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Photonic interconnects between quantum systems will play a central role in both scalable quantum computing and quantum networking. Entanglement of remote qubits via photons has been demonstrated in many platforms; however, improving the rate of entanglement generation will be instrumental for integrating photonic links into modular quantum computers. We present an ion trap system that has the highest reported free-space photon collection efficiency for quantum networking. We use a pair of in-vacuum aspheric lenses, each with a numerical aperture of 0.8, to couple 10(1)% of the 493 nm photons emitted from a 138Ba+ ion into single-mode fibers. We also demonstrate that proximal effects of the lenses on the ion position and motion can be mitigated. [ABSTRACT FROM AUTHOR]

Annular-illumination quantitative phase imaging based on Kramers–Kronig relations (AIKK) achieves a large space-bandwidth-time product. The reconstruction algorithm is non-iteration, parameter-free, and object-independent constitutionally. Based on the observation and analyticity of intensity spectrum characteristics and symmetry in spatial and frequency domains, we propose a single-frame two-color illumination imaging based AIKK (SFTC-AIKK). In addition, we apply the two-color mode to synthetic aperture imaging, and only one measurement is sufficient with a monochrome camera. We employ SFTC-AIKK to achieve resolution corresponding to nearly two times the objective NA at camera-limited frame rate to applications with observing dynamic target at various spatial and temporal scales. [ABSTRACT FROM AUTHOR]

Ultrasound has been implemented as a powerful tool for noninvasive imaging and non-contact ranging. However, the size and single-function of traditional ultrasonic probes have limited their adaptability to complex application scenarios in the artificial intelligence era. This paper reports a multifunctional microsensor based on a piezoelectric micromachined ultrasonic transducer (pMUT) array that can be used for ranging and 2D imaging at the same time, in air, with a small working size (2 × 0.8 mm2) and low driving voltage (10 V). A back-end circuit was also designed to optimize the performance of the pMUT array, resulting in a peak-to-peak value of 158 mV. The characterization of the multifunctional microsensor demonstrated that it is capable of performing ranging and 2D imaging simultaneously with high spatial resolution (∼1 mm in ranging and ∼0.2 × 0.2 mm2 in 2D-imaging), even in complex application scenarios. This paper describes a system that integrates micro-electro-mechanical systems device, back-end circuit, imaging algorithm, and denoising algorithm, which allow the microsensor to provide multiple functions. This makes it a promising tool for a wide range of human–machine interaction applications, such as gesture recognition, robotics, and healthcare. [ABSTRACT FROM AUTHOR]

Synthetic aperture sonar (sas) systems are designed to observe stationary scatterers located near the sediment interface. Less commonly, a sas system may be used to observe scattering features located above the sonar in the water column. The Undersea Remote Sensing (USRS) project, sponsored by the Office of Naval Research, was a collaborative Directed Research Initiative (DRI) focused on studying dynamic estuarine water column features. During the USRS DRI, researchers from multiple institutions gathered to observe tidal features at various estuaries along the coast of the United States using both in situ and remote sensing techniques, including sas. The first studied estuary was the mouth of the Connecticut River (CTR). Data captured by a sas system deployed during a tidal event were post-processed to create three-dimensional observations of the structure of the leading edge of the CTR's ebb plume front. From these observations, lobed structures similar in scale to previously reported instabilities are revealed, with the present observations providing additional insight regarding the structure of the bubble distribution behind the front. Velocity estimates of plume features were also determined from sas data and shown to compare favorably with concurrent marine radar estimates. [ABSTRACT FROM AUTHOR]

A fundamental challenge in acoustic data processing is to separate a measured time series into relevant phenomenological components. A given measurement is typically assumed to be an additive mixture of myriad signals plus noise whose separation forms an ill-posed inverse problem. In the setting of sensing elastic objects using active sonar, we wish to separate the early-time return from the object's geometry from late-time returns caused by elastic or compressional wave coupling. Under the framework of morphological component analysis (MCA), we compare two separation models using the short-duration and long-duration responses as a proxy for early-time and late-time returns. Results are computed for a broadside response using Stanton's elastic cylinder model as well as on experimental data taken from an in-air circular synthetic aperture sonar system, whose separated time series are formed into imagery. We find that MCA can be used to separate early and late-time responses in both the analytic and experimental cases without the use of time-gating. The separation process is demonstrated to be compatible with image reconstruction. The best separation results are obtained with a flexible, but computationally intensive, frame based signal model, while a faster Fourier transform based method is shown to have competitive performance. [ABSTRACT FROM AUTHOR]

This work concerns the development and testing of a setup that uses laser-induced ultrasound sources to achieve synthetic transmit aperture ultrasound imaging. The sources are created by sequentially firing 32 contiguous multi-mode optical fibers to illuminate an optically absorbing film with nanosecond-pulsed laser light. Ultrasound is generated by the photoacoustic effect and insonifies the sample under investigation. Ultrasound that has interacted with the sample is detected in reflection mode using a conventional ultrasound transducer array. We present a custom-developed optical fiber multiplexing setup that enables sequential firing of the optical fiber array and characterize the acoustic fields produced by the laser-induced approach using hydrophone measurements. The integrated setup is used to make images of wire phantoms. Following this, images are taken of a breast-mimicking phantom as well as the wrist of one of the authors. Imaging results from the new approach and from conventional ultrasound imaging are compared. The lateral and axial point-spread function values show broad agreement between the two approaches, whereas the phantom and in vivo images exhibit some differences in contrast values. This work is, to our knowledge, the first instance of laser-induced ultrasound synthetic transmit aperture imaging using a clinical ultrasound array. [ABSTRACT FROM AUTHOR]

In this paper, we investigate two deep learning approaches to recovering initial temperature profiles from thermographic images in non-destructive material testing. First, we trained a deep neural network (DNN) in an end-to-end fashion by directly feeding the surface temperature measurements to the DNN. Second, we turned the surface temperature measurements into virtual waves (a recently developed concept in thermography), which we then fed to the DNN. To demonstrate the effectiveness of these methods, we implemented a data generator and created a dataset comprising a total of 100 000 simulated temperature measurement images. With the objective of determining a suitable baseline, we investigated several state-of-the-art model-based reconstruction methods, including Abel transformation, curvelet denoising, and time- and frequency-domain synthetic aperture focusing techniques. Additionally, a physical phantom was created to support evaluation on completely unseen real-world data. The results of several experiments suggest that both the end-to-end and the hybrid approach outperformed the baseline in terms of reconstruction accuracy. The end-to-end approach required the least amount of domain knowledge and was the most computationally efficient one. The hybrid approach required extensive domain knowledge and was more computationally expensive than the end-to-end approach. However, the virtual waves served as meaningful features that convert the complex task of the end-to-end reconstruction into a less demanding undertaking. This in turn yielded better reconstructions with the same number of training samples compared to the end-to-end approach. Additionally, it allowed more compact network architectures and use of prior knowledge, such as sparsity and non-negativity. The proposed method is suitable for non-destructive testing (NDT) in 2D where the amplitudes along the objects are considered to be constant (e.g., for metallic wires). To encourage the development of other deep-learning-based reconstruction techniques, we release both the synthetic and the real-world datasets along with the implementation of the deep learning methods to the research community. [ABSTRACT FROM AUTHOR]

Passive synthetic aperture (PSA) extension for a moving array has the ability to enhance the accuracy of direction-of-arrival (DOA) estimation by constructing a larger virtual aperture. The array element overlap in array continuous measurements is required for the traditional extended towed array measurement (ETAM) methods. Otherwise, the phase factor estimation is biased, and the aperture extension fails when multiple sources exist. To solve this problem, passive aperture extension with sparse Bayesian learning (SBL) is proposed. In this method, SBL is used to simultaneously estimate the phase correction factors of different targets, followed by phase compensation applied to the extended aperture manifold vectors for DOA estimation. Simulation and experimental data results demonstrate that this proposed method successfully extends the aperture and provides higher azimuth resolution and accuracy compared to conventional beamforming (CBF) and SBL without extension. Compared with the traditional ETAM methods, the proposed method still performs well even when the array elements are not overlapped during the motion. [ABSTRACT FROM AUTHOR]

This paper aims to implement a laser-induced ultrasound imaging reconstruction method based on the delay-and-sum beamforming through the synthetic aperture focusing technique (SAFT) for a circular scanning, performed with a tomograph that had one acoustic sensor and a system that rotates the sample around a fixed axis. The proposed method, called the Single-sensor Scanning Synthetic Aperture Focusing Technique, considers the size of the sensor and the detection procedure inside the SAFT's algebra. This image reconstruction method was evaluated numerically, using the Green function for the laser-induced ultrasound wave equation to generate a forward problem, and experimentally, using a solid object of polylactic acid, and a Sprague–Dawley rat heart located in a tissue-mimicking phantom. The resulting images were compared to those obtained from the time reversal and the conventional delay-and-sum reconstruction algorithms. The presented method removes the sidelobe artifacts and the comet tail sign, which produces a more distinguishable target on the image. In addition, the proposed method has a faster performance and lower computational load. The implementation of this method in photoacoustic microscopy techniques for image reconstruction is discussed. [ABSTRACT FROM AUTHOR]

To provide optimal depth resolution with a coded-aperture Laue diffraction microscope, an accurate position of the coded-aperture and its scanning geometry need to be known. However, finding the geometry by trial and error is a time-consuming and often challenging process because of the large number of parameters involved. In this paper, we propose an optimization approach to automate the focusing process after data is collected. We demonstrate the robustness and efficiency of the proposed approach with experimental data taken at a synchrotron facility. [ABSTRACT FROM AUTHOR]

Both forward and inverse design methods have been developed for focal field engineering, which has applications in many areas including super-resolution imaging and optical lithography, high-density optical storage, and particle manipulation. However, a certain method is normally targeted at a unique focal field distribution. Here, we report on a versatile focal field design method based on a cascaded artificial neural network (CANN) for the inverse design of focal field distributions in a high numerical aperture focusing system. The CANN consists of a forward and an inverse artificial neural network. Once trained properly, the CANN can predict modulation phase patterns for multiple focal field distributions. We demonstrate the effectiveness of the CANN by the design of focal field distributions along the optical axis including a uniform optical needle and an anti-point spread function with lengths up to 14 wavelengths and multiple focal spots with controllable intensities as well as those in the focal plane including flat-top and sub-diffraction focal spots. [ABSTRACT FROM AUTHOR]

Estimation of modal wavenumbers is important for inference of geoacoustic properties and matched field processing in shallow water waveguides. However, it is challenging in a range-dependent environment, because modal content varies locally in response to changes in the environment. Moreover, the scales of the spatial variations in the waveguide may be on the same order as the range aperture required for resolvability of the individual modes. To this end, high-resolution (HR) wavenumber estimation methods have been widely used. In this paper, the matrix pencil and MUSIC algorithms are generalized to geometry involving a synthetic horizontal aperture (SHA) formed by a towed acoustic source and a fixed full-spanning vertical line array (VLA). The performance of the proposed methods is evaluated by simulated data in a noisy shallow water environment. Numerical results show that, when compared with the previous methods, the proposed methods significantly outperform the previous methods in terms of aperture requirement. [ABSTRACT FROM AUTHOR]

Geoacoustic inversion using moving sensors attracts lots of interest due to the ease of deployment and low cost. However, the well-established techniques, such as matched-field inversion (MFI), may run into difficulties when the sensors are in a range-dependent environment for mismatch issues and increasing unknown parameters. Given a range-dependent environment, the paper focuses on the inversion using a synthetic aperture created by moving sensors in the presence of the Doppler effect. The derivation is given to obtain an equivalent range-independent environmental model for fast inversion, instead of a range-dependent one. The received fields are modified using the Doppler-shifted wavenumbers. The simulations and results of the SWellEx-96 experimental data verify the effectiveness of the proposed inversion method. [ABSTRACT FROM AUTHOR]

Chemical explosions are ground truth events that provide data, which, in turn, can enhance the understanding of wave propagation, damage assessment, and yield estimation. On 4 August 2020, Beirut, Lebanon was shocked by a catastrophic explosion, which caused devastating damage to the Mediterranean city. A second strong chemical explosion took place at the Xiangshui, China chemical plant on 21 March 2019. Both events generated shock waves that transitioned to infrasound waves, seismic waves, as well as hydroacoustic signals with accompanying T-phases in the case of the Beirut event. In this work, the seismo-acoustic signatures, yields, and associated damage of the two events are investigated. The differentiainterferometry synthetic aperture radar analysis quantified the surface damage and the estimated yield range, equivalent to 2,4,6-trinitrotoluene [C7H5(NO2)3] (TNT), through a "boom" relation of the peak overpressure was evaluated. Infrasound propagation modeling identified a strong duct in the stratosphere with the propagation to the west in the case of the Beirut-Port explosion. In the case of the Xiangshui explosion, the modeling supports the tropospheric propagation toward the Kochi University of Technology (KUT) sensor network in Japan. Although the Beirut yield (202–270 ± 100 tons) was slightly larger than the Xiangshui yield (201 ± 83.5 tons), the near-source damage areas are almost the same based on the distribution of damaged buildings surrounding the explosions. [ABSTRACT FROM AUTHOR]

Synthetic aperture sonar (SAS) provides high-resolution acoustic imaging by processing coherently the backscattered signal recorded over consecutive pings as the bearing platform moves along a predefined path. Coherent processing requires accurate estimation and compensation of the platform's motion for high quality imaging. The motion of the platform carrying the SAS system can be estimated by cross-correlating redundant recordings at successive pings due to the spatiotemporal coherence of statistically homogeneous backscatter. This data-driven approach for estimating the motion of the SAS platform is essential when positioning information from navigational instruments is absent or inadequately accurate. Herein, the problem of platform motion estimation from coherence measurements of diffuse backscatter is formulated in a probabilistic framework. A variational autoencoder is designed to disentangle the ping-to-ping platform displacement from three-dimensional (3D) spatiotemporal coherence measurements. Unsupervised representation learning from unlabeled data offers robust 3D platform motion estimation. Including a small amount of labeled data during training improves further the platform motion estimation accuracy. [ABSTRACT FROM AUTHOR]

Quantitative phase imaging (QPI) is a valuable label-free modality that has gained significant interest due to its wide potentials, from basic biology to clinical applications. Most existing QPI systems measure microscopic objects via interferometry or nonlinear iterative phase reconstructions from intensity measurements. However, all imaging systems compromise spatial resolution for the field of view and vice versa, i.e., suffer from a limited space bandwidth product. Current solutions to this problem involve computational phase retrieval algorithms, which are time-consuming and often suffer from convergence problems. In this article, we presented synthetic aperture interference light (SAIL) microscopy as a solution for high-resolution, wide field of view QPI. The proposed approach employs low-coherence interferometry to directly measure the optical phase delay under different illumination angles and produces large space-bandwidth product label-free imaging. We validate the performance of SAIL on standard samples and illustrate the biomedical applications on various specimens: pathology slides, entire insects, and dynamic live cells in large cultures. The reconstructed images have a synthetic numeric aperture of 0.45 and a field of view of 2.6 × 2.6 mm2. Due to its direct measurement of the phase information, SAIL microscopy does not require long computational time, eliminates data redundancy, and always converges. [ABSTRACT FROM AUTHOR]

We study the diffusion of ocean waves by ice bodies much smaller than a wavelength, such as pancakes and small ice floes. We argue that inhomogeneities in the ice cover at scales comparable to that of the wavelength significantly increase diffusion, producing a contribution to wave attenuation comparable to what is observed in the field and usually explained by viscous effects. The resulting attenuation spectrum is characterized by a peak at the scale of the inhomogeneities in the ice cover, which could explain the rollover of the attenuation profile at small wavelengths observed in field experiments. The proposed attenuation mechanism leads to the same behaviors that would be produced by a viscous wave model with effective viscosity linearly dependent on the ice thickness. This may explain recent findings that viscous wave models require a thickness-dependent viscosity to fit experimental attenuation data. Experimental validation is carried out using wave buoy attenuation data and synthetic aperture radar image analysis. [ABSTRACT FROM AUTHOR]

This work demonstrates that automated mine countermeasure (MCM) tasks are greatly facilitated by characterizing the seafloor environment in which the sensors operate as a first step within a comprehensive strategy for how to exploit information from available sensors, multiple detector types, measured features, and target classifiers, depending on the specific seabed characteristics present within the high-frequency synthetic aperture sonar (SAS) imagery used to perform MCM tasks. This approach is able to adapt as environmental characteristics change and includes the ability to recognize novel seabed types. Classifiers are then adaptively retrained through active learning in these unfamiliar seabed types, resulting in improved mitigation of challenging environmental clutter as it is encountered. Further, a segmentation constrained network algorithm is introduced to enable enhanced generalization abilities for recognizing mine-like objects from underrepresented environments within the training data. Additionally, a fusion approach is presented that allows the combination of multiple detectors, feature types spanning both measured expert features and deep learning, and an ensemble of classifiers for the particular seabed mixture proportions measured around each detected target. The environmentally adaptive approach is demonstrated to provide the best overall performance for automated mine-like object recognition. [ABSTRACT FROM AUTHOR]

Range-coherent matched field processing (MFP) coherently combines snapshots to localize a moving, narrowband source. This approach differs from existing MFP approaches that treat each snapshot as having a random phase due to both unknown motion through the medium and imprecise knowledge of the source frequency. Range-coherent MFP requires determination of the source phase acquired between snapshots. With that information, MFP can be applied to the cross-spectrum of snapshots acquired at different times, since relative phase between snapshots is determined by the medium properties, source location, and source velocity. Viewed another way, range-coherent MFP is simply MFP applied to a passive synthetic aperture formed from a moving source. The synthetic aperture geometry depends on source velocity, which is included in the MFP search space. Range-coherent MFP produces robust velocity estimates at low signal-to-noise ratio (SNR), which permits the use of a longer fast Fourier transform in pre-processing. The synthetic aperture array gain plus the increased input SNR afforded by the enhanced pre-processing significantly lowers the required signal level for successful localization. In data from the SWellEx-96 experiment, range-coherent MFP successfully localizes a source that is too quiet for conventional methods to localize. [ABSTRACT FROM AUTHOR]

Circular synthetic aperture sonar (CSAS) is a method for improving the resolution and target detection capabilities of a synthetic aperture sonar system. CSAS data are difficult to focus because of their large aperture sizes and elevation sensitivity. This difficulty has sometimes been addressed by using transponders or distributing isotropic scatterers in the field of view of the system; however, this comes at the cost of reduced practicality. As an alternative, map-drift based multipoint autofocus ("multilateration") was proposed by Cantalloube and Nahum [IEEE Trans. Geosci. Remote Sens. 49, 3730–37 (2011)] for autofocusing analogous circular synthetic aperture radar data. Multilateration also solves the problem of aberration spatial variance by providing a three-dimensional navigation correction. In circular synthetic aperture focusing problems, though, correcting aberrations is a joint navigation and elevation estimation problem, and the present work extends the multilateration approach to simultaneously solve both a navigation solution and coordinate corrections for the multilateration control patches. Additionally, methods for addressing the stability and behavior of the inverse problem are addressed, and an adaptive weighting scheme for reducing the influence of outliers is presented. The field results demonstrate near optimal point-spread functions on distributions of natural isotropic scatterers and robustness in regions with bathymetric variability. [ABSTRACT FROM AUTHOR]

In order to overcome the limitations of traditional ultrasonic imaging methods, which cannot directly give the imaging results of defects in a pipeline and have low imaging quality, a frequency domain synthetic aperture focusing pipeline imaging method based on phase migration is proposed. The measured data were reconstructed by frequency domain synthetic aperture focusing, and the results were compared with those of time-domain synthetic aperture focusing imaging. The results show that the frequency domain synthetic aperture imaging method is more accurate for the location and quantification of defects in a pipeline, the influence of noise waves on the imaging transverse resolution is reduced, and the imaging resolution is increased by nearly 30%. It was found that the quantitative errors of axial double defects are 5.2% and 17.9%, and that of circumferential defects is 7.5%. These results show that the frequency domain synthetic aperture focusing pipeline imaging algorithm based on phase migration can achieve the accurate determination of multiple defects in pipelines. [ABSTRACT FROM AUTHOR]

On the basis of a fishnet-like structure, we analyze a metamaterial design involving dimer aperture arrays. It is shown that this approach leads to very strong Fano resonances within the transmission spectrum. The role of the Wood anomaly in the enhancement of the magnetic field is pointed out in order to explain this transmission characteristic. A sensitivity numerical analysis of this resonant feature is carried out. A figure of merit, defined as the ratio between the sensitivity and the width at half maximum of the resonance, as high as 830, is obtained. To our knowledge, this value is greater than the ones reported so far in literature using the inter-particle electromagnetic induced transparency principle. This property is of great interest for environment control applications, especially for sensing of highly diluted media, such as gaseous phase pollutants, as a complement to conventional spectroscopy techniques. [ABSTRACT FROM AUTHOR]

The correlation between two pulse-echo ultrasound signals is used to achieve a wide range of ultrasound techniques, such as Doppler imaging and elastography. Prior theoretical descriptions of pulse-echo correlations were restricted to stationary scatterers. Here, a theory for the correlation of moving scatterers is presented. An expression is derived for the correlation of two pulse-echo signals with arbitrary transmit and receive apertures acquired from a medium undergoing bulk motion using the Fresnel approximation. The derivation is shown to coincide with prior derivations in the absence of scatterer motion. The theory was compared against simulations in applications of phase-shift estimation and aperture coherence measurements. The phase-shift estimate and jitter were accurately predicted under axial and transverse motion for focused transmit apertures and for sequential and interleaved synthetic transmit apertures. The theory also accurately predicted how motion affects the correlation coefficient between receive aperture elements for a synthetic transmit aperture. The presented theory provides a framework for analyzing the correlations of arbitrary pulse-echo configurations for applications in which scatterer motion is expected. [ABSTRACT FROM AUTHOR]

In this study, we developed microwave-induced thermoacoustic endoscopy (TAE), which employs a high-repetition-rate pulsed microwave generator for external excitation and a side-view focused ultrasound transducer for internal acoustic detection. The system yields a lateral resolution of 1.5 mm and an axial resolution of 0.35 mm. The penetration depths of saline-containing tube (5% NaCl) and tumor lesions in biological tissues are 9 and 6 cm under current experimental conditions, respectively. To improve the signal-to-noise ratio (SNR) of the reconstructed image and eliminate the off-focus distortion of the transducer, we applied the synthetic aperture focusing technique (SAFT) and coherence weighting factor into the reconstruction algorithm. Additionally, we carried out in vivo rat experiments to evaluate clinical feasibility of this technique. We could clearly distinguish multiple tumor lesions embedded inside the rat abdomen from the surrounding normal tissues. [ABSTRACT FROM AUTHOR]

Sonar systems that exploit correlation for navigation, such as correlation velocity logs and micronavigation for synthetic aperture sonar, often make redundant estimates of the spatial coherence of the scattered field at several spatial lags. Two models for the correlation of these redundant measurements are described. First, an analytical model is derived using the assumption of stationary Gaussian statistics. Next, a numerical model is described that accounts for non-stationary processes present in measurements of seafloor scattering. These models are compared to normal-incidence scattering data collected at Seneca Lake, NY. Both models show good agreement with the measurements when the spatial separation between redundant hydrophone pairs is less than the coherence length. At greater spatial separation, the analytical model diverges from the measurements. This disagreement is explained by a lack of stationarity in the measured data which is captured by the numerical model. Finally, spatial variations in the volume scattering strength of the sediment are identified as a source of the non-stationarity in the measurements. [ABSTRACT FROM AUTHOR]

Synthetic aperture sonar (SAS) provides high-resolution acoustic imaging by processing coherently the backscattered acoustic signal recorded over consecutive pings. Traditionally, object detection and classification tasks rely on high-resolution seafloor mapping achieved with widebeam, broadband SAS systems. However, aspect- or frequency-specific information is crucial for improving the performance of automatic target recognition algorithms. For example, low frequencies can be partly transmitted through objects or penetrate the seafloor providing information about internal structure and buried objects, while multiple views provide information about the object's shape and dimensions. Sub-band and limited-view processing, though, degrades the SAS resolution. In this paper, SAS imaging is formulated as an ℓ1-norm regularized least-squares optimization problem which improves the resolution by promoting a parsimonious representation of the data. The optimization problem is solved in a distributed and computationally efficient way with an algorithm based on the alternating direction method of multipliers. The resulting SAS image is the consensus outcome of collaborative filtering of the data from each ping. The potential of the proposed method for high-resolution, narrowband, and limited-aspect SAS imaging is demonstrated with simulated and experimental data. [ABSTRACT FROM AUTHOR]

The probability density function of the acoustic field amplitude scattered by the seafloor was measured in a rocky environment off the coast of Norway using a synthetic aperture sonar system, and is reported here in terms of the probability of false alarm. Interpretation of the measurements focused on finding the appropriate class of statistical models (single versus two-component mixture models), and on appropriate models within these two classes. It was found that two-component mixture models performed better than single models. The two mixture models that performed the best (and had a basis in the physics of scattering) were a mixture between two K distributions, and a mixture between a Rayleigh and generalized Pareto distribution. Bayes' theorem was used to estimate the probability density function of the mixture model parameters. It was found that the K-K mixture exhibits a significant correlation between its parameters. The mixture between the Rayleigh and generalized Pareto distributions also had a significant parameter correlation, but also contained multiple modes. It is concluded that the mixture between two K distributions is the most applicable to this dataset. [ABSTRACT FROM AUTHOR]

Multi-element photoacoustic tomography systems have either a non-movable focus or a non-uniform light field distribution over the region of interest, significantly limiting the depth-of-field and resolution of images. In this study, focus-tunable photoacoustic tomography (FT-PAT) based on a clinical ultrasound array transducer with uniform laser excitation was developed to achieve high-resolution imaging in deep tissue. An adjustable line-focusing structure was used to condense the laser beam, and the excited photoacoustic signal was processed via a synthetic-aperture focusing technique. Carbon rods at different depths were used to evaluate the focus-tunable ability in a tissue phantom. In vivo focus-tunable imaging performance was demonstrated by an experiment involving imaging of carbon nanoparticle-labeled living nude mouse covered by chicken breast. The signal-to-noise ratio of targets at different depths was changed by focus adjustment, which demonstrates that the FT-PAT system has potential clinical applications in deep tumor imaging and subsequent diagnoses. [ABSTRACT FROM AUTHOR]

Presents an analysis of the property of amplified spontaneous emission (ASE) and saturable absorber for a terawatt xenon chloride laser system. Investigation of the dependence of ASE on gain in the wide-aperture amplifier; Autocorrelation trace of amplified ultraviolet pulses; Discussion on subpicosecond amplification in wide-aperture amplifiers.

Presents a study on the structure or the near-zone fields transmitted through an electrically small aperture in a perfectly conducting plane. Derivation of equations; Description of the small circular aperture; Numerical results.