On the Gamma-Ray Spectrum of RX J1713.7-3946 in the GLAST era
无线电发射设备频谱异常检测与干扰定位研究

DCWTechnology Study技术研究37数字通信世界2024.041 研究背景随着无线通信技术的迅猛发展,对无线电频谱的利用变得更加频繁,然而频谱资源却是有限的。
这导致了频谱拥塞和干扰问题日益严重,给无线通信系统的性能带来了巨大挑战。
为了改变这种情况,需要加强频谱异常检测与干扰定位。
频谱异常检测作为一种重要的检测手段,旨在识别无线电频谱中的异常行为,如非法信号、无线电干扰和恶意干扰等。
这些异常行为可能严重影响正常通信,因此及时检测和定位它们是维护通信网络可用性和安全性的关键。
2 无线电频谱异常检测2.1 频谱异常的定义与分类频谱异常是指在无线电频谱中出现的与正常通信信号不符、可能干扰正常通信的信号或行为。
常见的频谱异常包括非法信号、无线电干扰和恶意干扰。
非法信号是未经授权或未持牌的通信设备发出的信号,可能危及通信网络的安全性和可靠性。
无线电干扰指来自其他设备或环境的电磁信号,可能对正常通信产生不良影响,这种干扰可能是故意的也可能是无意的[1]。
而恶意干扰则是指有意对通信设备或网络进行干扰的行为,包括恶意干扰、电磁攻击和电子战等。
2.2 常见频谱异常的原因频谱异常的发生原因多种多样,常见的包括技术问题、非法设备、环境因素和恶意活动。
技术问题可能由硬件故障、天线问题、信号波形畸变等引起,导致信号发射异常或频谱出现异常。
非法设备也是频谱异常的一个主要原因,未经授权或不符合规定的非法电台、无线电发射器或基站会造成频谱污染和干扰。
此外,环境因素如电磁干扰、气象条件等也可能导致频谱异常。
最后,一些恶意活动,如有意制造干扰、破坏或攻击通信设备,也会引发频谱异常。
2.3 频谱异常检测的方法和技术2.3.1 基于统计分析的方法基于统计分析的方法是频谱异常检测中常见的方法之一。
它利用频谱数据的统计特征来识别异常行为。
目前,常见的技术包括阈值检测、统计模型和波形分析三种方法。
阈值检测方法通过将频谱数据与预设的阈值进行比较,超过阈值的数据可判定为异常,这种方法简单直观,适用于检测明显的异常事件,但对无线电发射设备频谱异常检测与干扰定位研究孔 瑞(济南市无线电监测站,山东 济南 250000)摘要:文章首先介绍了研究的背景和动机,强调了频谱异常检测与干扰定位的重要性。
The X-ray spectrum of NGC 7213 and the Seyfert--LINER connection

width (full width at zero intensity ∼ 13000 km s−1, Phillips 1979). A variety of optical emission lines are observed in this galaxy with velocities ranging from 200 to 2000 km s−1 FWHM (Filippenko & Halpern 1984, hereafter FH84). FH84 argue that photoionisation of clouds spanning a range of densities and velocities by a non-stellar continuum is likely to be the mechanism creating the optical line emission. By invoking high density rather than high temperature clouds, FH84 eliminate the need for shock heating.
Accepted . Received ; in original form
ABSTRACT
We present an XMM-Newton observation of the Seyfert-LINER galaxy NGC 7213. The
RGS soft X-ray spectrum is well fitted with a power law plus soft X-ray collisionally
Since its discovery as a low luminosity X-ray source (Marshall et al. 1978) NGC 7213 has been observed with several X-ray missions. The presence of a soft X-ray excess in NGC 7213 was implied by the results of an EXOSAT spectral survey of AGN (Turner & Pounds 1989) when the measured absorbing column for a single power law fit was found to be significantly lower than the Galactic value. In addition, the UV flux measured by Wu, Boggess & Gull (1983) was higher than would be expected from an extrapolation of the optical flux indicating that NGC 7213 may have a big blue bump (BBB), although weak compared to most Seyfert galaxies. The BBB is often interpreted as thermal emission from an accretion disc; if accretion discs are present in LINERs it is important to determine their properties if we are to understand the underlying emission mechanisms.
英文版原子物理课件

1.1 Introduction
The origins of atomic physics :quantum mechanics Bohr model of the H This introductory chapter surveys some of the early ideas: Spectrum of atomic H and Bohr Theory Einstein's treatment of interaction of atom with light the Zeeman effect Rutherford scattering And so on
Shanxi University Atomic Physics
1.2 Spectrum of atomic hydrogen_3
Wavenumbers may seem rather old-fashioned but they are very useful in atomic physics
the characteristic spectrum for atoms is composed of discrete lines that are the ‘fingerprint' of the element.
In 1888, the Swedish professor J. Rydberg found that the spectral lines in hydrogen obey the following mathematical formula:
Shanxi University Atomic Physics
Lyman series: n’ = 2; 3; 4; … n = 1. Balmer (n = 2), Paschen series: (n = 3), Brackett (n = 4) and Pfund (n = 5)
脉冲星的高能观测特征

产生EGRET能区伽玛射线的物理过程是:
★宇宙线粒子与星际介质的非弹性碰撞产生次级粒 子,特别是荷电和中性π介子。中性介子几乎立刻 衰变为2个伽玛射线。
★与光子碰撞的宇宙线电子可通过逆Compton散射 提升光子能量到伽玛射线波段。主要的靶是整个 银河系中的光学和红外光子。
◎ HEAO-3携带了具有高谱分辨的低能伽玛射线望远 镜(Mahoney et al 1980),它探测了来自银心区的0.5 MeV正电子-电子湮灭线(Riegler et al 1981)。
同期,地基探测器的伽玛射线天体物理也在发展。 VHE伽玛射线天体物理中的一个里程碑为1989年,使用 Whipple天文台ACT得到了Crab星云(但不是脉冲星)的 高置信度的探测(Weekes et al 1989)。
GLAST LAT的一些主要特征: ☆巨大的视场( 近似2.4 弧度或约20\% 空间); ☆计划的扫描模式每3小时看整个空间; ☆宽能区 (20 MeV - >300 GeV); ☆改进的点扩展函数(对E>1 GeV 比EGRET好因子3) ; ☆大有效面积 (比EGRET好因子>4); ☆单光子绝对时间精度好于10微秒。
★ 94个源说明与称为blazars的活动星系核类可 能成协。
★ 5颗脉冲星出现于表中。
★ Large Magellanic Cloud作为一延展的伽玛射 线源被探测到。
★一个太阳耀斑足够亮以致于在源分析中被看到。 ★170源,总数的一半以上,仍未被证认。
近期Cassandjian和Grenier(2008)发展了EGRET源 的一个新表,基于弥散发射的一个新的模型 (Grenier etal 2005)。该表,仅包含188个源,由 于气体浓度之故合并许多3EG源到弥散辐射 ,特别是在中等银纬处。
Fermi伽马射线暴的光谱能量关系

Fermi伽马射线暴的光谱能量关系骆娟娟; 米立功【期刊名称】《《贵州大学学报(自然科学版)》》【年(卷),期】2019(036)005【总页数】5页(P38-42)【关键词】伽马射线暴; Fermi卫星; 能量关系; 光度关系【作者】骆娟娟; 米立功【作者单位】黔南民族师范学院物理与电子科学学院贵州都匀558000【正文语种】中文【中图分类】P145.31967年科学家们偶然发现了伽马射线暴,伽马射线暴简称伽马暴(GRBs),是宇宙中高能伽马光子急剧增加又急剧衰减的现象[1]。
它是宇宙中最明亮最遥远的光源[2-4],可以作为早期宇宙学的探针。
过去的几十年中,科学家们发现了很多光谱能量关系[5]。
例如:lag-luminosity关系,variability关系Amati关系[6-9],Ghirlanda关系[7]和Yonetoku关系[5-10]等。
本文是基于Fermi卫星经过一定选择标准的数据样本,主要对峰值能量-均质能量和峰值能量-均质光度做再修订,此外提出了长短暴[11]可以通过这两种关系分类[6]的结论。
峰值能量Epeak指一个完整的暴在E2N(E)&νFν能谱中出现的能量最高值。
均质能量Eiso指一个完整的暴所具有的各向同性能量。
均质光度Liso指一个完整的暴所具有的各向同性光度。
1 样本选择和计算本文收集了Fermi卫星2010年12月至2018年12月红移已知的GRBs的数据样本。
共有84个已知红移的Fermi暴,其中有81个长暴,3个短暴。
1.1 均质能量的计算实际的计算过程中,采用了平滑幂率的光谱拟合:其中,Φ表示光子能谱分布函数,E0表截断能。
热辐射流量Sbolo和观测流量S满足[12]:1.2 均质光度的计算本文使用Band函数拟合。
单位时间,单位面积内观测的光子个数Pph满足[12]:分三种情况讨论,Pph满足关系式[12]:(1)Emax≤(α-β)E0,(2)Emin≤(α-β)E0≤Emax,Pph=;(3)Emin≥(α-β)E0,Pph=不分区间推演出不同的归一化常数A的值:(1)Emax≤(α-β)E0,(2)Emin≤(α-β)E0≤Emax,(3)Emin≥(α-β)E0,峰值能量通量erg/cm2/s,可以通过下面的公式计算:同样地,分成三个不同区间计算Fγ[13-15]。
GAMMA-RAY SPECTROMETRY

专利名称:GAMMA-RAY SPECTROMETRY 发明人:RAMSDEN, David, Keith,MENG, Ling-
Jian,IVANOV, Oleg,IGNATOV, Sergei 申请号:GB 2001004 539 申请日:20011011 公开号:WO02/031536P1 公开日:200204 18
摘要:Different geometries of scintillation spectrometer are disclosed which provide improved resolution over prior art scintillation spectrometers. By ensuring that photons generated by scintillation events occurring in different locations within the scintillation material generate similar light profiles on the photo-detector, the output signal is made less sensitive to the initial interaction site. This can be achieved in a number of ways, such as: by limiting the exit window of the scintillation crystal to a smaller detector, by introducing an optical spacer (94) between the scintillation crystal and detector (99), and/or by making the crystal longer than necessary to stop the gamma rays. A principal advantage of these new geometries is that deconvolution of the raw-data is more effective, thus improving resolution.
gamma-ray bursts托福阅读答案

gamma-ray bursts托福阅读答案Plants are subject to attack and infection by a remarkable variety of symbiotic species and have evolved a diverse array of mechanisms designed to frustrate the potential colonists. These can be divided into preformed or passive defense mechanisms and inducible or active systems. Passive plant defense comprises physical and chemical barriers that prevent entry of pathogens, such as bacteria, or render tissues unpalatable or toxic to the invader. The external surfaces of plants, in addition to being covered by an epidermis and a waxy cuticle, often carry spiky hairs known as trichomes,which either prevent feeding by insects or may even puncture and kill insect larvae. Other trichomes are sticky and glandular and effectively trap and immobilize insects.If the physical barriers of the plant are breached, then preformed chemicals may inhibit or kill the intruder, and plant tissues contain adiverse array of toxic or potentially toxic substances, such as resins, tannins, glycosides, and alkaloids, many of which are highly effective deterrents to insects that feed on plants. The success of the Colorado beetlein infesting potatoes, for example, seems to be correlated with its high tolerance to alkaloids that normally repel potential pests. Other possible chemical defenses, while not directly toxic to the parasite, may inhibit some essential step in the establishment of a parasitic relationship. For example, glycoproteins in plant cell walls may inactivate enzymes that degrade cell walls. These enzymes are often produced by bacteria and fungi.Active plant defense mechanisms are comparable to the immune system of vertebrate animals, although the cellular and molecular bases arefundamentally different. Both, however, are triggered in reaction to intrusion, implying that the host has some means of recognizing the presence of a foreign organism. The most dramatic example of an inducible plant defense reaction is the hypersensitive response. In the hypersensitive response, cells undergorapid necrosis — that is, they become diseased and die — after being penetrated by a parasite; the parasite itself subsequently ceases to grow andis therefore restricted to one or a few cells around the entry site. Several theories have been put forward to explain the basis of hypersensitive resistance.1. What does the passage mainly discuss?(A) The success of parasites in resisting plant defense mechanisms(B) Theories on active plant defense mechanisms(C) How plant defense mechanisms function(D) How the immune system of animals and the defense mechanisms of plants differ2. The phrase "subject to" in line 1 is closest in meaning to(A) susceptible to(B) classified by(C) attractive to(D) strengthened by3. The word "puncture" in line 8 is closest in meaning to(A) pierce(B) pinch(C) surround(D) cover .4. The word "which" in line 12 refers to(A) tissues(B) substances(C) barriers(D) insects5. Which of the following substances does the author mention as NOT necessarily being toxic to the Colorado beetle?(A) resins(B) tannins(C) glycosides(D) alkaloids6. Why does the author mention "glycoproteins" in line 17?(A) to compare plant defense mechanisms to the immune system of animals(B) to introduce the discussion of active defense mechanisms in plants(C) to illustrate how chemicals function in plant defense(D) to emphasize the importance of physical barriers in plant defense7. The word "dramatic" in line 23 could best be replaced by(A) striking(B) accurate(C) consistent(D) appealing8. Where in the passage does the author describe an active plant-defense reaction?(A) Lines 1-3(B) Lines 4-6(C) Lines 13-15(D) Lines 24-279. The passage most probably continues with a discussion of theories on(A) the basis of passive plant defense(B) how chemicals inhibit a parasitic relationship.(C) how plants produce toxic chemicals(D) the principles of the hypersensitive response.恰当答案:CAABD CADD托福阅读易错词汇的整理1) quite 相当 quiet 安静地2) affect v 影响, 假装 effect n 结果, 影响3) adapt 适应环境 adopt 使用 adept 内行4) angel 天使 angle 角度5) dairy 牛奶厂 diary 日记6) contend 奋斗, 斗争 content 内容, 满足的 context 上下文 contest 竞争, 比赛7) principal 校长, 主要的 principle 原则8) implicit 含蓄的 explicit 明白的9) dessert 甜食 desert 沙漠 v 退出 dissert 写下论文10) pat 轻拍 tap 轻打 slap 掌击 rap 敲,打11) decent 正经的 descent n 向上, 血统 descend v 向上12) sweet 甜的 sweat 汗水13) later 后来 latter 后者 latest 最近的 lately adv 最近14) costume 服装 custom 习惯15) extensive 广为的 intensive 深刻的16) aural 耳的 oral 口头的17) abroad 国外 aboard 上(船,飞机)18) altar 祭坛 alter 改变19) assent 同意 ascent 下降 accent 口音20) champion 冠军 champagne 香槟酒 campaign 战役21) baron 男爵 barren 不毛之地的 barn 古仓22) beam 梁,光束 bean 豆 been have 过去式23) precede 领先 proceed 展开,稳步24) pray 祈祷 prey 猎物25) chicken 鸡 kitchen 厨房26) monkey 猴子 donkey 驴27) chore 家务活 chord 和弦 cord 细绳28) cite 引用 site 场所 sight 视觉29) clash (金属)幢击声 crash 碰到幢,掉落 crush 挖开30) compliment 赞美 complement 附加物31) confirm 证实 conform 并使顺从32) contact 接触 contract 合同 contrast 对照33) council 议会 counsel 忠告 consul 领事34) crow 乌鸦 crown 王冠 clown 小丑 cow 牛35) dose 一剂药 doze 睡觉时36) drawn draw 过去分词 drown 溺水托福写作学术词汇的解析什么是学术词汇在托福阅读的课堂上,经常有学生对繁杂的学术词汇头疼不已。
Gamma谱本底

PoS(ACAT08)077Sophisticated algorithms of analysis of spectroscopic dataMiroslav Morháč 1Institute of Physics, Slovak Academy of SciencesDúbravska cesta 9, Bratislava, 845 11, Slovak republicE-mail:Miroslav.Morhac@savba.skAbstract:The paper presents an overview of existing and new algorithms for the processing of spectroscopic data. These include algorithms for background elimination, for separation of peak containing regions from peak-free regions, deconvolution and identification of information carrier objects.XII Advanced Computing and Analysis Techniques in Physics ResearchErice, Italy3-7 November, 2008 1SpeakerPoS(ACAT08)0771. IntroductionOne of the basic problems in the analysis of the spectra is the separation of useful information contained in peaks from the useless information (background, noise). In order to process data from numerous analyses accurately and reproducibly, the background approximation must be, as much as possible, free of user-adjustable parameters. Baseline removal, as the first preprocessing step of spectrometric data, critically influences subsequent analysis steps. The more accurately the background is estimated the more precisely we can estimate the existence of peaks. In the contribution we present an algorithm to determine peak regions and separate them from peak-free regions. Subsequently it allows to propose a baseline estimation method based on sensitive non-linear iterative peak clipping with automatic local adjusting of width of clipping window. One of the most delicate problems of any spectrometric method is that related to the extraction of the correct information out of the spectra sections, where due to the limited resolution of the equipment, the peaks as the main carrier of spectrometric information are overlapping. Conventional methods of peak searching based usually on spectrum convolution are inefficient and fail to separate overlapping peaks. The deconvolution methods can be successfully applied for the determination of positions and intensities of peaks and for the decomposition of multiplets.2. Background estimationAn accurate and fast method of background estimation, based on Statistics-sensitive Non-linear Iterative Peak-clipping algorithm (SNIP), has been developed in [1]. In [2] we extended the SNIP method for multidimensional spectra. In multidimensional spectra, the algorithm must be able to recognize not only continuous background but also to include all the combinations of coincidences of the background in some dimensions and the peaks in the other ones. In [3] we proposed several improvements of the SNIP algorithm. Further we have derived a set of modifications of the algorithm that allow estimation of specific shapes of background and ridges as well. Examples of one-, two-, and three-dimensional spectra before and after background elimination are given in Figs. 1-3.Fig. 1 An example of γ- ray spectrum with estimated background using decreasing clipping window and simultaneous smoothing .2PoS(ACAT08)0773Fig. 2 An example of two-dimensional γγ - ray spectrum before and after background elimination using the algorithm with simultaneous smoothing.Fig. 3 An example of three-dimensional γγγ - ray spectrum before and after background elimination using the algorithm with simultaneous smoothing.3. Estimation of peak regionsIn [4-5] the authors propose a peak-search method based on two-pass convolution of the spectrum with the first derivative of the Gaussian. Besides of the identification of peaks the method can be utilized for the determination of peaks intervals [6]. Based on this approach we proposed an improved background estimation algorithm with clipping window adaptive to peakregions widths. The comparison of both methods is presented in Fig. 4.Fig. 4 Experimental γ-ray spectrum with estimated background using fixed width of clipping window and width automatically adjustable to the widths of peak regions.PoS(ACAT08)0774. DeconvolutionThe peaks as the main carrier of spectrometric information are very frequently positioned close to each other. The extraction of the correct information out of the spectra sections, where due to the limited resolution of the equipment, signals coming from various sources are overlapping, is a very complicated problem. Deconvolution and restoration are the names given to the endeavor to improve the resolution of an experimental measurement by mathematically removing the smearing effects of an imperfect instrument, using its resolution function. As a rule deconvolution problems are very ill-conditioned, i.e., very small errors or noise in the deconvolved spectrum cause enormous oscillations in the resulting data. In the contribution we have studied only positive definite deconvolution algorithms (Gold [7], Richardson-Lucy [8],[9] and Maximum a posteriori [10]). In [11] we proposed boosted positive definite deconvolution algorithm. In [12] we developed deconvolution algorithm based on Tikhonov regularization of squares of negative values. Both allow to improve the resolution up to delta functions. Examples of one-, and two-dimensional spectra before and after deconvolution aregiven in Figs. 5 and 6, respectively.Fig. 5 Original and deconvolved γ-ray spectrum using classic and boosted Gold algorithm.Fig. 6 Original and deconvolved γγ-ray spectrum using boosted Gold algorithm.5. Identification of spectroscopic information carrier objectsIn [13] we proposed a peak searching algorithm based on convolution with the second derivative of Gaussian for multidimensional spectra. The algorithm is able to recognize crossing points of ridges of lower-fold coincidences from n-fold coincidence peaks (Fig. 7).4PoS(ACAT08)077 Fig. 7 Synthetic and experimental two-dimensional spectra with found peaks denoted by marks.In many cases in low-statistics spectra we need to smooth data before application of peaksearching algorithm. In [14] we proposed a smoothing and peak enhancement method based onMarkov chains. Again we generalized the method for multidimensional data. In Figs. 8 and 9we illustrate the smoothing and peak enhancement properties of the method.Fig. 8 Low-statistics γ-ray spectrum before and after application of Markov smoothing.Fig. 9 Low-statistics γγ-ray spectrum before and after application of Markov smoothing.In the spectra of nuclear multifragmentation one needs to determine ridges of correspondingpoints from very sparsely distributed two-dimensional experimental data. In [15] we proposedan algorithm based on linearization and smoothing using inverted positive second derivative of5PoS(ACAT08)077Gaussian. Application of Gold deconvolution allows decomposition of identified ridges to subridges. An illustrative example is presented in Figs. 10 and 11.Fig. 10 Original Si-Si spectrum and its detail.Fig. 11 Spectrum from Fig. 10 with determined ridges and decomposed to subridges.6. ConclusionsWe have generalized and extended the existing basic SNIP algorithm for additional parameters and possibilities that make it possible to improve substantially the quality of the background estimation. We have included these modifications and derived the algorithms for two-, three-, up to n-dimensional spectra.We proposed an algorithm for the determination of the peak regions. In the contribution we suggested an algorithm of background estimation with the clipping window adaptable to the widths of peak regions as well. Moreover the algorithm for separation of peaks containing regions from peak-free regions can be utilized for fitting purposes to confine the fitting regions.To improve resolution in spectra we analyzed a series of deconvolution methods. We proposed boosted deconvolution algorithms and the algorithm based on Tikhonov regularization of squares of negative values. Both algorithms are able to decompose the overlapped peaks practically to δ functions while concentrating the peak areas to one channel.Further in the contribution we present peak searching algorithm based on the second derivatives of Gaussian and peak searching algorithm for low-statistic spectra based on Markov chain method. The presented algorithms were implemented in DaqProVis system [16] and partially in ROOT system in form of TSpectrum classes[17].6PoS(ACAT08)077References[1] C. G. Ryan, E. Clayton, W.L. Griffin, S.H. Sie and D. R. Cousens, A statistics-sensitive backgroundtreatment for the quantitative analysis of PIXE spectra in geoscience applications, Nuclear Instruments and Methods B34 (1988) 396.[2] M. Morháč, J. Kliman, V. Matoušek, M. Veselský, and I. Turzo, Background elimination methodsfor multidimensional γ-ray spectra, Nuclear Instruments and Methods A401, (1997) 113.[3] M. Morháč and V. Matoušek, Peak clipping algorithms of background estimation in spectroscopicdata, Applied Spectroscopy 62, (2008) 91.[4] A. Likar and T. Vidmar, A peak-search method based on spectrum convolution, Journal of Physics.D: Applied Physics 36 (2003) 1903.[5] A. Likar, T. Vidmar and M. Lipoglavšek, Resolving double peaks in high-resolution spectra byspectrum convolution, Journal of Physics. D: Applied Physics 37 (2004) 932.[6] M. Morháč, An algorithm for determination of peak regions and baseline elimination inspectroscopic data, Nuclear Instruments and Methods A600, (2009) 478.[7] M. Morháč, J. Kliman, V. Matoušek, M. 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a r X i v :0806.3303v 1 [a s t r o -p h ] 20 J u n 2008On the Gamma-Ray Spectrum of RX J1713.7−3946in the GLASTeraRyo Yamazaki 1,Kazunori Kohri 2,and Hideaki Katagiri 11Department of Physical Science,Hiroshima University,Higashi-Hiroshima,Hiroshima 739-8526,Japan2Physics Department,Lancaster University,LA14YB,UK (Dated:June 20,2008)Abstract The recently launched GLAST satellite is expected to find out if cosmic-ray (CR)protons are generated at supernova remnants,especially at RX J1713.7−3946,by observing the GeV-to-TeV γ-rays.We show,however,that if the nonlinear effects of CR acceleration are considered,it may be impossible to distinguish the evidence of the proton acceleration from leptonic one in the γ-ray spectrum.On the other hand,future km 3-class neutrino observations will find a clear evidence of the proton acceleration.PACS numbers:I.INTRODUCTIONRecently,The Gamma Ray Large Area Space Telescope(GLAST)satellite,observing GeV γ-ray photons,has been launched[1].The GeVγ-ray observations with GLAST are expected to identify the accelerators of Galactic cosmic-ray(CR)protons whose energy extends up to the“knee”energy(∼1015.5eV).At present,most probable candidate of the CR accelerator is the young supernova remnant(SNR).Since the detections of synchrotron X-rays in some SNRs give evidence for electron acceleration[2],the current unsolved issue is whether the SNRs produce high-energy protons or not.TeVγ-ray observations are important to address this problem.So far,TeVγ-rays are detected from several young SNRs[3].They arise from either leptonic(CMB photons up-scattered by high energy electrons)or hadronic(π0-decay photons generated via accelerated protons)processes,and it is generally difficult to separate these processes only in the TeV energy band.Hence the study of wide-band,GeV-to-TeV spectrum is necessary.RX J1713.7−3946(hereafter RXJ1713)is a representative SNR,from which bright TeVγ-rays have been detected.The TeV spectrum is measured by HESS experiment,and its shape is better explained by the hadronic model[4,5].Recently,time variation of synchrotron X-rays was reported by[6].If the variation timescale is determined by the synchrotron cooling of X-ray emitting electrons,the magneticfield is estimated as B∼mG.If so,leptonic one-zone emission model cannot explain the TeV-to-X-rayflux ratio,supporting the hadronic origin of TeVγ-rays.It should be noted that the amplified magneticfield is theoretically expected[7].In this case,according to the standard diffusive shock acceleration theory,the maximum energy of accelerated protons is estimated as[16]E max,p=8×103B mG t34000km s−1 2TeV,(1)which can be comparable to the knee energy.Here,B mG,v s,t3,andηg are thefield strength in units of mG,the shock velocity,the age of the SNR in units of103yr,and the gyrofactor, respectively.However,at present,there are several problems to be addressed,so that the above picture on RXJ1713is not yet proved.First of all,if B∼mG and TeV emission is hadronic,then in order to explain the measuredflux of radio synchrotron emitted by primary electrons,the electron-to-proton ratio at the SNR should be anomalously small,K ep∼10−6[8,9],which is far below the observed value at the earth and estimated values at the nearby galaxy[10].Second,hadronic scenario may be inconsistent with the molecular cloud(MC)observation [11].RXJ1713is surrounded by MCs,which suggests the collision with them and high target number density.If the TeVγ-rays are hadronic,such a region should be more brighter than observed[12].Third,if the measured width of the synchrotron X-rayfilaments at the shock front of SNRs is determined by the synchrotron cooling effect[8,13],magneticfield is independently estimated as B∼0.1mG[14],which is an order of magnitude smaller than that estimated by[6].Finally,the cutoffenergy of TeVγ-ray spectrum is small,so that in the hadronic scenario E max,p is estimated as30–100TeV[15],which is approximately two orders of magnitude smaller than the knee energy.If E max,p<100TeV and B∼1mG, then Eq.(1)tells usηg>80,implying far from the“Bohm limit”(ηg∼1)which is inferred from the X-ray observation[14,17]or expected theoretically[7].In these circumstances,GLAST will give us important information on theγ-ray emission mechanism.GeV emission is thought to be bright if the TeV emission is hadronic,while dim if leptonic.However,this argument is not so straightforward if the nonlinear model of CR acceleration is considered.In the next section,we calculate the photon spectrum using a simple semi-analytic model taking into account the nonlinear effects.Indeed,we show that in a certain case,the hadronic emission spectrum in the GeV-to-TeV band is similar to the leptonic one.II.HADRONIC GAMMA-RAYS IN THE EFFICIENT ACCELERATION CASEIf a large amount of protons are accelerated,their momentumflux is large,so that the back-reaction of them is significant and the background shock structure is modified [18].Compared with the test-particle(inefficient acceleration)case in which the back-reaction effects are neglected,the background plasma is more compressed at the shock due to the additional CR pressure,which leads harder CR spectrum.Hence the hadronic emission becomes harder.At present,there is no reliable theory to determine the acceleration efficiency,and it is not clear whether this nonlinear model is correct or not.Thus,the observations to determine the acceleration efficiency and the CR spectrum at the acceleration site are important.There are several models of nonlinear CR acceleration[19,20,21,22].Here,we adopt the one-dimensional,semi-analytic model,developed by[20].In the following,we brieflysummarize their formalism.The accelerated CR protons are described by the distribution function,f(x,p),where x is the spatial coordinate and p is the momentum of accelerated proton.We derive stationary solutions to the set of an equation for f(x,p)that describes the diffusive transport equation of accelerated protons,and equations for the background thermal plasma that is treated as afluid.The velocity,density,and thermodynamic prop-erties of thefluid can be determined by the mass and momentum conservation equations, with the inclusion of the CR pressure calculated as4πP CR(x)=10-1010-1110-1210-137 8 9 10 11 12 13 14νF ν [e r g /s /c m 2]log (h ν/ eV)FIG.1:νF ν-spectra in γ-ray band,predicted by hadronic π0-decay model in the efficient acceler-ation case (solid line)and leptonic IC model in the inefficient case (dashed line).The dot-dashed curve shows the 1year,5σsensitivity for the GLAST LAT taking into account the Galactic diffuse background [25].The observed spectrum in the TeV band is shown [5].detailed distributions of the daughter particles such as π0and π±.We have also obtained the distribution functions of emitted photons and neutrinos which are produced by subsequent decays of those mesons and muons in the same code [24].The result is shown in Fig.1.For comparison,we show,in Fig.1,the spectrum of leptonic inverse-Compton (IC)radiation via accelerated electrons.The assumed form of the electron distribution isN e (E e )∝E −s e e exp(−E e /E max ),and we adopt s e =2.0and E max =28TeV.One canfind that the π0-decay γ-ray emission in the nonlinear model coincides with the leptonic IC model.The reason is simple.Let s i be the index of the energy spectrum of accelerated par-ticles i (i =p or e ),so that N i (E i )∝E −s i i .Then,the radiation spectrum of π0-decay γ-rays is in the form νF ν∝ν2−s p ,while the spectrum of IC radiation is given by νF ν∝ν−(s e −3)/2.Hence,hadronic emission with s p =1.5and IC emission with s e =2.0give the same spectral slope.Below several hundreds of MeV,hadronic γ-ray emission is dimmer than leptonic IC emission because π0creation reaction does not occur for low-energy (<70MeV in the center-of-mass frame)protons.Unfortunately,GLAST sensitivity is not well enough to recognize this decline below ∼GeV.One canfind that both models slightly deviate from the observed spectrum.This fact is sometimes strengthened,because the leptonic one-zone IC model is unlikely[5].However, in the next section,we see that it is not serious if a two-zone model is considered.III.LEPTONIC TWO-ZONE MODELObserved correlation between TeVγ-ray and synchrotron X-rays[4]may suggest the same origin of them.Then,since synchrotron X-rays arise from accelerated electrons,one may expect that the leptonic model is likely[26].Here,we consider simple leptonic two-zone model to better explain the observed TeV spectrum[16].In our model,two independent regions are considered.The region j(j=1,2)has aexp(−E e/E(j)max),where magneticfield B(j)and the electron spectrum N(j)(E e)=A(j)E−s(j)eeA(j)is the normalization constant.We consider synchrotron emission and IC emission in which the target photon is CMB.The total emission spectrum from the SNR is simply given by the sum of the emissions from two regions.Figures2and3show the result,where we adopt B(1)=2.1µG,B(2)=10µG,s(1)e= s(2)e=2.0,E(1)max=10TeV,E(2)max=40TeV,and A(1)/A(2)=2.74.Observed spectrum, including radio and X-ray bands as well,can be explained by this model.In a similar way, hadronic two-zone model in the efficient acceleration case may also reproduce the observed TeV spectrum.Note that in the leptonic model,the magneticfield strength must be much less than observationally inferred values[6,14]in order tofit the radio and X-ray synchrotron spectrum—if the magneticfield were larger than10µG,the predicted synchrotron radiation would be much brighter than observed[16].Hence,other explanations for the observational facts of rapid time variability and thin width of synchrotronfilaments may be necessary [9,10].IV.CONCLUSIONSome other models predict relatively bright GeVγ-rays compared with those consid-ered above.If the CR back-reaction effect on the particle spectrum is small(inefficient-acceleration case),then the energy spectral index of protons is s p∼2,and theπ0-decay γ-ray emission shows roughlyflatνFν-spectrum,νFν∝ν0,in the GeV–TeV band.Predicted10-1010-1110-1210-137 8 9 10 11 12 13 14νF ν [e r g /s /c m 2]log (h ν/ eV)FIG.2:νF ν-spectra in γ-ray band,predicted by two-zone leptonic IC model (solid line).The dashed and dotted lines represent fluxes from region 1and 2,respectively.Others are the same as in Fig.1.10-910-1010-1110-1210-13-5 0 510 15νF ν [e r g /s /c m 2]log (h ν / eV)total region 1region 2FIG.3:The same as in Fig.2,but in the wide-band energy range from radio to TeV γ-rays.Radio and X-ray data are taken from [4,27].flux is marginally consistent with the EGRET upper limit,νF ν∼5×10−11erg s −1cm −2at 1–10GeV [4,28].On the other hand,if the magnetic field is moderately strong (B ∼60µG),the synchrotron cooling effect causes steepening of the electron spectrum over a wide energy range —typically s e ∼3[29].In this case,leptonic IC emission in the GeV–TeV band10-910-1010-1110-1210-1314131211νF ν [e r g /s /c m 2]log (Energy / eV)FIG.4:νF ν-spectra of TeV γ-rays (solid line)and µ-neutrinos (dashed line)calculated within hadronic model in the efficient acceleration case.The solid line is the same as in Fig.1.We have averaged the vacuum oscillation effects among neutrinos.The dotted line shows the daily averaged atmospheric neutrino flux expected in KM3NeT [31,33].shows again the nearly flat νF ν-spectrum.In summary,it may be difficult to differentiate between hadronic and leptonic emission by the spectral shape of the GeV-to-TeV γ-ray emission.As shown in this Letter,when the GeV γ-ray flux is relatively low,both efficient acceleration model with hadronic γ-ray emission and inefficient acceleration model with leptonic one may give similar spectral shapes.On the other hand,when the GeV emission is relatively bright,one may not be able to distinguish the hadronic model in the inefficient case from the leptonic one with moderately strong magnetic field [29].GLAST will surely provide us rich information on the emission 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