Off-axis digital holographic decarrier phase recovery algorithm combined with linear regression

Benefitting from the high measurement efficiency, off-axis digital holography (DH) has become a most powerful DH technique for fast and high-accuracy measurement. Owing to the carrier frequency, the real image can be isolated easily in the Fourier spectrum of one off-axis hologram, so that the Fourier transform algorithm (FTA) is the most widely used algorithm for off-axis DH to realize the phase retrieval. In the FTA, one of the most important tasks is to figure out the accurate peak position of the real image and then shift the real image to the center of spectrum to remove the carrier. However, owing to the digitalization of the hologram, the peak position of the real spectrum is always not located at an integral pixel position in the practical applications, resulting in carrier residuals, thereby lowering the retrieval quality. Much work on accurately determining the peak position has been conducted to suppress the carrier residuals, such as by using the spectrum centroid method and zero padding. However, those estimation algorithms can achieve only satisfied accuracy in some situations. Then, spatial carrier phase shift (SCPS) is utilized to expand the utilization of space-bandwidth and avoid the spectrum leakage caused by band-pass filtering. The SCPS decomposes one off-axis hologram into several sub-holograms, in which the carrier induces the phase shifts between sub-holograms. Many on-axis phase retrieval algorithms are combined with SCPS to retrieve the phase from one off-axis hologram. However, the retrieved phase is usually composed of the sample phase and the carrier, so the accurate carrier information is also required to remove the carrier and obtain the correct reconstructed phase. In this paper, an accurate phase retrieval with carrier removal from single off-axis hologram by using the linear regression is proposed to achieve the simultaneous phase retrieval and carrier removal. In this method, four phase-shifted sub-holograms are extracted first from one off-axis hologram by SCPS. Since the phase shift between sub-holograms is linearly proportional to the carrier, the linear regression can be combined with least-square method to retrieve the phase and carrier simultaneously. Both the simulation and experimental results show that the proposed method can determine the carrier accurately and obtain correct phase without carrier. We believe that this proposed method can be applied to practical measurement.

Beamforming Algorithm Based on the Orthogonal Phase Bases With Trigonometric Estimation for Microwave Power Transfer Systems

Microwave power transfer (MPT) has been widely studied, as sensors or mobile/wearable devices have been used, especially for IoT applications. A beamforming algorithm is essential and important for both the performance and the system complexity of MPT systems. In this paper, a beamforming algorithm that requires only 3 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -2 transmission sequences for the Tx array with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> elements to estimate the optimum set of the transmission phases is proposed. The proposed algorithm is simply based on trigonometric calculations, and can be directly applied to an MPT system without element calibration. Calculation of the optimum phase set of the Tx only requires the information of the received power level from the Rx. Since simultaneous phase shifting of the multiple elements is performed during the power transmission sequence, it can have a relatively high Rx SNR, compared to the methods based on phase shifting of only one element at each sequence. In addition, optimum transmission phase sets for multiple Rx’s can be obtained from a beamforming procedure using the proposed algorithm, if the received power levels from the multiple Rx’s are collected. For verification of the proposed algorithm, a 5.2 GHz 8×4 Tx array having an output power of 0.5 W per Tx element was implemented. Beamforming experiment was performed using the proposed algorithm. A received power of 45 mW at 2 m distance was achieved, which is very close to the simulated value.

Extraction of Absolute Water Level Using TanDEM-X Bistatic Observations With a Large Perpendicular Baseline

The application of Wetland synthetic aperture radar interferometry (InSAR) has often been restricted in practical hydrological monitoring because it is based on relative estimates of water level changes between two synthetic aperture radar acquisitions, as opposed to absolute water levels obtained by ground measurements. TanDEM-X bistatic observations can provide absolute water level estimates using simultaneous phase measurements by a two-satellite constellation with TerraSAR-X. We evaluated two datasets of TanDEM-X bistatic observations acquired during an experimental science phase on August 26 and 31, 2015, with a very large baseline configuration to extract absolute water levels of Everglades wetland in southern Florida, USA. The perpendicular baselines are 1.43 and 1.36 km, and the ambiguities of height were calculated as 3.61 and 3.90 m in each interferometric pair, respectively. Hourly water level measurements provided by the Everglades depth estimation network (EDEN) were used to verify the estimated absolute water levels. Several stage stations located in densely vegetated areas that showed incoherence were excluded from the verification as outliers. The verification results show an excellent agreement (degree of determination > 0.95) between the InSAR derived absolute water levels and the stage station measurements. The root mean square error (RMSE) between the TanDEM-X results and stage records was 0.77 and 0.66 m, respectively. Severe volume decorrelations over the vegetated area, owing to the large perpendicular baselines, were detected, despite near zero temporal baseline of the bistatic observations. The absolute water levels can be used as excellent constraints for wetland surface flow models.

From digital holographic microscopy to optical coherence tomography – separate past and a common goal

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3D deformation measurement in digital holographic interferometry using a multitask deep learning architecture.

The extraction of absolute phase from an interference pattern is a key step for 3D deformation measurement in digital holographic interferometry (DHI) and is an ill-posed problem. Estimating the absolute unwrapped phase becomes even more challenging when the obtained wrapped phase from the interference pattern is noisy. In this paper, we propose a novel multitask deep learning approach for phase reconstruction and 3D deformation measurement in DHI, referred to as TriNet, that has the capability to learn and perform two parallel tasks from the input image. The proposed TriNet has a pyramidal encoder-two-decoder framework for multi-scale information fusion. To our knowledge, TriNet is the first multitask approach to accomplish simultaneous denoising and phase unwrapping of the wrapped phase from the interference fringes in a single step for absolute phase reconstruction. The proposed architecture is more elegant than recent multitask learning methods such as Y-Net and state-of-the-art segmentation approaches such as UNet++. Further, performing denoising and phase unwrapping simultaneously enables deformation measurement from the highly noisy wrapped phase of DHI data. The simulations and experimental comparisons demonstrate the efficacy of the proposed approach in absolute phase reconstruction and 3D deformation measurement with respect to the existing conventional methods and state-of-the-art deep learning methods.

Simultaneous Distillation Extraction (SDE) and Headspace Solid-Phase Microextraction (HS-SPME) for the Determination of Volatile Organic Compounds (VOCs) by Gas Chromatography – Mass Spectrometry (GC-MS) in Perilla Frutescens Foliage from South Korea

In the recent past, meat consumption has increased around the world, which resulted in high consumer demand for fresh perilla leaves. The present study aimed at comparison of the volatile organic compounds (VOCs) among three varieties of Perilla frutescens leaves from South Korea via simultaneous distillation extraction (SDE) and headspace solid phase microextraction (HS-SPME). A total of 138 VOCs were identified in leaves of P. frutescens varieties with 111 and 74 VOCs identified by SDE and HS-SPME, respectively. The P. frutescens for. viridis Makino leaves contained the highest concentrations of VOCs for both SDE (17.51 g/kg) and HS-SPME (1.463 g/kg) compared to the other varieties. Perilla ketone was the main volatile in P. frutescens var. acuta Kudo and P. frutescens var. japonica Hara while perilla aldehyde was the major compound in P. frutescens for. viridis Makino. Other major identified compounds were (E)-β-caryophellene, cumaldehyde, limonene, and octanol. Differences in the patterns of functional groups and terpene types were also demonstrated among the varieties. SDE provided more compounds while HS-SPME was more convenient for the determination.

Flexible STEM with Simultaneous Phase and Depth Contrast.

Recent advances in scanning transmission electron microscopy (STEM) have rekindled interest in multi-channel detectors and prompted the exploration of unconventional scan patterns. These emerging needs are not yet addressed by standard commercial hardware. The system described here incorporates a flexible scan generator that enables exploration of low-acceleration scan patterns, while data are recorded by a scalable eight-channel array of nonmultiplexed analog-to-digital converters. System integration with SerialEM provides a flexible route for automated acquisition protocols including tomography. Using a solid-state quadrant detector with additional annular rings, we explore the generation and detection of various STEM contrast modes. Through-focus bright-field scans relate to phase contrast, similarly to wide-field TEM. More strikingly, comparing images acquired from different off-axis detector elements reveals lateral shifts dependent on defocus. Compensation of this parallax effect leads to decomposition of integrated differential phase contrast (iDPC) to separable contributions relating to projected electric potential and to defocus. Thus, a single scan provides both a computationally refocused phase contrast image and a second image in which the signed intensity, bright or dark, represents the degree of defocus.

Investigation of modulation format conversion for optical channel deaggregation in elastic optical network

Our research investigates an optical channel deaggregation technique based on modulation format conversion that may be used in elastic optical networks (EONs) to achieve high spectral efficiency, flexibility, and high data rate. The modulation format conversion technique from 8-ary phase shift keying (8-PSK) to two simultaneous quadrature phase shift keying (QPSK) at 50 Gb / s has been simulated and investigated. 8-PSK and the converted QPSK signals are investigated and compared in terms of bit error rate (BER) and quality factor (Q-factor), and it is demonstrated that they substantially reduce the complexity of transmission and reception process, at high data rates in EON. Additionally, this approach is further exploited to tailor a protection scheme for network survivability. Channel deaggregation, which divides the channel into working and protection paths, is used to implement a dedicated path protection scheme in EON. To evaluate the effect of various network conditions such as traffic load, modulation format, and BER on EON survivability, network simulations are performed on the ARPANET network.

Role of Pr-Vacancies and O-Interstitials on the Activity and Stability of (Pr1−xLnx)2NiO4 (Ln = La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) towards Oxygen Reduction Reactions: A DFT Study

Praseodymium nickelate, Pr2NiO4 (PNO), is a promising electrode to promote oxygen reduction reaction (ORR) in a solid oxide fuel cell, but it exhibits phase transformation during electrochemical operation. The origin of the simultaneous phase transformation and high electrochemical performance remains obscure. We carried out a systematic density functional theory study to elucidate the mechanism for this conjugated phenomenon. Charge, electronic structure, and normal-mode analysis suggest the presence of peroxide. Our study shows that the formation of peroxide (O2 2−) is attributed to both oxygen interstitials and Pr vacancies. The peroxide species limits the oxygen ion migration due to the additional energy required to break its O–O bond, which leads to a decrease in ORR activity. Subsequently, we investigate the diffusion paths of Pr-ions while comparing them with those of other Ln3+ ions (La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) in PNO. The formation energies for various Ln3+ cation occupancies are calculated, as well as segregation energies in CeO2(111) surfaces. Finally, criteria for effective Ln3+ dopants are developed. La, Nd, and Pm are proposed as potential substituents in PNO to obtain a stable structure.