A Coherent Timing Solution for the Nearby Isolated Neutron Star RX J0720.4-3125
可靠性仿真在鱼雷产品上的应用

可靠性仿真在鱼雷产品上的应用王斗辉 1, 陈 欢 2, 郭 君 2, 吴 斌 2(1. 工业和信息化部 电子第五研究所, 广东 广州, 615123; 2. 中国船舶集团有限公司 第705研究所, 陕西 西安, 710077)摘 要: 针对传统可靠性试验耗时长、成本高的问题, 给出了可靠性仿真的基本内容和工作流程, 针对鱼雷产品中的典型电子组件开展可靠性仿真建模、热应力和振动应力仿真分析、故障预计和可靠性评估, 以得到产品设计薄弱环节、潜在故障信息和平均首发故障时间等。
分析结果表明, 可靠性仿真能够确保在鱼雷产品设计早期消除故障源, 从而提高鱼雷产品的鲁棒性和故障预测能力。
关键词: 鱼雷; 可靠性; 电子组件; 仿真建模; 应力分析中图分类号: TJ630 文献标识码: A 文章编号: 2096-3920(2024)01-0166-08DOI: 10.11993/j.issn.2096-3920.2023-0030Application of Reliability Simulation in Torpedo ProductsWANG Douhui1, CHEN Huan2, GUO Jun2, WU Bin2(1. CEPRI, Guangzhou 615123, China; 2. The 705 Research Institute, China State Shipbuilding Corporation Limited, Xi’an 710077, China)Abstract: The traditional reliability test is time-consuming and requires high cost. Therefore, this article provided the basic content and workflow of reliability simulation and conducted reliability simulation modeling, thermal stress simulation analysis, vibration stress simulation analysis, fault prediction, and reliability evaluation for typical electronic components in a certain torpedo product, so as to obtain weak links in product design, potential fault information, and average first failure time. The analysis results show that the reliability simulation can ensure the elimination of fault sources in the early stage of torpedo product design and thus improve torpedo product robustness and fault prediction ability.Keywords: torpedo; reliability; electronic components; simulation modeling; stress analysis0 引言随着技术的发展, 对装备可靠性水平的要求越来越高, 但对研制和生产周期的要求则越来越短,完全按传统的典型环境仿真方法对装备进行可靠性试验, 对于可靠性指标要求较高的产品, 无论是时间还是试验费用等都难以保证, 为此需要找到一种在研制初期即可针对仿真模型, 在开展建模仿真的基础上进行可靠性设计及评价的新途径。
时滞忆阻Cohen-Grossberg神经网络周期解的存在性

时滞忆阻Cohen-Grossberg神经网络周期解的存在性王有刚;武怀勤【摘要】研究了一类具有时变时滞的忆阻Cohen-Grossberg神经网络的周期动力行为.借助M-矩阵理论,微分包含理论和Mawhin-like收敛定理,证明了网络系统周期解的存在性.最后,用一个数值算例验证了本文结论的正确性和可行性,并通过图形模拟直观地描述了周期解和平衡点的存在性.%The objective of this paper is to investigate the periodic dynamical behaviors for a class of Memristive Cohen-Grossberg neural networks with time-varying delays. By employing M-matrix theory, differential inclusions theory and the Mawhin-like coin-cidence theorem in set-valued analysis, the existence of the periodic solution for the network system was proved. Finally, an illustra-tive example was given to demonstrate the validity of the theoretical results and the existence of periodic solution and equilibrium point was described visually by graphical simulation.【期刊名称】《西华大学学报(自然科学版)》【年(卷),期】2017(036)005【总页数】10页(P22-30,35)【关键词】忆阻;Cohen-Grossberg神经网络;周期解;时变时滞【作者】王有刚;武怀勤【作者单位】吕梁学院数学系,山西吕梁 033001;燕山大学理学院,河北秦皇岛066004【正文语种】中文【中图分类】TP1831971年, 华裔科学家蔡少棠(Leon O. Chua)从理论推断在电阻、电容和电感器之外,应该还有一种组件,代表着电荷与磁通量之间的关系。
TPO听力题目

What does the professor say about Frantzen’s painting of a farm scene? It resembles a photograph. It may be Frantzen’s best-know painting. It was painted in the Impressionist style. It was painted while Frantzen lived abroad. Why did Frantzen go to the Sales Barn? To study human form and movement To earn money by painting portraits To paint farm animals in an outdoor setting To meet people who could model for her paintings What does the professor imply about the painting of the young woman surrounded by pumpkins? It was painted at an art fair. It combines Impressionism with Realism. It convinced Frantzen that she was a good illustrator. It was originally meant to be used in an advertisement. What does the professor discuss Frantzen’s difficulties as a young painter? He wants to point out mistakes that young artists commonly make. He thinks her example can inspire the students in their own lives. Her difficulties remind him of the difficulties he himself experienced as a young artist. Her difficulties are the subject of some of the paintings in the gallery that the students will visit. What does the professor imply when he says this: The students can understand Frantzen’s art without knowing about her life. The students should pay very close attention to what he is going to say. Some of his students are already familiar with Frantzen’s life story. Some of his students may not appreciate Frantzen’s work. Answers: CCABBA
基于非标准Keystone变换的捷变频雷达相参积累算法

第45卷 第12期2023年12月系统工程与电子技术SystemsEngineeringandElectronicsVol.45 No.12December2023文章编号:1001 506X(2023)12 3836 09 网址:www.sys ele.com收稿日期:20220818;修回日期:20221119;网络优先出版日期:20230105。
网络优先出版地址:https:∥kns.cnki.net/kcms/detail/11.2422.TN.20230105.1653.005.html基金项目:国家自然科学基金(62001510)资助课题 通讯作者.引用格式:张亮,杜庆磊,周必雷,等.基于非标准Keystone变换的捷变频雷达相参积累算法[J].系统工程与电子技术,2023,45(12):3836 3844.犚犲犳犲狉犲狀犮犲犳狅狉犿犪狋:ZHANGL,DUQL,ZHOUBL,etal.Acoherentintegrationalgorithmoffrequency agileradarbasedonnon stand ardKeystonetransform[J].SystemsEngineeringandElectronics,2023,45(12):3836 3844.基于非标准犓犲狔狊狋狅狀犲变换的捷变频雷达相参积累算法张 亮1,2, ,杜庆磊1,周必雷1,瞿奇哲1,王永良1(1.空军预警学院,湖北武汉430019;2.中国人民解放军94326部队,山东济南250000) 摘 要:针对捷变频雷达(frequency agileradar,FAR)相参积累难题,提出基于非标准Keystone变换(Keystonetransform,KT)的FAR相参积累算法,与标准KT相比,所提算法增加了距离补偿环节,构造了不同的虚拟慢时间。
同时,考虑到目标距离信息通常未知,利用距离补偿后信号的周期性,大幅缩小了距离搜索区间。
完美怎么用英语写作文

Writing an essay in English that is considered perfect involves several key components:clear structure,coherent arguments,correct grammar,and engaging vocabulary.Here is a stepbystep guide to help you write an essay that could be seen as perfect:1.Understand the Prompt:Before you start writing,make sure you fully understand the question or prompt.This will guide the direction of your essay and ensure that your content is relevant.2.Plan Your Essay:Outline the main points you want to cover.This will help you organize your thoughts and create a logical flow to your essay.3.Introduction:Start with a strong introduction that grabs the readers attention.Introduce the topic and provide a brief overview of what you will discuss in the essay.4.Body Paragraphs:Each paragraph should focus on one main idea that supports your thesis e topic sentences to introduce each paragraph,followed by evidence or examples to support your point.Make sure to explain how each piece of evidence relates back to your thesis.5.Coherent Arguments:Ensure that your arguments are logical and flow from one to the next.Each paragraph should build upon the previous one,creating a cohesive narrative.e of Evidence:Support your claims with evidence such as facts,statistics,quotes,or examples.Make sure to cite your sources properly to avoid plagiarism.7.Grammar and Punctuation:Check your essay for grammatical errors and correct punctuation.This is crucial for maintaining the credibility and professionalism of your writing.8.Vocabulary:Use a wide range of vocabulary to express your ideas clearly and effectively.Avoid repetition and clichés.9.Conciseness:Be concise and to the point.Avoid unnecessary words and phrases that do not add value to your argument.10.Transitions:Use transitional phrases to connect your ideas smoothly.This helps to guide the reader through your essay and makes it easier to follow.11.Conclusion:Summarize your main points and restate your thesis in a new way.Theconclusion should leave a lasting impression on the reader.12.Revise and Edit:After writing your first draft,take the time to revise and edit your essay.Look for areas where you can improve clarity,strengthen arguments,or correct errors.13.Proofread:Finally,proofread your essay to catch any typos,grammatical mistakes,or inconsistencies that may have been missed during the editing process.14.Get Feedback:If possible,have someone else read your essay and provide feedback.A fresh set of eyes can often spot errors or areas for improvement that you may have overlooked.By following these steps and focusing on clarity,coherence,and correctness,you can write an essay in English that is wellstructured and engaging,which could be considered perfect by many standards.。
2024新课标1卷英语

1.What is the main idea of the passage?A.The history of technology.B.The impact of social media.C.The benefits of exercise.(答案)D.The challenges of modern education.2.Which word best describes the author's tone in the text?A.SarcasticB.Optimistic(答案)C.PessimisticD.Neutral3.What does the phrase "in the long run" mean in the context?A.ImmediatelyB.Eventually(答案)C.OccasionallyD.Rarely4.According to the passage, what is the most effective way to learn a new language?A.Watching foreign movies.B.Listening to music in that language.C.Practicing with a language tutor.(答案)D.Reading books translated into that language.5.Why did the scientist decide to conduct the experiment?A.To prove a previous theory wrong.B.To discover a new element.C.To test a new hypothesis.(答案)D.To replicate a famous study.6.What is the purpose of the author writing this article?A.To entertain readers with a story.B.To persuade readers to adopt a new habit.(答案)C.To inform readers about a recent event.D.To analyze a complex issue.7.Which of the following is NOT mentioned in the passage as a cause of climate change?A.DeforestationB.OverpopulationC.Increased use of renewable energy(答案)D.Industrial emissions8.What can be inferred from the last sentence of the passage?A.The problem will never be solved.B.More research is needed.(答案)C.The solution is simple and straightforward.D.The author is uncertain about the future.。
改进型music算法 相干信号

改进型music算法相干信号英文回答:Improving the music algorithm for coherent signals is an interesting challenge. Currently, the music algorithm is widely used for signal processing in various applications, including audio processing, radar systems, and wireless communications. However, there is always room for improvement to enhance its performance and accuracy.One possible improvement to the music algorithm is to incorporate machine learning techniques. By training a machine learning model with a large dataset of coherent signals, the algorithm can learn to better identify and extract relevant features from the signals. This can lead to improved accuracy and robustness in detecting and classifying coherent signals.Another improvement could be the integration of deep learning algorithms. Deep learning models, such asconvolutional neural networks (CNNs) or recurrent neural networks (RNNs), have shown great success in various signal processing tasks. By incorporating deep learning into the music algorithm, it can potentially improve the algorithm's ability to handle complex and non-linear coherent signals.Furthermore, optimizing the parameter selection process can also enhance the music algorithm's performance. The music algorithm relies on selecting the number of signal sources and the signal subspace dimension. By developing more efficient and accurate methods for determining these parameters, the algorithm can better adapt to different signal scenarios and improve its overall performance.To illustrate the potential improvements, let's consider the example of music source separation. Currently, the music algorithm is used to separate different sourcesin an audio signal. However, it may struggle when the sources are highly correlated or when there are overlapping sources. By incorporating machine learning techniques, the algorithm can learn to better distinguish between different sources and separate them more accurately.For instance, let's say we have a music recording with vocals and instruments playing simultaneously. The current music algorithm may have difficulty separating the vocals from the instruments if they are highly correlated. However, by training a machine learning model with a large datasetof vocal and instrumental tracks, the algorithm can learnto differentiate between the two and successfully separate them in the given recording.中文回答:改进相干信号的music算法是一个有趣的挑战。
电感耦合等离子体原子发射光谱法的英文

电感耦合等离子体原子发射光谱法的英文Inductively coupled plasma atomic emission spectroscopy (ICP-AES) is a powerful analytical technique that is widely used for the determination of trace elements in various samples. It is based on the principle of inductively coupled plasma, in which a high-frequency electromagnetic field is used to create a plasma from a sample gas. This plasma is then used to excite the atoms of the elements in the sample, causing them to emit characteristic light that can be detected and quantified.ICP-AES offers several advantages over other analytical techniques, such as high sensitivity, multi-element analysis capability, and the ability to analyze a wide range of sample types. It is commonly used in environmental, pharmaceutical, food, and materials analysis, as well as in research and industrial applications.The instrumentation for ICP-AES consists of a sample introduction system, an inductively coupled plasma source, a spectrometer, and a detector. The sample is typically introduced into the plasma using a nebulizer or an ICP torch, where it is atomized and excited by the plasma. The light emitted by the excited atoms is then dispersed by the spectrometer and detected by the detector.One of the key advantages of ICP-AES is its high sensitivity, which allows for the detection of trace elements at levels as low as parts per billion. This makes it an ideal technique for the analysis of samples with low concentrations of elements, such as environmental samples or biological fluids.In addition to its high sensitivity, ICP-AES also offers a high level of precision and accuracy in elemental analysis. The technique is capable of analyzing multiple elements simultaneously, which reduces the time and cost associated with analysis compared to traditional methods that require separate analyses for each element.ICP-AES is also a versatile technique that can be used to analyze a wide range of sample types, including liquids, solids, and gases. It is commonly used in conjunction with sample preparation techniques such as digestion, extraction, and dilution to analyze complex samples.Overall, ICP-AES is a powerful and versatile analytical technique that is widely used for the determination of trace elements in various samples. Its high sensitivity, precision, and multi-element analysis capability make it an indispensable tool for researchers and analysts in a wide range of fields.。
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a r X i v :a s t r o -p h /0506419v 1 17 J u n 2005To appear in ApJLPreprint typeset using L A T E X style emulateapj v.6/22/04A COHERENT TIMING SOLUTION FOR THE NEARBY ISOLATED NEUTRON STAR RX J0720.4−3125D.L.Kaplan 1,2and M.H.van Kerkwijk 3To appear in ApJLABSTRACTWe present the results of a dedicated effort to measure the spin-down rate of the nearby isolated neutron star RX J0720.4−paring arrival times of the 8.39-sec pulsations for data from Chandra we derive an unambiguous timing solution for RX J0720.4−3125that is accurate to <0.1cycles over >5years.Adding data from XMM and ROSAT ,the final solution yields ˙P=(6.98±0.02)×10−14s s −1;for dipole spin-down,this implies a characteristic age of 2Myr and a magnetic field strength of 2.4×1013G.The phase residuals are somewhat larger than those for purely regular spin-down,but do not show conclusive evidence for higher-order terms or a glitch.From our timing solution as well as recent X-ray spectroscopy,we concur with recent suggestions that RX J0720.4−3125is most likely an off-beam radio pulsar with a moderately high magnetic field.Subject headings:pulsars:individual (RX J0720.4−3125)—stars:neutron —X-rays:stars1.INTRODUCTIONOne of the interesting results from ROSAT All-Sky Survey (Voges et al.1996)was the discovery of seven ob-jects that appear to be nearby,thermally-emitting neu-tron stars that have little if any magnetospheric emis-sion (see Haberl 2004for a review).These objects,known most commonly as “isolated neutron stars,”are distinguished by their long periods ( 3s,when mea-sured),largely thermal spectra with cool temperatures (kT 100eV),faint optical counterparts (when de-tected),and lack of radio emission.It is not yet clear what sets the isolated neutron stars apart from the nearby,relatively young rotation-powered pulsars that also have cool thermal emission —sources like PSR B0656+14and PSR B1055−52—which tend to have short (<1s)spin periods,∼1012-G magnetic fields,non-thermal (i.e.power-law)components in their X-ray spectra,and radio pulsations (e.g.,Pavlov &Zavlin 2003;Kaplan 2004).The isolated neutron stars are known to have longer periods,but their spin-down rates (and hence magnetic fields )are unknown,largely be-cause it has not yet been possible to determine a reliable,coherent timing solution (Kaplan et al.2002,hereafter Paper I;Zane et al.2002).In this Letter we report a new analysis of the varia-tions of the 8.39-s period of the second brightest source of the group,RX J0720.4−3125(Haberl et al.1997).We describe our analysis of Chandra data obtained specifically for timing purposes,as well as archival ROSAT ,Chandra ,and XMM data,in §2.In §3,we show that with the new data,we can avoid the pitfalls of the previous phase-coherent timing analyses and obtain a reliable timing solution.We discuss possible timing noise in §4and the implications of our result in §5.1Pappalardo Fellow2Center for Space Research,Massachusetts Institute of Technol-ogy,77Massachusetts Avenue,37-664D,Cambridge,MA 02139,USA;dlk@3Department of Astronomy and Astrophysics,University of Toronto,60St.George Street,Toronto,ON M5S 3H8,Canada;mhvk@astro.utoronto.ca2.OBSERVATIONSOur primary data were eight observations with the Advanced CCD Imaging Spectrometer (ACIS;Garmire et al.2003)aboard the Chandra X-ray Observa-tory (CXO ;Weisskopf et al.2000).These were designed for timing accuracy,consisting of two sets of four expo-sures geometrically spaced over a period of about two weeks and separated by about half a year.We combined these with data from other Chandra observations,as well as from observations with XMM-Newton (Jansen et al.2001)and ROSAT (Tr¨u mper 1993).A log of all obser-vations is given in Table 1.For the Chandra data,we processed the level-1event lists to the level-2stage following standard procedures and the latest calibration set (CALDB version 3.0.0).For the ACIS continuous-clocking data,this includes correcting the recorded event times for readout,dither,and spacecraft motion —corrections that used to re-quire additional steps (Zavlin et al.2000).We ex-tracted events within 1′′of the source,and then ap-plied a clock correction of 284.7µs to the arrival times (Davis,Holmes,&Myers 2003);the arrival times should now be accurate to 6µs.For the HRC-S/LETG data,we extracted zeroth-order events from a circle with ra-dius 10pixels (1.′′3),and first-order events using the stan-dard LETG spectral extraction windows,but limited to 10≤λ≤65˚A .Finally,we used the axbary program to barycenter all of the events (using the optical po-sition:αJ2000=07h 20m 24.s 96,δJ2000=−31◦25′50.′′2;Kaplan et al.2003)For the XMM data,we used the standard procedures emchain and epchain (XMMSAS version 6.1.0)to repro-cess the observations.One additional step was necessary for the PN data set 622-U2,for which we found a small number of duplicate events (frames 963685–963719);we removed these before processing.Next,we extracted all single-pixel events within 37.′′5of the source position,and used barycen to convert the arrival times to the solar-system barycenter 4.4Some portions of the 2000and 2002XMM /PN ob-servations were affected by a known processing problem2Kaplan&van KerkwijkTABLE1Log of Observations and Times of ArrivalInstrument a ID b Date Exp.Counts TOA c(ks)(MJD)PSPC......3381993-09-27 3.2580049257.2547031(25)HRI........8841996-11-0333.71266250391.3006530(16)HRI........9441998-04-208.1307450925.6881172(36)HRC........3682000-02-01 5.4347251575.3026910(46)HRC........7452000-02-0226.11514951576.2804856(27)HRC........3692000-02-04 6.1366751578.7722735(65)PN/ff/thin..78-S32000-05-1321.114410451677.2260789(5)MOS2/thin.78-S22000-05-1343.97391551677.4127431(7)PN/ff/med.175-S32000-11-2125.715303751869.8413358(14)MOS1/open175-U22000-11-21 6.81776251869.8433759(14)MOS2/open175-U22000-11-217.22108451869.9571032(6)ACIS-CC...27742001-12-0415.0318*******.7881789(11)ACIS-CC...27732001-12-0510.62284752248.2835843(13)ACIS-CC...27722001-12-06 4.1879052249.6286894(26)PN/ff/thin..533-S32002-11-0628.319984152584.9260561(5)PN/ff/thin..534-S32002-11-0830.221217752587.0013053(4)MOS1/open622-U22003-05-027.61762952761.6222174(14)MOS2/open622-U22003-05-027.51878852761.6226056(12)PN/sw/thick622-U22003-05-0272.821016052761.9950589(5)PN/sw/thin711-S72003-10-2718.111287652939.8228751(9)PN/sw/thick711-S82003-10-2725.013868952939.8228774(8)MOS1/open711-U22003-10-2713.83332352939.8506513(5)MOS2/open711-U22003-10-2713.83563652940.1162720(5)ACIS-CC...46662004-01-0610.11904853010.2635608(14)ACIS-CC...46672004-01-07 4.8893853011.2639869(20)ACIS-CC...46682004-01-11 5.2933453015.5407400(19)ACIS-CC...46692004-01-19 5.2939153023.1274147(23)HRC........53052004-02-2735.72159753062.4142490(27)PN/ff/thin..815-S12004-05-2231.621985553147.6811948(4)ACIS-CC...46702004-08-0310.11743253220.9975987(14)ACIS-CC...46712004-08-05 5.1805153222.2171299(21)ACIS-CC...46722004-08-09 5.1855653226.2443808(25)ACIS-CC...46732004-08-23 5.1713353240.1824669(24)HRC........55812005-01-2367.74480153393.6657119(18)a PSPC:Position Sensitive Proportional Counter(Briel&Pfeffermann1995)aboard ROSAT.HRI:High-Resolution Imager(Zombeck et al.1995)aboardROSAT.HRC:High-Resolution Camera for spectroscopy aboard Chandra(HRC-S;Kraft et al.1997),used with the Low-Energy Transmission Grat-ing.ACIS:Chandra’s Advanced CCD Imaging Spectrometer(Garmire et al.2003),used in continuous clocking mode.EPIC-pn:XMM’s European Pho-ton Imaging Camera with PN detectors(Str¨u der et al.2001),used in full-frame(ff)or small window(sw)mode,with thin,medium,or thickfilter.EPIC-MOS1/2:European Photon Imaging Cameras with MOS detectorsaboard XMM(Turner et al.2001),used in small-window mode with thin orno(open)filter.b Observation identifier(CXO,ROSAT)or revolution number and exposureidentifier(XMM).c The TOA is defined as the time of maximum light closest to the middle ofeach observation,and is given with1-σuncertainties.The reduction of the ROSAT data followed that inPaper I,except that we properly corrected the eventtimes to the Barycentric Dynamical Time(TDB)sys-tem instead of the Coordinated Universal Time(UTC)system returned by the FTOOLS barycentering tasks(seeCropper et al.2004).We used the corrections suppliedin Cox(2000,p.14).that rejected significant portions of the observations;seehttp://xmm.vilspa.esa.es/sas/documentation/watchout/lost_events.shtml. This should not introduce any systematic error,though it meansthat our TOAs for these observations are not as precise as possiblewith all events.However,since the present TOA uncertaintiesare smaller than the timing noise(§4),we decided not to try toremedy this problem.3.TIMING ANALYSISOur goal was to use times-of-arrival(TOAs)to infer a phase-coherent timing solution involving the spin period and its derivative,where each cycle of the source was counted.To measure TOAs we needed an initial refer-ence period,something which we determined using a Z21 test(Rayleigh statistic;Buccheri et al.1983)on the com-bined2004January ACIS and2004February HRC data. Wefind P=8.3911159(10)s(here and below,numbers in parentheses indicate twice the formal1-σuncertain-ties in the last digit unless otherwise indicated),which is consistent with our earlier value(Paper I)but much more accurate because we could coherently connect ob-servations over a much longer(52day)time span. Using this period,we constructed binned light curvesA Timing Solution for RX J0720.4−31253Fig. 1.—Phase residuals for RX J0720.4−3125.The top panelshows the residuals for each TOA compared to a linear(˙ν=0)model.The solid curve gives the best-fit quadratic(˙ν=0,¨ν=0)ephemeris for all data(Tab.2,with a0.27-s systematic uncertaintyadded in quadrature).The vertical dashed line indicates the ref-erence time t0.The bottom panel shows the residuals relative tothe quadratic model.We also show a best-fit cubic model(¨ν=0;dotted line)and a model that includes a glitch in frequency nearMJD52800(∆f≈1×10−9;dashed curve).(with16phase bins)and determined the TOAs byfittinga sinusoid(appropriate for the sinusoidal pulsations ofRX J0720.4−3125;Haberl et al.1997);the uncertaintieswere calculated from the uncertainties in the phases ofthefitted sinusoids(we verified that we obtain consistentresults if we change the binning or measure TOAs usingcross-correlation instead).Here,the TOA is defined asthe time of maximum light closest to the middle of theobservation,a choice which minimizes co-variance withsmall changes in period.We present TOAs for all of thedata in Table1.We then determined a timing solution for only theChandra data using an iterative procedure.Wefirst usedthe reference period to determine cycle counts for thefiveabove-mentioned observations,as well as the next obser-vation closest in time.Wefit these cycle counts toφ(t)=φ0+ν(t−t0)+16¨ν(t−t0)3...,(1)whereφ0is the cycle count plus phase at reference time t0,νis the spin-frequency,˙νis its derivative,¨νis the second derivative.We then iterated,using the improved solution to determine the cycle count for the next ob-servation,etc.We started with˙ν=¨ν=0,but left˙νfree once that significantly improved thefit;¨νwas not required(cf.,§4below).Thefinal ephemeris listed in Table2has small,≤0.1cycle,residuals,andfits the Chandra data well:χ2ν≡χ2/N dof=1.06(with N dof=13degrees of free-dom).To test the uniqueness of our ephemeris,we tried changing the cycle counts(adding or subtracting one or more cycles)at the least unambiguous points,but found that the resulting solutions were very poor(e.g.,alter-ing the cycles between the2001ACIS and2000HRC observations gaveχ2ν=89.26).To improve and extend the ephemeris,we added the XMM and ROSAT data into the solution(see Table2). As for the Chandra data alone,the cycle counts are unambiguous and,as can be seen in Fig.1,the resid-TABLE2X-ray Timing Ephemerides for RX J0720.4−3125 Quantity a CXO only All data b Dates(MJD)51575–5339449257–53394t0(MJD)....53010.2635605(18)53010.2635637(24)ν(Hz)......0.11917366926(46)0.11917366908(38)˙ν(Hz s−1)..−9.97(11)×10−16−9.918(30)×10−16 TOA rms(s)0.180.31χ2/DOF....13.8/13=1.0630.7/31=0.99P(s)........8.391115305(32)8.391115532(26)˙P(s s−1)....7.019(80)×10−146.983(22)×10−14˙E(erg s−1)..4.7×10304.7×1030B dip(G)....2.5×10132.4×1013τchar(yr)....1.9×1061.9×106Note.—Uncertainties quoted are twice the formal1-σuncertainties in thefit.a˙E=1045I454π2ν˙νis the spin-down luminosity(with I=1045I45g cm2the moment of inertia);B dip=3.2×10194Kaplan&van Kerkwijkbyfitting the phase residuals with a third-order(¨ν=0) solution like that shown in Fig.1.This does in fact im-prove thefit—givingχ2ν=6.02for N dof=30with an rms of0.32s—though it is still formally unacceptable. Wefind¨ν≈2.4(4)×10−25Hz s−2(this also changes ˙νby3%from the value in Tab.2),giving a timing noise measurement of∆8≡log10(|¨ν|(108)3/6ν)=−0.5. This value is on the high side of,but not outside the range expected from relations between˙P and∆8found for radio pulsars(Arzoumanian et al.1994)and mag-netars(Woods et al.2000;Gavriil&Kaspi2002).We do not believe it is likely that the third-order solution represents a real long-term change in˙ν,since the value of¨νchanges significantly if one uses just the Chan-dra,Chandra+XMM,or all of the data5[8(6),18(4), or2.4(4)×10−25Hz s−2,withχ2ν=0.64,2.81,or6.02 respectively].A second possibility is a sudden change in rota-tion—a glitch,as proposed(and largely rejected)by de Vries et al.(2004)to account for variations in spec-tral shape(differences of10%in the inferred temper-ature)and pulse shape(changes of50–100%in pulsed fraction)observed between2000and2003.The system-atic increase in the residuals after MJD53000in Fig-ure1might indeed indicate a glitch.We triedfitting a simple glitch model,in which we assumed that only the frequency changed,that the recovery time was longer than the span of our observations,and that the glitch occurred on2003July1(MJD52821),in between the two XMM observations that showed the largest spec-tral change(de Vries et al.2004).Wefind a reasonable fit for a glitch with∆f=1.3×10−9Hz and a recov-ery time>3yr,givingχ2ν=7.7(see Fig.1).This would be a small glitch,with∆f/f=1.1×10−8com-pared to values of10−9to10−6for radio pulsars(with smaller values more typical for larger magneticfields; Lyne,Shemar,&Smith2000).It also implies that ener-getically,the putative glitch would be insignificant:the change in kinetic energy of∼1036ergs(van Riper et al. 1991)would only be noticeable if dissipated in<1day given the bolometric luminosity of RX J0720.4−3125of 2×1032d2300ergs s−1(where d=300d300pc is the dis-tance to RX J0720.4−3125;Kaplan et al.2003).In prin-ciple,however,it could still have altered the light curve and spectrum of RX J0720.4−3125through realignment of the magneticfield relative to the spin axis. Finally,a more mundane explanation for the rela-tively poorfit is that the data are from different instru-ments with different energy responses(even among a sin-gle instrument aboard XMM,the changingfilters alter the response).The pulse profile of RX J0720.4−3125 is known to depend on energy(Cropper et al.2001; Paper I;Haberl et al.2004)and to change over time (de Vries et al.2004).While the changes to the shape are small,some systematic offsets are expected between the pulse profiles as measured by different instruments or at different times.We hope to investigate this in more detail in the near future.At present,we cannot distinguish between the various5From Fig.1,it may appear that one could obtain a betterfit by reducing the cycle count for the1998HRI point by one;however, doing that,the other ROSAT points cannot be reproduced any more.possibilities for the relatively poorfits.The predicted future behavior is different,however,and thus further observations of RX J0720.4−3125(some of which are in progress)should be able to distinguish between these models.5.DISCUSSION&CONCLUSIONSFrom our timing solution,we infer a spin-down rate ˙P=6.98(2)×10−14s s−1.This is consistent with the limits derived in Paper I and by Zane et al.(2002),but inconsistent with the tentative solution of Cropper et al. (2004),who found˙P=(1.4±0.6)×10−13s s−1at99% confidence(but who noted that elements of their solution were inconsistent with each other and that their analy-sis was subject to confusing aliases).In Table2,we list derived parameters—rotational energy loss rate,mag-neticfield,and characteristic age(the latter two under the assumption of magnetic dipole spin-down).The values of P and˙P place RX J0720.4−3125well above above most of the radio-pulsar“death-lines”pro-posed so far(e.g.,Young,Manchester,&Johnston1999) and in a region populated by radio pulsars in P-˙P diagrams like that in Paper I(its parameters are ap-proximately between those of PSR J1830−1135,with P=6.2s,˙P=5×10−14s s−1,and PSR J1847−0130, with P=6.7s,˙P=1.3×10−12s s−1).Hence, RX J0720.4−3125may well be a radio pulsar itself,but one whose radio beam(s)do not intersect our line of sight. Its inferred magneticfield,B=2.4×1013G,is not excep-tional;the Parkes Multi-beam Survey(Manchester et al. 2001)in particular has discovered a fair number of ra-dio pulsars with B 1013G(e.g.,Camilo et al.2000; Morris et al.2002;McLaughlin et al.2003),and it is now clear the distribution of magneticfields isflatter than previously assumed(Vranesevic et al.2004).With˙E=4.7×1030ergs s−1,RX J0720.4−3125is not expected to have much non-thermal X-ray emis-sion:from the relation of Becker&Tr¨u mper(1997), one estimates L X,non−th∼10−3˙E≃5×1027ergs s−1, much smaller than the thermal emission,L X,therm≃2×1032d300ergs s−1.This is consistent with lim-its from Chandra and XMM(Paerels et al.2001; Pavlov,Zavlin,&Sanwal2002;Kaplan et al.2003). What is somewhat puzzling is the inferred age of2Myr. Tracing RX J0720.4−3125back to OB associations where it might have been born put it close to the Trumpler10 association∼0.7Myr ago(Motch,Zavlin,&Haberl 2003;Kaplan2004).Similarly,based on its estimated temperature and luminosity,most standard cooling mod-els(modified URCA for1.4M⊙neutron stars)put RX J0720.4−3125at 1Myr(Heyl&Hernquist1998; Paper I;Cropper et al.2004).It is of course possible that RX J0720.4−3125was born with a long period and/or had significantly non-dipole braking,such that the spin-down age is not a good es-timate of its true age.However,no case with as long a birth period as would be required for RX J0720.4−3125 is known among radio pulsars(cf.Kramer et al.2003; Gavriil et al.2004).Another possible explanation is that RX J0720.4−3125 was ejected from a binary system with a massive com-panion∼0.7Myr ago,either when the companion un-derwent a supernova or during a binary exchange inter-A Timing Solution for RX J0720.4−31255action.In this case,a relatively long period is expected: if the neutron star accreted matter from its compan-ion,its spin period would have tended toward the equi-librium period,P eq≈5s(B/1013G)6/7(˙M/˙M Edd)−3/7 (where˙M is the accretion rate and˙M Edd is the Edding-ton rate).A relatively short cooling age would also be consistent with this model:the accretion and accompa-nying steady hydrogen burning could reheat the neutron star(or keep it hot).Of course,it remains to be seen that a suitable evolutionary scenario can be found.In any case,the prediction for the model with two supernovae is that there may well be another 1Myr old neutron star whose proper motion traces back to the same origin as RX J0720.4−3125(cf.Vlemmings et al.2004). Finally,we can compare the magneticfield strength of 2.4×1013G with what is inferred from the broad absorp-tion feature in the spectrum(observed to be at0.3keV, which corresponds to0.39keV at the surface for a grav-itational redshift of0.3;Haberl et al.2004;Vink et al. 2004).If due to a proton cyclotron line,one infers B≃6×1013G(Haberl et al.2004),which is substan-tially larger than inferred from the spin-down.This may simply reflect the inadequacy of the dipole spin-down model,or the presence of higher order multipoles.On the other hand,based on a comparison with other sources, van Kerkwijk et al.(2004)suggested that the absorption feature was due to the transition from the ground state to the second excited tightly bound state of neutral hydro-gen,which would require B≃2×1013G and matches the spin-down value nicely.If that is the case,higher signal-to-noise spectra should reveal the transition to thefirst excited state at∼0.15keV.We thank an anonymous referee for useful comments, and Kaya Mori,George Pavlov,Saul Rappaport,Deepto Chakrabarty,and Peter Woods for helpful discussions. 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