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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Photometric classification of Hyper Suprime-Cam transients using machine learning

Abstract The advancement of technology has resulted in a rapid increase in supernova (SN) discoveries. The Subaru/Hyper Suprime-Cam (HSC) transient survey, conducted from fall 2016 through spring 2017, yielded 1824 SN candidates. This gave rise to the need for fast type classification for spectroscopic follow-up and prompted us to develop a machine learning algorithm using a deep neural network with highway layers. This algorithm is trained by actual observed cadence and filter combinations such that we can directly input the observed data array without any interpretation. We tested our model with a dataset from the LSST classification challenge (Deep Drilling Field). Our classifier scores an area under the curve (AUC) of 0.996 for binary classification (SN Ia or non-SN Ia) and 95.3% accuracy for three-class classification (SN Ia, SN Ibc, or SN II). Application of our binary classification to HSC transient data yields an AUC score of 0.925. With two weeks of HSC data since the first detection, this classifier achieves 78.1% accuracy for binary classification, and the accuracy increases to 84.2% with the full dataset. This paper discusses the potential use of machine learning for SN type classification purposes.

Takahashi, Ichiro↗
NASA NTRS2011

The Two Components of the Evolved Massive Binary LZ Cephei: Testing the Effects of Binarity on Stellar Evolution

We present an in-dep(h study of the two components of the binary system LZ Cep to constrain the effects of binarity on the evolution of massive stars. Methods. We analyzed a set of high-resolution, high signal-to-noise ratio optical spectra obtained over the orbital period of the system to perform a spectroscopic disentangling and derive an orbital solution. We subsequently determine the stellar properties of each component by means of an analysis with the CMFGEN atmosphere code. Finally, with the derived stellar parameters, we model the Hipparcos photometric light curve using the program NIGHTFALL to obtain the orbit inclination and the stellar masses. Results.LZ Cep is a O9III+ON9.7V binary. It is as a semi-detailed system in which either the primary or the secondary star almost fills up its Roche lobe. The dynamical masses are about 16.0 Stellar Mass (primary) and 6.5 Stellar Mass (secondary). The latter is lower than the typical mass of late-type O stars. The secondary component is chemically more evolved than the primary (which barely shows any sign of CNO processing), with strong helium and nitrogen enhancements as well as carbon and oxygen depletions. These properties (surface abundances and mass) are typical of Wolf-Rayet stars, although the spectral type is ON9.7V. The luminosity of the secondary is consistent with that of core He-burning objects. The preferred, tentative evolutionary scenario to explain abe observed properties involves mass transfer from the secondary - which was initially more massive- towards the primary. The secondary is now almost a core He-burning object, probably with only a thin envelope of H-rich and CNO processed material. A very inefficient mass transfer is necessary to explain the chemical appearance of the primary. Alternative scenarios are discussed but they are affected by greater uncertainties.

Mahy, L.↗
DOE OSTI2015

CfAIR2: Near-infrared light curves of 94 TYPE Ia supernovae

CfAIR2 is a large, homogeneously reduced set of near-infrared (NIR) light curves (LCs) for Type Ia supernovae (SNe Ia) obtained with the 1.3 m Peters Automated InfraRed Imaging TELescope. This data set includes 4637 measurements of 94 SNe Ia and 4 additional SNe Iax observed from 2005 to 2011 at the Fred Lawrence Whipple Observatory on Mount Hopkins, Arizona. CfAIR2 includes JHK{sub s} photometric measurements for 88 normal and 6 spectroscopically peculiar SN Ia in the nearby universe, with a median redshift of z ∼ 0.021 for the normal SN Ia. CfAIR2 data span the range from −13 days to +127 days from B-band maximum. More than half of the LCs begin before the time of maximum, and the coverage typically contains ∼13–18 epochs of observation, depending on the filter. We present extensive tests that verify the fidelity of the CfAIR2 data pipeline, including comparison to the excellent data of the Carnegie Supernova Project. CfAIR2 contributes to a firm local anchor for SN cosmology studies in the NIR. Because SN Ia are more nearly standard candles in the NIR and are less vulnerable to the vexing problems of extinction by dust, CfAIR2 will help the SN cosmology community develop more precise and accurate extragalactic distance probes to improve our knowledge of cosmological parameters, including dark energy and its potential time variation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Does UV CETI Suffer from the MAD Syndrome?

Photometric data have been analysed and searched for events of flaring and other variability. Some flaring has been detected, though probably not at a level that will hinder our continuing spectral analysis. X-ray diagnostics for the very hot coronal emission measure are under investigation in order to determine whether or not the very hot coronal plasma contributes significantly to the observed X-ray flux in the EUV. The key test of the MAD syndrome lies in whether or not the coronal lines indicate a depletion in met- als in the corona relative to the underlying photosphere. While some progress has been made in this direction, not as much work has been accomplished as expected due to the increasing commitments of the PI to the CXO project as it nears launch. A no-cost extension has been granted in order to further the analysis and carry out the next stages of the investigation: to construct an emission measure distribution with which to compute a synthetic continuum to compare with the observed continuum.

Drake, Jeremy↗
NASA NTRS2019

Experimentally-Derived Phase Function Approximations in Support of the Orbital Debris Program Office

The NASA Orbital Debris Program Office (ODPO) has used various optical assets to acquire photometric data of Earth-orbiting objects to define the orbital debris environment. To better characterize and model optical data acquired from ground-based telescopes, the Optical Measurements Center (OMC) at NASA Johnson Space Center emulates illumination conditions seen in space by using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. One of the OMC goals is to improve the size calculation used for optical data by developing an optical-based Size Estimation Model. The current size estimation requires applying a Lambertian phase function, a set albedo value, and range to the observed magnitude. The first step to improving the sampled brightness of laboratory targets is to remove aspect-angle dependencies. Then, the volume of possible object viewing angles is sampled at 21 combinations of azimuth and elevation angles for each solar phase angle. Finally, the acquired images are input into an image processing program that generates approximations for the object’s Bidirectional Reflectance Distribution Function (BRDF) and phase function. The BRDF is a radiometric concept that identifies an object’s material composition by matching a BRDF approximated with photometric data collected by ground-based telescopes with a BRDF generated experimentally from a known object in the laboratory. This paper presents the initial BRDF and phase function approximations for various fragments/targets acquired in the OMC and how the findings will be incorporated into ODPO models. A Lambertian sphere is used as a baseline for initial size estimation calculations and phase function comparisons. Spacecraft materials and fragments from hypervelocity laboratory impact tests are also presented to compare against the current assumed Lambertian phase function used for size estimates. This paper presents the preliminary phase function analysis and plan forward to utilize a laboratory-based phase function to improve the current optical size estimates using BRDF measurements for a large volume of targets composed of various shapes, sizes, and materials.

Hostetler, J.↗
DOE OSTI2015

POPULATION EFFECTS ON THE METALLICITY DISTRIBUTION FUNCTION DERIVED FROM THE RED GIANT BRANCH

We have tested the reliability of the red giant branch (RGB) as a metallicity indicator accounting for observational errors as well as the complexity of star formation histories and chemical evolution histories observed in various stellar systems. We generate model color–magnitude diagrams (CMDs) produced with a variety of evolutionary histories and compare the resultant metallicity estimates from the colors and magnitudes of RGB stars to the true input metallicities. We include realistic models for photometric errors and completeness in our synthetic CMDs. As expected, for simple simple stellar populations dominated by old stars, the RGB provides a very accurate estimate of the modular metallicity value for a population. An error in the age of a system targeted for this type of study may produce metallicity errors of a few tenths of a dex. The size of this metallicity error depends linearly on the age error, and we find this dependence to be stronger with more precise photometry. If the population has experienced any significant star formation within the last ∼6 Gyr, the metallicity estimates, [M/H], derived from the RGB may be in error by up to ∼0.5 dex. Perhaps the most important consideration for this technique is an accurate, independent estimate of the average age for the target stellar system, especially if it is probable that a significant fraction of the population formed less than ∼6 Gyr ago.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Dark energy survey year 3 results: cosmology from galaxy clustering and galaxy–galaxy lensing in harmonic space

We present the joint tomographic analysis of galaxy-galaxy lensing and galaxy clustering in harmonic space (HS), using galaxy catalogues from the first three years of observations by the Dark Energy Survey (DES Y3). We utilize the redMaGiC and MagLim catalogues as lens galaxies and the metacalibration catalogue as source galaxies. The measurements of angular power spectra are performed using the pseudo-$C_\ell$ method, and our theoretical modelling follows the fiducial analyses performed by DES Y3 in configuration space, accounting for galaxy bias, intrinsic alignments, magnification bias, shear magnification bias and photometric redshift uncertainties. We explore different approaches for scale cuts based on non-linear galaxy bias and baryonic effects contamination. Our fiducial covariance matrix is computed analytically, accounting for mask geometry in the Gaussian term, and including non-Gaussian contributions and super-sample covariance terms. To validate our HS pipelines and covariance matrix, we used a suite of 1800 log-normal simulations. We also perform a series of stress tests to gauge the robustness of our HS analysis. In the $\Lambda$CDM model, the clustering amplitude $S_8 =\sigma _8(\Omega _m/0.3)^{0.5}$ is constrained to $S_8 = 0.704\pm 0.029$ and $S_8 = 0.753\pm 0.024$ (68 per cent C.L.) for the redMaGiC and MagLim catalogues, respectively. For the wCDM, the dark energy equation of state is constrained to $w = -1.28 \pm 0.29$ and $w = -1.26^{+0.34}_{-0.27}$, for redMaGiC and MagLim catalogues, respectively. These results are compatible with the corresponding DES Y3 results in configuration space and pave the way for HS analyses using the DES Y6 data.

(cosmology:) cosmological parameters↗
DOE OSTI2017

Non-negative Matrix Factorization for Self-calibration of Photometric Redshift Scatter in Weak-lensing Surveys

Photo- z error is one of the major sources of systematics degrading the accuracy of weak-lensing cosmological inferences. Zhang et al. proposed a self-calibration method combining galaxy–galaxy correlations and galaxy–shear correlations between different photo- z bins. Fisher matrix analysis shows that it can determine the rate of photo- z outliers at a level of 0.01%–1% merely using photometric data and do not rely on any prior knowledge. In this paper, we develop a new algorithm to implement this method by solving a constrained nonlinear optimization problem arising in the self-calibration process. Based on the techniques of fixed-point iteration and non-negative matrix factorization, the proposed algorithm can efficiently and robustly reconstruct the scattering probabilities between the true- z and photo- z bins. The algorithm has been tested extensively by applying it to mock data from simulated stage IV weak-lensing projects. We find that the algorithm provides a successful recovery of the scatter rates at the level of 0.01%–1%, and the true mean redshifts of photo- z bins at the level of 0.001, which may satisfy the requirements in future lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Using a Neural Network Classifier to Select Galaxies with the Most Accurate Photometric Redshifts

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will produce several billion photometric redshifts (photo-z's), enabling cosmological analyses to select a subset of galaxies with the most accurate photo-z. For this work, we perform initial redshift fits on Subaru Strategic Program galaxies with deep grizy photometry using Trees for Photo-Z (TPZ) before applying a custom neural network classifier (NNC) tuned to select galaxies with (z phot – z spec )/(1 + z spec ) < 0.10. We consider four cases of training and test sets ranging from an idealized case to using data augmentation to increase the representation of dim galaxies in the training set. Selections made using the NNC yield significant further improvements in outlier fraction and photo-z scatter (σ z ) over those made with typical photo-z uncertainties. As an example, when selecting the best third of the galaxy sample, the NNC achieves a 35% improvement in outlier rate and a 23% improvement in σ z compared to using uncertainties from TPZ. For cosmology and galaxy evolution studies, this method can be tuned to retain a particular sample size or to achieve a desired photo-z accuracy; our results show that it is possible to retain more than a third of an LSST-like galaxy sample while reducing σ z by a factor of 2 compared to the full sample, with one-fifth as many photo-z outliers. For surveys like LSST that are not limited by shot noise, this method enables a larger number of tomographic redshift bins and hence a significant increase in the total signal to noise of galaxy angular power spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Does UV CETI Suffer from the Mad Syndrome?

Photometric data have been analyzed and searched for events of flaring and other variability. Some flaring has been detected, though probably not at a level that will hinder our continuing spectral analysis. X-ray diagnostics for the very hot coronal emission measure are under investigation in order to determine whether or not the very hot coronal plasma contributes significantly to the observed X-ray flux in the (EUV) Extreme Ultraviolet Radiation. The key test of the MAD syndrome lies in whether or not the coronal lines indicate a depletion in metals in the corona relative to the underlying photosphere.

Drake, Jeremy↗
DOE OSTI2018

Efficient derivatization of methylphosphonic and aminoethylsulfonic acids related to nerve agents simultaneously in soils using trimethyloxonium tetrafluoroborate for their enhanced, qualitative detection and identification by EI-GC–MS and GC–FPD

Trimethyloxonium tetrafluoroborate (TMO·BF 4 ) has been used here in the simultaneous derivatization of phosphonic and 2-aminoethylsulfonic acids related to nerve agents in different soils for their enhanced detection and identification by electron ionization gas chromatography-mass spectrometry (EI-GC–MS). The panel of acids consisted of five Schedule 2 phosphonic acids (methyl methylphosphonic acid, ethyl methylphosphonic acid, isopropyl methylphosphonic acid, pinacolyl methylphosphonic acid and cyclohexyl methylphosphonic acid) along with two sulfonic acids, N,N-diethyl-2-aminoethylsulfonic acid and N,N-diisopropyl-2-aminoethylsulfonic acid. The acids were converted to their corresponding methyl esters at ambient temperature when present at a 10 μg g -1 concentration in three separate soils: Virginia type A soil, Ottawa sand and Nebraska EPA soil. The concentration of the acids reflects values typically encountered during proficiency tests (PTs) administered annually by the Organisation for the Prohibition of Chemical Weapons (OPCW). Derivatization times to yield detectable signals for the methyl ester products for all the acids was found to vary among all three soil samples, however, it was found that generally the most optimal time across all the matrices involved was 3 h after the addition of TMO·BF 4 . Concomitantly, the analysis of the samples was complemented using GC coupled to flame photometric detection (GC–FPD). The inclusion of GC–FPD in the analysis yielded stronger signals for all seven methylated analytes making their detection after merely 3 h possible relative to the ones initially obtained with EI-GC–MS. Regarding the three soils employed in our study, a greater methylating efficiency was found in the Virginia type A soil and Ottawa sand yielding results that were significantly larger in magnitude to those found during the same time points for the Nebraska EPA soil sample. Prolonged reaction times (up to 72 h) were explored to find the time for the highest yield of methyl ester production were found instead to be deleterious to the process showcasing the importance of the fast yielding nature of the process specifically in situations where time-sensitive analysis is crucial (e.g. OPCW-PT).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

IDENTIFICATION OF 1.4 MILLION ACTIVE GALACTIC NUCLEI IN THE MID-INFRARED USING WISE DATA

We present an all-sky sample of ≈1.4 million active galactic nuclei (AGNs) meeting a two-color infrared photometric selection criteria for AGNs as applied to sources from the Wide-field Infrared Survey Explorer final catalog release (AllWISE). We assess the spatial distribution and optical properties of our sample and find that the results are consistent with expectations for AGNs. These sources have a mean density of ≈38 AGNs per square degree on the sky, and their apparent magnitude distribution peaks at g ≈ 20, extending to objects as faint as g ≈ 26. We test the AGN selection criteria against a large sample of optically identified stars and determine the “leakage” (that is, the probability that a star detected in an optical survey will be misidentified as a quasi-stellar object (QSO) in our sample) rate to be ≤4.0 × 10{sup −5}. We conclude that our sample contains almost no optically identified stars (≤0.041%), making this sample highly promising for future celestial reference frame work as it significantly increases the number of all-sky, compact extragalactic objects. We further compare our sample to catalogs of known AGNs/QSOs and find a completeness value of ≳84% (that is, the probability of correctly identifying a known AGN/QSO is at least 84%) for AGNs brighter than a limiting magnitude of R ≲ 19. Our sample includes approximately 1.1 million previously uncataloged AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2000

The AGN Content of the Micron all Sky Survey

The Two Micron All Sky Survey (2MASS) began routine operations from its northern facility on Mt. Hopkins, AZ in June of 1997, and from its southern facility on Cerro Tololo, Chile in March of 1998. At each site, highly automated 1.3 m telescopes equipped with identical 3-channel cameras, are systematically imaging the sky in three near infrared wavelength bands, J (1.25 um), H (1.65 um) and K-s (2.17 um). The Survey will ultimately produce an Image Atlas containing nearly two million 512 x 1024 pixel images (1 arcsec/pix) in the three colors, a highly complete and reliable catalog containing approx. 300 million point sources having SNR greater than 10 photometry at J less or = 15.8, H less or = 15.1 and K-s less or = 14.3 mag. and an astrometric accuracy greater than 0.511 RMS, and a catalog of 1-2 million resolved sources, primarily galaxies, having SNR greater than 10 photometric accuracy at J less than or = 15.5, H less than or = 14.8 and K-s less than or = 13.5 mag. The 2MASS Sampler, an introductory set of data, was released to the community in December of 1998 (see http://www.ipac.caltech.edu/2mass/). We review the near IR and optical/IR properties of "conventional" QSOs from UV and optical samples, and estimate the number that will be detected by 2MASS. We also discuss 2MASS's ability to test for for new populations of extremely red AGN that have been missed by UV and Visual surveys, as suggested by from IRAS and radio studies. Results of spectroscopic follow-up of 2MASS-selected new AGN candidates will also be presented.

Cutri, R. M.↗
DOE OSTI2017

On the Statistical Properties of the Lower Main Sequence

Astronomy is in an era where all-sky surveys are mapping the Galaxy. The plethora of photometric, spectroscopic, asteroseismic, and astrometric data allows us to characterize the comprising stars in detail. Here we quantify to what extent precise stellar observations reveal information about the properties of a star, including properties that are unobserved, or even unobservable. We analyze the diagnostic potential of classical and asteroseismic observations for inferring stellar parameters such as age, mass, and radius from evolutionary tracks of solar-like oscillators on the lower main sequence. We perform rank correlation tests in order to determine the capacity of each observable quantity to probe structural components of stars and infer their evolutionary histories. We also analyze the principal components of classic and asteroseismic observables to highlight the degree of redundancy present in the measured quantities and demonstrate the extent to which information of the model parameters can be extracted. We perform multiple regression using combinations of observable quantities in a grid of evolutionary simulations and appraise the predictive utility of each combination in determining the properties of stars. We identify the combinations that are useful and provide limits to where each type of observable quantity can reveal information about a star. We investigate the accuracy with which targets in the upcoming TESS and PLATO missions can be characterized. We demonstrate that the combination of observations from GAIA and PLATO will allow us to tightly constrain stellar masses, ages, and radii with machine learning for the purposes of Galactic and planetary studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A DECADE of dwarfs: first detection of weak lensing around spectroscopically confirmed low-mass galaxies

We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5σ$ lower than $Λ$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $Λ$CDM predictions.

To, Chun-Hao [Chicago U., Astron. Astrophys. Ctr.;↗
DOE OSTI2017

Effects of self-calibration of intrinsic alignment on cosmological parameter constraints from future cosmic shear surveys

Intrinsic alignments (IA) of galaxies have been recognized as one of the most serious contaminants to weak lensing. These systematics need to be isolated and mitigated in order for ongoing and future lensing surveys to reach their full potential. The IA self-calibration (SC) method was shown in previous studies to be able to reduce the GI contamination by up to a factor of 10 for the 2-point and 3-point correlations. The SC method does not require the assumption of an IA model in its working and can extract the GI signal from the same photo-z survey offering the possibility to test and understand structure formation scenarios and their relationship to IA models. In this paper, we study the effects of the IA SC mitigation method on the precision and accuracy of cosmological parameter constraints from future cosmic shear surveys LSST, WFIRST and Euclid. We perform analytical and numerical calculations to estimate the loss of precision and the residual bias in the best fit cosmological parameters after the self-calibration is performed. We take into account uncertainties from photometric redshifts and the galaxy bias. We find that the confidence contours are slightly inflated from applying the SC method itself while a significant increase is due to the inclusion of the photo-z uncertainties. The bias of cosmological parameters is reduced from several-σ, when IA is not corrected for, to below 1-σ after SC is applied. These numbers are comparable to those resulting from applying the method of marginalizing over IA model parameters despite the fact that the two methods operate very differently. We conclude that implementing the SC for these future cosmic-shear surveys will not only allow one to efficiently mitigate the GI contaminant but also help to understand their modeling and link to structure formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The DESI-Lensing Mock Challenge: large-scale cosmological analysis of 3x2-pt statistics

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of analysis including cosmological measurements, modelling, covariance and parameter likelihood. In this paper we present the results of an end-to-end simulation study designed to test the analysis pipeline for the combination of the Dark Energy Spectroscopic Instrument (DESI) Year 1 galaxy redshift dataset and separate weak gravitational lensing information from the Kilo-Degree Survey, Dark Energy Survey and Hyper-Suprime-Cam Survey. Our analysis employs the 3x2-pt correlation functions including cosmic shear and galaxy-galaxy lensing, together with the projected correlation function of the spectroscopic DESI lenses. We build realistic simulations of these datasets including galaxy halo occupation distributions, photometric redshift errors, weights, multiplicative shear calibration biases and magnification. We calculate the analytical covariance of these correlation functions including the Gaussian, noise and super-sample contributions, and show that our covariance determination agrees with estimates based on the ensemble of simulations. We use a Bayesian inference platform to demonstrate that we can recover the fiducial cosmological parameters of the simulation within the statistical error margin of the experiment, investigating the sensitivity to scale cuts. This study is the first in a sequence of papers in which we present and validate the large-scale 3x2-pt cosmological analysis of DESI-Y1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Automatic detection of cataclysmic variables from SDSS images

Abstract Investigating rare and new objects have always been an important direction in astronomy. Cataclysmic variables (CVs) are ideal and natural celestial bodies for studying the accretion process of semi-detached binaries with accretion processes. However, the sample size of CVs must increase because a lager gap exists between the observational and the theoretical expanding CVs. Astronomy has entered the big data era and can provide massive images containing CV candidates. CVs as a type of faint celestial objects, are highly challenging to be identified directly from images using automatic manners. Deep learning has rapidly developed in intelligent image processing and has been widely applied in some astronomical fields with excellent detection results. YOLOX, as the latest YOLO framework, is advantageous in detecting small and dark targets. This work proposes an improved YOLOX-based framework according to the characteristics of CVs and Sloan Digital Sky Survey (SDSS) photometric images to train and verify the model to realise CV detection. We use the Convolutional Block Attention Module to increase the number of output features with the feature extraction network and adjust the feature fusion network to obtain fused features. Accordingly, the loss function is modified. Experimental results demonstrate that the improved model produces satisfactory results, with average accuracy (mean average Precision at 0.5) of 92.0%, Precision of 92.9%, Recall of 94.3%, and $F1-score$ of 93.6% on the test set. The proposed method can efficiently achieve the identification of CVs in test samples and search for CV candidates in unlabeled images. The image data vastly outnumber the spectra in the SDSS-released data. With supplementary follow-up observations or spectra, the proposed model can help astronomers in seeking and detecting CVs in a new manner to ensure that a more extensive CV catalog can be built. The proposed model may also be applied to the detection of other kinds of celestial objects.

Astronomy & Astrophysics↗