Spectral Mapping Research Articles

Linear Combination of Hamiltonian Simulation for Nonunitary Dynamics with Optimal State Preparation Cost.

We propose a simple method for simulating a general class of nonunitary dynamics as a linear combination of Hamiltonian simulation (LCHS) problems. LCHS does not rely on converting the problem into a dilated linear system problem or on the spectral mapping theorem. The latter is the mathematical foundation of many quantum algorithms for solving a wide variety of tasks involving nonunitary processes, such as the quantum singular value transformation. The LCHS method can achieve optimal cost in terms of state preparation. We also demonstrate an application for open quantum dynamics simulation using the complex absorbing potential method with near-optimal dependence on all parameters.

Spectral mapping theorems for essential spectra and regularized functional calculi

Gramsch and Lay [8] gave spectral mapping theorems for the Dunford-Taylor calculus of a closed linear operator $T$ , \[ \widetilde{\sigma}_i(f(T)) = f(\widetilde{\sigma}_i(T)), \] for several extended essential spectra $\widetilde {\sigma }_i$ . In this work, we extend such theorems for the regularized functional calculus introduced by Haase [10, 11] assuming suitable conditions on $f$ . At the same time, we answer in the positive a question made by Haase [11, Remark 5.4] regarding the conditions on $f$ which are sufficient to obtain the spectral mapping theorem for the usual extended spectrum $\widetilde \sigma$ . We use the model case of bisectorial-like operators, although the proofs presented here are generic, and are valid for similar functional calculi.

Photoluminescence, Reflection Contrast, Raman, and Second Harmonic Generation Spectroscopies Spatially Resolve Strain, Alloying, Defects, and Electronic Characteristics of Lateral MX2 Heterostructures.

Lateral heterostructures of two-dimensional (2D) transition metal dichalcogenides offer promise as platforms for a wide variety of applications from exotic physics to environmental control. Further development and study of these heterostructures require characterization methods that assess the quality of the heterostructures. Here, we extend current characterization strategies to create photoluminescence (PL), Raman, reflection contrast, and second harmonic generation (SHG) maps of individual monolayer core-shell WS2-MoS2 lateral heterostructures that were synthesized via water vapor assisted chemical vapor transport. Together, these methods provide the correlations required to resolve the effects of excitons, trions, lattice defects, strain, and alloying. The comparisons show substantial differences, especially in the regions near and at the narrow heterointerface. Comparisons between the different spectral maps show the importance of metal alloying for understanding the electronic and spatial structures of heterostructures. The results are compared to previous work on similar lateral heterostructures created by different methods.

Developmental changes in endogenous testosterone have sexually-dimorphic effects on spontaneous cortical dynamics.

The transition from childhood to adolescence is associated with an influx of sex hormones, which not only facilitates physical and behavioral changes, but also dramatic changes in neural circuitry. While previous work has shown that pubertal hormones modulate structural and functional brain development, few of these studies have focused on the impact that such hormones have on spontaneous cortical activity, and whether these effects are modulated by sex during this critical developmental window. Herein, we examined the effect of endogenous testosterone on spontaneous cortical activity in 71 typically-developing youth (ages 10-17 years; 32 male). Participants completed a resting-state magnetoencephalographic (MEG) recording, structural MRI, and provided a saliva sample for hormone analysis. MEG data were source-reconstructed and the power within five canonical frequency bands (delta, theta, alpha, beta, and gamma) was computed. The resulting power spectral density maps were analyzed via vertex-wise ANCOVAs to identify spatially specific effects of testosterone and sex by testosterone interactions, while covarying out age. We found robust sex differences in the modulatory effects of testosterone on spontaneous delta, beta, and gamma activity. These interactions were largely confined to frontal cortices and exhibited a stark switch in the directionality of the correlation from the low (delta) to high frequencies (beta/gamma). For example, in the delta band, greater testosterone related to lower relative power in prefrontal cortices in boys, while the reverse pattern was found for girls. These data suggest testosterone levels are uniquely related to the development of spontaneous cortical dynamics during adolescence, and such levels are associated with different developmental patterns in males and females within regions implicated in executive functioning.

Hyper-entanglement between pulse modes and frequency bins.

Hyper-entanglement between two or more photonic degrees of freedom (DOF) can enhance and enable new quantum protocols by allowing each DOF to perform the task it is optimally suited for. Here we demonstrate the generation of photon pairs hyper-entangled between pulse modes and frequency bins. The pulse modes are generated via parametric downconversion in a domain-engineered crystal and subsequently entangled to two frequency bins via a spectral mapping technique. The resulting hyper-entangled state is characterized and verified via measurement of its joint spectral intensity and non-classical two-photon interference patterns from which we infer its spectral phase. The protocol combines the robustness to loss, intrinsic high dimensionality and compatibility with standard fiber-optic networks of the energy-time DOF with the ability of hyper-entanglement to increase the capacity and efficiency of the quantum channel, already exploited in recent experimental applications in both quantum information and quantum computation.

Grain Growth and Dust Segregation Revealed by Multiwavelength Analysis of the Class I Protostellar Disk WL 17

The first step toward planet formation is grain growth from (sub)micrometer to millimeter/centimeter sizes. Grain growth has been reported not only in Class II protoplanetary disks but also in Class 0/I protostellar envelopes. However, early-stage grain growth occurring in Class 0/I stages has rarely been observed on the protostellar disk scale. Here we present the results from the Atacama Large Millimeter/submillimeter Array Band 3 (λ = 3.1 mm) and 7 (λ = 0.87 mm) archival data of the Class I protostellar disk WL 17 in the ρ Ophiuchus molecular cloud. Disk substructures are found in both bands, but they are different: while a central hole and a symmetric ring appear in Band 3, an off-center hole and an asymmetric ring are shown in Band 7. Furthermore, we obtain an asymmetric spectral index map with a low mean value of α = 2.28 ± 0.02, suggestive of grain growth and dust segregation on the protostellar disk scale. Our radiative transfer modeling verifies these two features by demonstrating that 10 cm sized large grains are symmetrically distributed, whereas 10 μm sized small grains are asymmetrically distributed. In addition, the analysis shows that the disk is expected to be massive and gravitationally unstable. We thus suggest a single Jupiter-mass protoplanet formed by gravitational instability as the origin of the ring-like structure, grain growth, and dust segregation identified in WL 17.

Metrewave Galactic Plane with the uGMRT (MeGaPluG) Survey: Lessons from the pilot study

Context. The advent of wide-band receiver systems on interferometer arrays has enabled the undertaking of high-sensitivity and highresolution radio continuum surveys of the Galactic plane in a reasonable amount of telescope time. Yet, to date, there have been only a few such studies of the first quadrant of the Milky Way carried out at frequencies below 1 GHz. The Giant Metrewave Radio Telescope (GMRT) has recently upgraded its receivers with wide-band capabilities (now called the uGMRT), offering a prime opportunity to conduct high resolution surveys, while also demonstrating sensitivity to the extended structures. Aims. We wish to assess the feasibility of conducting a large-scale snapshot survey, the Metrewave Galactic Plane with the uGMRT Survey (MeGaPluG), to simultaneously map extended sources and compact objects at an angular resolution lower than 10″ and a point source sensitivity of 0.15 mJy beam−1. Methods. We performed an unbiased survey of a small portion of the Galactic plane, covering the W43/W44 regions (l = 29° – 35° and |b| < 1°) in two frequency bands: 300–500 MHz and 550–750 MHz. The 200 MHz wide-band receivers on the uGMRT were employed to observe the target field in several pointings, spending nearly 14 min on each pointing in two separate scans. We developed an automated pipeline for the calibration and a semi-automated self-calibration procedure was used to image each pointing using multi-scale CLEAN and outlier fields. Results. We produced continuum mosaics of the surveyed region at a final common resolution of 25″ in the two bands that have central frequencies of 400 MHz and 650 MHz, with a point source sensitivity better than 5 mJy beam−1. A spectral index map was also obtained, which is helpful to distinguish between thermal and nonthermal emission. By cross-matching with other surveys, we validated the positions and flux densities obtained from our data. We plan to cover a larger footprint of the Galactic plane in the near future based on the lessons drawn from this study.

Region-specific changes in brain activity and memory after continuous positive airway pressure therapy in obstructive sleep apnea: a pilot high-density electroencephalography study.

Limited channel electroencephalography (EEG) investigations in obstructive sleep apnea (OSA) have revealed deficits in slow wave activity (SWA) and spindles during sleep and increased EEG slowing during resting wakefulness. High-density EEG (Hd-EEG) has also detected local parietal deficits in SWA (delta power) during NREM. It is unclear whether effective continuous positive airway pressure (CPAP) treatment reverses regional SWA deficits, and other regional sleep and wake EEG abnormalities, and whether any recovery relates to improved overnight memory consolidation. A clinical sample of men with moderate-severe OSA underwent sleep and resting wake recordings with 256-channel Hd-EEG before and after 3 months of CPAP. Declarative and procedural memory tasks were administered pre- and post-sleep. Topographical spectral power maps and differences between baseline and treatment were compared using t-tests and statistical nonparametric mapping (SnPM). In 11 compliant CPAP users (5.2 ± 1.1 hours/night), total sleep time did not differ after CPAP but N1 and N2 sleep were lower and N3 was higher. Centro-parietal gamma power during N3 increased and fronto-central slow spindle activity during N2 decreased (SnPM < 0.05). No other significant differences in EEG power were observed. When averaged specifically within the parietal region, N3 delta power increased after CPAP (p = 0.0029) and was correlated with the change in overnight procedural memory consolidation (rho = 0.79, p = 0.03). During resting wakefulness, there were trends for reduced delta and theta power. Effective CPAP treatment of OSA may correct regional EEG abnormalities, and regional recovery of SWA may relate to procedural memory improvements in the short term.

Soil color mapping based on Munsell system in the northeast of China

Soil color is the most readily available soil property, soil scientists often use the Munsell system to describe soil color and to quickly understand the physical, chemical, and biological properties of soil through soil color variation. Currently, soil color mapping studies often rely on indirect acquisition of Munsell color data from soil spectral information. As a result, there may be some discrepancies between the mapped colors and the colors perceived by humans. In this study, we collected 880 dry and 827 moist Munsell samples from the Northeast China to test the method developed for soil color mapping. We selected a set of covariates (climate, topography, evapotranspiration, regolith thickness, and remote sensing images) for digital soil color mapping, these covariates were related to soil formation or organic matter accumulation processes. Finally, the dry and moist topsoil color mapping with 30-m resolution was obtained for cropland in Northeast China. These covariates all played positive roles in the soil classification process, among which annual temperature mean (MAT), mean annual precipitation (MAP), land surface temperature (LST), and mean annual potential evapotranspiration (MAPET) had the highest contribution. We summarized the difficulties that usually occur in soil color mapping, and put forward a ‘stepwise classification’ method. According to the three-dimensional attributes of the Munsell system, the measured color data were divided into seven color groups (four dry and three moist color groups). Among all color groups, the highest accuracy of mapping validation was 0.69 and the lowest was 0.58. The kappa coefficient, usually affected by classification bias, was small (0.3). The color differences between measured and predicted colors were found to be 1.21 (dry color) and 1.36 (moist color). Compared to direct classification, the stepwise classification method improved classification accuracy and reduced mapping color differences. Our soil color mapping for two cases of dry and moist corresponded well with spectral color maps. The correlation between soil organic matter (SOM) content and soil color (dry and moist) was analyzed in 807 samples. The darker the soil color was, the higher the SOM content was. In summary, soil color holds the potential to serve as a surrogate for assessing cropland quality, particularly in evaluating SOM.

Remote Excitation of Tip-Enhanced Photoluminescence with a Parallel AgNW Coupler.

Tip-enhanced photoluminescence (TEPL) microscopy allows for the correlation of scanning probe microscopic images and photoluminescent spectra at the nanoscale level in a similar way to tip-enhanced Raman scattering (TERS) microscopy. However, due to the higher cross-section of fluorescence compared to Raman scattering, the diffraction-limited background signal generated by far-field excitation is a limiting factor in the achievable spatial resolution of TEPL. Here, we demonstrate a way to overcome this drawback by using remote excitation TEPL (RE-TEPL). With this approach, the excitation and detection positions are spatially separated, minimizing the far-field contribution. Two probe designs are evaluated, both experimentally and via simulations. The first system consists of gold nanoparticles (AuNPs) through photoinduced deposition on a silver nanowire (AgNW), and the second system consists of two offset parallel AgNWs. This latter coupler system shows a higher coupling efficiency and is used to successfully demonstrate RE-TEPL spectral mapping on a MoSe2/WSe2 lateral heterostructure to reveal spatial heterogeneity at the heterojunction.

Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays

Intensity-mapping observations measure galaxy clustering fluctuations from spectral–spatial maps, requiring stable noise properties on large angular scales. We have developed specialized readouts and analysis methods for achieving large-scale noise stability with Teledyne 2048 × 2048 H2RG infrared detector arrays. We designed and fabricated a room-temperature low-noise ASIC Video8 amplifier to sample each of the 32 detector outputs continuously in sample-up-the-ramp mode with interleaved measurements of a stable reference voltage that remove current offsets and 1/f noise from the amplifier. The amplifier addresses rows in an order different from their physical arrangement on the array, modulating temporal 1/f noise in the H2RG to high spatial frequencies. Finally, we remove constant signal offsets in each of the 32 channels using reference pixels. These methods will be employed in the upcoming SPHEREx orbital mission that will carry out intensity-mapping observations in near-infrared spectral maps in deep fields located near the ecliptic poles. We also developed a noise model for the H2RG and Video8 to optimize the choice of parameters. Our analysis indicates that these methods hold residual 1/f noise near the level of SPHEREx photon noise on angular scales smaller than ∼30′.

A deep learning framework for crop mapping with reconstructed Sentinel-2 time series images

Timely and accurate access to regional scale crop plant area and spatial distribution is essential for regional agricultural production and food security, especially in the context of global population growth and climate change. Deep learning has become prevalent in crop mapping under complex conditions due to its powerful feature extraction and nonlinear ability. This study proposes a time-series image classification framework using Attention-based Bidirectional Gated Recurrent Unit (A-BiGRU) to map rice, maize, and soybean in Fujin, China, from reconstructed Sentinel-2 time-series images. Firstly, the reconstructed Sentinel-2 time-series images with 10 spectral dimensions and 22 temporal dimensions were obtained by linear interpolation and Savitzky-Golay (SG) filter. Then, a neural network, the A-BiGRU was developed to identify different crops by taking advantage of their unique growth patterns. The attention mechanism enables temporal neural networks to focus on the critical growth periods of crops. Additionally, the structure of GRU is simpler than that of long short-term memory (LSTM) and simple recurrent neural network (SRNN), which reduces the number of parameters and alleviates overfitting. Compared to GRU, BiGRU can fully uses the time-series information of the entire crop growth cycle. To assess the effectiveness of the proposed method, we compared two deep learning methods (LSTM and SRNN) and three widely used non-deep learning classifiers (Spectral Angle Mapping (SAM), Support Vector Machine (SVM)) and eXtreme Gradient Boosting (XGBoost). The results demonstrate that A-BiGRU achieved the highest accuracy, with an overall accuracy of 0.9804, a macro F1 score of 0.9788 and a kappa score of 0.9714. We also selected four typical regions and compared the classification results with optical images, which showed that the proposed method has a good recognition effect. Therefore, the A-BiGRU method is capable of achieving high-precision crop mapping.

Mapping of Inland Excess Water Using Geographical Information System and High-Resolution Satellite Images: A Case Study of SREM, Serbia

Abstract Extreme hydrological events, such as floods and droughts, are becoming more frequent as a result of climate change, leading to negative impacts on various economic sectors. The Pannonian-Carpathian Basin is particularly affected by the increasing frequency of hazardous hydrological events. Agricultural production, which is a highly significant economic sector in the region, is particularly vulnerable to these unfavourable climatic conditions. Changes in precipitation patterns and soil moisture levels can lead to reduced crop yields, while floods can pollute water sources and erode fertile soil. Mapping of Inland Excess Water (IEW), also known as ponding water or waterlogged areas, is crucial for informed decision-making, damage compensation, risk management, and future prevention planning. Remote sensing technology and machine learning have been demonstrated to be valuable tools for the mapping of IEW. The 2014 floods in Southeastern and Central Europe serve as a reminder of the importance of effective flood risk management. This study used a Geographical Information System (GIS) and a Semi-automated Classification Processing (SCP) tool to process high-resolution RapidEye satellite images from the 2014 floods in the Srem region of Serbia. The Spectral Angle Mapping (SAM) classification model was used to produce a map of IEW. The SAM model achieved an overall accuracy of 92.68 %. The study found that IEW affected approximately 2.90 % or 99.59 km² of the territory in Srem. The obtained maps can be used by responsible water management agencies to prevent and control excessive inland water.

High-resolution [O i] Line Spectral Mapping of TW Hya Consistent with X-Ray-driven Photoevaporation

Theoretical models indicate that photoevaporative and magnetothermal winds play a crucial role in the evolution and dispersal of protoplanetary disks and affect the formation of planetary systems. However, it is still unclear what wind-driving mechanism is dominant or if both are at work, perhaps at different stages of disk evolution. Recent spatially resolved observations by Fang et al. of the [O i] 6300 Å spectral line, a common disk wind tracer in TW Hya, revealed that about 80% of the emission is confined to the inner few astronomical units of the disk. In this work, we show that state-of-the-art X-ray-driven photoevaporation models can reproduce the compact emission and the line profile of the [O i] 6300 Å line. Furthermore, we show that the models also simultaneously reproduce the observed line luminosities and detailed spectral profiles of both the [O i] 6300 Å and the [Ne ii] 12.8 μm lines. While MHD wind models can also reproduce the compact radial emission of the [O i] 6300 Å line, they fail to match the observed spectral profile of the [O i] 6300 Å line and underestimate the luminosity of the [Ne ii] 12.8 μm line by a factor of 3. We conclude that, while we cannot exclude the presence of an MHD wind component, the bulk of the wind structure of TW Hya is predominantly shaped by a photoevaporative flow.

Synthetic Photoconductive Antenna Array for Terahertz 3-D Imaging and Spectroscopy

We propose a 3D imaging and spectroscopy approach in the terahertz (THz) domain based on the synthetic aperture (SA) imaging technique achieved using a time domain spectroscopy system (TDS). The proposed system enables the imaging and spectroscopy of an object in a stationary position in transmission configuration. We demonstrate the reconstruction of 3D amplitude images with a sub-millimeter resolution of a multi-material object from 0.6 to 1 THz using the back-projection algorithm. The reconstructed data is further used to characterize the optical properties of the substrates forming the object by calculating the refractive index and the absorption coefficient of its constituents in the reconstruction frequency band. We demonstrate the use of the SA not only for imaging, but also for material characterization. Consequently, we are able to reconstruct 2D high-resolution spectral maps of the real refractive index at different THz frequencies of the imaged object.

Drug classification with a spectral barcode obtained with a smartphone Raman spectrometer

Measuring, recording and analyzing spectral information of materials as its unique finger print using a ubiquitous smartphone has been desired by scientists and consumers. We demonstrated it as drug classification by chemical components with smartphone Raman spectrometer. The Raman spectrometer is based on the CMOS image sensor of the smartphone with a periodic array of band pass filters, capturing 2D Raman spectral intensity map, newly defined as spectral barcode in this work. Here we show 11 major components of drugs are classified with high accuracy, 99.0%, with the aid of convolutional neural network (CNN). The beneficial of spectral barcodes is that even brand name of drug is distinguishable and major component of unknown drugs can be identified. Combining spectral barcode with information obtained by red, green and blue (RGB) imaging system or applying image recognition techniques, this inherent property based labeling system will facilitate fundamental research and business opportunities.

Totally (m, n)-paranormal operators

In this paper, we investigate the class of totally (m, n)-paranormal operators on Hilbert space and prove some additional properties of totally (m, n)-paranormal operators on Hilbert space. Also, we show that Weyl's theorem holds for operators in this class. Moreover, we also show that for totally (m, n)-paranormal operators, the Weyl spectrum satisfies the spectral mapping theorem.

A novel radio imaging method for physical spectral index modelling

ABSTRACT We present a new method, called ‘forced-spectrum fitting’, for physically based spectral modelling of radio sources during deconvolution. This improves upon current common deconvolution fitting methods, which often produce inaccurate spectra. Our method uses any pre-existing spectral index map to assign spectral indices to each model component cleaned during the multifrequency deconvolution of wsclean, where the pre-determined spectrum is fitted. The component magnitude is evaluated by performing a modified weighted linear least-squares fit. We test this method on a simulated LOFAR high-band antenna (HBA) observation of the 3C 196 QSO and a real LOFAR HBA observation of the 4C+55.16 FRI galaxy. We compare the results from the forced-spectrum fitting with traditional joined-channel deconvolution using polynomial fitting. Because no prior spectral information was available for 4C+55.16, we demonstrate a method for extracting spectral indices in the observed frequency band using ‘clustering’. The models generated by the forced-spectrum fitting are used to improve the calibration of the data sets. The final residuals are comparable to existing multifrequency deconvolution methods, but the output model agrees with the provided spectral index map, embedding correct spectral information. While forced-spectrum fitting does not solve the determination of the spectral information itself, it enables the construction of accurate multifrequency models that can be used for wide-band calibration and subtraction.

Dual branch deep interactive UNet for monaural noisy-reverberant speech enhancement

Noise and reverberation can severely degrade speech quality and intelligibility, so many deep neural network-based noisy-reverberant speech enhancement methods have been proposed, among which classic methods include spectral masking and spectral mapping. Spectrum masking and spectrum mapping have their advantages and disadvantages in different noise environments, and they are complementary. This paper proposes a dual branch deep interactive UNet (DBDIUNet) for monaural speech enhancement to combine the advantages of spectral mapping and spectral masking. The DBDIUNet uses a classical encoder-decoder architecture, including a shared encoder and two decoders. One decoder outputs the complex ideal ratio mask (cIRM), and the other outputs the enhanced complex spectrum. The two signals are coupled by coherent averaging to get the enhanced speech signal. A novel deep interaction structure is proposed for the interaction of information between the two decoders, which achieves a very significant performance improvement at the minimal cost of computational consumption and hyperparameters. Compared with the noisy speech on the Interspeech 2020 deep noise suppression challenge blind test set, DBDIUNet improves the WB-PESQ, NB-PESQ, STOI, SI-SDR indicators by 1.575, 0.955, 7.9%, 8.67 respectively. In the noisy-reverberant speech enhancement test, DBDIUNet improves the WB-PESQ, STOI, SI-SDR, DNSMOS, and SRMR by 0.98, 10.24%, 5.43, 1.51, 3.43, respectively, which exceeds the state-of-the-art model.

Earth to Mars: A Protocol for Characterizing Permafrost in the Context of Climate Change as an Analog for Extraplanetary Exploration.

Abstract Permafrost is important from an exobiology and climate change perspective. It serves as an analog for extraplanetary exploration, and it threatens to emit globally significant amounts of greenhouse gases as it thaws due to climate change. Viable microbes survive in Earth's permafrost, slowly metabolizing and transforming organic matter through geologic time. Ancient permafrost microbial communities represent a crucial resource for gaining novel insights into survival strategies adopted by extremotolerant organisms in extraplanetary analogs. We present a proof-of-concept study on ∼22 Kya permafrost to determine the potential for coupling Raman and fluorescence biosignature detection technology from the NASA Mars Perseverance rover with microbial community characterization in frozen soils, which could be expanded to other Earth and off-Earth locations. Besides the well-known utility for biosignature detection and identification, our results indicate that spectral mapping of permafrost could be used to rapidly characterize organic carbon characteristics. Coupled with microbial community analyses, this method has the potential to enhance our understanding of carbon degradation and emissions in thawing permafrost. Further, spectroscopy can be accomplished in situ to mitigate sample transport challenges and in assessing and prioritizing frozen soils for further investigation. This method has broad-range applicability to understanding microbial communities and their associations with biosignatures and soil carbon and mineralogic characteristics relevant to climate science and astrobiology.