Multi-wavelength Imaging Research Articles

A population of faint, old, and massive quiescent galaxies at 3

Here we present a sample of 12 massive quiescent galaxy candidates at z∼3-4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$z\\sim 3-4$$\\end{document} observed with the James Webb Space Telescope (JWST) Near Infrared Spectrograph (NIRSpec). These galaxies were pre-selected from the Hubble Space Telescope imaging and 10 of our sources were unable to be spectroscopically confirmed by ground based spectroscopy. By combining spectroscopic data from NIRSpec with multi-wavelength imaging data from the JWST Near Infrared Camera (NIRCam), we analyse their stellar populations and their formation histories. We find that all of our galaxies classify as quiescent based on the reconstruction of their star formation histories but show a variety of quenching timescales and ages. All our galaxies are massive (∼0.1-1.2×1011\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 0.1-1.2\ imes 10^{11}$$\\end{document} M⊙\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\\odot$$\\end{document}), with masses comparable to massive galaxies in the local Universe. We find that the oldest galaxy in our sample formed ∼1.0×1011\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 1.0\ imes 10^{11}$$\\end{document} M⊙\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\\odot$$\\end{document} of mass within the first few hundred million years of the Universe and has been quenched for more than a billion years by the time of observation at z∼3.2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$z\\sim 3.2$$\\end{document} (∼2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 2$$\\end{document} billion years after the Big Bang). Our results point to very early formation of massive galaxies requiring a high conversion rate of baryons to stars in the early Universe.

Multi-Spectral Food Classification and Caloric Estimation Using Predicted Images.

In nutrition science, methods that accomplish continuous recognition of ingested foods with minimal user intervention have great utility. Our recent study showed that using images taken at a variety of wavelengths, including ultraviolet (UV) and near-infrared (NIR) bands, improves the accuracy of food classification and caloric estimation. With this approach, however, analysis time increases as the number of wavelengths increases, and there are practical implementation issues associated with a large number of light sources. To alleviate these problems, we proposed a method that used only standard red-green-blue (RGB) images to achieve performance that approximates the use of multi-wavelength images. This method used RGB images to predict the images at each wavelength (including UV and NIR bands), instead of using the images actually acquired with a camera. Deep neural networks (DNN) were used to predict the images at each wavelength from the RGB images. To validate the effectiveness of the proposed method, feasibility tests were carried out on 101 foods. The experimental results showed maximum recognition rates of 99.45 and 98.24% using the actual and predicted images, respectively. Those rates were significantly higher than using only the RGB images, which returned a recognition rate of only 86.3%. For caloric estimation, the minimum values for mean absolute percentage error (MAPE) were 11.67 and 12.13 when using the actual and predicted images, respectively. These results confirmed that the use of RGB images alone achieves performance that is similar to multi-wavelength imaging techniques.

The Non-Thermal Radio Emissions of the Solar Transition Region and the Proposal of an Observational Regime

The transition region is a very thin but most peculiar layer in the solar atmosphere located between the solar chromosphere and the corona. It is a key region for understanding coronal heating, solar eruption triggers, and the origin of solar winds. Here, almost all physical parameters (density, temperature, and magnetic fields) have the maximum gradient. Therefore, this region should be highly dynamic, including fast energy releasing and transporting, plasma heating, and particle accelerating. The physical processes can be categorized into two classes: thermal and non-thermal processes. Thermal processes can be observed at ultraviolet (UV) and extreme ultraviolet (EUV) wavelengths via multi-wavelength images. Non-thermal processes accelerate non-thermal electrons and produce radio emissions via the gyrosynchrotron mechanism resulting from the interaction between the non-thermal electrons and magnetic fields. The frequency range spans from several GHz to beyond 100 GHz, in great number of bursts with narrowband, millisecond lifetime, rapid frequency drifting rates, and being referred to as transition region small-scale microwave bursts (TR-SMBs). This work proposes a new type of Solar Ultra-wide Broadband Millimeter-wave Spectrometer (SUBMS) that can be used to observe TR-SMBs. From SUBMS observations, we can derive rich dynamic information about the transition region, such as information about non-thermal energy release and propagation, the flows of plasma and energetic particles, the magnetic fields and their variations, the generation and transportation of various waves, and the formation and evolution of the source regions of solar eruptions. Such an instrument can actually detect the non-thermal signals in the transition region during no flare as well as the eruptive high-energy processes during solar flares.

Electrically-switched differential microscopy based on computing liquid-crystal platforms

Abstract Detection of transparent phase specimens especially biological cells with desired contrasts is of great importance in visual display and medical diagnosis. Due to the pure-phase nature, conventional detection approaches may damage samples or require complex operations. Computing liquid crystal (LC) is a thin and flat optical element with excellent capability in optical field modulation, which gives a feasible way to this issue from the perspective of analog optical computing. We here propose and experimentally implement an electrically switched two-dimensional (2D) differential microscopy based on computing LC platforms. The Pancharatnam–Berry phase LC polarization grating induces light’s spin separation to promote the 2D differential operation. Using the electrically tunable LC plate as the system phase retardance provider, the detecting mode can be flexibly switched from bright-field images to edge-enhanced images with desired contrasts. Remarkably, owing to the wavelength-independent feature closely related to the geometric phases, our proposed scheme is demonstrated to be applicable to the multi-wavelength microscopy imaging. These results open avenues to form real-time all-optical image processing and may facilitate multifunctional differential microscopy.

Machine-learning-based mapping of blood oxygen saturation from dual-wavelength optoacoustic measurements

We developed a novel machine-learning-based algorithm based on a gradient boosting regressor for three-dimensional pixel-by-pixel mapping of blood oxygen saturation based on dual-wavelength optoacoustic data. Algorithm training was performed on in silico data produced from Monte-Carlo-generated absorbed light energy distributions in tissue-like vascularized media for probing wavelengths of 532 and 1064 nm and the empirical instrumental function of the optoacoustic imaging setup with further validation of the independent in silico data. In vivo optoacoustic data for rabbit-ear vasculature was employed as a testing dataset. The developed algorithm allowed in vivo blood oxygen saturation mapping and showed clear differences in blood oxygen saturation values in veins at 15 °C and 43 °C due to functional arteriovenous anastomoses. These results indicated that dual-wavelength optoacoustic imaging could serve as a cost-effective alternative to complicated multiwavelength quantitative optoacoustic imaging.

Multiple-wavelength range-gated active imaging principle integrating spectral information for five-dimensional imaging.

The combined multiple-wavelength range-gated active imaging (WRAI) principle is able to determine the position of a moving object in a four-dimensional space and to deduce its trajectory and its speed independently of the video frequency. By combining two wavelength categories, it determines the depth of moving objects in the scene with the warm color category and the precise moment of a moving object's position with the cold color category. Therefore, since each object had the ability to transmit information from different wavelengths, related to the spectral reflectances, it became interesting to identify their spectral signatures from these reflectances. Using a conventional method of spectral classification, it was shown that it is possible to identify objects in a 3D scene from their a priori known spectral signatures and, thanks to this, to reveal especially the fifth dimension in the imaging of the WRAI principle. The experimental tests confirmed that it is possible to record moving objects in a five-dimensional space represented by a single image, thus validating this multi-wavelength imaging method.

Gnuastro: Visualizing the Full Dynamic Range in Color Images

Color plays a crucial role in the visualization, interpretation, and analysis of multi-wavelength astronomical images. However, generating color images that accurately represent the full dynamic range of astronomical sources is challenging. In response, Gnuastro v0.22 introduces the program astscript-color-faint-gray, which is extensively documented in the Gnuastro manual. It employs a nonlinear transformation to assign an 8-bit RGB (Red–Green–Blue) value to brighter pixels, while the fainter ones are shown in an inverse grayscale. This approach enables the simultaneous visualization of low surface brightness features within the same image. This research note is reproducible with Maneage, on the Git commit c206945.

Multi-wavelength interference phase imaging for automatic breast cancer detection and delineation using diffuse reflection imaging

Millions of women globally are impacted by the major health problem of breast cancer (BC). Early detection of BC is critical for successful treatment and improved survival rates. In this study, we provide a progressive approach for BC detection using multi-wavelength interference (MWI) phase imaging based on diffuse reflection hyperspectral (HS) imaging. The proposed findings are based on the measurement of the interference pattern between the blue (446.6 nm) and red (632 nm) wavelengths. We consider implementing a comprehensive image processing and categorization method based on the use of Fast Fourier (FF) transform analysis pertaining to a change in the refractive index between tumor and normal tissue. We observed that cancer growth affects tissue organization dramatically, as seen by persistently increased refractive index variance in tumors compared normal areas. Both malignant and normal tissue had different depth data collected from it that was analyzed. To enhance the categorization of ex-vivo BC tissue, we developed and validated a training classifier algorithm specifically designed for categorizing HS cube data. Following the application of signal normalization with the FF transform algorithm, our methodology achieved a high level of performance with a specificity (Spec) of 94% and a sensitivity (Sen) of 90.9% for the 632 nm acquired image categorization, based on preliminary findings from breast specimens under investigation. Notably, we successfully leveraged unstained tissue samples to create 3D phase-resolved images that effectively highlight the distinctions in diffuse reflectance features between cancerous and healthy tissue. Preliminary data revealed that our imaging method might be able to assist specialists in safely excising malignant areas and assessing the tumor bed following resection automatically at different depths. This preliminary investigation might result in an effective "in-vivo" disease description utilizing optical technology using a typical RGB camera with wavelength-specific operation with our quantitative phase MWI imaging methodology.

Towards Mixed-State Coded Diffraction Imaging.

Coherent diffraction imaging (CDI) is a computational technique for reconstructing a complex-valued optical field from an intensity measurement. The approach is to illuminate an object with a coherent beam of light to form a diffraction pattern, and use a phase retrieval algorithm to reconstruct the object's complex transmittance from the measurement. However, as the name implies, conventional CDI assumes highly coherent illumination. Recent works therefore extend CDI to account for partial coherence and imperfect detection, by modeling light as an incoherent mixture of multiple fields (e.g., multiple wavelengths) and recovering each field simultaneously. In this work, we make strides towards the practical implementation and usage of multi-wavelength diffraction imaging. In particular, we provide novel analysis of the noise characteristics of multi-wavelength diffraction imaging, and show that it is preferable to coherent diffraction imaging under high signal-independent noise. Additionally, we present a compact coded diffraction imaging system and corresponding phase retrieval algorithms to robustly and simultaneously recover complex fields representing multiple wavelengths. Using a novel mixed-norm color prior, our prototype system reconstructs a larger number of multi-wavelength fields from fewer measurements than existing methods, and supports applications such as micron-scale optical path difference measurement via synthetic wavelength holography.

Disappearing Galaxies: The Orientation Dependence of JWST-bright, HST-dark, Star-forming Galaxy Selection

Galaxies that are invisible in deep optical–near-infrared imaging but detected at longer wavelengths have been the focus of several recent observational studies, with speculation that they could constitute a substantial missing population and even dominate the cosmic star formation rate density at z ≳ 4. The depths now achievable with JWST at the longest wavelengths probed by the Hubble Space Telescope (HST), coupled with the transformative resolution at longer wavelengths, are already enabling detailed, spatially resolved characterization of sources that were invisible to HST, often known as “HST-dark” galaxies. However, until now, there has been little theoretical work to compare against. We present the first simulation-based study of this population, using highly resolved galaxies from the Feedback in Realistic Environments project, with multiwavelength images along several lines of sight forward-modeled using radiative transfer. We naturally recover a population of modeled sources that meet commonly used selection criteria (H AB > 27 mag and H AB − F444W > 2.3). These simulated HST-dark galaxies lie at high redshifts (z = 4–7), have high levels of dust attenuation (A V = 2–4), and display compact recent star formation (R 1/2,4.4 μm ≲ 1 kpc). Orientation is very important: for all but one of the 17 simulated galaxy snapshots with HST-dark sight lines, there exist other sight lines that do not meet the criteria. This result has important implications for comparisons between observations and models that do not resolve the detailed star-dust geometry, such as semianalytic models or coarsely resolved hydrodynamical simulations. Critically, we demonstrate that HST-dark sources are not an unexpected or exotic population, but a subset of high-redshift, highly dust-attenuated sources viewed along certain lines of sight.

Metasurfaces based terahertz and mid- and long-wave infrared high-efficiency beam splitting devices

The multi-mode composite imaging technology integrates the advantages of different sensors, and thus has the advantages of high image quality, strong information acquisition capability, high target detection and recognition ability, strong adaptability to complex environments, and high stability and robustness of the system. Among them, the terahertz and infrared composite imaging technology combines the characteristics of terahertz band and infrared band, has the advantages of wide spectrum coverage, high resolution and strong penetration, and has broad application prospects. As one of the key components of the common aperture composite imaging system, the efficient optical splitters in terahertz and infrared band are still lacking at present, and their performance needs to be improved urgently. In this paper, a kind of dichroic metasurface with a simple structure and high performance is proposed by combining simulation experiment and theoretical explanation. When used as a spectroscopic device at an incident angle of 45°, it achieves a transmission coefficient greater than 97% near the center frequency of 1.1 THz, and a reflection coefficient greater than 98% in a wavelength range of 3–5 μm for medium-wave infrared and 8–14 μm for long-wave infrared. The design has good robustness to structural mismatches and machining errors such as structural misalignment, structural fillet, small magnification scaling, and polarization insensitivity. When the incident angle changes in a range of 0–60°, the device still maintains excellent spectral characteristics. In this paper, based on Babinet theorem and equivalent circuit model, the electromagnetic response characteristics of the metasurface are analyzed theoretically, and the analysis results are in agreement with the simulation results. The results of this study prove the feasibility of metasurface as a spectral device in the multiwavelength composite imaging system of terahertz and infrared bands, and provide support for future studying new composite imaging detection technology. In addition, the metasurface structure described in this paper has broad application prospects in many fields such as multi-band infrared stealth, laser and pump light separation in lasers, and provides a valuable reference for designing terahertz and infrared spectroscopy in various scenarios. In the following figure, for S wave and P wave at an incident angle of 45°, panel (a) shows the reflection coefficients varying with the wavelength of metasurface and panel (b) displays terahertz transmission coefficient changing with frequency.

NIR-II fluorescence imaging without intended excitation light.

Nowadays, second near-infrared window (NIR-II) dyes are almost excited by laser diodes, but none of the white light (400-700 nm) excited NIR-II imaging has been studied because of the lack of suitable optical probes. Herein, a novel blue-shifted NIR-II dye, TPA-TQT, has been selected for use in multi-wavelength white light emitting diode (LED) excited NIR-II imaging. This white LED barely caused photo-quenching of the dyes, especially indocyanine green (ICG), whereas the ICG's brightness decreased by 90% under continuous 808 nm laser irradiation. Compared to single-wavelength LED, multi-wavelength LED showed a lower background and similar signal-to-background ratios. This system provided high image resolution to identify blood vessels (103 μm), lymphatic capillaries (129.8 μm), and to monitor hindlimb ischemia-reperfusion and lymphatic inflammation. Furthermore, white LED excited NIR-II fluorescence imaging-guided surgery (FIGS) was successfully performed in 4T1 tumor-bearing mice. Impressively, the lighting LED-based NIR-II FIGS was found to clearly delineate small lesions of metastatic tumors of about ∼350 μm diameter and further was able to guide surgical removal. Overall, multi-wavelength LED-based NIR-II imaging is a promising imaging strategy for tumor delineation and other biomedical applications.

Gold nanoparticle-mediated photothermal therapy guidance with multi-wavelength photomagnetic imaging

Difficulty in heating tumors with high spatial selectivity while protecting surrounding healthy tissues from thermal harm is a challenge for cancer photothermal treatment (PTT). To mitigate this problem, PTT mediated by photothermal agents (PTAs) has been established as a potential therapeutic technique to boost selectivity and reduce damage to surrounding healthy tissues. Various gold nanoparticles (AuNP) have been effectively utilized as PTAs, mainly using strategies to target cancerous tissue and increase selective thermal damage. Meanwhile, imaging can be used in tandem to monitor the AuNP distribution and guide the PTT. Mainly, the parameters impacting the induced temperature can be determined using simulation tools before treatment for effective PTT. However, accurate simulations can only be performed if the amount of AuNPs accumulated in the tumor is known. This study introduces Photo-Magnetic Imaging (PMI), which can appropriately recover the AuNP concentration to guide the PTT. Using multi-wavelength measurements, PMI can provide AuNP concentration based on their distinct absorption spectra. Tissue-simulating phantom studies are conducted to demonstrate the potential of PMI in recovering AuNP concentration for PTT planning. The recovered AuNP concentration is used to model the temperature increase accurately in a small inclusion representing tumor using a multiphysics solver that takes into account the light propagation and heat diffusion in turbid media.

Polarization-insensitive dual-wavelength dispersion tunable metalens achieved by global modulation method

Integrating a thermal imaging system equipped with an optical metalens other than a traditional lens into an unmanned aerial vehicle (UAV) will increase its endurance considerably. In the design of metalens, simultaneously controlling dispersion and polarization properties is significant. However, via a propagation phase modulation method in which the phase is tuned locally, it is difficult and time-consuming to obtain enough different nanostructures to control multiwavelength independently while maintain the polarization-insensitive property. To this end, by using a global modulation method, a polarization-insensitive dual-wavelength achromatic and super-chromatic metalens are designed respectively. Only the geometric parameters of two nanofins are required to be optimized (through genetic algorithm) to modulate dual-wavelengths. Then they are superimposed on each other to form cross-shaped meta-atoms. In order to control the influence between the two crossed nanofins, an additional term Δf is introduced into the phase equation to modify the shape of the wavefront, whereby the phase dispersion can be easily engineered. Compared with local modulation, the number of unique nanostructures that need to be optimized can be reduced to two (operating at dual wavelengths) by the Pancharatnam–Berry (PB) phase based global modulation method. Therefore, the proposed design strategy, characterized by its simplicity, efficiency, and timesaver, is expected to circumvent difficulties encountered in the local design approaches. This strategy holds significant potential for widespread applications in multiwavelength imaging and spectroscopy.

Internal Activities in a Solar Filament and Heating in Its Threads

Filaments are one of the most common features in the solar atmosphere and are of significance in solar, stellar, and laboratory plasma physics. Using data from the Chinese Hα Solar Explorer, the Solar Upper Transition Region Imager, and the Solar Dynamics Observatory, we report on multiwavelength imaging and spectral observations of the activation of a small filament. The filament activation produces several localized dynamic brightenings, which are probably produced by internal reconnections of the braided magnetic fields in the filament. The filament expands during the activation, and its threads reconnect with the ambient magnetic fields, which leads to the formation of hot arcades or loops overlying the filament. The thermal energy of each of these localized brightenings is estimated in the order of 1025–1027 erg, and the total energy is estimated to be ∼1.77 × 1028 erg. Our observations demonstrate that the internal magnetic reconnections in the filament can lead to localized heating in the filament threads and prompt external reconnections with ambient corona structures and thus could contribute to the energy and mass transferring into the corona.

Varstrometry for Off-nucleus and Dual Subkiloparsec Active Galactic Nuclei (VODKA): Investigating the Nature of SDSS J0823+2418 at z = 1.81, A Likely Lensed Quasar

Dual quasars at small physical separations are an important precursor phase of galaxy mergers, ultimately leading to the coalescence of the two supermassive black holes. Starting from a sample of dual and/or lensed quasar candidates discovered using astrometric jitter in Gaia data, we present a pilot case study of one of the most promising yet puzzling candidate dual quasars at cosmic noon (z ∼ 1.8). Using multiwavelength imaging and spectroscopy from X-ray to radio, we test whether the SDSS J0823+2418 system is two individual quasars in a bound pair at separation ∼0.″64, or instead a single quasar being gravitationally lensed by a foreground galaxy. We find consistent flux ratios (∼1.25−1.45) between the two sources in optical, near-IR (NIR), UV, and radio, and thus similar spectral energy distributions, suggesting a strong-lensing scenario. However, differences in the radio spectral index, as well as changing X-ray fluxes, hint at either a dual quasar with otherwise nearly identical properties or perhaps lensing-based time lag of ∼3 days paired with intrinsic variability. We find with lens mass modeling that the relative NIR positions and magnitudes of the two quasars and a marginally detected central galaxy are consistent with strong lensing. Archival Sloan Digital Sky Survey spectra likewise suggest a foreground absorber via Mg ii absorption lines. We conclude that SDSS J0823+2418 is likely a lensed quasar, and therefore that the VODKA sample contains a population of these lensed systems (perhaps as high as 50%) as well as dual quasars.

Self-consistent dust and non-LTE line radiative transfer with SKIRT

We introduce Monte-Carlo-based non-local thermodynamic equilibrium (non-LTE) line radiative transfer calculations in the three-dimensional (3D) dust radiative transfer code SKIRT, which was originally set up as a dust radiative transfer code. By doing so, we developed a generic and powerful 3D radiative transfer code that can self-consistently generate spectra with molecular and atomic lines against the underlying continuum. We tested the accuracy of the non-LTE line radiative transfer module in the extended SKIRT code using standard benchmarks. We find excellent agreement between the S KIRT results, the published benchmark results, and the results obtained using the ray-tracing non-LTE line radiative transfer code MAGRITTE, which validates our implementation. We applied the extended SKIRT code on a 3D hydrodynamic simulation of a dusty active galactic nucleus (AGN) torus model and generated multiwavelength images with CO rotational-line spectra against the underlying dust continuum. We find that the low-J CO emission traces the geometrically thick molecular torus, whereas the higher-J CO lines originate from the gas with high kinetic temperature located in the innermost regions of the torus. Comparing the calculations with and without dust radiative transfer, we find that higher-J CO lines are slightly attenuated by the surrounding cold dust when seen edge-on. This shows that atomic and molecular lines can experience attenuation, an effect that is particularly important for transitions at mid- and near-infrared wavelengths. Therefore, our self-consistent dust and non-LTE line radiative transfer calculations can help the observational data from Herschel, ALMA, and JWST be interpreted.

Deep-Learning-Based High-Intensity Focused Ultrasound Lesion Segmentation in Multi-Wavelength Photoacoustic Imaging.

Photoacoustic (PA) imaging can be used to monitor high-intensity focused ultrasound (HIFU) therapies because ablation changes the optical absorption spectrum of the tissue, and this change can be detected with PA imaging. Multi-wavelength photoacoustic (MWPA) imaging makes this change easier to detect by repeating PA imaging at multiple optical wavelengths and sampling the optical absorption spectrum more thoroughly. Real-time pixel-wise classification in MWPA imaging can assist clinicians in monitoring HIFU lesion formation and will be a crucial milestone towards full HIFU therapy automation based on artificial intelligence. In this paper, we present a deep-learning-based approach to segment HIFU lesions in MWPA images. Ex vivo bovine tissue is ablated with HIFU and imaged via MWPA imaging. The acquired MWPA images are then used to train and test a convolutional neural network (CNN) for lesion segmentation. Traditional machine learning algorithms are also trained and tested to compare with the CNN, and the results show that the performance of the CNN significantly exceeds traditional machine learning algorithms. Feature selection is conducted to reduce the number of wavelengths to facilitate real-time implementation while retaining good segmentation performance. This study demonstrates the feasibility and high performance of the deep-learning-based lesion segmentation method in MWPA imaging to monitor HIFU lesion formation and the potential to implement this method in real time.

Multi-wavelength imaging with extended depth of field using coded apertures and radial quartic phase functions

This study demonstrates a new multi-wavelength imaging technique with an extended depth of field. The spatial and spectral information of the objects is encoded into a single bipolar function of sparse dots using coded phase masks (CPMs) and a radial quartic phase function (RQPF). Each wavelength produces an intensity response of sparse dots with a unique set of distances between the dots, enabling the decoding of multispectral information. The RQPF is introduced to extend the depth of focus for different wavelengths. A library of point spread holograms (PSHs) is prerecorded with uniquely designed CPMs by placing the point objects of multiple wavelengths at the system input. For reconstruction, the object hologram is cross-correlated with a PSH corresponding to the wavelength of the object. The results are compared with direct imaging and with the conventional technique of interferenceless coded aperture correlation holography. The method is unique because the number of camera shots required for multi-wavelength imaging is the same as for monochromatic imaging.

Circular ribbon flare triggered from an incomplete fan-spine configuration

Context. Circular ribbon flares are characterised by circular, semi-circular, or elliptical ribbon brightenings. As the physics of such solar events involves a true 3D magnetic topology, they have been extensively studied in contemporary solar research. Aims. In order to understand the triggering processes and the complex magnetic topology involved in circular ribbon flares, we carried out a thorough investigation of an M-class circular ribbon flare that originated within close proximity of a quasi-separatrix layer (QSL). Methods. We combined multi-wavelength Atmospheric Imaging Assembly (AIA) and Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) observations with photospheric Helioseismic and Magnetic Imager (HMI) observations and coronal magnetic field modelling analysis using the non-linear force free field (NLFFF) model. Results. The circular ribbon flare occurred from a complex magnetic configuration characterised by negative magnetic patches surrounded by positive-polarity regions on three sides. As the negative polarity patches were not surrounded by positive-polarity regions on all four sides, the corresponding coronal field was devoid of any null points. This led to the formation of an incomplete fan-spine-like configuration that deviated from classical fan-spine configurations in null-point topology. Further, an observationally identified QSL structure was situated within the active region, very close to the flaring region. The presence of the QSL was verified by the NLFFF modelling. The far end of the spine-like lines terminated very close to one footpoint location of the QSL lines. Our analysis suggests that activities at this location led to the activation of a flux rope situated within the fan-like lines and triggering of the circular ribbon flare via perturbation of the overall fan-spine-like structure. Further, we identified RHESSI X-ray sources from the footpoints of the QSL structure, which suggests that slipping reconnections can also lead to discernible signatures of particle acceleration.