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Between 30% and 50% of white dwarfs (WDs) show heavy elements in their atmospheres. This pollution is thought to arise from the accretion of planetesimals perturbed by outer planet(s) to within the WD's tidal disruption radius. A small fraction of these WDs show either emission or absorption from circumstellar (C-S) gas. The abundances of metals in the photospheres of WDs with C-S gas are mostly similar to the bulk composition of the Earth. The C-S component arises from gas produced through collisions and/or the sublimation of disintegrating planetesimals. High-resolution spectroscopic observations of WD 1124−293 reveal photospheric and C-S absorption of Ca in multiple transitions. Here, we present high signal-to-noise ratio spectra, an updated WD atmosphere analysis, and a self-consistent model of its C-S gas. We constrain the abundances of Ca, Mg, and Fe in the photosphere of WD 1124−293, and find agreement with the abundances of these three species in the C-S gas. We find the location of the C-S gas is ∼100 white dwarf radii, the C-S and photospheric compositions are thus far consistent, the gas is not isothermal, and the amount of C-S Ca has not changed in two decades. We also demonstrate how to use Cloudy to model C-S gas viewed in absorption around polluted WDs. Modeling the abundances of gas around polluted WDs with Cloudy provides a new method to measure the composition of exoplanetesimals and will allow a direct comparison to the composition of rocky bodies in the solar system. [ABSTRACT FROM AUTHOR]

Biological cells estimate concentration gradients of signaling molecules with a precision that is limited not only by sensing noise, but additionally by the cell's own stochastic motion. We ask for the theoretical limits of gradient estimation in the presence of both motility and sensing noise. We introduce a minimal model of a stationary chemotactic agent in the plane subject to rotational diffusion with rotational diffusion coefficient D. The agent uses Bayesian estimation to optimally infer the gradient direction relative to itself from noisy concentration measurements. Meanwhile, this direction changes on a time-scale 1/D. We show that the optimal effective measurement time, which characterizes the time interval over which past gradient measurements should be averaged to reduce sensing noise, does not scale with the rotational diffusion time 1/D, but with the square root (rD)−1/2, where r is a rate of information gain defined as a signal-to-noise ratio normalized per unit time. This result for gradient sensing parallels a recent result by Mora et al (2019 Phys. Rev. Lett.) for sensing absolute concentration in time-varying environments. [ABSTRACT FROM AUTHOR]

In the first paper of this series, we demonstrated that neural networks can robustly and efficiently estimate kinematic parameters for optical emission-line spectra taken by SITELLE at the Canada–France–Hawaii Telescope. This paper expands upon this notion by developing an artificial neural network to estimate the line ratios of strong emission lines present in the SN1, SN2, and SN3 filters of SITELLE. We construct a set of 50,000 synthetic spectra using line ratios taken from the Mexican Million Model database replicating H ii regions. Residual analysis of the network on the test set reveals the network's ability to apply tight constraints to the line ratios. We verified the network's efficacy by constructing an activation map, checking the [ N ii ] doublet fixed ratio, and applying a standard k-fold cross-correlation. Additionally, we apply the network to SITELLE observations of M33; the residuals between the algorithm's estimates and values calculated using standard fitting methods show general agreement. Moreover, the neural network reduces the computational costs by two orders of magnitude. Although standard fitting routines do consistently well depending on the signal-to-noise ratio of the spectral features, the neural network can also excels at predictions in the low signal-to-noise regime within the controlled environment of the training set as well as on observed data when the source spectral properties are well constrained by models. These results reinforce the power of machine learning in spectral analysis. [ABSTRACT FROM AUTHOR]

Imaging surveys of CO and other molecular transition lines are fundamental to measuring the large-scale distribution of molecular gas in the Milky Way. Due to finite angular resolution and sensitivity, however, observational effects are inevitable in the surveys, but few studies are available on the extent of uncertainties involved. The purpose of this work is to investigate the dependence of observations on angular resolution (beam sizes), sensitivity (noise levels), distances, and molecular tracers. To this end, we use high-quality CO images of a large-scale region (25.°8 < l < 49.°7 and ∣b∣ < 5°) mapped by the Milky Way Imaging Scroll Painting (MWISP) survey as a benchmark to simulate observations with larger beam sizes and higher noise levels, deriving corresponding beam filling and sensitivity clip factors. The sensitivity clip factor is defined to be the completeness of observed flux. Taking the entire image as a whole object, we found that 12CO has the largest beam filling and sensitivity clip factors and C18O has the lowest. For molecular cloud samples extracted from images, the beam filling factor can be described by a characteristic size, l1/4 = 0.762 (in beam size), at which the beam filling factor is approximately 1/4. The sensitivity clip factor shows a similar relationship but is more correlated with the mean voxel signal-to-noise ratio of molecular clouds. This result may serve as a practical reference on beam filling and sensitivity clip factors in further analyses of the MWISP data and other observations. [ABSTRACT FROM AUTHOR]

Objective. Fetal heart rate (HR) monitoring is routinely used during pregnancy and labor to assess fetal well-being. The noninvasive fetal electrocardiogram (ECG), obtained by electrodes on the maternal abdomen, is a promising alternative to standard fetal monitoring. Subtraction of the maternal ECG from the abdominal measurements results in fetal ECG signals, in which the fetal HR can be determined typically through R-peak detection. However, the low signal-to-noise ratio and the nonstationary nature of the fetal ECG make R-peak detection a challenging task. Approach. We propose an alternative approach that instead of performing R-peak detection employs deep learning to directly determine the fetal HR from the extracted fetal ECG signals. We introduce a combination of dilated inception convolutional neural networks (CNN) with long short-term memory networks to capture both short-term and long-term temporal dynamics of the fetal HR. The robustness of the method is reinforced by a separate CNN-based classifier that estimates the reliability of the outcome. Main results. Our method achieved a positive percent agreement (within 10% of the actual fetal HR value) of 97.3% on a dataset recorded during labor and 99.6% on set-A of the 2013 Physionet/Computing in Cardiology Challenge exceeding top-performing state-of-the-art algorithms from the literature. Significance. The proposed method can potentially improve the accuracy and robustness of fetal HR extraction in clinical practice. [ABSTRACT FROM AUTHOR]

We report a neutronics study of a blanket mock-up using a discharge-type compact fusion neutron source. Deuterium–deuterium fusion neutrons were irradiated to the mock-ups composed of tritium breeder and neutron reflector/moderator. The tritium production rate (TPR) per source neutron was measured by a single-crystal diamond detector with a 6Li-enriched lithium fluoride film convertor after the calibration process. Despite the low neutron yield, energetic alpha and triton particles via 6Li(n, t)α neutron capture as well as 12C via elastic scattering were successfully detected by the SDD with high signal to noise ratios. The TPRs were experimentally evaluated with errors of 8.4%–8.5% at the 1σ level at the positions with high thermal neutron fluxes where the errors were dominantly introduced by uncertainties in the monitoring of the neutron production rate. The calculated to experimental (C/E) values of TPR were evaluated to be 0.91–1.27 (FENDL-2.1) and 0.94–1.28 (FENDL-3.1). As the neutron source can generate 14 MeV neutrons using a mixed gas of deuterium and tritium, this approach provides more opportunities for blanket neutronics experiments. [ABSTRACT FROM AUTHOR]

Black-holes are known to span at least 9 orders of magnitude in mass: from the stellar-mass objects observed by the Laser Interferometer Gravitational-Wave Observatory Scientific Collaboration and Virgo Collaboration, to supermassive black-holes like the one observed by the Event Horizon Telescope at the heart of M87. Regardless of the mass scale, all of these objects are expected to form binaries and eventually emit observable gravitational radiation, with more massive objects emitting at ever lower gravitational-wave frequencies. We present the tool, gwent , for modeling the sensitivities of current and future generations of gravitational wave detectors across the entire gravitational-wave spectrum of coalescing black-hole binaries (BHBs). We provide methods to generate sensitivity curves for pulsar timing arrays (PTAs) using a novel realistic PTA sensitivity curve generator (Hazboun, Romano and Smith 2019 Phys. Rev. D 100 104028), space-based interferometers using adaptive models that can represent a wide range of proposed detector designs (Amaro-Seoane et al 2017 arXiv:1702.00786), and ground-based interferometers using realistic noise models that can reproduce current (Abbott et al 2016 Phys. Rev. Lett. 116 061102), second, and third generation designs (Hild et al 2011 Class. Quantum Grav. 28 094013), as well as novel variations of the essential design parameters. To model the signal from BHBs at any mass scale, we use phenomenological waveforms capable of modeling the inspiral, merger, and ringdown for sources with varying mass ratios and spins (Khan et al 2016 Phys. Rev. D 93 044007; Husa et al 2016 Phys. Rev. D 93 044006). Using this adaptable framework, we produce signal-to-noise ratios (SNR) for the combination of any modeled parameter, associated with either the detector or the source. By allowing variation across each detector and source parameter, we can pinpoint the most important factors to determining the optimal performance for particular instrument designs. The adaptability of our detector and signal models can easily be extended to new detector designs and other models of gravitational wave signals. [ABSTRACT FROM AUTHOR]

Optical fibre backscatter reflectometry is an important technique for Structural Health Monitoring (SHM). In recent years, increasing the intensity of backscattered light in backscatter reflectometry has shown the advantage of improving the signal detection in shape sensing and temperature detection due to the increase of signal to noise ratio and this approach could potentially be used to improve the performance of an SHM system. Doping nanoparticles (NPs) is a method to increase the intensity of backscattered light in distributed fibre optic sensing. The increased intensity of light backscattered by the NPs needs to be investigated to design suitable optical sensing fibres with NPs for backscatter reflectometry. In this work NPs were added to refractive index matching liquid and tested with commercial NP suspensions experimentally between the tips of two optical fibres. An estimate of the intensity of backscattered light from the NPs in this structure was performed by simulation to give a better understanding of the expected levels of intensities of scattered light from NPs in this distributed fibre optic sensing configuration. We present analytical models based on Mie theory and the Monte Carlo Method. Simulated results are presented, for a broad bandwidth Gaussian spectra shape incident light with a central wavelength around 1550 nm, to match the experimental conditions in this work. The novelty is in developing this model for scattered light by NPs at optical fibre interfaces and the evaluation of the possibility of detection by the calculated scattered intensity levels. [ABSTRACT FROM AUTHOR]

Objective. High-resolution serosal recordings provide detailed information about the bioelectrical conduction patterns in the gastrointestinal (GI) tract. However, equivalent knowledge about the electrical activity through the GI tract wall remains largely unknown. This study aims to capture and quantify the bioelectrical activity across the wall of the GI tract. Approach. A needle-based microelectrode array was used to measure the bioelectrical activity across the GI wall in vivo. Quantitative and qualitative evaluations of transmural slow wave characteristics were carried out in comparison to the serosal slow wave features, through which the period, amplitude, and SNR metrics were quantified and statistically compared. Main results. Identical periods of 4.7 ± 0.3 s with amplitudes of 0.17 ± 0.04 mV versus 0.31 ± 0.1 mV and signal to noise ratios of 5.5 ± 1.3 dB versus 14.4 ± 1.1 dB were observed for transmural and serosal layers, respectively. Four different slow wave morphologies were observed across the transmural layers of the GI wall. Similar amplitudes were observed for all morphology types, and Type 1 and Type 2 were of the highest prevalence, dominating the outer and inner layers. Type 2 was exclusive to the middle layer while Type 4 was primarily observed in the middle layer as well. Significance. This study demonstrates the validity of new methodologies for measuring transmural slow wave activation in the GI wall and can now be applied to investigate the source and origin of GI dysrhythmias leading to dysmotility, and to validate novel therapeutics for GI health and disease. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) on Earth today has biogenic and anthropogenic sources. During the Covid-19 pandemic, observations of global NO2 emissions have shown a significant decrease in urban areas. Drawing upon this example of NO2 as an industrial byproduct, we use a one-dimensional photochemical model and synthetic spectral generator to assess the detectability of NO2 as an atmospheric technosignature on exoplanets. We consider cases of an Earth-like planet around Sun-like, K-dwarf, and M-dwarf stars. We find that NO2 concentrations increase on planets around cooler stars because there are fewer short-wavelength photons that can photolyze NO2. In cloud-free results, present Earth-level NO2 on an Earth-like planet around a Sun-like star at 10 pc can be detected with signal-to-noise ratio ∼5 within ∼400 hr with a 15 m LUVOIR-like telescope when observed in the 0.2–0.7 μm range where NO2 has a strong absorption. However, clouds and aerosols can reduce the detectability and could mimic the NO2 feature. Historically, global NO2 levels were 3× higher, indicating the capability of detecting a civilization at the stage where Earth's civilization was 40 yr ago. Transit and direct imaging observations to detect infrared spectral signatures of NO2 on habitable planets around M-dwarfs would need several hundred hours of observation time, both due to weaker NO2 absorption in this region and because of masking features by dominant H2O and CO2 bands in the infrared part of the spectrum. Non-detection at these levels could be used to place upper limits on the prevalence of NO2 as a technosignature. [ABSTRACT FROM AUTHOR]

Sample selection is a necessary preparation for weak lensing measurement. It is well-known that selection itself may introduce bias to the measured shear signal. Using image simulation and the Fourier_Quad shear measurement pipeline, we quantify the selection bias in various commonly used selection criteria (signal-to-noise ratio, magnitude, etc.). We propose a new selection criterion defined in the power spectrum of the galaxy image. This new selection criterion has a low selection bias, and it is particularly convenient for shear measurement pipelines based on Fourier transformation. [ABSTRACT FROM AUTHOR]

We analyzed archival molecular line data of pre-main-sequence (PMS) stars in the Lupus and Taurus star-forming regions obtained with ALMA surveys with an integration time of a few minutes per source. We stacked the data of 13CO and C18O (J = 2–1 and 3–2) and CN (N = 3–2, J = 7/2–5/2) lines to enhance the signal-to-noise ratios and measured the stellar masses of 45 out of 67 PMS stars from the Keplerian rotation in their circumstellar disks. The measured dynamical stellar masses were compared to the stellar masses estimated from the spectroscopic measurements with seven different stellar evolutionary models. We found that the magnetic model of Feiden provides the best estimate of the stellar masses in the mass range of 0.6 M⊙ ≤ M⋆ ≤ 1.3 M⊙ with a deviation of <0.7σ from the dynamical masses, while all the other models underestimate the stellar masses in this mass range by 20%–40%. In the mass range of <0.6 M⊙, the stellar masses estimated with the magnetic model of Feiden have a larger deviation (>2σ) from the dynamical masses, and other, nonmagnetic stellar evolutionary models of Siess et al., Baraffe et al., and Feiden show better agreement with the dynamical masses with the deviations of 1.4σ–1.6σ. Our results show the mass dependence of the accuracy of these stellar evolutionary models. [ABSTRACT FROM AUTHOR]

Weak gravitational lensing measurements based on photometry are limited by shape noise: the variance in the unknown unlensed orientations of the source galaxies. If the source is a disk galaxy with a well-ordered velocity field, however, velocity field data can support simultaneous inference of the shear, inclination, and position angle, virtually eliminating shape noise. We use the Fisher information matrix formalism to forecast the precision of this method in the idealized case of a perfectly ordered velocity field defined on an infinitesimally thin disk. For nearly face-on targets, one shear component, γ×, can be constrained to , where I0 is the signal-to-noise ratio of the central intensity pixel and npix is the number of pixels across a diameter enclosing 80% of the light. This precision degrades with inclination angle by a factor of 3 by i = 50°. The uncertainty on the other shear component, γ+, is about 1.5 (7) times larger than the γ× uncertainty for targets at i = 10° (50°). For an arbitrary galaxy position angle on the sky, these forecasts apply not to γ+ and γ× as defined on the sky but to two eigenvectors in (γ+, γ×, μ) space, where μ is the magnification. We also forecast the potential of less expensive partial observations of the velocity field, such as slit spectroscopy. We conclude by outlining some ways in which real galaxies depart from our idealized model and thus create random or systematic uncertainties not captured here. In particular, our forecast γ× precision is currently limited only by the data quality rather than scatter in galaxy properties because the relevant type of scatter has yet to be measured. [ABSTRACT FROM AUTHOR]

Positron emission tomography-magnetic resonance (PET-MR) scanners could improve radiotherapy planning through combining PET and MR functional imaging. This depends on acquiring high quality and quantitatively accurate images in the radiotherapy position. This study evaluated PET-MR image quality using a flat couch and coil bridge for pelvic radiotherapy. MR and PET image quality phantoms were imaged in three setups: phantom on the PET-MR couch with anterior coil on top (diagnostic), phantom on a flat couch with coil on top (couch), and phantom on the flat couch with coil on a coil bridge (radiotherapy). PET images were also acquired in each setup without the anterior coil. PET attenuation correction of the flat couch and coil bridge were generated using kilovoltage computed tomography (CT) images and of the anterior coil using megavoltage CT images. MR image quality was substantially affected, with MR signal to noise ratio (SNR) relative to the diagnostic setup of 89% ± 2% (mean ± standard error of the mean, couch) and 54% ± 1% (radiotherapy), likely due to the increased distance between the patient and receive coils. The reduction impacted the low-contrast detectability score: 23 ± 1 (diagnostic), 19.7 ± 0.3 (couch) and 15 ± 1 (radiotherapy). All other MR metrics agreed within one standard error. PET quantitative accuracy was also affected, with measured activity with anterior coil being different to diagnostic without anterior coil by −16.7% ± 0.2% (couch) and −17.7 ± 0.1% (radiotherapy), without attenuation correction modification. Including the couch and coil bridge attenuation correction reduced this difference to −7.5% ± 0.1%, and including the anterior coil reduced this to −2.7% ± 0.1%. This was better than the diagnostic setup with anterior coil (difference −8.3% ± 0.2%). This translated into greater PET SNR performance for the fully corrected radiotherapy setup compared to diagnostic with coil. However contrast recovery was unchanged by the modified attenuation correction, with the diagnostic setup remaining ∼2% better. Quantitative PET in the radiotherapy setup is possible if appropriate attenuation correction is used. Pelvic radiotherapy PET-MR imaging protocols will need to consider the impact on PET-MR image quality. [ABSTRACT FROM AUTHOR]

The quality of reconstructed dynamic PET images, as well as the statistical reliability of the estimated pharmacokinetic parameters is often compromised by high levels of statistical noise, particularly at the voxel level. Many denoising strategies have been proposed, both in the temporal and spatial domain, which substantially improve the signal to noise ratio of the reconstructed dynamic images. However, although most filtering approaches are fairly successful in reducing the spatio-temporal inter-voxel variability, they may also average out or completely eradicate the critically important temporal signature of a transient neurotransmitter activation response that may be present in a non-steady state dynamic PET study. In this work, we explore an approach towards temporal denoising of non-steady state dynamic PET images using an artificial neural network, which was trained to identify the temporal profile of a time-activity curve, while preserving any potential activation response. We evaluated the performance of a feed-forward perceptron neural network to improve the signal to noise ratio of dynamic [11C]raclopride activation studies and compared it with the widely used highly constrained back projection (HYPR) filter. Results on both simulated Geant4 Application for Tomographic Emission data of a realistic rat brain phantom and experimental animal data of a freely moving animal study showed that the proposed neural network can efficiently improve the noise characteristics of dynamic data in the temporal domain, while it can lead to a more reliable estimation of voxel-wise activation response in target region. In addition, improvements in signal-to-noise ratio achieved by denoising the dynamic data using the proposed neural network led to improved accuracy and precision of the estimated model parameters of the lp-ntPET model, compared to the HYPR filter. The performance of the proposed denoising approach strongly depends on the amount of noise in the dynamic PET data, with higher noise leading to substantially higher variability in the estimated parameters of the activation response. Overall, the feed-forward network led to a similar performance as the HYPR filter in terms of spatial denoising, but led to notable improvements in terms of temporal denoising, which in turn improved the estimation activation parameters. [ABSTRACT FROM AUTHOR]

Direct exoplanet spectroscopy aims to measure the spectrum of an exoplanet while simultaneously minimizing the light collected from its host star. Isolating the planet light from the starlight improves the signal-to-noise ratio (S/N) per spectral channel when noise due to the star dominates, which may enable new studies of the exoplanet atmosphere with unprecedented detail at high spectral resolution (>30,000). However, the optimal instrument design depends on the flux level from the planet and star compared to the noise due to other sources, such as detector noise and thermal background. Here we present the design, fabrication, and laboratory demonstration of specially-designed optics to improve the S/N in two potential regimes in direct exoplanet spectroscopy with adaptive optics instruments. The first is a pair of beam-shaping lenses that increase the planet signal by improving the coupling efficiency into a single-mode fiber at the known position of the planet. The second is a grayscale apodizer that reduces the diffracted starlight for planets at small angular separations from their host star. The former especially increases S/N when dominated by detector noise or thermal background, while the latter helps reduce stellar noise. We show good agreement between the theoretical and experimental point spread functions in each case and predict the exposure time reduction (∼33%) that each set of optics provides in simulated observations of 51 Eridani b using the Keck Planet Imager and Characterizer instrument at W. M. Keck Observatory. [ABSTRACT FROM AUTHOR]

Accurate and efficient determination of stellar atmospheric parameters (T eff , logg, [Fe/H]) is essential for large-scale sky survey to conduct Galactic archeology and stellar evolution history. This paper proposes a novel data-driven model based on statistical features and Catboost algorithm (SCDD). The model extracts the statistical features of the spectra by windows, and constructs a nonlinear mapping based on the Catboost algorithm between the spectral features and the stellar parameters. After being trained using LAMOST DR6 spectral data set, the SCDD showed excellent results in the estimation of the stellar parameters. In the condition of that the g-band signal-to-noise ratio (S/Ng) is higher than 100, the root mean square errors (RMSEs) of Teff, logg, and [Fe/H] are 36 K, 0.077 dex and 0.037 dex, respectively. Compared with the StarNet and Cannon2 models, SCDD performs better in mean absolute error and RMSE, which proves its good fitting ability. In addition, this paper compares the parameters estimated by the SCDD with those of APOGEE. The results are in good agreement, which shows that the model we proposed is reliable. [ABSTRACT FROM AUTHOR]

We report the discovery of a 10 comoving megaparsec (cMpc)-scale structure traced by massive submillimeter galaxies (SMGs) at z ∼ 4.6. These galaxies are selected from an emission line search of ALMA Band 7 observations targeting 184 luminous submillimeter sources (S850μm ≥ 6.2 mJy) across 1.6 degrees2 in the COSMOS field. We identify four [C ii ] emitting SMGs and two probable [C ii ] emitting SMG candidates at z = 4.60–4.64 with velocity-integrated signal-to-noise ratio of S/N > 8. Four of the six emitters are near-infrared blank SMGs. After excluding one SMG whose emission line is falling at the edge of the spectral window, all galaxies show clear velocity gradients along the major axes that are consistent with rotating gas disks. The estimated rotation velocities of the disks are 330–550 km s−1 and the inferred host dark-matter halo masses are ∼2–8 × 1012M⊙. From their estimated halo masses and [C ii ] luminosity function, we suggest that these galaxies have a high (50%–100%) duty cycle and high (∼0.1) baryon conversion efficiency (SFR relative to baryon accretion rate), and that they contribute ≃2% to the total star formation rate density at z = 4.6. These SMGs are concentrated within just 0.3% of the full survey volume, suggesting they are strongly clustered. The extent of this structure and the individual halo masses suggest that these SMGs will likely evolve into members of a ∼1015M⊙ cluster at z = 0. This survey reveals a synchronized dusty starburst in massive halos at z > 4, which could be driven by mergers or fed by smooth gas accretion. [ABSTRACT FROM AUTHOR]

As an emerging field in the discipline of optics, plasmonics and metasurfaces have been demonstrated to enable a new degree of freedom to manipulate light for arbitrary beam steering, spectral splitting as well as precise wavefront shaping. However, it has been mostly studied in parallel with the field of diffractive optics, and awaits the unveiling of how the hybridizations between plasmonic effect and diffraction effect interact and impact. Here, we have theoretically proposed a new type of polarization-insensitive meta-grating structure across the broadband visible regime. The structure design combines the width gradient (critical resonant length) from a trapezoid-nanoantenna with the height gradient from a blazed grating profile. The hybridized meta-grating creates both plasmonic effect and grating effect, which enables all the optical incident photons to be directed to the same orientation regardless of the light polarization. As we know, both metasurfaces and diffractive optical elements (such as gratings) are, more often than not, quite sensitive to the incident light polarization. Moreover, if placing our meta-grating on a flexible/stretchable substrate (such as polydimethylsiloxane), the outgoing angle can be effectively adjusted by tuning the period or density of meta-grating arrays. Such meta-grating architectures can be potentially manufactured by existing photolithography and nanoimprint techniques, and can easily find a wide range of practical polarization-insensitive applications, including broadband deflector and emitter, tunable display and imaging device, high signal-to-noise ratio spectrometer, polarization-insensitive plasmonic coupler, etc. [ABSTRACT FROM AUTHOR]

Many deep learning (DL)-based image restoration methods for low-dose CT (LDCT) problems directly employ the end-to-end networks on low-dose training data without considering dose differences. However, the radiation dose difference has a great impact on the ultimate results, and lower doses increase the difficulty of restoration. Moreover, there is increasing demand to design and estimate acceptable scanning doses for patients in clinical practice, necessitating dose-aware networks embedded with adaptive dose estimation. In this paper, we consider these dose differences of input LDCT images and propose an adaptive dose-aware network. First, considering a large dose distribution range for simulation convenience, we coarsely define five dose levels in advance as lowest, lower, mild, higher and highest radiation dose levels. Instead of directly building the end-to-end mapping function between LDCT images and high-dose CT counterparts, the dose level is primarily estimated in the first stage. In the second stage, the adaptively learned low-dose level is used to guide the image restoration process as the pattern of prior information through the channel feature transform. We conduct experiments on a simulated dataset based on original high dose parts of American Association of Physicists in Medicine challenge datasets from the Mayo Clinic. Ablation studies validate the effectiveness of the dose-level estimation, and the experimental results show that our method is superior to several other DL-based methods. Specifically, our method provides obviously better performance in terms of the peak signal-to-noise ratio and visual quality reflected in subjective scores. Due to the dual-stage process, our method may suffer limitations under more parameters and coarse dose-level definitions, and thus, further improvements in clinical practical applications with different CT equipment vendors are planned in future work. [ABSTRACT FROM AUTHOR]

We demonstrate theoretically and experimentally a method to break the Rayleigh limit of an imaging system by modulating only the aperture of the imaging optics. By fully utilizing the useful information extracted from an image sequence, a superresolution image with high-frequency components beyond the cutoff frequency of the imaging system is reconstructed. Resolution enhancement of 2 times is achieved experimentally. Simulation results show that the method can still work with the signal-to-noise ratio of ~ 10 for the acquired images. [ABSTRACT FROM AUTHOR]

Phase modulation is a crucial step when the frequency-based wavefront optimization technique is exploited to measure the optical transmission matrix (TM) of a scattering medium. We report a simple but powerful method, direct digital frequency synthesis (DDS) technology to modulate the phase front of the laser and measure the TM. By judiciously modulating the phase front of a He–Ne laser beam, we experimentally generate a high quality focus at any targeted location through a 2 mm thick 120 grit ground glass diffuser, which is commercially used in laser display and laser holographic display for improving brightness uniformity and reducing speckle. The signal to noise ratio (SNR) of the clear round focus is ∼ 50 and the size is about 44 μm. Our study will open up new avenues for enhancing light energy delivery to the optical engine in laser TV to lower the power consumption, phase compensation to reduce the speckle noise, and controlling the lasing threshold in random lasers. [ABSTRACT FROM AUTHOR]

Using photometry collected with the Zwicky Transient Facility, we are conducting an ongoing survey for binary systems with short orbital periods (with the goal of identifying new gravitational-wave sources detectable by the upcoming Laser Interferometer Space Antenna (LISA). We present a sample of 15 binary systems discovered thus far, with orbital periods ranging from 6.91 to 56.35 minutes. Of the 15 systems, seven are eclipsing systems that do not show signs of significant mass transfer. Additionally, we have discovered two AM Canum Venaticorum systems and six systems exhibiting primarily ellipsoidal variations in their lightcurves. We present follow-up spectroscopy and high-speed photometry confirming the nature of these systems, estimates of their LISA signal-to-noise ratios, and a discussion of their physical characteristics. [ABSTRACT FROM AUTHOR]

Recent developments of x-ray free electron lasers and pulsed electron sources have enabled ultrafast scattering to become an increasingly powerful tool for exploring molecular dynamics. This article describes our recent experimental and methodological advances in ultrafast gas-phase x-ray scattering experiments at the LCLS. A re-designed short-pathlength windowless diffractometer is coupled with careful optimization of sample density and independent normalization of x-ray intensity fluctuations to provide gas-phase scattering patterns with exceptionally high signal-to-noise ratios. These advances, coupled with careful geometry optimization and data treatment, provide both ground- and excited-state signals in excellent agreement with high level ab initio total scattering patterns. [ABSTRACT FROM AUTHOR]

We introduce an example of thermodynamic uncertainty relation (TUR) for systems modeled by a generalised Langevin dynamics with memory, determining the motion of a micro-bead driven in a complex fluid. Contrary to TURs typically discussed in the previous years, our observables and the entropy production rate are one-time variables. The bound to the signal-to-noise ratio (SNR) of such state-dependent observables can only in some cases be mapped to the entropy production rate. For example, this is true for steady states and for a subclass of Markovian systems. In fact, the presence of memory in the system complicates the thermodynamic interpretation of the uncertainty relation. [ABSTRACT FROM AUTHOR]

We present a new constraint on the Lyman continuum (LyC) escape fraction at. We obtain deep, high sensitivity far-UV imaging with the Advanced Camera for Surveys Solar Blind Channel on the Hubble Space Telescope, targeting 11 star-forming galaxies at 1.2 < z < 1.4. The galaxies are selected from the 3D-HST survey to have high Hα equivalent width (EW) with an EW > 190 Å, low stellar mass (M* < 1010M⊙), and U-band magnitude of U < 24.2. These criteria identify young, low metallicity star-bursting populations similar to the early star-forming galaxies believed to have reionized the universe. We do not detect any LyC signal (with a signal-to-noise ratio > 3) in the individual galaxies or in the stack in the far-UV images. We place 3σ limits on the relative escape fraction of individual galaxies to be and a stacked 3σ limit of. Measuring various galaxy properties, including stellar mass, dust attenuation, and star formation rate, we show that our measured values fall within the broad range of values covered by the confirmed LyC emitters from the literature. In particular, we compare the distribution of Hα and [O III ] EWs of confirmed LyC emitters and non-detections, including the galaxies in this study. Finally, we discuss if a dichotomy seen in the distribution of Hα EWs can perhaps distinguish the LyC emitters from the non-detections. [ABSTRACT FROM AUTHOR]

We present a large high-resolution study of the distribution and evolution of C iv absorbers, including the weakest population with equivalent widths. By searching 369 high-resolution, high signal-to-noise ratio spectra of quasars at from Keck/HIRES and VLT/UVES, we find 1268 C iv absorbers with Å (our ∼50% completeness limit) at redshifts. A Schechter function describes the observed equivalent width distribution with a transition from power-law to exponential decline at. The power-law slope α rises by ∼7%, and the transition equivalent width W⋆ falls by ∼20% from to 3.6. We find that the comoving redshift path density, , of Å absorbers rises by ∼1.8 times from z ≃ 4.0 to 1.3, while the Å rises by a factor of ∼8.5. We quantify the observed evolution by a model in which decreases linearly with increasing redshift. The model suggests that populations with larger thresholds evolve faster with redshift and appear later in the universe. The cosmological Technicolor Dawn simulations at z = 3–5 overproduce the observed abundance of absorbers with while yielding better agreement at higher. Our empirical linear model successfully describes C iv evolution in the simulations and the observed evolution of Å C iv for the past. Combining our measurements with the literature gives us a picture of C iv absorbing structures becoming more numerous and/or larger in physical size over the last of cosmic time (z ∼ 6–0). [ABSTRACT FROM AUTHOR]

This study presents a comprehensive chemodynamical analysis of LAMOST J1109+0754, a bright (V = 12.8), extremely metal-poor ([Fe/H] = −3.17) star, with a strong r-process enhancement ([Eu/Fe] = +0.94 ± 0.12). Our results are based on the 7D measurements supplied by Gaia and the chemical composition derived from a high-resolution (R ∼ 110,000), high signal-to-noise ratio (optical spectrum obtained by the 2.4 m Automated Planet Finder Telescope at Lick Observatory. We obtain chemical abundances of 31 elements (from lithium to thorium). The abundance ratios ([X/Fe]) of the light elements (Z ≤ 30) suggest a massive Population III progenitor in the 13.4–29.5 M⊙ mass range. The heavy-element (30 < Z ≤ 90) abundance pattern of J1109+075 agrees extremely well with the scaled-solar r-process signature. We have developed a novel approach to trace the kinematic history and orbital evolution of J1109+0754 with a cOsmologically deRIved timE-varyiNg Galactic poTential (the ORIENT) constructed from snapshots of a simulated Milky Way analog taken from the Illustris-TNG simulation. The orbital evolution within this Milky Way–like galaxy, along with the chemical abundance pattern, implies that J1109+0754 likely originated in a low-mass dwarf galaxy located ∼60 kpc from the center of the Galaxy, which was accreted ∼6–7 Gyr ago, and that the star now belongs to the outer-halo population. [ABSTRACT FROM AUTHOR]

In this work we model the noise properties of a computed radiography (CR) mammography system by adding an extra degree of freedom to a well-established noise model, and derive a variance-stabilizing transform (VST) to convert the signal-dependent noise into approximately signal-independent. The proposed model relies on a quadratic variance function, which considers fixed-pattern (structural), quantum and electronic noise. It also accounts for the spatial-dependency of the noise by assuming a space-variant quantum coefficient. The proposed noise model was compared against two alternative models commonly found in the literature. The first alternative model ignores the spatial-variability of the quantum noise, and the second model assumes negligible structural noise. We also derive a VST to convert noisy observations contaminated by the proposed noise model into observations with approximately Gaussian noise and constant variance equals to one. Finally, we estimated a look-up table that can be used as an inverse transform in denoising applications. A phantom study was conducted to validate the noise model, VST and inverse VST. The results show that the space-variant signal-dependent quadratic noise model is appropriate to describe noise in this CR mammography system (errors< 2.0% in terms of signal-to-noise ratio). The two alternative noise models were outperformed by the proposed model (errors as high as 14.7% and 9.4%). The designed VST was able to stabilize the noise so that it has variance approximately equal to one (errors< 4.1%), while the two alternative models achieved errors as high as 26.9% and 18.0%, respectively. Finally, the proposed inverse transform was capable of returning the signal to the original signal range with virtually no bias. [ABSTRACT FROM AUTHOR]

X-ray CT polymer gel dosimetry (PGD) remains a promising tool for three dimensional verification of high-dose treatment deliveries such as non-coplanar stereotactic irradiations. Recent demonstrations have shown a proof-of-principle application of linac-integrated cone beam CT-imaged (LI-CBCT) PGDs for 3D dose verification. LI-CBCT offers advantages over previous CT based PGD, including close to real-time imaging of the irradiated dosimeter, as well as the ability to maintain the dosimeter in the same physical location for irradiation and imaging, thereby eliminating spatial errors due to dosimeter re-positioning for read-out that may occur for other systems. However the dosimetric characteristics of a LI-CBCT PGD system remain to be established. The work herein determines the dosimetric properties and critical parameters needed to perform cone beam PGD. In particular, we show that imaging the dosimeter 20–30 min post irradiation offers excellent recovery of maximum polymerization yield (90%), averaging with as few as 10 image averages can provide ∼90% gamma pass rates (3%, 3 mm) as compared to treatment planning, and that eliminating outlier averaging points can improve the precision and signal to noise ratio of resultant images. In summary, with appropriate methodology LI-CBCT PGD can provide dosimetric data capable of verification of complex high dose radiation deliveries in three dimensions and may find use in commissioning and validation of novel complex treatments. [ABSTRACT FROM AUTHOR]

We developed a deep convolutional neural network (CNN) based method to remove streaking artefact from accelerated radial acquisitions of myocardial T1-mapping images. A deep CNN based on a modified U-Net architecture was developed and trained to remove the streaking artefacts from under-sampled T1 mapping images. A total of 2090 T1-weighted images for 33 patients (55 ± 15 years, 19 males) and five healthy subjects (30 ± 14 years, 2 males) were used for training and testing the network. The images were acquired using radial slice interleaved T1 mapping sequence (STONE) and retrospectively under-sampled to achieve acceleration rate of 4 (corresponding to 48 spokes). The dataset was split into training and testing subsets with 23 subjects (60%) and 15 subjects (40%), respectively. For generating voxel-wise T1 maps, a two-parameter fitting model was used. Network performance was evaluated using normalized mean square error (NMSE), structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) metrics. The proposed network allowed fast (<0.3 s/image) removal of the artefact from all T1-weighted testing images and the corresponding T1 maps with PSNR = 64.3 ± 1.02, NMSE = 0.2 ± 0.09 and SSIM = 0.9 ± 0.3 × 10−4. There was no statistically significant difference between the measured T1 maps for both per-subject (reference: 1085 ± 37 ms, CNN: 1088 ± 37 ms, p = 0.4) and per-segment (reference: 1084 ± 48 ms, CNN: 1083 ± 58 ms, p = 0.9) analyses. In summary, deep CNN allows fast and reliable removal of streaking artefact from under-sampled radial T1 mapping images. Our results show that the highly non-linear operations of deep CNN processing of T1 mapping images do not impact accurate reconstruction of myocardial T1 maps. [ABSTRACT FROM AUTHOR]

This work compared the impact of x-ray tube performance and automatic dose rate control (ADRC) parameter selection on system imaging efficiency of two Siemens angiography systems: a Siemens Megalix x-ray tube installed on an Artis Zee system (denoted 'MEGALIX') and a newer generation Gigalix x-ray tube installed on an Artis Q (denoted 'GIGALIX'). A method was used that accounted for two potential sources of bias in this comparison: differences in radiation output between the x-ray tubes and differences between the x-ray detectors on the two systems. First, ADRC x-ray factors (tube voltage, tube current, pulse length, focus size, spectral prefilter) and radiation output were recorded as a function of poly(methyl) methacrylate (PMMA) thickness on the MEGALIX unit. These factors were then applied manually on the GIGALIX system and incident air kerma rate (IAKR) and signal difference to noise ratio (SDNR) were measured. Second, the ADRC on the GIGALIX system was used to give the x-ray factors and both IAKR and SDNR relevant to the GIGALIX based system directly. This method enabled the SDNR to be measured from images acquired on the same x-ray detector. SDNR and IAKR were measured on both systems using a PMMA phantom covering thicknesses from 6 cm to 40 cm. A small 0.3 mm iron insert was used to measure SDNR, which was then multiplied by modulation transfer function based weighting factors for focal spot blurring and motion blurring. These factors were evaluated for an object motion of 25 mm s−1 and at a spatial frequency of 1.4 mm−1 in the object plane, relevant to interventional cardiology, giving a spatial frequency dependent SDNR(u). In the second phase of the study, a technical figure of merit (FOM) was used to express imaging performance of both systems, calculated as SDNR2(u)/IAKR. Averaged over all phantom thicknesses, the FOM of the GIGALIX-based system was 42% and 73% higher compared to that of the MEGALIX based system, for fluoroscopy and acquisition mode respectively. The results indicate that increased x-ray tube power and smaller foci can improve overall system efficiency and reduce doses. [ABSTRACT FROM AUTHOR]

We present a method by which multi-harmonic signals acquired during a normal tapping mode (amplitude modulated) AFM scan of a sample in air or vacuum with standard microcantilevers can be used to map quantitatively the local mechanical properties of the sample such as elastic modulus, adhesion, and indentation. The approach is based on the observation that during the tapping mode operation in air or vacuum, the 0th and 2nd harmonic signals of microcantilever vibration are encountered under most operating conditions and can be mapped with sufficient signal to noise ratio. By measuring the amplitude and phase of the driven harmonic as well as the 0th and 2nd harmonic observables, we find analytical/semi-analytical formulas that relate these multi-harmonic observables to local mechanical properties for several classical tip-sample interaction models. Least squares estimation of the local mechanical properties is performed pixel by pixel. The method is validated through computations as well as experimental data acquired on a polymer blend made of Polystyrene and Polyolefin elastomer. [ABSTRACT FROM AUTHOR]

We describe the first spectroscopic tomographic (spectrotomographic) weak-lensing measurement for a galaxy cluster based only on background galaxies with spectroscopically determined redshifts. We use the massive cluster A2029 to demonstrate the power of combining spectroscopy and lensing to obtain accurate masses and to overcome biases from contamination and photometric redshift errors. We detect the shear signal from the cluster at > 3.9σ significance. The shear signal scales with source redshift in a way that is consistent with the angular diameter distance ratio variation in a ΛCDM universe. Furthermore, the amplitude of the measured signal is consistent with the X-ray mass. Upcoming spectroscopic instruments such as the Prime Focus Spectrograph on Subaru will permit spectrotomographic weak-lensing measurements with a signal-to-noise ratio comparable with current photometric-redshift-based weak-lensing measurements for hundreds of galaxy clusters. Thus, spectrotomography may enable sensitive cosmological constraints that complement and are independent of other measurement techniques. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to explore the use of a logarithmic amplifier to improve the spatial resolution (RES) of a low-cost electrical impedance tomography (EIT) system. In an EIT system, the measured signal has a large dynamic range from µV to mV, which requires high-RES (analog to digital conversion) cards. The logarithmic amplifier reduces the dynamic range by expanding lower values and compressing higher values, thereby improving the sensitivity and at the same time preventing the signal from saturation. In addition, a low-RES analog to digital conversion (ADC) cards can be used, making the system cost effective. This work evaluates the performance of a logarithmic amplifier and a linear amplifier used for signal conditioning in a low-cost EIT system. Approach: Two EIT systems based on a linear amplifier and logarithmic amplifier were designed. Phantom experiments were carried out with very small amounts of current injection. The signal-to-noise ratio (SNR), image quality, minimum detectable size and minimum detectable conductivity change were obtained. Main results: The logarithmic amplifier-based EIT system increased the average SNR by 4 dB. It also showed improvement in the RES and contrast-to-noise ratio of the images. The minimum size detectable by the logarithmic amplifier-based system was of radius 0.25 cm in a tank of radius 11 cm and the minimum change in conductivity detectable was 11%. Significance: Logarithmic amplifier-based signal conditioning is a promising technique for improving the spatial RES of a low-cost EIT system that has a low-RES ADC. [ABSTRACT FROM AUTHOR]

High impedance coils (HICs) are suitable as a building block of receive arrays for MRI-guided radiotherapy (MRIgRT) as HICs do not require radiation-attenuating capacitors and dense support materials. Recently, we proved the feasibility of using HICs to create a radiation transparent (i.e. radiolucent) window. In this work, we constructed a fully functional 32-channel array based on this design. The anterior element is flexible and follows the shape of the subject, while the posterior element is rigid to support the subject. Both elements feature a 2 × 8 channel layout. Here, we discuss the construction process and characterize the array's radiolucency and imaging performance. The dosimetric impact of the array was quantified by assessing the surface dose increase and attenuation of a single beam. The imaging performance of the prototype was compared to the clinical array in terms of visual appearance, signal-to-noise ratio (SNR), and acceleration performance, both in phantom and in-vivo measurements. Dosimetry measurements showed that on-body placement changed the anterior and posterior surface dose by +3% and −16% of the dose maximum. Attenuation under the anterior support materials and conductors was 0.3% and ≤1.5%, respectively. Phantom and in-vivo imaging with this array demonstrated an improvement of the SNR at the surface and the image quality in general. Simultaneous irradiation did not affect the SNR. G-factors were reduced considerably and clinically used sequences could be accelerated by up to 45%, which would greatly reduce pre-beam imaging times. Finally, the maximally achievable temporal resolution of abdominal 3D cine imaging was improved to 1.1 s, which was > 5 × faster than could be achieved with the clinical array. This constitutes a big step towards the ability to resolve respiratory motion in 3D. In conclusion, the proposed 32-channel array is compatible with MRIgRT and can significantly reduce scan times and/or improve the image quality of all on-line scans. [ABSTRACT FROM AUTHOR]

Mass transfer in an interacting binary will often strip the mass donor of its entire envelope and spin up the mass gainer to near critical rotation. The nearby B-type star Regulus represents a binary in the post-mass transfer stage: it is a rapid rotator with a very faint companion in a 40 days orbit. Here we present the results of a search for the spectral features of the stripped-down star in an extensive set of spectra with high signal-to-noise ratio and high resolution obtained with the CFHT/ESPaDOnS and TBL/NARVAL spectrographs. We first determine revised orbital elements in order to set accurate estimates of the orbital Doppler shifts at the times of observation. We then calculate cross-correlation functions of the observed and model spectra, and we search for evidence of the companion signal in the residuals after removal of the strong primary component. We detect a weak peak in the co-added residuals that has the properties expected for a faint pre-white dwarf. We use the dependence of the peak height and width on assumed secondary velocity semiamplitude to derive the semiamplitude, which yields masses of M1/M⊙ = 3.7 ± 1.4 and M2/M⊙ = 0.31 ± 0.10 (assuming orbital inclination equals the spin inclination of Regulus). We estimate the temperature of the pre-white dwarf Teff = (20 ± 4) kK through tests with differing temperature model spectra, and we find the radius R2/R⊙ = 0.061 ± 0.011 from the component temperatures and the flux ratio associated with the amplitude of the signal in the cross-correlation residuals. [ABSTRACT FROM AUTHOR]

A novel design method for a fiber-optic Fabry–Perot (FP) acoustic sensor based on a flywheel-like diaphragm has been proposed and experimentally demonstrated. Through theory analysis and simulation, we have established a sensing model based on the flywheel-like diaphragm and illustrated the acoustic sensor's resonant frequency regulation method. A flywheel-like diaphragm-based acoustic sensor has been fabricated and a dual-wavelength system is used to demodulate the phase fluctuation caused by the acoustic wave. Experimental results show that the proposed acoustic sensor has an acoustic pressure sensitivity of 1.3967 rad Pa−1 and noise-limited minimum detectable pressure of. The signal to noise ratio (SNR) of 1 kHz, 9 kHz, and 20 kHz are achieved to be 10.39 dB, 60.51 dB, and 37.14 dB, respectively. Over a fairly broad response range (1 kHz to 20 kHz), the average SNR is up to 45.57 dB. Moreover, our acoustic sensor's directivity map approximates to a heart shape. Its excellent frequency response characteristics, sensitivity, and directivity pattern are believed to have bright application prospects. [ABSTRACT FROM AUTHOR]

Over the last 30 years, there have been dramatic changes in phased array coil technology leading to increasing channel density and parallel imaging functionality. Current receiver array coils are rigid and often mismatched to patient's size. Recently there has been a move towards flexible coil technology, which is more conformal to the human anatomy. Despite the advances of so-called flexible surface coil arrays, these coils are still relatively rigid and limited in terms of design conformability, compromising signal-to-noise ratio (SNR) for flexibility, and are not designed for optimum parallel imaging performance. The purpose of this study is to report on the development and characterization of a 15-channel flexible foot and ankle coil, rapidly designed and constructed using highly decoupled radio-frequency (RF) coil elements. Coil performance was evaluated by performing SNR and g-factor measurements. In vivo testing was performed in a healthy volunteer using both the 15-channel coil and a commercially available 8-channel foot coil. The highly decoupled elements used in this design allow for extremely rapid development and prototyping of application-specific coils for different patient sizes (adult vs child) with minimal additional design consideration in terms of coil overlap and geometry. Image quality was comparable to a commercially available RF coil. [ABSTRACT FROM AUTHOR]

Methods for source detection in high noise environments are important for single-photon emission computed tomography medical imaging and especially crucial for homeland security applications, which is our main interest. In the latter case, one deals with passively detecting the presence of low emission nuclear sources with significant background noise (with signal to noise ratio 1% or less). In passive emission problems, direction sensitive detectors are needed, to match the dimensionalities of the image and the data. Collimation, used for that purpose in standard Anger γ-cameras, is not an option. Instead, Compton γ-cameras (and their analogs for other types of radiation) can be utilized. Backprojection methods suggested before by two of the authors and their collaborators enable detection in the presence of a random uniform background. In most practical applications, however, cargo packing in shipping containers and trucks creates regions of strong absorption and scattering, while leaving some streaming gaps open. In such cases backprojection methods prove ineffective and lose their detection ability. Nonetheless, visual perception of the backprojection pictures suggested that some indications of presence of a source might still be in the data. To learn such features (if they do exist), a deep neural network approach is implemented in 2D, which indeed exhibits higher sensitivity and specificity than the backprojection techniques in a low scattering case and works well when presence of complex cargo makes backprojection fail completely. [ABSTRACT FROM AUTHOR]

Spectroscopy is a powerful tool for detecting variability in the rapidly oscillating Ap (roAp) stars. The technique requires short integrations times and high resolution, and so is limited to only a few telescopes and instruments. To test the capabilities of the High Resolution Spectrograph (HRS) at the Southern African Large Telescope (SALT) for the study of pulsations in roAp stars, we collected 2.45 hr of high-resolution data of the well studied roAp star α Cir in a previously unused instrument configuration. We extracted radial velocity measurements using different rare earth elements, and the core of Hα, via the cross correlation method. We performed the same analysis with a set of α Cir data collected with the High Accuracy Radial velocity Planet Searcher spectrograph to provide a benchmark for our SALT HRS test. We measured significant radial velocity variations in the HRS data and show that our results are in excellent agreement between the two data sets, with similar signal-to-noise ratio detections of the principal pulsation mode. With the HRS data, we report the detection of a second mode, showing the instrument is capable of detecting multiple and low-amplitude signals in a short observing window. We concluded that SALT HRS is well-suited for characterizing pulsations in Ap stars, opening a new science window for the telescope. Although our analysis focused on roAp stars, the fundamental results are applicable to other areas of astrophysics where high temporal and spectral resolution observations are required. [ABSTRACT FROM AUTHOR]

A third object in the vicinity of a binary system causes variations in the eccentricity and the inclination of the binary through the Kozai–Lidov (KL) effect. We examine if such variations leave a detectable imprint on the gravitational waves of a binary consisting of intermediate-mass black holes and stellar-mass objects. As a proof of concept, we present an example where LISA may detect the KL-modulated gravitational wave signals of such sources from at least a distance of 1 Mpc if the perturbation is caused by a supermassive black hole tertiary. Although the quick pericenter precession induced by general relativity significantly reduces the appropriate parameter space for this effect by quenching the KL oscillations, we still find reasonable parameters where the KL effect may be detected with high signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

A traditional single-pixel camera needs a large number of measurements to reconstruct the object with compressive sensing computation. Compared with the 1/0 matrices in classical measurement, the 1/−1 matrices in the complementary measurement has better property for reconstruction computation and returns better reconstruction results. However, each row of the 1/−1 matrices needs two measurements with the traditional single-pixel camera which results into double measurements compared with the 1/0 matrices. In this paper, we consider the pseudo complementary measurement which only takes the same amount of measurements with the row number of some properly designed 1/0 matrix to compute the total luminous flux of the objective and derives the measurement data of the corresponding 1/−1 matrix in a mathematical way. The numerical simulation and experimental result show that the pseudo complementary measurement is an efficient tool for the traditional single-pixel camera imaging under low measurement rate, which can combine the advantages of the classical and complementary measurements and significantly improve the peak signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

This paper expands the linear iterative near-field phase retrieval (LIPR) formalism to achieve quantitative material thickness decomposition. Propagation-based phase contrast x-ray imaging with subsequent phase retrieval has been shown to improve the signal-to-noise ratio (SNR) by factors of up to hundreds compared to conventional x-ray imaging. This is a key step in biomedical imaging, where radiation exposure must be kept low without compromising the SNR. However, for a satisfactory phase retrieval from a single measurement, assumptions must be made about the object investigated. To avoid such assumptions, we use two measurements collected at the same propagation distance but at different x-ray energies. Phase retrieval is then performed by incorporating the Alvarez-Macovski (AM) model, which models the x-ray interactions as being comprised of distinct photoelectric and Compton scattering components. We present the first application of dual-energy phase retrieval with the AM model to monochromatic experimental x-ray projections at two different energies for obtaining split x-ray interactions. Our phase retrieval method allows us to separate the object investigated into the projected thicknesses of two known materials. Our phase retrieval output leads to no visible loss in spatial resolution while the SNR improves by factors of 2 to 10. This corresponds to a possible x-ray dose reduction by a factor of 4 to 100, under the Poisson noise assumption. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated the feasibility of reducing noise with deep learning-based methods for low-dose fluorodeoxyglucose (FDG) positron emission tomography (PET). This work aimed to investigate the feasibility of noise reduction for tracers without sufficient training datasets using a deep transfer learning approach, which can utilize existing networks trained by the widely available FDG datasets. In this study, the deep transfer learning strategy based on a fully 3D patch-based U-Net was investigated on a 18F-fluoromisonidazole (18F-FMISO) dataset using single-bed scanning and a 68Ga-DOTATATE dataset using whole-body scanning. The datasets of 18F-FDG by single-bed scanning and whole-body scanning were used to obtain pre-trained U-Nets separately for subsequent cross-tracer and cross-protocol transfer learning. The full-dose PET images were used as the labels while low-dose PET images from 10% counts were used as the inputs. Three types of U-Nets were obtained: a U-Net trained by FDG dataset, a pre-trained FDG U-Net fine-tuned by another less-available tracer (FMISO/DOATATE), and a U-Net completely trained by a large number of less-available tracer datasets (FMISO/DOATATE), used as the reference U-Net. The denoising performance of the three types of U-Nets was evaluated on single-bed 18F-FMISO and whole-body 68Ga-DOTATATE separately and compared using normalized root-mean-square error (NRMSE), signal-to-noise ratio (SNR), and relative bias of region of interest (ROI). For cross-tracer transfer learning, all the U-Nets provided denoised images with similar quality for both tracers. There was no significant difference in terms of NRMSE and SNR when comparing the former two U-Nets with the reference U-Net. The ROI biases for these U-Nets were similar. For cross-tracer and cross-protocol transfer learning, the pre-trained single-bed FDG U-Net fine-tuned by whole-body DOTATATE data provided the most consistent images with the reference U-Net. Fine-tuning significantly reduced the NRMSE and the ROI bias and improved the SNR when comparing the fine-tuned U-Net with the U-Net trained by single-bed FDG only (NRMSE: 96.3% ± 21.1% versus 120.6% ± 18.5%, ROI bias: −10.5% ± 13.0% versus −14.7% ± 6.4%, SNR: 4.2 ± 1.4 versus 3.9 ± 1.6, for fine-tuned U-Net and the U-Net trained by single-bed FDG, respectively, with p < 0.01 in all cases). This work demonstrated that it is feasible to utilize existing networks well-trained by FDG datasets to reduce the noise for other less-available tracers and other scanning protocols by using the fine-tuning strategy. [ABSTRACT FROM AUTHOR]

In this paper, a nonuniform projection distribution (NUPD) CT method is proposed for the region-of-interest-specific examination in the solitary lung nodule follow-up application in order to reduce redundant x-ray projections exposed on normal tissues. The method exploits personal previous lung CT scan information to design a nonuniform x-ray projection modulation scheme where x-rays are sparsely modulated over the areas outside of the nodule in each projection view. The nonuniform projection modulation scheme could obstruct 71.84% of the x-ray projections within each scanning view in the case of a 40-mm-diameter region of interest of a solitary lung nodule, and eventually, 96.80% of the x-ray projections are eliminated in a complete circular scan in cooperation with the double sparse sampling protocol. We also devise a prior image-guided patchwise low-rank reconstruction in NUPD CT to improve the imaging quality. The proposed reconstructions have the highest Peak Signal to Noise Ratio values compared with other methods for both the full field of view (FOV) and region of interest (ROI). The structural similarities with the references are 0.9922 for the complete FOV and above 0.9999 for the ROI. [ABSTRACT FROM AUTHOR]

Shapiro time delay is one of the fundamental tests of general relativity and post-Newtonian theories of gravity. Consequently, its measurements can be used to probe the parameter γ which is related to spacetime curvature produced by a unit mass in the post-Newtonian formalism of gravity. To date all measurements of time delay have been conducted on astronomical scales. It was asserted in 2010 that gravitational wave detectors on Earth could be used to measure Shapiro delay on a terrestrial scale via massive rotating systems. Building on that work, we consider how measurements of Shapiro delay can be made using next-generation gravitational wave detectors. We perform an analysis for measuring Shapiro delay with the next-generation gravitational wave detectors Cosmic Explorer and Einstein Telescope to determine how precisely the effect can be measured. Using a rotating mass unit design, we find that Cosmic Explorer and Einstein Telescope can measure the Shapiro delay signal with amplitude signal to noise ratios upwards of ∼28 and ∼43 in 1 year of integration time, respectively. By measuring Shapiro delay with this technique, next-generation interferometers will allow for terrestrial measurements of γ in the paramaterized post-Newtonian formalism of gravity with sub-percent precision. [ABSTRACT FROM AUTHOR]

Scalar, tensor waves induce oscillatory perturbations in Keplerian systems that can be probed with measurements of pulsar timing residuals. In this paper, we consider the imprint of coherent oscillations produced by ultralight axion dark matter on the Roemer time delay. We use the angle-action formalism to calculate the time evolution of the observed signal and its dependence on the orbital parameters and the axion phase. We derive exact analytical expressions for arbitrary binary pulsar mass ratio and eccentricity, alleviating the need for long numerical integrations. We emphasize the similarity of the expected signal-to-noise ratio with the response of a harmonic oscillator to an external oscillatory driving. We validate our theoretical predictions with numerical simulations. Our results furnish a useful benchmark for numerical codes and analysis procedures and, hopefully, will motivate the search for such imprints in real data. [ABSTRACT FROM AUTHOR]

The cosmic infrared background (CIB) anisotropies and cosmic microwave background (CMB) lensing are powerful measurements for exploring cosmological and astrophysical problems. In this work, we measure the autocorrelation power spectrum of the CIB anisotropies in the Herschel–SPIRE HerMES Large Mode Survey (HeLMS) field, and the cross-power spectrum with the CMB lensing measurements from the Planck satellite. The HeLMS field covers more than 270 deg2, which is much larger than in previous analysis. We use the Herschel Level 1 time stream data to merge the CIB maps at 250, 350, and 500 μm bands, and mask the areas where the flux is greater than or there are no measured data. We obtain the final CIB power spectra at 100 ≤ ℓ ≤ 20,000 by considering several effects, such as beam function, mode coupling, transfer function, and so on. We also calculate the theoretical CIB auto- and cross-power spectra of CIB and CMB lensing by assuming that the CIB emissivity follows a Gaussian distribution in redshift. We find that, for the CIB auto-power spectra, we obtain signal-to-noise ratios (S/Ns) of 15.9, 15.7, and 15.3 at 250, 350, and 500 μm, and for the CIB ⨯ CMB lensing power spectra, S/Ns of 7.5, 7.0, and 6.2 at 250, 350, and 500 μm, respectively. Comparing to previous works, the constraints on the relevant CIB parameters are improved by factors of 2– 5 in this study. [ABSTRACT FROM AUTHOR]

Simultaneous recording of large-scale neural network activity in vivo is essential for unraveling fundamental processing mechanisms in the brain. For such applications, optical imaging becomes indispensable because it is minimally-invasive, allows flexible recording characteristics, and provides high signal-to-noise ratio. However, physical limitations hinder the pursuit of increasing the imaging scale, speed, and penetration depth for increasing this method's applicability for the growing field of neuroscience. In this review, we first summarize the practical requirements and limitations in current functional imaging systems, followed by a review of the latest hardware developments to supercede current limitations, specifically for the widely adopted multiphoton microscopy. We then introduce advances in point-spread-function (PSF) engineering, i.e. the manipulation of the microscope's PSF, and discuss the possibility of integrating computational approaches together with PSF engineering to further enhance performance. We expect that future integration of computational imaging and advanced optical methods will be adopted to meet the emerging requirements of modern neuroscience. [ABSTRACT FROM AUTHOR]