Realistic Spectra Research Articles

A modification to the Schrödinger equation for broader bandwidth gravity-capillary waves on deep water with depth-uniform current

We derive a nonlinear Schrödinger equation for the propagation of the three-dimensional broader bandwidth gravity-capillary waves including the effect of depth-uniform current. In this derivation, the restriction of narrow bandwidth constraint is extended, so that this equation will be more appropriate for application to a realistic sea wave spectrum. From this equation, an instability condition is obtained and then instability regions in the perturbed wavenumber space for a uniform wave train are drawn, which are in good agreement with the exact numerical results. As it turns out, the corrections to the stability properties that occur at the fourth-order term arise from an interaction between the mean flow and the frequency-dispersion term. Since the frequency-dispersion term, in the absence of depth-uniform current, for pure capillary waves is of opposite sign for pure gravity waves, so too are the corrections to the instability properties. doi: 10.1017/S1446181123000020

Detecting Outliers in Cardiopulmonary Exercise Testing Data of Ski Racers – A Comparison of Methods and their Effect on the Performance of Fatigue Prediction

Abstract In sports science, cardiopulmonary data is used to assess exercise intensity, performance and health status of athletes and derive relevant target values. However, sensors may produce flawed data and data may include a wide variety of artifacts, which could potentially lead to false conclusions. Thus, appropriate and customized pre-processing algorithms are a vital prerequisite for producing reliable and valid analysis results. To find adequate outlier detection methods for this type of data, we compared three algorithms by applying them on seven ergospirometric measures of junior ski racing athletes and applied a model to predict fatigue during skiing based on the pre-processed data. While values that lie outside a realistic spectrum were consistently labelled as outliers by all methods, and mean values and standard deviations changed in similar ways, methods differed from each other when it comes to changing trends, recurring patterns, and subsequent outliers. Decomposing the sensor data into different components (trend, seasonality, remainder) before dealing with outliers increased average predictive performance the most. However, pre-processing remarkably improved prediction results for certain study participants and not for others. Thus, handling outliers correctly prior to deriving information from ergospirometric data is recommended but more research should be conducted to find methods that achieve more consistent improvement.

Fringing Analysis and Simulation for the Vera C. Rubin Observatory’s Legacy Survey of Space and Time

The presence of fringing in astronomical Charge-Coupled Device (CCD) images will have an impact on photometric quality and measurements. Yet its impact on the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) has not been fully studied. We present a detailed study on fringing for CCDs already implemented on the Rubin Observatory LSST Camera’s focal plane. After making physical measurements and knowing the compositions, we developed a model for the e2v CCDs. We present a method to fit for the internal height variation of the epoxy layer within the sensors based on fringing measurements in a laboratory setting. This method is generic enough that it can be easily modified to work for other CCDs. Using the derived fringing model, we successfully reproduce comparable fringing amplitudes that match the observed levels in images taken by existing telescopes with different optical designs. This model is then used to forecast the expected level of fringing in a single LSST y-band sky background exposure with Rubin telescope optics in the presence of a realistic time-varying sky spectrum. The predicted fringing amplitude in LSST images ranges from 0.04% to 0.2% depending on the location of a CCD on the focal plane. We find that the predicted variation in surface brightness caused by fringing in LSST y-band sky background images is about 0.6 , which is 40 times larger than the current measurement error. We conclude that it is necessary to include fringing correction in the Rubin’s LSST image processing pipeline.

The DESI PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) Mock Challenge

The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass (M *), star formation rate (SFR), stellar metallicity (Z), and stellar age (t age), for >10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M *, SFR, Z, and t age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/

Minimal Auxiliary Basis Set Approach for the Electronic Excitation Spectra of Organic Molecules.

We report a minimal auxiliary basis model for time-dependent density functional theory (TDDFT) with hybrid density functionals that can accurately reproduce excitation energies and absorption spectra from TDDFT while reducing cost by about 2 orders of magnitude. Our method, dubbed TDDFT-ris, employs the resolution-of-the-identity technique with just one s-type auxiliary basis function per atom for the linear response operator, where the Gaussian exponents are parametrized across the periodic table using tabulated atomic radii with a single global scaling factor. By tuning on a small test set, we determine a single functional-independent scale factor that balances errors in excitation energies and absorption spectra. Benchmarked on organic molecules and compared to standard TDDFT, TDDFT-ris has an average energy error of only 0.06 eV and yields absorption spectra in close agreement with TDDFT. Thus, TDDFT-ris enables simulation of realistic absorption spectra in large molecules that would be inaccessible from standard TDDFT.

Do the small numbers in the quark mixing arise from new physics?

We put forward the conjecture that the small numbers in the V_text {CKM} matrix, are generated by physics beyond the Standard Model. We identify as small numbers V_{ub} and the strength of CP violation, measured by |text {Im}Q|, where Q stands for a rephasing invariant quartet of V_text {CKM}. We illustrate how the conjecture can be realised in the context of an extension of the Standard Model where an up-type vector-like quark is introduced leading to a realistic spectrum of quark masses and an effective V_text {CKM} in agreement with experiment.

Testing quadratic maximum likelihood estimators for forthcoming Stage-IV weak lensing surveys

ABSTRACTHeadline constraints on cosmological parameters from current weak lensing surveys are derived from two-point statistics that are known to be statistically sub-optimal, even in the case of Gaussian fields. We study the performance of a new fast implementation of the Quadratic Maximum Likelihood (QML) estimator, optimal for Gaussian fields, to test the performance of Pseudo-Cℓ estimators for upcoming weak lensing surveys and quantify the gain from a more optimal method. Through the use of realistic survey geometries, noise levels, and power spectra, we find that there is a decrease in the errors in the statistics of the recovered E-mode spectra to the level of $\sim \!\! 20\, {{\ \rm per\ cent}}$ when using the optimal QML estimator over the Pseudo-Cℓ estimator on the largest angular scales, while we find significant decreases in the errors associated with the B-modes. This raises the prospects of being able to constrain new physics through the enhanced sensitivity of B-modes for forthcoming surveys that our implementation of the QML estimator provides. We test the QML method with a new implementation that uses conjugate-gradient and finite-differences differentiation methods resulting in the most efficient implementation of the full-sky QML estimator yet, allowing us to process maps at resolutions that are prohibitively expensive using existing codes. In addition, we investigate the effects of apodization, B-mode purification, and the use of non-Gaussian maps on the statistical properties of the estimators. Our QML implementation is publicly available and can be accessed from GitHub.

Data Augmentation for Neutron Spectrum Unfolding with Neural Networks

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and physically motivated neutron energy spectra. Using an IAEA compendium of 251 spectra, we compare the unfolding performance of neural networks trained on spectra from these algorithms, when unfolding real-world spectra, to two baselines. We also investigate general methods for evaluating the performance of and optimizing feature engineering algorithms.

Test signal generator for simulating electron events from a momentum microscope

Preparing experiments that utilize free electron lasers is challenging because obtaining access to the facility is difficult. The integration of detectors into the data acquisition system needs to be tested before the beamtime starts. In this study, we develop a test signal generator that simulates the signals from a delay-line detector used in a time-of-flight electron spectrometer. The output signals of the simulator are connected to the time-to-digital converter electronics and simulate a realistic energy spectrum of a real spectrometer. Through this method, the detector electronics can be tested and integrated into the data acquisition system at the free electron laser before the actual instrument is available on site. In addition, the saturation behavior of the signal processing chain can be tested by changing the number of simulated electrons per pulse.

Resolution enhancement of NMR by decoupling with the low-rank Hankel model.

Nuclear magnetic resonance (NMR) spectroscopy has become a formidable tool for biochemistry and medicine. Although J-coupling carries essential structural information it may also limit the spectral resolution. Homonuclear decoupling remains a challenging problem. In this work, we introduce a new approach that uses a specific coupling value as prior knowledge, and the Hankel property of the exponential NMR signal to achieve broadband heteronuclear decoupling using the low-rank method. Our results on synthetic and realistic HMQC spectra demonstrate that the proposed method not only effectively enhances resolution by decoupling, but also maintains sensitivity and suppresses spectral artefacts. The approach can be combined with non-uniform sampling, which means that the resolution can be further improved without any extra acquisition time.

Cycle-by-cycle crack closure measurements and fatigue crack growth in CT specimen made of 7075-T7351 aluminium

In this study, an advanced piezoelectric strain sensor is applied to measure the crack opening loads of a compact tension specimen with a fatigue crack under variable amplitude block loading. The crack opening loads are subsequently utilised to modify the stress intensity factor range by taking into account the proportion of each load cycle for which the fatigue crack remained closed. This effective stress intensity factor is applied to collapse the growth rate curve, which initially displays a strong dependence on stress ratio, into a single master curve where the only variable governing crack extension is the effective stress intensity factor. The findings of this study provide strong evidence for the crack closure concept, which is important for the development of algorithms which can compress/truncate large spectrums. These algorithms rely on a detailed understanding of how much the crack is open or closed during each load cycle. Furthermore, the results indicate that the piezoelectric sensor could be used to study crack closure under realistic spectrum loading conditions, which will be the subject of future investigations.

Phase Resolved Simulation of the Landau–Alber Stability Bifurcation

It has long been known that plane wave solutions of the cubic nonlinear Schrödinger Equation (NLS) are linearly unstable. This fact is widely known as modulation instability (MI), and sometimes referred to as Benjamin–Feir instability in the context of water waves. In 1978, I.E. Alber introduced a methodology to perform an analogous linear stability analysis around a sea state with a known power spectrum, instead of around a plane wave. This analysis applies to second moments, and yields a stability criterion for power spectra. Asymptotically, it predicts that sufficiently narrow and high-intensity spectra are unstable, while sufficiently broad and low-intensity spectra are stable, which is consistent with empirical observations. The bifurcation between unstable and stable behaviour has no counterpart in the classical MI (where all plane waves are unstable), and we call it Landau–Alber bifurcation because the stable regime has been shown to be a case of Landau damping. In this paper, we work with the realistic power spectra of ocean waves, and for the first time, we produce clear, direct evidence for an abrupt bifurcation as the spectrum becomes narrow/intense enough. A fundamental ingredient of this work was to look directly at the nonlinear evolution of small, localised inhomogeneities, and whether these can grow dramatically. Indeed, one of the issues affecting previous investigations of this bifurcation seem to have been that they mostly looked for the indirect evidence of instability, such as an increase in overall extreme events. It is also found that a sufficiently large computational domain is crucial for the bifurcation to manifest.

Impact of hypermagnetic fields on relic gravitational waves, neutrino oscillations and baryon asymmetry

In this paper, we study the evolution of random hypermagnetic fields (HMFs) in the symmetric phase of the early universe before the electroweak phase transition. The behavior of HMFs is driven by the analog of the chiral magnetic effect accounting for the asymmetries of leptons and Higgs bosons. These asymmetries are also dynamical variables of the model and evolve together with HMFs. Moreover, we account for the contribution of the hyper-MHD turbulence in the effective diffusion coefficient and the [Formula: see text]-dynamo parameter. The realistic spectrum of seed HMFs consists of two branches: Batchelor and Kolmogorov ones. The impact of HMFs on the production of relic gravitational waves (GWs) and the baryon asymmetry of the universe (BAU), as well as flavor oscillations of supernova neutrinos in the stochastic GWs generated is considered. We establish the constraint on the strength of the seed HMF comparing the spectral density of produced GWs with the observations of the LIGO-Virgo-KAGRA collaborations. The stronger upper bound on the seed HMF is obtained from the condition of not exceeding the observed value of BAU.

AnaBHEL (Analog Black Hole Evaporation via Lasers) Experiment: Concept, Design, and Status

Accelerating relativistic mirrors have long been recognized as viable settings where the physics mimic those of the black hole Hawking radiation. In 2017, Chen and Mourou proposed a novel method to realize such a system by traversing an ultra-intense laser through a plasma target with a decreasing density. An international AnaBHEL (Analog Black Hole Evaporation via Lasers) collaboration was formed with the objectives of observing the analog Hawking radiation, shedding light on the information loss paradox. To reach these goals, we plan to first verify the dynamics of the flying plasma mirror and characterize the correspondence between the plasma density gradient and the trajectory of the accelerating plasma mirror. We will then attempt to detect the analog Hawking radiation photons and measure the entanglement between the Hawking photons and their “partner particles”. In this paper, we describe our vision and strategy of AnaBHEL using the Apollon laser as a reference, and we report on the progress of our R&D concerning the key components in this experiment, including the supersonic gas jet with a graded density profile, and the superconducting nanowire single-photon Hawking detector. In parallel to these hardware efforts, we performed computer simulations to estimate the potential backgrounds, and derived analytic expressions for modifications to the blackbody spectrum of the Hawking radiation for a perfectly reflecting point mirror, due to the semi-transparency and finite-size effects specific to flying plasma mirrors. Based on this more realistic radiation spectrum, we estimate the Hawking photon yield to guide the design of the AnaBHEL experiment, which appears to be achievable.

Distributed Raman Spectrum Data Augmentation System Using Federated Learning with Deep Generative Models.

Chemical agents are one of the major threats to soldiers in modern warfare, so it is so important to detect chemical agents rapidly and accurately on battlefields. Raman spectroscopy-based detectors are widely used but have many limitations. The Raman spectrum changes unpredictably due to various environmental factors, and it is hard for detectors to make appropriate judgments about new chemical substances without prior information. Thus, the existing detectors with inflexible techniques based on determined rules cannot deal with such problems flexibly and reactively. Artificial intelligence (AI)-based detection techniques can be good alternatives to the existing techniques for chemical agent detection. To build AI-based detection systems, sufficient amounts of data for training are required, but it is not easy to produce and handle fatal chemical agents, which causes difficulty in securing data in advance. To overcome the limitations, in this paper, we propose the distributed Raman spectrum data augmentation system that leverages federated learning (FL) with deep generative models, such as generative adversarial network (GAN) and autoencoder. Furthermore, the proposed system utilizes various additional techniques in combination to generate a large number of Raman spectrum data with reality along with diversity. We implemented the proposed system and conducted diverse experiments to evaluate the system. The evaluation results validated that the proposed system can train the models more quickly through cooperation among decentralized troops without exchanging raw data and generate realistic Raman spectrum data well. Moreover, we confirmed that the classification model on the proposed system performed learning much faster and outperformed the existing systems.

Two-dimensional spectroscopy of two-dimensional materials: A Mahan-Nozières-De Dominicis model of electron-exciton scattering

In this paper, we provide a systematically convergable and efficient numerical approach to simulate multitime correlation functions in the Mahan-Nozi\`eres-De Dominicis model, which crudely mimics the spectral properties of doped two-dimensional (2D) semiconductors such as monolayer transition metal dichalcogenides. We apply this approach to study the coherent 2D electronic spectra of the model. We show that several experimentally observed phenomena, such as peak asymmetry and coherent oscillations in the waiting-time dependence of the trion-exciton cross peaks of the 2D rephasing spectrum, emerge naturally in our approach. Additional features are also present which find no correspondence with experimentally expected behavior. We trace these features to the infinite hole mass property of the model. We use this understanding to construct an efficient approach which filters out configurations associated with the lack of exciton recoil, enabling the connection to previous work and providing a route to the construction of realistic 2D spectra over a broad doping range in 2D semiconductors.

Differential evolution reveals the effect of polar and nonpolar solvents on carotenoids: A case study of astaxanthin optical response modeling

• Unique software that simulates optical response of biological pigments was developed • Differential evolution is used for finding the best model to fit experimental data • Multimode Brownian oscillator models were created to simulate carotenoid absorption • The optimal settings of Differential evolution allowing fast convergence were found • Differential evolution allowed distinguishing models for polar and nonpolar solvents The task to simulate realistic absorption spectra of electronic transitions in pigment molecules takes the form of the art of optimization, particularly if one must choose between the quality of the results obtained and the calculation time necessary to get such quality. The semiclassical theory of optical response provides us with a good opportunity to escape a so-called sum-over-state procedure of considering the innumerable number of vibronic states of a pigment by applying a correlation function approach. This approach, known as the multimode Brownian oscillator model (MBOM), involves replacing an infinite set of vibronic states, which interacts with an electronic transition, with a finite set of effective vibronic modes. Thus, the parameters of effective vibronic modes and an electronic transition can be found only by fitting experimental data. This situation gives rise to the following problem: as the number of free parameters increases, it becomes more difficult to find a single solution. To overcome this obstacle, differential evolution (DE), a method of global optimization, which is based on the idea of natural selection, seems to be the right choice. To test the efficiency of DE in solving quantum mechanical problems, we simulated absorption spectra of astaxanthin (AST) in 18 different organic solvents by using the MBOM. To do so, we developed software that implements both the DE algorithm and linear absorption modeling procedures. We have shown that simulating practically identical AST spectra, DE allows determining the effect of polar and nonpolar solvents on several parameters of MBOM of AST with high accuracy.

Improved Boundary Conditions for Coupled Geospace Models: An Application in Modeling Spacecraft Surface Charging Environment

AbstractSpacecraft surface charging in the inner magnetosphere often occurs in the pre‐midnight to the dawn sector when electron fluxes of tens of keV increase. Inner magnetosphere ring current models can be used to simulate/predict the spacecraft surface charging environment, with their outer boundary conditions specified either based on observations or provided by other models, such as MHD models. In the latter approach, using MHD quantities, the flux spectrum at the outer boundary is commonly assumed to follow a Kappa or Maxwellian distribution function. Such a method however often departs greatly from the realistic spectrum at E < tens of keV, a crucial energy range in the surface charging anomaly. In order to achieve a better representation of the surface charging environment, we propose to combine the MHD‐parameterized flux spectrum with an empirical electron flux model of E < 40 keV to set the electron flux boundary condition. Results indicate that as opposed to the case where the MHD‐parameterized flux distribution is solely used at the model boundary, simulations with the new boundary condition yields a more intense surface charging environment. The integrated electron flux between 10 < E < 50 keV, a measure of the severity of the surface charging environment, is significantly enhanced by 1‐2 orders of magnitude, leading to a much better agreement with Van Allen Probes measurements. This study hence demonstrates a reasonable solution to the setting of outer boundary conditions for inner magnetosphere models and is recommended for coupled geospace circulation models.

A MODIFICATION TO THE SCHRÖDINGER EQUATION FOR BROADER BANDWIDTH GRAVITY-CAPILLARY WAVES ON DEEP WATER WITH DEPTH-UNIFORM CURRENT

AbstractWe derive a nonlinear Schrödinger equation for the propagation of the three-dimensional broader bandwidth gravity-capillary waves including the effect of depth-uniform current. In this derivation, the restriction of narrow bandwidth constraint is extended, so that this equation will be more appropriate for application to a realistic sea wave spectrum. From this equation, an instability condition is obtained and then instability regions in the perturbed wavenumber space for a uniform wave train are drawn, which are in good agreement with the exact numerical results. As it turns out, the corrections to the stability properties that occur at the fourth-order term arise from an interaction between the mean flow and the frequency-dispersion term. Since the frequency-dispersion term, in the absence of depth-uniform current, for pure capillary waves is of opposite sign for pure gravity waves, so too are the corrections to the instability properties.

Dust in the wind with resonant drag instabilities – I. The dynamics of dust-driven outflows in GMCs and H ii regions

ABSTRACT Radiation-dust driven outflows, where radiation pressure on dust grains accelerates gas, occur in many astrophysical environments. Almost all previous numerical studies of these systems have assumed that the dust was perfectly coupled to the gas. However, it has recently been shown that the dust in these systems is unstable to a large class of ‘resonant drag instabilities’ (RDIs) which de-couple the dust and gas dynamics and could qualitatively change the non-linear outcome of these outflows. We present the first simulations of radiation-dust driven outflows in stratified, inhomogeneous media, including explicit grain dynamics and a realistic spectrum of grain sizes and charge, magnetic fields and Lorentz forces on grains (which dramatically enhance the RDIs), Coulomb and Epstein drag forces, and explicit radiation transport allowing for different grain absorption and scattering properties. In this paper, we consider conditions resembling giant molecular clouds (GMCs), H ii regions, and distributed starbursts, where optical depths are modest (≲1), single-scattering effects dominate radiation-dust coupling, Lorentz forces dominate over drag on grains, and the fastest-growing RDIs are similar, such as magnetosonic and fast-gyro RDIs. These RDIs generically produce strong size-dependent dust clustering, growing non-linear on time-scales that are much shorter than the characteristic times of the outflow. The instabilities produce filamentary and plume-like or ‘horsehead’ nebular morphologies that are remarkably similar to observed dust structures in GMCs and H ii regions. Additionally, in some cases they strongly alter the magnetic field structure and topology relative to filaments. Despite driving strong micro-scale dust clumping which leaves some gas ‘behind,’ an order-unity fraction of the gas is always efficiently entrained by dust.