Flux Bins Research Articles

X-Ray Polarization Variability of High Spectral Peak BL Lacertaes: Cases of 1ES 1959+650 and PKS 2155–304

Abstract The high-energy-peaked BL Lacertae objects (HBLs) are the main targets of the Imaging X-ray Polarimetry Explorer (IXPE) for investigating the mechanisms of radiation and particle acceleration in jets. In this Letter, we report the first IXPE observations of two HBLs, 1ES 1959+650 and PKS 2155–304. Both sources exhibit X-ray polarization with a confidence level exceeding 99%, as well as significant variability in polarization across different time intervals and energy ranges. Notably, PKS 2155–304 demonstrates the highest X-ray polarization among all blazars detected by IXPE within its entire energy band (2–8 keV), with a polarization degree of ΠX = 21.9% ± 1.9% (MDP99 ∼ 6.0%). An even higher polarization is observed in the 3–4 keV band, reaching ΠX = 28.6% ± 2.7% (MDP99 ∼ 8.1%) with a confidence level of 10.8σ. Furthermore, no polarization is detected above the 5 keV energy band. For 1ES 1959+650, the highest detected polarization degree in the 2–8 keV band is ΠX = 12.4% ± 0.7% (MDP99 ∼ 2.2%), with an electric vector position angle (EVPA) of ψ X = 19.°7 ± 1.°6. The X-ray polarization of 1ES 1959+650 exhibits evident variability, accompanied by the variations of ψ X, flux, spectrum, and energy bin. We discuss possible implications of these observational findings, including the variability in polarization, rotation of EVPA, and transition between synchrotron and synchrotron–self-Compton. We speculate that the X-rays observed during different IXPE observations originate from distinct regions in the jet and may involve diverse mechanisms for particle acceleration.

Constraining below-threshold radio source counts with machine learning

We propose a machine-learning-based technique to determine the number density of radio sources as a function of their flux density, for use in next-generation radio surveys. The method uses a convolutional neural network trained on simulations of the radio sky to predict the number of sources in several flux bins. To train the network, we adopt a supervised approach wherein we simulate training data stemming from a large domain of possible number count models going down to fluxes a factor of 100 below the threshold for source detection. We test the model reconstruction capabilities as well as benchmark the expected uncertainties in the model predictions, observing good performance for fluxes down to a factor of ten below the threshold. This work demonstrates that the capabilities of simple deep learning models for radio astronomy can be useful tools for future surveys.

Detecting galaxies in a large H i spectral cube

The upcoming square kilometer array (SKA) is expected to produce humongous amount of data for undertaking H i science. We have developed an MPI-based Python pipeline to deal with the large data efficiently with the present computational resources. Our pipeline divides such large H i 21-cm spectral cubes into several small cubelets, and then processes them in parallel using publicly available H i source finder SoFiA-2. The pipeline also takes care of sources at the boundaries of the cubelets and also filters out false and redundant detections. By comapring with the true source catalog, we find that the detection efficiency depends on the SoFiA-2 parameters, such as the smoothing kernel size, linking length and threshold values. We find the optimal kernel size for all flux bins to be between 3–5 and 7–15 pixels, respectively, in the spatial and frequency directions. Comparing the recovered source parameters with the original values, we find that the output of SoFiA-2 is highly dependent on kernel sizes and a single choice of kernel is not sufficient for all types of H i galaxies. We also propose the use of alternative methods to SoFiA-2, which can be used in our pipeline to find sources more robustly.

Surface Mass-Balance Gradients From Elevation and Ice Flux Data in the Columbia Basin, Canada

The mass-balance—elevation relation for a given glacier is required for many numerical models of ice flow. Direct measurements of this relation using remotely-sensed methods are complicated by ice dynamics, so observations are currently limited to glaciers where surface mass-balance measurements are routinely made. We test the viability of using the continuity equation to estimate annual surface mass balance between flux-gates in the absence of in situ measurements, on five glaciers in the Columbia Mountains of British Columbia, Canada. Repeat airborne laser scanning surveys of glacier surface elevation, ice penetrating radar surveys and publicly available maps of ice thickness are used to estimate changes in surface elevation and ice flux. We evaluate this approach by comparing modeled to observed mass balance. Modeled mass-balance gradients well-approximate those obtained from direct measurement of surface mass balance, with a mean difference of +6.6 ± 4%. Regressing modeled mass balance, equilibrium line altitudes are on average 15 m higher than satellite-observations of the transient snow line. Estimates of mass balance over flux bins compare less favorably than the gradients. Average mean error (+0.03 ± 0.07 m w.e.) between observed and modeled mass balance over flux bins is relatively small, yet mean absolute error (0.55 ± 0.18 m w.e.) and average modeled mass-balance uncertainty (0.57 m w.e.) are large. Mass conservation, assessed with glaciological data, is respected (when estimates are within 1σ uncertainties) for 84% of flux bins representing 86% of total glacier area. Uncertainty on ice velocity, especially for areas where surface velocity is low (<10 m a−1) contributes the greatest error in estimating ice flux. We find that using modeled ice thicknesses yields comparable modeled mass-balance gradients relative to using observations of ice thickness, but we caution against over-interpreting individual flux-bin mass balances due to large mass-balance residuals. Given the performance of modeled ice thickness and the increasing availability of ice velocity and surface topography data, we suggest that similar efforts to produce mass-balance gradients using modern high-resolution datasets are feasible on larger scales.

Weak-lensing Power Spectrum Reconstruction by Counting Galaxies. I. The ABS Method

Abstract We propose an analytical method of blind separation (ABS) of cosmic magnification from the intrinsic fluctuations of galaxy number density in the observed galaxy number density distribution. The ABS method utilizes the different dependences of the signal (cosmic magnification) and contamination (galaxy intrinsic clustering) on galaxy flux to separate the two. It works directly on the measured cross-galaxy angular power spectra between different flux bins. It determines/reconstructs the lensing power spectrum analytically, without assumptions of galaxy intrinsic clustering and cosmology. It is unbiased in the limit of an infinite number of galaxies. In reality, the lensing reconstruction accuracy depends on survey configurations, galaxy biases, and other complexities due to a finite number of galaxies and the resulting shot noise fluctuations in the cross-galaxy power spectra. We estimate its performance (systematic and statistical errors) in various cases. We find that stage IV dark energy surveys such as Square Kilometre Array and Large Synoptic Survey Telescope are capable of reconstructing the lensing power spectrum at and accurately. This lensing reconstruction only requires counting galaxies and is therefore highly complementary to cosmic shear measurement by the same surveys.

Monte Carlo analysis of a control technique for a tunable white lighting system

A simulated colour control mechanism for a multi-coloured LED lighting system is presented. The system achieves adjustable and stable white light output and allows for system-to-system reproducibility after application of the control mechanism. The control unit works using a pre-calibrated lookup table for an experimentally realized system, with a calibrated tristimulus colour sensor. A Monte Carlo simulation is used to examine the system performance concerning the variation of luminous flux and chromaticity of the light output. The inputs to the Monte Carlo simulation are variations of the LED peak wavelength, the LED rated luminous flux bin, the influence of the operating conditions, ambient temperature, driving current and the spectral response of the colour sensor. The system performance is investigated by evaluating the outputs from the Monte Carlo simulation. The outputs show that the applied control system yields an uncertainty on the luminous flux of 2.5% within a 95% coverage interval which is a significant reduction from the 8% of the uncontrolled system. A corresponding uncertainty reduction in Δu ′v ′ is achieved from an average of 0.0193 to 0.00125 within 95% coverage range after using the control system.

Weak lensing reconstruction through cosmic magnification – II. Improved power spectrum determination and map-making

The existence of galaxy intrinsic clustering severely hampers the weak lensing reconstruction from cosmic magnification. In paper I \citep{Yang2011}, we proposed a minimal variance estimator to overcome this problem. By utilizing the different dependences of cosmic magnification and galaxy intrinsic clustering on galaxy flux, we demonstrated that the otherwise overwhelming galaxy intrinsic clustering can be significantly suppressed such that lensing maps can be reconstructed with promising accuracy. This procedure relies heavily on the accuracy of determining the galaxy bias from the same data. Paper I adopts an iterative approach, which degrades toward high redshift. The current paper presents an alternative method, improving over paper I. We prove that the measured galaxy clustering between flux bins allows for simultaneous determination of the lensing power spectrum and the flux dependence of galaxy bias, at this redshift bin. Comparing to paper I, the new approach is not only more straightforward, but also more robust. It identifies an ambiguity in determining the galaxy bias and further discovers a mathematically robust way to suppress this ambiguity to non-negligible level ($\sim 0.1%$). The accurately determined galaxy bias can then be applied to the minimal variance estimator proposed in paper I to improve the lensing map-making. The gain at high redshift is significant. These maps can be used to measure other statistics, such as cluster finding and peak statistics. Furthermore, by including galaxy clustering measurement between different redshift bins, we can also determine the lensing cross power spectrum between these bins, up to a small and correctable multiplicative factor.

FOREGROUND PREDICTIONS FOR THE COSMIC MICROWAVE BACKGROUND POWER SPECTRUM FROM MEASUREMENTS OF FAINT INVERTED RADIO SOURCES AT 5 GHz

We present measurements of a population of matched radio sources at 1.4 and 5 GHz down to a flux limit of 1.5 mJy in 7 sq. degs. of the NOAO Deep Field South. We find a significant fraction of sources with inverted spectral indices that all have 1.4 GHz fluxes less than 10 mJy, and are therefore too faint to have been detected and included in previous radio source count models that are matched at multiple frequencies. Combined with the matched source population at 1.4 and 5 GHz in 1 sq. deg. in the ATESP survey, we update models for the 5 GHz differential number counts and distributions of spectral indices in 5 GHz flux bins that can be used to estimate the unresolved point source contribution to the cosmic microwave background temperature anisotropies. We find a shallower logarithmic slope in the 5 GHz differential counts than in previously published models for fluxes < 100 mJy as well as larger fractions of inverted spectral indices at these fluxes. Because the Planck flux limit for resolved sources is larger than 100 mJy in all channels, our modified number counts yield at most a 10% change in the predicted Poisson contribution to the Planck temperature power spectrum. For a flux cut of 5 mJy with the South Pole Telescope and a flux cut of 20 mJy with the Atacama Cosmology Telescope we predict a ~30% and ~10% increase, respectively, in the radio source Poisson power in the lowest frequency channels of each experiment relative to that predicted by previous models.

X-ray spectral evolution in the ultraluminous X-ray source M33 X-8

The bright ultraluminous X-ray source (ULX), M33 X-8, has been observed several times by XMM-Newton, providing us with a rare opportunity to `flux bin' the spectral data and search for changes in the average X-ray spectrum with flux level. The aggregated X-ray spectra appear unlike standard sub-Eddington accretion state spectra which, alongside the lack of discernible variability at any energy, argues strongly against conventional two-component, sub-Eddington models. Although the lack of variability could be consistent with disc-dominated spectra, sub-Eddington disc models are not sufficiently broad to explain the observed spectra. Fits with a ~ Eddington accretion rate slim disc model are acceptable, but the fits show that the temperature decreases with flux, contrary to expectations, and this is accompanied by the appearance of a harder tail to the spectrum. Applying a suitable two-component model reveals that the disc becomes cooler and less advection dominated as the X-ray flux increases, and this is allied to the emergence of an optically-thick Comptonisation medium. We present a scenario in which this is explained by the onset of a radiatively-driven wind from the innermost regions of the accretion disc, as M33 X-8 exceeds the Eddington limit. Furthermore, we argue that the direct evolution of this spectrum with increasing luminosity (and hence radiation pressure) leads naturally to the two-component spectra seen in more luminous ULXs.

Weak lensing reconstruction through cosmic magnification - I. A minimal variance map reconstruction

We present a concept study on weak lensing map reconstruction through the cosmic magnification effect in galaxy number density distribution. We propose a minimal variance linear estimator to minimize both the dominant systematical and statistical errors in the map reconstruction. It utilizes the distinctively different flux dependences to separate the cosmic magnification signal from the overwhelming galaxy intrinsic clustering noise. It also minimizes the shot noise error by an optimal weighting scheme on the galaxy number density in each flux bin. Our method is in principle applicable to all galaxy surveys with reasonable redshift information. We demonstrate its applicability against the planned Square Kilometer Array survey, under simplified conditions. Weak lensing maps reconstructed through our method are complementary to that from cosmic shear and CMB and 21cm lensing. They are useful for cross checking over systematical errors in weak lensing reconstruction and for improving cosmological constraints.

Simulations of the cosmic infrared and submillimeter background for future large surveys

<i>Context. <i/>Herschel and Planck are surveying the sky at unprecedented angular scales and sensitivities over large areas. But both experiments are limited by source confusion in the submillimeter. The high confusion noise in particular restricts the study of the clustering properties of the sources that dominate the cosmic infrared background. At these wavelengths, it is more appropriate to consider the statistics of the unresolved component. In particular, high clustering will contribute in excess of Poisson noise in the power spectra of CIB anisotropies.<i>Aims. <i/>These power spectra contain contributions from sources at all redshift. We show how the stacking technique can be used to separate the different redshift contributions to the power spectra.<i>Methods. <i/>We use simulations of CIB representative of realistic Spitzer, Herschel, Planck, and SCUBA-2 observations. We stack the 24 <i>μ<i/>m sources in longer wavelengths maps to measure mean colors per redshift and flux bins. The information retrieved on the mean spectral energy distribution obtained with the stacking technique is then used to clean the maps, in particular to remove the contribution of low-redshift undetected sources to the anisotropies.<i>Results. <i/>Using the stacking, we measure the mean flux of populations 4 to 6 times fainter than the total noise at 350 <i>μ<i/>m at redshifts <i>z<i/> = 1 and <i>z<i/> = 2, respectively, and as faint as 6 to 10 times fainter than the total noise at 850 <i>μ<i/>m at the same redshifts. In the deep Spitzer fields, the detected 24 <i>μ<i/>m sources up to <i>z<i/> ~ 2 contribute significantly to the submillimeter anisotropies. We show that the method provides excellent (using COSMOS 24 <i>μ<i/>m data) to good (using SWIRE 24 <i>μ<i/>m data) removal of the <i>z<i/> < 2 (COSMOS) and <i>z<i/> < 1 (SWIRE) anisotropies.<i>Conclusions. <i/>Using this cleaning method, we then hope to have a set of large maps dominated by high redshift galaxies for galaxy evolution study (e.g., clustering, luminosity density).

SUBMILLIMETER NUMBER COUNTS FROM STATISTICAL ANALYSIS OF BLAST MAPS

We describe the application of a statistical method to estimate submillimeter galaxy number counts from confusion limited observations by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Our method is based on a maximum likelihood fit to the pixel histogram, sometimes called 'P(D)', an approach which has been used before to probe faint counts, the difference being that here we advocate its use even for sources with relatively high signal-to-noise ratios. This method has an advantage over standard techniques of source extraction in providing an unbiased estimate of the counts from the bright end down to flux densities well below the confusion limit. We specifically analyse BLAST observations of a roughly 10 sq. deg. map centered on the Great Observatories Origins Deep Survey South (GOODS-S) field. We provide estimates of number counts at the three BLAST wavelengths, 250, 350, and 500 microns; instead of counting sources in flux bins we estimate the counts at several flux density nodes connected with power-laws. We observe a generally very steep slope for the counts of about -3.7 at 250 microns and -4.5 at 350 and 500 microns, over the range ~0.02-0.5 Jy, breaking to a shallower slope below about 0.015 Jy at all three wavelengths. We also describe how to estimate the uncertainties and correlations in this method so that the results can be used for model-fitting. This method should be well-suited for analysis of data from the Herschel satellite.

A deep VLA survey at 6 cm in the Lockman Hole

We have obtained a deep radio image with the Very Large Array at 6 cm in the Lockman Hole. The noise level in the central part of the field is about 11 microJy. From these data we have extracted a catalogue of 63 radio sources. The analysis of the radio spectral index suggests a flattening of the average radio spectra and an increase of the population of flat spectrum radio sources in the faintest flux bin. Cross correlation with the ROSAT/XMM X-ray sources list yields 13 reliable radio/X-ray associations, corresponding to about 21 per cent of the radio sample. Most of these associations (8 out of 13) are classified as Type II AGN. Using optical CCD (V and I) and K' band data we found an optical identification for 58 of the 63 radio sources. This corresponds to an identification rate of about 92 per cent, one of the highest percentages so far available. From the analysis of the colour-colour diagram and of the radio flux - optical magnitude diagram we have been able to select a subsample of radio sources whose optical counterparts are likely to be high redshift (z>0.5) early-type galaxies, hosting an Active Galactic Nucleus responsible of the radio activity. We also find evidence that at these faint radio limits a large fraction (about 60 per cent) of the faintest optical counterparts (i.e. sources in the magnitude range 22.5 4.

Constraining the LogN-LogSRelation of Far-Infrared Unresolved Sources Using aP(D)Analysis; Application to FIRBACK Maps Obtained by ISO

The FIRBACK survey is a deep imaging survey carried out with ISOPHOT on board ISO, at 170 μ m. The survey covers ≈4 sq deg in three high galactic latitude fields (FIRBACK South Marano, FIRBACK North 1 and FIRBACK/ELAIS North 2). In these fields, fluctuations due to unresolved extra-galactic sources were isolated for the first time [1]. We are using a P(D) (probability distribution of fluctuations) analysis to gain information about the N(≥S) curve of the unresolved sources which make up the background. Many planned surveys ( e.g. SIRTF, FIRST, PLANCK...) will pose the same analysis challenges and we hope that the outcome of this study will be useful in that context. As a preparation to the analysis of the FIRBACK maps we analyze simulated sky maps. We create histograms of number of pixels per flux bin. The histograms are binned such that there are enough pixels per bin to allow us to apply Gaussian estimates for the errors. We then calculate the expected number of pixels within the relevant flux ranges and evaluate the χ 2 statistic. We will use a maximum likelihood algorithm to find the parameters of N(≥S) .

Dosimetry modeling of inhaled formaldehyde: binning nasal flux predictions for quantitative risk assessment.

Interspecies extrapolations of tissue dose and tumor response have been a significant source of uncertainty in formaldehyde cancer risk assessment. The ability to account for species-specific variation of dose within the nasal passages would reduce this uncertainty. Three-dimensional, anatomically realistic, computational fluid dynamics (CFD) models of nasal airflow and formaldehyde gas transport in the F344 rat, rhesus monkey, and human were used to predict local patterns of wall mass flux (pmol/[mm(2)-h-ppm]). The nasal surface of each species was partitioned by flux into smaller regions (flux bins), each characterized by surface area and an average flux value. Rat and monkey flux bins were predicted for steady-state inspiratory airflow rates corresponding to the estimated minute volume for each species. Human flux bins were predicted for steady-state inspiratory airflow at 7.4, 15, 18, 25.8, 31.8, and 37 l/min and were extrapolated to 46 and 50 l/min. Flux values higher than half the maximum flux value (flux median) were predicted for nearly 20% of human nasal surfaces at 15 l/min, whereas only 5% of rat and less than 1% of monkey nasal surfaces were associated with fluxes higher than flux medians at 0.576 l/min and 4.8 l/min, respectively. Human nasal flux patterns shifted distally and uptake percentage decreased as inspiratory flow rate increased. Flux binning captures anatomical effects on flux and is thereby a basis for describing the effects of anatomy and airflow on local tissue disposition and distributions of tissue response. Formaldehyde risk models that incorporate flux binning derived from anatomically realistic CFD models will have significantly reduced uncertainty compared with risk estimates based on default methods.