分类： 核科学技术 >> 辐射物理与技术 提交时间： 2024-05-30
摘要： Cone-beam computed tomography (CBCT) is mostly used for position verification during the treatment pro#2;cess. However, severe image artifacts in CBCT hinder its direct use in dose calculation and adaptive radiationtherapy re-planning for proton therapy. In this study, an improved U-Net neural network named CBAM-U-Netwas proposed for CBCT noise reduction in proton therapy, which is a CBCT denoised U-Net network with con#2;volutional block attention modules. The datasets contained 20 groups of head and neck images. The CT imageswere registered to CBCT images as ground truth. The original CBCT denoised U-Net network, sCTU-Net, wastrained for model performance comparison. The synthetic CT(SCT) images generated by CBAM-U-Net and theoriginal sCTU-Net are called CBAM-SCT and U-Net-SCT images, respectively. The HU accuracies of the CT,CBCT, and SCT images were compared using four metrics: mean absolute error (MAE), root mean square error(RMSE), peak signal-to-noise ratio (PSNR), and structure similarity index measure (SSIM). The mean values ofthe MAE, RMSE, PSNR, and SSIM of CBAM-SCT images were 23.80 HU, 64.63 HU, 52.27 dB, and 0.9919,respectively, which were superior to those of the U-Net-SCT images. To evaluate dosimetric accuracy, the rangeaccuracy was compared for a single-energy proton beam. The γ-index pass rates of a 4 cm × 4 cm scannedfield and simple plan were calculated to compare the effects of the noise reduction capabilities of the originalU-Net and CBAM-U-Net on the dose calculation results. CBAM-U-Net reduced noise more effectively thansCTU-Net, particularly in high-density tissues. We proposed a CBAM-U-Net model for CBCT noise reductionin proton therapy. Owing to the excellent noise reduction capabilities of CBAM-U-Net, the proposed modelprovided relatively explicit information regarding patient tissues. Moreover, it can be used in dose calculationand adaptive treatment planning in the future.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Ruibiao Luo
Liping Fu
Wentao Luo
Nicola R. Napolitano
Linghua Xie
Mario Radovich
Jing Liu
Rui Li
Valeria Amaro
Zhu Chen
Dezi Liu
Zuhui Fan
Giovanni Covone
Mattia Vaccari
摘要： The multi-band photometry of the VOICE imaging data, overlapping with 4.9 deg$^2$ of the Chandra Deep Field South (CDFS) area, enables both shape measurement and photometric redshift estimation to be the two essential quantities for weak lensing analysis. The depth of $mag_{AB}$ is up to 26.1 (5$\sigma$ limiting) in $r$-band. We estimate the Excess Surface Density (ESD; $\Delta\Sigma$) based on galaxy-galaxy measurements around galaxies at lower redshift (0.10<$z_l$<0.35) while we select the background sources to be at higher redshift ranging from 0.3 to 1.5. The foreground galaxies are divided into two major categories according to their colour (blue/red), each of which has been further divided into high/low stellar mass bins. Then the halo masses of the samples are estimated by modelling the signals, and the posterior of the parameters are samples via Mote Carlo Markov Chain (MCMC) process. We compare our results with the existing Stellar-to-Halo Mass Relation (SHMR) and find that the blue low stellar mass bin (median $M_*=10^{8.31}M_\odot$) deviates from the SHMR relation whereas all other three samples agrees well with empirical curves. We interpret this discrepancy as the effect of a low star formation efficiency of the low-mass blue dwarf galaxy population dominated in the VOICE-CDFS area.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Sha-Sha Li
Hai-Cheng Feng
H. T. Liu
J. M. Bai
Rui Li
Kai-Xing Lu
Jian-Guo Wang
Ying-Ke Huang
Zhi-Xiang Zhang
摘要： Changing-look active galactic nucleus NGC~4151, which has attracted a lot of attention, is undergoing the second dramatic outburst stage in its evolutionary history. To investigate the geometry and kinematics of the broad-line region (BLR), and measure the mass of supermassive black hole in NGC~4151, we perform a seven-month photometric and spectroscopic monitoring program in 2020--2021, using the 2.4 m telescope at Lijiang Observatory. We successfully measure the time lags of the responses from broad \ha, \hb, \hg, \hei, and \heii\ emission lines to continuum variation, which are $7.63_{-2.62}^{+1.85}$, $6.21_{-1.13}^{+1.41}$, $5.67_{-1.94}^{+1.65}$, $1.59_{-1.11}^{+0.86}$, and $0.46_{-1.06}^{+1.22}$ days, respectively, following radial stratification. The ratios of time lags among these lines are $1.23 : 1.00 : 0.91 : 0.26 : 0.07$. We find that the continuum lag between the ultraviolet and optical bands can significantly affect the lag measurements of \hei\ and \heii. Virial and infalling gas motions coexist in this campaign, which is different from previous results, implying the evolutionary kinematics of BLR. Based on our measurements and previous ones in the literature, we confirm that the BLR of NGC~4151 is basically virialized. Finally, we compute the black hole mass through multiple lines, and the measurement from \hb\ to be $ 3.94_{-0.72}^{+0.90} \times 10^7 M_{\odot}$, which is consistent with previous results. The corresponding accretion rate is $0.02_{-0.01}^{+0.01} L_{\rm Edd} c^{-2}$, implying a sub-Eddington accretor.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Fabrizio Gentile
Crescenzo Tortora
Giovanni Covone
Léon V. E. Koopmans
Rui Li
Laura Leuzzi
Nicola R. Napolitano
摘要： The unprecedented number of gravitational lenses expected from new-generation facilities such as the ESA Euclid telescope and the Vera Rubin Observatory makes it crucial to rethink our classical approach to lens-modelling. In this paper, we present LeMoN (Lens Modelling with Neural networks): a new machine-learning algorithm able to analyse hundreds of thousands of gravitational lenses in a reasonable amount of time. The algorithm is based on a Bayesian Neural Network: a new generation of neural networks able to associate a reliable confidence interval to each predicted parameter. We train the algorithm to predict the three main parameters of the Singular Isothermal Ellipsoid model (the Einstein radius and the two components of the ellipticity) by employing two simulated datasets built to resemble the imaging capabilities of the Hubble Space Telescope and the forthcoming Euclid satellite. In this work, we assess the accuracy of the algorithm and the reliability of the estimated uncertainties by applying the network to several simulated datasets of 10.000 images each. We obtain accuracies comparable to previous studies present in the current literature and an average modelling time of just 0.5s per lens. Finally, we apply the LeMoN algorithm to a pilot dataset of real lenses observed with HST during the SLACS program, obtaining unbiased estimates of their SIE parameters. The code is publicly available on GitHub (https://github.com/fab-gentile/LeMoN).
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Rui Li
Nicola R. Napolitano
Haicheng Feng
Ran Li
Valeria Amaro
Linghua Xie
Crescenzo Tortora
Maciej Bilicki
Massimo Brescia
Stefano Cavuoti
Mario Radovich
摘要： In the era of large sky surveys, photometric redshifts (photo-z) represent crucial information for galaxy evolution and cosmology studies. In this work, we propose a new Machine Learning (ML) tool called Galaxy morphoto-Z with neural Networks (GaZNet-1), which uses both images and multi-band photometry measurements to predict galaxy redshifts, with accuracy, precision and outlier fraction superior to standard methods based on photometry only. As a first application of this tool, we estimate photo-z of a sample of galaxies in the Kilo-Degree Survey (KiDS). GaZNet-1 is trained and tested on $\sim140 000$ galaxies collected from KiDS Data Release 4 (DR4), for which spectroscopic redshifts are available from different surveys. This sample is dominated by bright (MAG$\_$AUTO$<21$) and low redshift ($z < 0.8$) systems, however, we could use $\sim$ 6500 galaxies in the range $0.8 < z < 3$ to effectively extend the training to higher redshift. The inputs are the r-band galaxy images plus the 9-band magnitudes and colours, from the combined catalogs of optical photometry from KiDS and near-infrared photometry from the VISTA Kilo-degree Infrared survey. By combining the images and catalogs, GaZNet-1 can achieve extremely high precision in normalized median absolute deviation (NMAD=0.014 for lower redshift and NMAD=0.041 for higher redshift galaxies) and low fraction of outliers ($0.4$\% for lower and $1.27$\% for higher redshift galaxies). Compared to ML codes using only photometry as input, GaZNet-1 also shows a $\sim 10-35$% improvement in precision at different redshifts and a $\sim$ 45% reduction in the fraction of outliers. We finally discuss that, by correctly separating galaxies from stars and active galactic nuclei, the overall photo-z outlier fraction of galaxies can be cut down to $0.3$\%.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： The Hubble tension, revealed by a $\sim 5\sigma$ discrepancy between measurements of the Hubble-Lemaitre constant from early- and local-Universe observations, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure $H_0$, such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys like DESI (Dark Energy Spectroscopic Instrument). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24,440,816 candidate QSOs contained in the 9th data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours of a group's members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identify 620 new candidate multiply imaged lensed quasars (101 Grade-A, 214 Grade-B, 305 Grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI. The catalogues and images of the candidates in this work are available online (https://github.com/EigenHermit/lensed_qso_cand_catalogue_He-22/).
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： The Hubble tension, revealed by a $\sim 5\sigma$ discrepancy between measurements of the Hubble-Lemaitre constant from early- and local-Universe observations, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure $H_0$, such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys like DESI (Dark Energy Spectroscopic Instrument). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24,440,816 candidate QSOs contained in the 9th data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours of a group's members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identify 620 new candidate multiply imaged lensed quasars (101 Grade-A, 214 Grade-B, 305 Grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI. The catalogues and images of the candidates in this work are available online (https://github.com/EigenHermit/lensed_qso_cand_catalogue_He-22/).
分类： 天文学 >> 天文学 提交时间： 2023-02-19
JUNO Collaboration
Jie Zhao
Baobiao Yue
Haoqi Lu
Yufeng Li
Jiajie Ling
Zeyuan Yu
Angel Abusleme
Thomas Adam
Shakeel Ahmad
Rizwan Ahmed
Sebastiano Aiello
Muhammad Akram
Abid Aleem
Tsagkarakis Alexandros
Fengpeng An
Qi An
Giuseppe Andronico
Nikolay Anfimov
Vito Antonelli
摘要： The physics potential of detecting $^8$B solar neutrinos is exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model independent manner by using three distinct channels of the charged-current (CC), neutral-current (NC) and elastic scattering (ES) interactions. Due to the largest-ever mass of $^{13}$C nuclei in the liquid-scintillator detectors and the potential low background level, $^8$B solar neutrinos would be observable in the CC and NC interactions on $^{13}$C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC and ES channels to guarantee the $^8$B solar neutrino observation. From the sensitivity studies performed in this work, we show that one can reach the precision levels of 5%, 8% and 20% for the $^8$B neutrino flux, $\sin^2\theta_{12}$, and $\Delta m^2_{21}$, respectively, using ten years of JUNO data. It would be unique and helpful to probe the details of both solar physics and neutrino physics. In addition, when combined with SNO, the world-best precision of 3% is expected for the $^8$B neutrino flux measurement.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： With the advent of new spectroscopic surveys from ground and space, observing up to hundreds of millions of galaxies, spectra classification will become overwhelming for standard analysis techniques. To prepare for this challenge, we introduce a family of deep learning tools to classify features in one-dimensional spectra. As the first application of these Galaxy Spectra neural Networks (GaSNets), we focus on tools specialized at identifying emission lines from strongly lensed star-forming galaxies in the eBOSS spectra. We first discuss the training and testing of these networks and define a threshold probability, PL, of 95% for the high quality event detection. Then, using a previous set of spectroscopically selected strong lenses from eBOSS, confirmed with HST, we estimate a completeness of ~80% as the fraction of lenses recovered above the adopted PL. We finally apply the GaSNets to ~1.3M spectra to collect a first list of ~430 new high quality candidates identified with deep learning applied to spectroscopy and visually graded as highly probable real events. A preliminary check against ground-based observations tentatively shows that this sample has a confirmation rate of 38%, in line with previous samples selected with standard (no deep learning) classification tools and follow-up by Hubble Space Telescope. This first test shows that machine learning can be efficiently extended to feature recognition in the wavelength space, which will be crucial for future surveys like 4MOST, DESI, Euclid, and the Chinese Space Station Telescope (CSST).
分类： 光学 >> 量子光学 提交时间： 2023-02-19
Fang Xiong
Peiran Yin
Tong Wu
Han Xie
Rui Li
Yingchun Leng
Yanan Li
Changkui Duan
Xi Kong
Pu Huang
Jiangfeng Du
摘要： Levitated oscillators with millimeter or sub-millimeter size are particularly attractive due to their potential role in studying various fundamental problems and practical applications. One of the crucial issues towards these goals is to achieve efficient measurements of oscillator motion, while this remains a challenge. Here we theoretically propose a lens-free optical detection scheme, which can be used to detect the motion of a millimeter or sub-millimeter levitated oscillator with a measurement efficiency close to the standard quantum limit with a modest optical power. We demonstrate experimentally this scheme on a 0.5 mm diameter micro-sphere that is diamagnetically levitated under high vacuum and room temperature, and the thermal motion is detected with high precision. Based on this system, an estimated acceleration sensitivity of $9.7 \times 10^{-10}\rm g/\sqrt{Hz}$ is achieved, which is more than one order improvement over the best value reported by the levitated mechanical system. Due to the stability of the system, the minimum resolved acceleration of $3.5\times 10^{-12}\rm g$ is reached with measurement times of $10^5$ s. This result is expected to have potential applications in the study of exotic interactions in the millimeter or sub-millimeter range and the realization of compact gravimeter and accelerometer.
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