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Chemical dynamics Simulation studies on benzene dimer (Bz2) and benzene–hexachlorobenzene (Bz–HCB) as performed in the past suggest that the coupling between the monomeric (intramolecular) vibrational modes and modes generated due to the association of two monomers (intermolecular) has to be neither strong nor weak for a fast dissociation of the complex. To find the optimum coupling, four complexes are taken into consideration in this work, namely, benzene–monofluorobenzene, benzene–monochlorobenzene, benzene–trifluorobenzene (Bz–TFB), and benzene–trichlorobenzene. Bz–TFB has the highest rate of dissociation among all seven complexes, including Bz2, Bz–HCB, and Bz–HFB (HFB stands for hexafluorobenzene). The set of vibrational frequencies of Bz–TFB is mainly the reason for this fast dissociation. The mass of chlorine in Bz–HCB is optimized to match its vibrational frequencies similar to those of Bz–TFB, and the dissociation of Bz–HCB becomes faster. The power spectrum of Bz–TFB, Bz–HCB, and Bz–HCB with the modified mass of chlorine is also computed to understand the extent of the said coupling in these complexes. [ABSTRACT FROM AUTHOR]

In this study, we extended the optimized potentials for liquid simulation-ionic-liquid virtual site (OPLS-VSIL) force field (FF) to imidazolium-based dicationic ionic liquids (DILs) and evaluated the ability of different OPLS-based FFs (i.e., OPLS-2009IL, 0.8*OPLS-2009IL, and OPLS-VSIL) in predicting different properties of the studied DIL by comparing their results with ab initio molecular dynamics (AIMD) simulation and experimental results. To achieve this purpose, MD simulations with three different OPLS-based FFs as well as AIMD simulation were performed for [C3(mim)2][NTF2]2 DIL and its structural, dynamical, vibrational, and volumetric properties were analyzed. Structural properties of the studied DIL, i.e., radial distribution functions (RDFs), structure factor, and hydrogen-bond network, showed that compared to 0.8*OPLS-2009IL FF, there is a much better agreement between the results of both OPLS-2009IL and OPLS-VSIL FFs with the AIMD simulation. On the other hand, the results of dynamical properties, such as mean square displacements, van Hove correlation functions as well as hydrogen bond, ion pair, and ion cage dynamics, depicted that in both 0.8*OPLS-2009IL and OPLS-VSIL FFs, the dynamics of the system is almost similar, and compared to OPLS-2009IL FF, they have better agreements with experimental results where they exist. So, it can be seen that although reducing the total charge of studied DIL by 20% leads to an increase in the dynamics of the system, the type distribution of partial charges on each atom does not significantly affect the system's dynamics. The calculated infrared (IR) and power spectra showed that the vibrational features of studied DIL in three OPLS-based FFs are mostly the same and reducing total charge and different type distribution of partial charges have no significant effect on the studied system. Furthermore, in volumetric properties, OPLS-VSIL FF shows somehow better agreement with experimental results. Overall, the evaluation of different structural, dynamical, vibrational, and volumetric properties of [C3(mim)2][NTF2]2 DIL shows that the OPLS-VSIL FF may be the best choice among the different studied OPLS FFs. [ABSTRACT FROM AUTHOR]

The velocity autocorrelation function (VACF) encapsulates extensive information about a fluid's molecular-structural and hydrodynamic properties. We address the following fundamental question: How well can a purely hydrodynamic description recover the molecular features of a fluid as exhibited by the VACF? To this end, we formulate a bona fide hydrodynamic theory of the tagged-particle VACF for simple fluids. Our approach is distinguished from previous efforts in two key ways: collective hydrodynamic modes and tagged-particle self-motion are modeled by linear hydrodynamic equations; the fluid's spatial velocity power spectrum is identified as a necessary initial condition for the momentum current correlation. This formulation leads to a natural physical interpretation of the VACF as a superposition of products of quasinormal hydrodynamic modes weighted commensurately with the spatial velocity power spectrum, the latter of which appears to physically bridge continuum hydrodynamical behavior and discrete-particle kinetics. The methodology yields VACF calculations quantitatively on par with existing approaches for liquid noble gases and alkali metals. Furthermore, we obtain a new, hydrodynamic form of the self-intermediate scattering function whose description has been extended to low densities where the Schmidt number is of order unity; various calculations are performed for gaseous and supercritical argon to support the general validity of the theory. Excellent quantitative agreement is obtained with recent MD calculations for a dense supercritical Lennard-Jones fluid. [ABSTRACT FROM AUTHOR]

Electric force microscopy probes the statistics of electric field fluctuations from a sample surface, both through measurement of the noncontact friction exerted on the oscillating charged probe and by determination of the power spectrum of stochastic probe frequency fluctuations, referred to as "jitter." Here we calculate the frequency jitter power spectrum determined over a conducting sample of finite thickness, whose response is characterized by a dielectric function that is wavevector-dependent. These calculations complement previous predictions of the coefficient of noncontact friction in an electric force microscopy measurement for the same model, and also previous predictions of the jitter power spectrum for a dielectric continuum. The inclusion both of a finite sample thickness and a wavevector-dependent dielectric response can significantly enhance the magnitude of the predicted jitter spectrum for a conductor, relative to a simpler model of an infinitely thick dielectric continuum. These calculations provide a baseline prediction of the jitter power spectrum generated by the dynamics of conduction electrons in a metal sample. [ABSTRACT FROM AUTHOR]

We present an innovative approach to constraining the non-cold dark matter model using a convolutional neural network (CNN). We perform a suite of hydrodynamic simulations with varying dark matter particle masses and generate mock 21 cm radio intensity maps to trace the dark matter distribution at z  = 3 in the postreionization epoch. Our proposed method complements the traditional power-spectrum analysis. We compare the results of the CNN classification between the mock maps with different dark matter masses with those from the two-dimensional power spectrum of the differential brightness temperature map of 21 cm radiation. We find that the CNN outperforms the power spectrum. Moreover, we investigate the impact of baryonic physics on the dark matter model constraint, including star formation, self-shielding of H  i gas, and ultraviolet background model. We find that these effects may introduce some contamination in the dark matter constraint, but they are insignificant compared to the system noise of the SKA instruments. [ABSTRACT FROM AUTHOR]

We present a novel methodology for exploring local features directly in the primordial power spectrum using a genetic algorithm pipeline coupled with a Boltzmann solver and Cosmic Microwave Background data (CMB). After testing the robustness of our pipeline using mock data, we apply it to the latest CMB data, including Planck 2018 and CamSpec PR4. Our model-independent approach provides an analytical reconstruction of the power spectra that best fits the data, with the unsupervised machine learning algorithm exploring a functional space built off simple 'grammar' functions. We find significant improvements upon the simple power-law behaviour, by Δχ2 ≲ −21, consistently with more traditional model-based approaches. These best-fits always address both the low-ℓ anomaly in the TT spectrum and the residual high-ℓ oscillations in the TT, TE, and EE spectra. The proposed pipeline provides an adaptable tool for exploring features in the primordial power spectrum in a model-independent way, providing valuable hints to theorists for constructing viable inflationary models that are consistent with the current and upcoming CMB surveys. [ABSTRACT FROM AUTHOR]

• Analysis of geomagnetic field's H time series during quiet geomagnetic condition. • The H time series from high latitude region shows anti-persistent behaviour. • H time series of quiet geomagnetic condition shows multifractal characteristics. • Change in multifractal characteristics with latitude is observed. • The cause of multifractality is identified as long-range correlations. The generation of geomagnetic time series frequently involves intricate spatio-temporal dynamics, wherein nonlinearity and scaling emerge as pivotal mechanisms. The present work investigates the fractal properties of geomagnetic field, and its sources during quiet geomagnetic conditions, by analyzing the horizontal component data of 1 min resolution (H time series) from different latitude regions. Analysis using Auto Correlation Function (ACF), Power spectrum analysis (PSA), Rescaled range analysis (R/S) and Detrended Fluctuation Analysis (DFA) gave indications of the presence of long-range correlations, fractal properties and scaling behaviour of quiet period H time series data. The strong q dependence of generalized Hurst exponent h(q) and scaling exponent Ʈ(q), obtained from the Multifractal Detrended Fluctuation Analysis (MFDFA) method, confirmed the multifractal behaviour of quiet period H time series. The multifractal source analysis of the quiet period H time series with its shuffled and surrogate time series data revealed that, the multifractal characteristics are caused almost entirely by the long-range correlations between small and large fluctuations. The analysis of the latitudinal variations in the multifractal characteristics is also performed as a part of the work, by considering H time series belonging to various latitudes under almost same longitude. The observed decrease in the generalized Hurst exponent values with increase in latitude indicates the change in the multifractal characteristics of the time series with latitude. Also the work revealed that, the H time series from high latitude region shows anti-persistent behaviour, even when the H time series from observatories located at the low and mid latitude regions exhibiting persistent behaviour. The change in the persistence, anti-persistence behaviour can be related to the strength of Earth's magnetic field. [ABSTRACT FROM AUTHOR]

Background: The development of a new imaging modality, such as 4D dynamic contrast‐enhanced dedicated breast CT (4D DCE‐bCT), requires optimization of the acquisition technique, particularly within the 2D contrast‐enhanced imaging modality. Given the extensive parameter space, cascade‐systems analysis is commonly used for such optimization. Purpose: To implement and validate a parallel‐cascaded model for bCT, focusing on optimizing and characterizing system performance in the projection domain to enhance the quality of input data for image reconstruction. Methods: A parallel‐cascaded system model of a state‐of‐the‐art bCT system was developed and model predictions of the presampled modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) were compared with empirical data collected in the projection domain. Validation was performed using the default settings of 49 kV with 1.5 mm aluminum filter and at 65 kV and 0.257 mm copper filter. A 10 mm aluminum plate was added to replicate the breast attenuation. Air kerma at the isocenter was measured at different tube current levels. Discrepancies between the measured projection domain metrics and model‐predicted values were quantified using percentage error and coefficient of variation (CoV) for MTF and NNPS, respectively. The optimal filtration was for a 5 mm iodine disk detection task at 49, 55, 60, and 65 kV. The detectability index was calculated for the default aluminum filtration and for copper thicknesses ranging from 0.05 to 0.4 mm. Results: At 49 kV, MTF errors were +5.1% and −5.1% at 1 and 2 cycles/mm, respectively; NNPS CoV was 5.3% (min = 3.7%; max = 8.5%). At 65 kV, MTF errors were ‐0.8% and ‐3.2%; NNPS CoV was 13.1% (min = 11.4%; max = 16.9%). Air kerma output was linear, with 11.67 µGy/mA (R2 = 0.993) and 19.14 µGy/mA (R2 = 0.996) at 49 and 65 kV, respectively. For iodine detection, a 0.25 mm‐thick copper filter at 65 kV was found optimal, outperforming the default technique by 90%. Conclusion: The model accurately predicts bCT system performance, specifically in the projection domain, under varied imaging conditions, potentially contributing to the enhancement of 2D contrast‐enhanced imaging in 4D DCE‐bCT. [ABSTRACT FROM AUTHOR]

Recent magnetoencephalography (MEG) studies have reported that functional connectivity (FC) and power spectra can be used as neural fingerprints in differentiating individuals. Such studies have mainly used correlations between measurement sessions to distinguish individuals from each other. However, it has remained unclear whether such correlations might reflect a more generalizable principle of individually distinctive brain patterns. Here, we evaluated a machine‐learning based approach, termed latent‐noise Bayesian reduced rank regression (BRRR) as a means of modelling individual differences in the resting‐state MEG data of the Human Connectome Project (HCP), using FC and power spectra as neural features. First, we verified that BRRR could model and reproduce the differences between metrics that correlation‐based fingerprinting yields. We trained BRRR models to distinguish individuals based on data from one measurement and used the models to identify subsequent measurement sessions of those same individuals. The best performing BRRR models, using only 20 spatiospectral components, were able to identify subjects across measurement sessions with over 90% accuracy, approaching the highest correlation‐based accuracies. Using cross‐validation, we then determined whether that BRRR model could generalize to unseen subjects, successfully classifying the measurement sessions of novel individuals with over 80% accuracy. The results demonstrate that individual neurofunctional differences can be reliably extracted from MEG data with a low‐dimensional predictive model and that the model is able to classify novel subjects. [ABSTRACT FROM AUTHOR]

Refraction seismic data acquired by wide‐angle ocean‐bottom seismometers are typically used to invert geological structures. Accurate and reliable first‐arrival traveltime picks are therefore critical to successful refraction data processing. Unfortunately, signal‐to‐noise ratios of refraction data acquired by wide‐angle ocean‐bottom seismometers at far offsets are usually low; thus, conventional methods such as the energy ratio method and correlation analysis method usually fail to accurately and efficiently determine the refraction phase. We therefore develop a novel first‐arrival wave recognition method based on the optimal dominant energy spectrum to improve the accuracy of refraction wave picking on wide‐angle ocean‐bottom seismometer data. The method consists of three steps. The first step is to obtain the optimal dominant energy spectrum according to the power spectrum density of sample scanning. Second, the initial position of the first‐arrival wave is recognized by combining the range of the optimal dominant energy spectrum and the maximum point of its derivative. Third, the modified cross‐correlation method adjusts the initial position to obtain a more accurate arrival time. In this paper, we illustrate the workflow and feasibility of the proposed method via testing on model data. Then, the method is used to determine the first‐arrival time of field wide‐angle ocean‐bottom seismometer data acquired in the Southwest Pacific Ocean and Xisha Islands. The results show that our method can accurately pick the refraction phase at offsets as far as 80 km, thus significantly reducing the uncertainties in first‐arrival phase picking. [ABSTRACT FROM AUTHOR]

We perform a detailed study of the cosmological bias of gravitational wave (GW) events produced by stellar binary black hole mergers (BBHM). We start from a BBHM distribution modelled inside the eagle hydrodynamical simulation using the population synthesis code mobse. We then compare our findings with predictions from different halo occupation distribution (HOD) prescriptions and find overall agreement, provided that the modelled properties of host galaxies and haloes in the semi-analytical treatment match those in the simulations. By highlighting the sources of these discrepancies, we provide the stepping stone to build future more robust models that prevent the shortcoming of both simulation-based and analytical models. Finally, we train a neural network to build a simulation-based HOD and perform feature importance analysis to gain intuition on which host halo/galaxy parameters are the most relevant in determining the actual distribution and power spectrum of BBHM. We find that the distribution of BBHM in a galaxy does not only depend on its size, star formation rate and metallicity, but also by its kinetic state, namely its total energy and velocity dispersion. [ABSTRACT FROM AUTHOR]

Cosmology is poised to measure the neutrino mass sum M ν and has identified several smaller-scale observables sensitive to neutrinos, necessitating accurate predictions of neutrino clustering over a wide range of length scales. The FlowsForTheMasses non-linear perturbation theory for the the massive neutrino power spectrum, |$\Delta ^2_\nu (k)$|⁠ , agrees with its companion N -body simulation at the |$10~{{\ \rm per\ cent}}-15~{{\ \rm per\ cent}}$| level for k ≤ 1  h  Mpc−1. Building upon the Mira-Titan IV emulator for the cold matter, we use FlowsForTheMasses to construct an emulator for |$\Delta ^2_\nu (k)$|⁠ , Cosmic-Eν , which covers a large range of cosmological parameters and neutrino fractions Ων, 0 h 2 ≤ 0.01 (M ν ≤ 0.93 eV). Consistent with FlowsForTheMasses at the 3.5 per cent level, it returns a power spectrum in milliseconds. Ranking the neutrinos by initial momenta, we also emulate the power spectra of momentum deciles, providing information about their perturbed distribution function. Comparing a M ν = 0.15 eV model to a wide range of N -body simulation methods, we find agreement to 3 per cent for k ≤ 3 k FS = 0.17  h  Mpc−1 and to 19 per cent for k ≤ 0.4  h  Mpc−1. We find that the enhancement factor, the ratio of |$\Delta ^2_\nu (k)$| to its linear-response equivalent, is most strongly correlated with Ων, 0 h 2, and also with the clustering amplitude σ8. Furthermore, non-linearities enhance the free-streaming-limit scaling |$\partial \log (\Delta ^2_\nu /\Delta ^2_{\rm m}) / \partial \log (M_\nu)$| beyond its linear value of 4, increasing the M ν-sensitivity of the small-scale neutrino density. [ABSTRACT FROM AUTHOR]

The patchiness in the reionization process alters the statistics of cosmic microwave background (CMB), with the kinematic Sunyaev–Zeldovich (kSZ) effect in the CMB temperature power spectrum being a notable consequence. In this work, we aim to explore the potential of future kSZ power spectrum measurements in inferring the details of the reionization process. In this pursuit, we capitalize on the recent developments in foreground mitigation techniques using the Cross-Internal Linear Combination (Cross-ILC) technique, which enables robust detection of the kSZ power spectrum with signal-to-noise ratio roughly 20σ–30σ in this decade by South pole Telescope (SPT-3G) and Simons Observatory (SO); and ≥80σ by CMB-S4 – substantially improving on the recent evidence for kSZ binned at ℓ = 3000 using SPT-SZ + SPTpol surveys. We use a fiducial kSZ power spectrum along with realistic error bars expected from the above technique for SPT-3G, SO, and CMB-S4 to constrain the parameter space for a physical model of reionization. We find that with the improved error bars it will be possible to place stringent constraints on reionization using solely the Cross-ILC recovered SPT-3G kSZ without imposing any prior on τ in the Bayesian inference. Notably, high-fidelity kSZ measurements from CMB-S4 coupled with τ measurements through LiteBIRD will enable unprecedented constraint on the midpoint of reionization with an error bar of ∼0.25 and the duration of reionization with an error bar at ∼0.21 exclusively using CMB data. This study highlights the need to capture kSZ power spectrum on a broad range of multipoles to gain insights into the inhomogeneous reionization era. [ABSTRACT FROM AUTHOR]

The article investigates the impact of different types of Bus clamping Pulse Width Modulation methods on the switching losses of a voltage source inverter. A controller based on a generalised modulation algorithm inspired by Bus Clamping Pulse Width Modulation is presented in this study. The implementation of the controller is based on the fact that for continual and split clamp PWM there exists a unique value of clamping position (γ ) for every load power factor angle, which results in minimum switching losses. The algorithm aims to minimise switching losses by combining and generalising all the unique values of clamping positions for continual and split clamp PWM. The controller dynamically adjusts the modulation technique and clamping position based on the sensed load phase current, resulting in reduced switching losses across the whole spectrum of load power factor angles compared to fixed clamping positions. Experimental and analytical evidence demonstrates the effectiveness of the proposed controller in achieving minimum switching loss operation during dynamic load changes. [ABSTRACT FROM AUTHOR]

We perform an analytical study on the propagation properties of Laguerre higher-order cosh-Gaussian beam (LhchGB) passing through liver tissue, utilizing the power spectrum refractive index and the extended Huygens-Fresnel integral. Our investigation includes numerical simulations based on the derived formula, illustrating how varying beam parameter configurations within liver tissue impact the properties of the beam. Additionally, we thoroughly discuss the influence of both optical parameters and biological tissue characteristics on the received intensity. Our observations indicate that the LhchGB undergoes changes in its shape as it traverses a considerable distance through this medium. The results presented in this paper hold significant importance for their potential applications in determining the deterioration or disruption of biological tissue, as well as in the fields of medical imaging and medical diagnosis. [ABSTRACT FROM AUTHOR]

The 21-cm line emitted by neutral hydrogen is the most promising probe of the Epoch of Reionization (EoR). Multiple radio interferometric instruments are on the cusp of detecting its power spectrum. It is therefore essential to deliver robust theoretical predictions, enabling sound inference of the coeval Universe properties. The nature of this signal traditionally required the modelling of |$\mathcal {O}(10^{7-8} \, {\rm Mpc}^3)$| volumes to suppress the impact of cosmic variance. However, the recently proposed Fixed & Paired (F&P) approach uses carefully crafted simulation pairs to achieve equal results in smaller volumes. In this work, we thoroughly test the applicability of and improvement granted by this technique to different observables of the 21-cm signal from the EoR. We employ radiation-magneto-hydrodynamics simulations to ensure the most realistic physical description of this epoch, greatly improving over previous studies using a seminumerical approach without accurate galaxy formation physics and radiative transfer. We estimate the statistical improvement granted by the F&P technique on predictions of the skewness, power spectrum, bispectrum, and ionized regions size distribution of the 21-cm signal at redshift 7 ≤ z ≤ 10 (corresponding to |${\ge}80{{\ \rm per\ cent}}$| of the gas being neutral). We find that the effective volume of F&P simulations is at least 3.5 times larger than traditional simulations. This directly translates into an equal improvement in the computational cost (in terms of time and memory). Finally, we confirm that a combination of different observables like skewness, power spectrum, and bispectrum across different redshifts can be utilized to maximize the improvement. [ABSTRACT FROM AUTHOR]

We present a Wide-band tapered gridded estimator (TGE), which incorporates baseline migration and variation of the primary beam pattern for neutral hydrogen (⁠|$H\, {\small I}$|⁠) 21-cm intensity mapping (IM) with large frequency bandwidth radio-interferometric observations. Here we have analysed |$394-494 \, {\rm MHz}$| (z  = 1.9–2.6) uGMRT data to estimate the Multifrequency Angular Power Spectrum (MAPS) C ℓ(Δν) from which we have removed the foregrounds using the polynomial fitting (PF) and Gaussian Process Regression (GPR) methods developed in our earlier work. Using the residual C ℓ(Δν) to estimate the mean-squared 21-cm brightness temperature fluctuation Δ2(k), we find that this is consistent with 0 ± 2σ in several k bins. The resulting 2σ upper limit |$\Delta ^2(k) \lt (4.68)^2 \, \rm {mK^2}$| at |$k=0.219\, \rm {Mpc^{-1}}$| is nearly 15 times tighter than earlier limits obtained from a smaller bandwidth (⁠|$24.4 \, {\rm MHz}$|⁠) of the same data. The 2σ upper limit |$[\Omega _{H\, {\small I}} b_{H\, {\small I}}] \lt 1.01 \times 10^{-2}$| is within an order of magnitude of the value expected from independent estimates of the |$H\, {\small I}$| mass density |$\Omega _{H\, {\small I}}$| and the |$H\, {\small I}$| bias |$b_{H\, {\small I}}$|⁠. The techniques used here can be applied to other telescopes and frequencies, including |$\sim 150 \, {\rm MHz}$| Epoch of Reionization observations. [ABSTRACT FROM AUTHOR]

Foreground removal is one of the biggest challenges in the detection of the Cosmic Dawn (CD) and Epoch of Reionization (EoR). Various foreground subtraction techniques have been developed based on the spectral smoothness of foregrounds. However, the sources with a spectral peak (SP) at megahertz may break down the spectral smoothness at low frequencies (<1000 MHz). In this paper, we cross-match the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) extragalactic source catalogue with three other radio source catalogues, covering the frequency range 72 MHz–1.4 GHz, to search for sources with spectral turnover. 4423 sources from the GLEAM catalogue are identified as SP sources, representing ≈3.2 per cent of the GLEAM radio source population. We utilize the properties of SP source candidates obtained from real observations to establish simulations and test the impact of SP sources on the extraction of CD/EoR signals. We statistically compare the differences introduced by SP sources in the residuals after removing the foregrounds with three methods, which are polynomial fitting, principal component analysis, and fast independent component analysis. Our results indicate that the presence of SP sources in the foregrounds has a negligible influence on extracting the CD/EoR signal. After foreground subtraction, the contribution from SP sources to the total power in the two-dimensional power spectrum within the EoR window is approximately 3–4 orders of magnitude lower than the CD/EoR signal. [ABSTRACT FROM AUTHOR]

The reconstruction method was proposed more than a decade ago to boost the signal of baryonic acoustic oscillations measured in galaxy redshift surveys, which is one of key probes for dark energy. After moving the observed overdensities in galaxy surveys back to their initial position, the reconstructed density field is closer to a linear Gaussian field, with higher-order information moved back into the power spectrum. We find that by jointly analysing power spectra measured from the pre- and post-reconstructed galaxy samples, higher-order information beyond the 2-point power spectrum can be efficiently extracted, which generally yields an information gain upon the analysis using the pre- or post-reconstructed galaxy sample alone. This opens a window to easily use higher-order information when constraining cosmological models. Baryon Acoustic Oscillations (BAO) are formed in the early universe and can be measured galaxy redshift survey to probe dark energy, but this feature is degraded with galaxy structure evolution. The authors propose a method that simultaneously use pre- and post-reconstruction power spectra to extract higher order information for surveys to constrain cosmological models. [ABSTRACT FROM AUTHOR]

This work considers which higher order modeling effects on the cosmic shear angular power spectra must be taken into account for Euclid. We identified the relevant terms and quantified their individual and cumulative impact on the cosmological parameter inferences from Euclid. We computed the values of these higher order effects using analytic expressions and calculated the impact on cosmological parameter estimations using the Fisher matrix formalism. We reviewed 24 effects and determined the ones that potentially need to be accounted for, namely: the reduced shear approximation, magnification bias, source-lens clustering, source obscuration, local Universe effects, and the flat Universe assumption. After computing these effects explicitly and calculating their cosmological parameter biases, using a maximum multipole of ℓ = 5000, we find that the magnification bias, source-lens clustering, source obscuration, and local Universe terms individually produce significant (> 0.25σ) cosmological biases in one or more parameters; accordingly, these effects must be accounted for and warrant further investigation. In total, we find biases in Ωm, Ωb, h, and σ8 of 0.73σ, 0.28σ, 0.25σ, and −0.79σ, respectively, for the flat ΛCDM. For the w0waCDM case, we found biases in Ωm, Ωb, h, ns, σ8, and wa of 1.49σ, 0.35σ, −1.36σ, 1.31σ, −0.84σ, and −0.35σ, respectively. These are increased relative to the ΛCDM due to additional degeneracies as a function of redshift and scale. [ABSTRACT FROM AUTHOR]

In a simultaneous wireless power and data transfer (SWPDT) system using common coils, achieving high-speed communication in high-power wireless charging systems is challenging due to power transfer interference on communication. Based on high-frequency data carrier-based SWPDT (HFDC-SWPDT) technology, this paper proposes an orthogonal-frequency simultaneous wireless power and data transfer (OF-SWPDT) method to minimize interference where the data carrier frequency is orthogonal to the power carrier frequency and its harmonics. In addition, a guard band is inserted between the spectra of power harmonics and data in order to further separate the power and data spectra. Thus, a high-power, high-speed SWPDT system is achieved. Finally, an 11 kW prototype with 64.125 kbps full-duplex communication is developed to validate the proposed method. [ABSTRACT FROM AUTHOR]

Space–time adaptive processing (STAP) is an effective technology in clutter suppression and moving target detection for airborne radar. When working in the heterogeneous environment, the number of training samples that satisfy independent and identically distributed (IID) conditions is insufficient, making it difficult to ensure the estimation accuracy of the clutter plus noise covariance matrix for traditional STAP methods. Sparse recovery–based STAP (SR–STAP) methods have received widespread attention in the past few years. The accurate estimation of the clutter plus noise covariance matrix can be achieved using only a few training samples. The iterative adaptive approach (IAA) can quickly and accurately estimate the power spectrum, but applying this method directly to the STAP method cannot produce good performance. In this paper, a fast IAA–based SR–STAP method is proposed. Based on the weighted l 1 problem, the IAA spectrum is used as a weighted term to obtain a good approximation. In order to obtain an analytical solution, we use the weighted l 2 norm to approximate the weighted l 1 norm without loss of performance. Compared with the IAA–STAP method, the proposed method is more robust to errors. Moreover, the proposed method has a fast computational speed. The effectiveness of the proposed method is demonstrated by simulations. [ABSTRACT FROM AUTHOR]

Gravitational lensing deflects the paths of photons, altering the statistics of cosmic backgrounds and distorting their information content. We take the cosmic infrared background (CIB), which provides plentiful information about galaxy formation and evolution, as an example to probe the effect of lensing on non-Gaussian statistics. Using the Websky simulations, we first quantify the non-Gaussianity of the CIB, revealing additional detail on top of its well-measured power spectrum. To achieve this, we use needlet-like multipole-band filters to calculate the variance and higher-point correlations. Using our simulations, we show the two-, three- and four-point spectra, and compare our calculated power spectra and bispectra to Planck values. We then lens the CIB, shell-by-shell with corresponding convergence maps, to capture the broad redshift extent of both the CIB and its lensing convergence. The lensing of the CIB changes the three- and four-point functions by a few tens of per cent at large scales, unlike with the power spectrum, which changes by less than two per cent. We expand our analyses to encompass the full intensity probability distribution functions (PDFs) involving all n -point correlations as a function of scale. In particular, we use the relative entropy between lensed and unlensed PDFs to create a spectrum of templates that can allow estimation of lensing. The underlying CIB model is missing the important role of star bursting, which we test by adding a stochastic lognormal term to the intensity distributions. The novel aspects of our filtering and lensing pipeline should prove useful for any radiant background, including line intensity maps. [ABSTRACT FROM AUTHOR]

The cosmological 21-cm signal offers a potential probe of the early Universe and the first ionizing sources. Current experiments probe the spatially dependent variance (Gaussianity) of the signal through the power spectrum (PS). The signal, however, is expected to be highly non-Gaussian due to the complex topology of reionization and X-ray heating. We investigate the non-Gaussianities of X-ray heating and reionization, by calculating the skew spectrum (SS) of the 21-cm signal using meraxes , which couples a semi-analytic galaxy population with seminumerical reionization simulations. The SS is the cross-spectrum of the quadratic temperature brightness field with itself. We generate a set of seven simulations from z = 30 to 5, varying the halo mass threshold for hosting star formation, the X-ray luminosity per star formation rate, and the minimum X-ray energy escaping host galaxies. We find the SS is predominantly negative as a function of redshift, transitioning to positive towards the start of reionization, and peaking during the mid-point of reionization. We do not see a negative dip in the SS during reionization, likely due to the specifics of modelling ionization sources. We normalize the SS by the PS during reionization isolating the non-Gaussianities. We find a trough (⁠|$k\sim \, 0.1\, \textrm {Mpc}^{-1}$|⁠) and peak (⁠|$k\sim \, 0.4{-}1\, \textrm {Mpc}^{-1}$|⁠) in the normalized SS during the mid-to-late periods of reionization. These correlate to the ionization topology, and neutral islands in the IGM. We calculate the cosmic variance of the normalized SS, and find these features are detectable in the absence of foregrounds with the SKA_LOW. [ABSTRACT FROM AUTHOR]

Despite several geological and geophysical studies that have focused on the estimation of the geometry of the sedimentary basins, the seismic documentation of sediment thickness is inadequately constrained due to the sparse spatial resolution of the expensive seismic and borehole measurements. To provide a new complementary insight into the morphology of the crystalline basement, I have re-examined the radially averaged power spectrum of magnetic anomalies for mapping depth to magnetic basement (DMB). DMB is a proxy of the non-magnetized sediment cover thickness over the magnetized crystalline basement. Synthetic models suggest that the accuracy of the method is not significantly influenced by the unknown magnetic fractal parameter and depth to the bottom of the magnetic slab. The windowing and window size effect on the estimated DMB can be substantial. Our synthetic tests suggest that the uncertainty of the calculated DMB increases with depth if the chosen window size is less than eight times the real DMB. I applied this method to the European, Greenland and North Atlantic regions because of the availability of seismically constrained sediment thickness or depth to the seismic basement (DSB), which allows comparison between DMB and DSB. The estimation of DMB was done by assuming a constant fractal parameter of three within a sliding window and with a variable size from 100 × 100 km in 10 km steps to a maximum size of 200 × 200 km until the estimated DMB is less than one eighth times of the window size. Comparison of DMB with DSB indicates a striking long-wavelength correlation along major sedimentary basins, while discrepancies may indicate limitations in the estimation methods for DMB and DSB. [ABSTRACT FROM AUTHOR]

A reconstruction framework based on proper orthogonal decomposition and the Bayesian estimation was designed for the spatial superresolution of a subsonic jet, and the simultaneous two PIV measurements of a subsonic jet with different magnifications were conducted for training and testing the framework. The measurement system successfully acquired paired particle images of broad and close-up views of the jet in the same plane, and low and high-resolution velocity fields were obtained. The artificial low-resolution velocity fields were also generated by average pooling of the measured high-resolution velocity fields, and the performance of the reconstruction framework was evaluated. The estimation accuracy of the proposed framework was compared with that of bicubic interpolation and machine learning-based reconstruction methods: convolutional neural network and downsampled skip-connection/multi-scale methods. The framework successfully reconstructed the high-resolution velocity field from the low-resolution velocity field of the artificial one and actually measured one. The minimum reconstruction error of the Bayesian estimation using actually measured low-resolution velocity field was 63%, outperforming bicubic interpolation. Although this reconstruction error of the proposed framework is almost the same as (slightly worse than) that of the neural network methods, its reconstruction process is clearer and simpler than the neural network method. The power spectra of turbulent kinetic energy showed that the proposed framework can accurately recover the original velocity field in a wide waveband compared to the other methods. Therefore, the proposed framework can be a superresolution method of experimental fluid dynamics. [ABSTRACT FROM AUTHOR]

A re-examination of some early classic turbulence literature, mainly of isotropic turbulence, is given in this selective review. Some early studies, including original concepts and points, are reviewed or highlighted. Two earliest studies and six major original concepts are found: (i) Lord Kelvin's pioneering elementary studies of homogeneous, isotropic turbulence; (ii) Kelvin's early introduction of Fourier Principles into turbulence studies; (iii) the Kelvin elementary concept of the direct energy cascade; (iv) the Kelvin early concept of the symmetry of turbulence; (v) the Taylor concept of the coefficient of eddy viscosity; (vi) the Taylor concept of the 'age' of the eddy; (vii) the Taylor–Fage–Townend concept of small eddies or microturbulence or small scale turbulence; and (viii) the Obukhov concept of a function of the inner Reynolds number (i.e., R e dependent coefficient) in both the balance equation and the energy distribution equation (the two-thirds law). Both Kelvin and Taylor should be regarded as the co-founders of the statistical theory of homogeneous, isotropic turbulence. The notion, 'the Maxwell–Reynolds decomposition of turbulent flow velocity', should be used. The Kolmogorov–Obukhov scaling laws are reviewed in detail. Heisenberg's inverse seventh power spectrum is briefly reviewed. The implications or significances of these early studies, original concepts and points are briefly discussed, with special reference to their possible links with modern approaches and theories. [ABSTRACT FROM AUTHOR]

This study explores the important role of assessing force levels in accurately controlling upper limb movements in human–computer interfaces. It uses a new method that combines entropy to improve the recognition of force levels. This research aims to differentiate between different levels of isometric contraction forces using electroencephalogram (EEG) signal analysis. It integrates eight different entropy measures: power spectrum entropy (PSE), singular spectrum entropy (SSE), logarithmic energy entropy (LEE), approximation entropy (AE), sample entropy (SE), fuzzy entropy (FE), alignment entropy (PE), and envelope entropy (EE). The findings emphasize two important advances: first, including a wide range of entropy features significantly improves classification efficiency; second, the fusion entropy method shows exceptional accuracy in classifying isometric contraction forces. It achieves an accuracy rate of 91.73% in distinguishing between 15% and 60% maximum voluntary contraction (MVC) forces, along with 69.59% accuracy in identifying variations across 15%, 30%, 45%, and 60% MVC. These results illuminate the efficacy of employing fusion entropy in EEG signal analysis for isometric contraction detection, heralding new opportunities for advancing motor control and facilitating fine motor movements through sophisticated human–computer interface technologies. [ABSTRACT FROM AUTHOR]

Many techniques have been studied for recovering information from shared media such as optical fiber that carries different types of communication, sensing, and data streaming. This article focuses on a simple method for retrieving the targeted information with the least necessary number of significant samples when using statistical population sampling. Here, the focus is on the statistical denoising and detection of the fiber Bragg grating (FBG) power spectra. The impact of the two-sided and one-sided sliding window technique is investigated. The size of the window is varied up to one-half of the symmetrical FBG power spectra bandwidth. Both, two- and one-sided small population sampling techniques were experimentally investigated. We found that the shorter sliding window delivered less processing latency, which would benefit real-time applications. The calculated detection thresholds were used for in-depth analysis of the data we obtained. It was found that the normality three-sigma rule does not need to be followed when a small population sampling is used. Experimental demonstrations and analyses also showed that novel denoising and statistical threshold detection do not depend on prior knowledge of the probability distribution functions that describe the FBG power spectra peaks and background noise. We have demonstrated that the detection thresholds' adaptability strongly depends on the mean and standard deviation values of the small population sampling. [ABSTRACT FROM AUTHOR]

In the present study, an effective analysis framework is developed for generating the floor response spectra (FRS) of nuclear power plants based on the explicit time-domain method (ETDM), an efficient approach recently proposed for nonstationary random vibration analysis of large-scale complex structures. The FRS obtained by the present approach are fully consistent with the code-specified ground response spectra (GRS), and the problems encountered in the traditional time-history method and direct spectra-to-spectra method can be completely avoided. The FRS of a real nuclear power plant are generated to demonstrate the feasibility of the proposed method to engineering practice. [ABSTRACT FROM AUTHOR]

We have detected solar-like oscillations in the mid-K-dwarf ϵ Indi A, making it the coolest dwarf to have measured oscillations. The star is noteworthy for harboring a pair of brown dwarf companions and a Jupiter-type planet. We observed ϵ Indi A during two radial velocity campaigns, using the high-resolution spectrographs HARPS (2011) and UVES (2021). Weighting the time series, we computed the power spectra and established the detection of solar-like oscillations with a power excess located at 5265 ± 110 μ Hz—the highest frequency solar-like oscillations so far measured in any star. The measurement of the center of the power excess allows us to compute a stellar mass of 0.782 ± 0.023 M ⊙ based on scaling relations and a known radius from interferometry. We also determine the amplitude of the peak power and note that there is a slight difference between the two observing campaigns, indicating a varying activity level. Overall, this work confirms that low-amplitude solar-like oscillations can be detected in mid-K-type stars in radial velocity measurements obtained with high-precision spectrographs. [ABSTRACT FROM AUTHOR]

We present a comprehensive timing analysis on the Be/X-ray binary pulsar RX J0440.9+4431 using observations from NICER and Insight - HXMT during the 2022–2023 outburst. The power density spectrum (PDS) of RX J0440.9+4431 exhibits typical aperiodic variability in X-ray flux across a wide frequency range. During a supercritical accretion state, we detect quasi-periodic oscillations (QPOs) at 0.2–0.5 Hz in the light curves of five pulses for RX J0440.9+4431. The observed QPOs manifest during flares, while the flares appear at the peaks of the pulse profiles on a time-scale of seconds and are primarily caused by an increase in hard photons. These flares can be explained by increased material ingestion in the accretion column at a fixed phase, primarily generating hard photons. Alternatively, an increase in accretion rate, independent of phase, may result in highly beamed hard photons within the accretion column, causing the flares. We argue the origin of QPOs to instabilities within the accretion flow. Additionally, we find that the break frequencies in the noise power spectra align well with |$\propto L_{\mathrm{x}}^{3 / 7}$| across three orders of magnitude in the luminosity, which points to a relatively strong magnetic field in RX J0440.9+4431, estimated to be ~1013 G. [ABSTRACT FROM AUTHOR]

Constraints on the potential properties of superconducting cosmic strings provide an indirect probe of physics beyond the standard model at energies inaccessible to terrestrial particle colliders. In this study, we perform the first joint Bayesian analysis to extract constraints on superconducting cosmic strings from current 21-cm signal measurements while accounting rigorously for the uncertainties in foregrounds and high redshift astrophysics. We include the latest publicly available 21-cm power spectrum upper limits from HERA, 21-cm global signal data from SARAS 3, and the synergistic probe of the unresolved X-ray background in our final analysis. This paper thus constitutes the first attempt to use 21-cm power spectrum data to probe cosmic strings. In contrast to previous works, we find no strong constraints can be placed on superconducting cosmic strings from current 21-cm measurements. This is because of uncertainties in the X-ray emission efficiency of the first galaxies, with X-ray emissivities greater than 3 × 1040 erg s−1 M |$_{\odot }^{-1}$|  yr able to mask the presence of cosmic strings in the 21-cm signal. We conclude by discussing the prospects for future constraints from definitive 21-cm signal measurements and argue that the recently proposed soft photon heating should be cause for optimism due to its potential to break degeneracies that would have otherwise made the signatures of cosmic strings difficult to distinguish from those of astrophysical origin. [ABSTRACT FROM AUTHOR]

Spatial variations in the Lyman-α forest opacity at z < 6 seem to require a late end to cosmic reionization. In this picture, the Universe contains neutral hydrogen 'islands' of up to 100 cMpc/ h in extent down to redshifts as low as z ∼ 5.3. This delayed end to reionization also seems to be corroborated by various other observables. An implication of this scenario is that the power spectrum of the cosmological 21-cm signal at z < 6 is enhanced relative to conventional reionization models by orders of magnitude. However, these neutral hydrogen islands are also predicted to be at the locations of the deepest voids in the cosmological large-scale structure. As a result, the distribution of the 21-cm signal from them is highly non-Gaussian. We derive the 21-cm bispectrum signal from these regions using high-dynamic-range radiative transfer simulations of reionization. We find that relative to conventional models in which reionization is complete at z > 6, our model has a significantly larger value of the 21-cm bispectrum. The neutral islands also imprint a feature in the isosceles bispectrum at a characteristic scale of ∼1 cMpc−1. We also study the 21-cm bispectrum for general triangle configuration by defining a triangle index. It should be possible to detect the 21-cm bispectrum signal at ν ≳ 200 MHz using SKA1-LOW for 1080 h of observation, assuming optimistic foreground removal. [ABSTRACT FROM AUTHOR]

Recently, hybrid bias expansions have emerged as a powerful approach to modelling the way in which galaxies are distributed in the Universe. Similarly, field-level emulators have recently become possible, thanks to advances in machine learning and N -body simulations. In this paper, we explore whether both techniques can be combined to provide a field-level model for the clustering of galaxies in real and redshift space. Specifically, here we will demonstrate that field-level emulators are able to accurately predict all the operators of a second-order hybrid bias expansion. The precision achieved in real and redshift space is similar to that obtained for the non-linear matter power spectrum. This translates to roughly 1–2 per cent precision for the power spectrum of a BOSS (Baryon Oscillation Spectroscopic Survey) and a Euclid-like galaxy sample up to |$k\sim 0.6\ h\, {\rm Mpc}^{-1}$|⁠. Remarkably, this combined approach also delivers precise predictions for field-level galaxy statistics. Despite all these promising results, we detect several areas where further improvements are required. Therefore, this work serves as a road map for the developments required for a more complete exploitation of upcoming large-scale structure surveys. [ABSTRACT FROM AUTHOR]

In the realm of ballistic target analysis, micro-motion attributes, such as warhead precession, nutation, and decoy oscillations, play a pivotal role. This paper addresses these critical aspects by introducing an advanced analytical model for assessing the Doppler power spectra of convex quadric revolution bodies during precession. Our model is instrumental in calculating the Doppler shifts pertinent to both precession and swing cones. Additionally, it extends to delineate the Doppler power spectra for configurations involving cones and sphere–cone combinations. A key aspect of our study is the exploration of the effects exerted by geometric parameters and observation angles on the Doppler spectra, offering a comparative perspective of various micro-motion forms. The simulations distinctly demonstrate how different micro-motion patterns of a cone influence the Doppler power spectra and underscore the significance of geometric parameters and observational angles in shaping these spectra. This research not only contributes to enhancing LIDAR target identification methodologies but also lays a groundwork for future explorations into complex micro-motions like nutation. [ABSTRACT FROM AUTHOR]

During the Epoch of Reionization (EoR), the ultraviolet radiation from the first stars and galaxies ionized the neutral hydrogen of the intergalactic medium, which can emit radiation through its 21 cm hyperfine transition. Measuring the 21 cm power spectrum is a key science goal for the future Square Kilometre Array (SKA); however, observing and interpreting it is a challenging task. Another high-potential probe of the EoR is the patchy kinetic Sunyaev–Zel'dovich (pkSZ) effect, observed as a foreground to the cosmic microwave background temperature anisotropies on small scales. Despite recent promising measurements, placing constraints on reionization from pkSZ observations is a non-trivial task, subject to strong model dependence. We propose to alleviate the difficulties in observing and interpreting the 21 cm and pkSZ power spectra by combining them. With a simple yet effective parametric model that establishes a formal connection between them, we can jointly fit mock 21 cm and pkSZ data points. We confirm that these observables provide complementary information on reionization, leading to significantly improved constraints when combined. We demonstrate that with as few as two measurements of the 21 cm power spectrum with 100 h of observations with the SKA, as well as a single ℓ = 3000 pkSZ data point, we can reconstruct the reionization history of the universe and its morphology. We find that the reionization history (morphology) is better constrained with two 21 cm measurements at different redshifts (scales). Therefore, a combined analysis of the two probes will give access to tighter constraints on cosmic reionization even in the early stages of 21 cm detections. [ABSTRACT FROM AUTHOR]

One challenge for applying current weak lensing analysis tools to the Nancy Grace Roman Space Telescope is that individual images will be undersampled. Our companion paper presented an initial application of Imcom – an algorithm that builds an optimal mapping from input to output pixels to reconstruct a fully sampled combined image – on the Roman image simulations. In this paper, we measure the output noise power spectra, identify the sources of the major features in the power spectra, and show that simple analytic models that ignore sampling effects underestimate the power spectra of the coadded noise images. We compute the moments of both idealized injected stars and fully simulated stars in the coadded images, and their one- and two-point statistics. We show that the idealized injected stars have root-mean-square ellipticity errors (1–6) × 10−4 per component depending on the band; the correlation functions are ≥2 orders of magnitude below requirements, indicating that the image combination step itself is using a small fraction of the overall Roman second moment error budget, although the fourth moments are larger and warrant further investigation. The stars in the simulated sky images, which include blending and chromaticity effects, have correlation functions near the requirement level (and below the requirement level in a wide-band image constructed by stacking all four filters). We evaluate the noise-induced biases in the ellipticities of injected stars, and explain the resulting trends with an analytical model. We conclude by enumerating the next steps in developing an image coaddition pipeline for Roman. [ABSTRACT FROM AUTHOR]

In modified gravity theories, gravitational waves can propagate differently from general relativity and their propagating speed can be either constant or acquire a time dependence. We consider the constant models first and update the constraints on cosmological parameters from the combinations of Planck 1 8 + BK 1 8 datasets. In this case, excluding superluminal propagation, we obtain the lower limit on the speed c g > 0. 2 2 at 95% C.L. A non-trivial propagating speed impacts the amplitude of tensor spectrum by adding a factor c g n t − 1 , where n t is the tensor tilt. We find that the value of c g has positive correlation with the tensor-to-scalar ratio and anti-correlation with the factor c g n t − 1 . Then we explore a time-dependent speed which contains the resonance of the stochastic gravitational wave background. If the speed of gravitational waves oscillates at primordial era, resonance continuously enhances stochastic gravitational wave background which produces observable effects on tensor power spectra. We derive the constraints on the amplitude of oscillatory speed and tensor parameters from the combinations of Planck18 + BK18 datasets. The numerical results show that the speed resonance of the stochastic gravitational wave background is sensitive to CMB observations. [ABSTRACT FROM AUTHOR]

Due to the alternating loads on pumping units and the integration of new energy sources, multisource DC microgrid pumping unit well groups experience increased fluctuations in voltage and power as well as superimposed peak and valley values. This work presents a distributed control strategy for pumping unit well groups on a multisource DC microgrid based on the weighted moving average algorithm. A centralized control program is implanted in the RTU of the single-well controller of each pumping unit, and communication with each well is realized via SCADA and multicast communication, resulting in a distributed well group system. The real-time power values of the pumping well group are calculated by grouping the power values, and each group is weighted using the total power fluctuation threshold of the well group as the control target. Then, a weighted moving average algorithm is used to predict the next power value and form a table of predicted real-time power spectra. According to the power values in the community power spectrum table, the inverter frequency is proportionally adjusted downwards to reach the power peak before deceleration; after the power peak is crossed, the frequency is increased in the same way to reach the power valley before acceleration. Finally, the peak and valley power values of the bus system level off and further learn to reach the set impulse; ultimately, a stable impulse is formed. In laboratory testing and field application in the Shengli Oilfield XIN-11 block, the group control software module effectively suppressed the active power peak and valley values and voltage fluctuations of the bus system, the active power fluctuation rate range decreased by more than 70%, and the DC bus voltage fluctuation range decreased by more than 80%; moreover, the active power decreased by approximately 6% without additional hardware costs. [ABSTRACT FROM AUTHOR]

We investigate inflation driven by the Higgs boson in the Palatini formulation of General Relativity. Our analysis primarily focuses on a small non-minimal coupling of the Higgs field to gravity in the range 0 < ξ ≲ 1. We incorporate the renormalization group running of the relevant parameters as computed within the Standard Model and allow for small corrections. In addition to ξ, our model features two tunable parameters: the low-energy value of the top Yukawa coupling and an effective jump of the Higgs self-interaction. Our results indicate that critical points leading to a large enhancement of the power spectrum can be produced. However, the observed amplitude of perturbations in the CMB cannot be matched within this setting. On the one hand, this makes it difficult to generate a sizable abundance of primordial black holes. On the other hand, our findings can be viewed as very positive since they provide further evidence that Palatini Higgs inflation has favourable high-energy properties due to robustness against quantum corrections. [ABSTRACT FROM AUTHOR]

Massive fields can imprint unique oscillatory features on primordial correlation functions or inflationary correlators, which is dubbed the cosmological collider signal. In this work, we analytically investigate the effects of a time-dependent mass of a scalar field on inflationary correlators, extending previous numerical studies and implementing techniques developed in the cosmological bootstrap program. The time-dependent mass is in general induced by couplings to the slow-roll inflaton background, with particularly significant effects in the case of non-derivative couplings. By linearly approximating the time dependence, the mode function of the massive scalar is computed analytically, on which we derive analytic formulae for two-, three-, and four-point correlators with the tree-level exchange of the massive scalar. The obtained formulae are utilized to discuss the phenomenological impacts on the power spectrum and bispectrum, and it is found that the scaling behavior of the bispectrum in the squeezed configuration, i.e., the cosmological collider signal, is modified from a time-dependent Boltzmann suppression. By investigating the scaling behavior in detail, we are in principle able to determine the non-derivative couplings between the inflaton and the massive particle. [ABSTRACT FROM AUTHOR]

Cortical electroencephalograms (EEGs) may help understanding of neuropsychiatric illness and new treatment mechanisms. The aperiodic component (1/f) of EEG power spectra is often treated as noise, but recent studies suggest that changes to the aperiodic exponent of power spectra may reflect changes in excitation/inhibition balance, a concept linked to antidepressant effects, epilepsy, autism, and other clinical conditions. One confound of previous studies is behavioral state, because factors associated with behavioral state other than excitation/inhibition ratio may alter EEG parameters. Thus, to test the robustness of the aperiodic exponent as a predictor of excitation/inhibition ratio, we analyzed video-EEG during active exploration in mice of both sexes during various pharmacological manipulations with the fitting oscillations and one over f (FOOOF) algorithm. We found that GABAA receptor (GABAAR)-positive allosteric modulators increased the aperiodic exponent, consistent with the hypothesis that an increased exponent signals enhanced cortical inhibition, but other drugs (ketamine and GABAAR antagonists at subconvulsive doses) did not follow the prediction. To tilt excitation/inhibition ratio more selectively toward excitation, we suppressed the activity of parvalbumin-positive interneurons with Designer Receptors Exclusively Activated by Designer Drugs (DREADDs). Contrary to our expectations, circuit disinhibition with the DREADD increased the aperiodic exponent. We conclude that the aperiodic exponent of EEG power spectra does not yield a universally reliable marker of cortical excitation/inhibition ratio. NEW & NOTEWORTHY Neuropsychiatric illness may be associated with altered excitation/inhibition balance. A single electroencephalogram (EEG) parameter, the aperiodic exponent of power spectra, may predict the ratio between excitation and inhibition. Here, we use cortical EEGs in mice to evaluate this hypothesis, using pharmacological manipulations of known mechanism. We show that the aperiodic exponent of EEG power spectra is not a reliable marker of excitation/inhibition ratio. Thus, alternative markers of this ratio must be sought. [ABSTRACT FROM AUTHOR]

Continuous gravitational-wave (CW) signals are long-lasting quasi-monochromatic gravitational-wave signals expected to be emitted by rapidly rotating non-axisymmetric neutron stars. Depending on the rotational frequency and sky location of the source, certain CW signals may behave in a similar manner to narrow-band artifacts present in ground-based interferometric detectors. Part of the detector characterization tasks in the current generation of interferometric detectors (Advanced LIGO, Advanced Virgo, and KAGRA) aim at understanding the origin of these narrow artifacts, commonly known as "spectral lines". It is expected that similar tasks will continue after the arrival of next-generation detectors (e.g., Einstein Telescope and Cosmic Explorer). Typically, a fraction of the observed lines in a given detector can be associated to one or more instrumental causes; others, however, have an unknown origin. In this work, we assess the similarity of CW signals to spectral lines in order to understand whether a CW signal may be mistaken for a noise artifact. Albeit astrophysically unlikely, our results do not rule out the possibility of a CW signal being visible in the detector's power spectrum. [ABSTRACT FROM AUTHOR]

Local transient solid holdup signals were measured by using an optical fiber probe at different axial and radial positions in the gas-solid cyclone reactor. The chaotic time series analysis of transient solid holdup was adopted to characterize the dynamic characteristics. The maximum and minimum solid holdup indicates that the high variability of gas-solid interaction. With the increase of the gas / solid ratio, the frequency of solid holdup fluctuation increased while the mean value of amplitude decreased; besides, the level of detail in the power spectrum fluctuations increased. In the diffusion chamber, the overall Kolmogorov entropy (K entropy) and correlation dimension (D c) were higher indicating the strong chaos characteristic of gas-solid flow. In the agglomeration chamber, higher solid holdup initially reduced gas-solid interaction, decreasing flow randomness, but a subsequent increase led to irregular particle collisions and an upturn of K entropy and D c. In the annulus chamber, K entropy and D c were lower around the inner wall and outer wall compared to the middle region. In the separation chamber, K entropy and D c tended to increase and then decrease as the radial position increased. Finally, the relationship between K entropy, D c , and time-averaged solid holdup was analyzed. [Display omitted] • Kolmogorov entropy and correlation dimension were studied in the cyclone reactor. • A subsequent increase of solid holdup leads to an upturn of chaotic properties. • The higher chaotic properties in the diffusion chamber may favor gas-solids mixing. [ABSTRACT FROM AUTHOR]