In this work we performed a spectrotemporal investigation of the lowmass Xray binary GX 99 using the Large Area Xray Proportional Counter LAXPC and Soft X ray Telescope SXT observation on board AstroSat. The source was detected in the soft state during the observation which results in a disk dominating energy spectrum within the energy range of 0.725.0 keV. We carried out the analysis at different flux levels. In the temporal analysis LAXPC data in all flux levels showed the presence of noise components describing broad Lorentzian components. We modeled the energydependent temporal properties of the source in order to identify the radiative origin of the observed variability. This source is not a wellstudied source hence we attempt to estimate various source characteristics like innerdisk radius flux and innerdisk temperature.
['Astrophysics - High Energy Astrophysical Phenomena']
Spectrotemporal study of atoll source GX 99 observed with AstroSat
{'Spectro-temporal study of atoll source GX 9+9 observed with AstroSat': 'Sree Bhattacherjee*, Arbind Pradhan, Biplob Sarkar  \n*Corresponding author  \nDepartment of Applied Sciences, Tezpur University, Napaam, Assam 784028, India Email of corresponding author: app21101@tezu.ac.in  \nAbstract -  In  this  work,  we  performed  a  spectro-temporal investigation  of  the  low-mass  X-ray  binary  GX  9+9  using  the Large Area X-ray Proportional Counter (LAXPC) and Soft Xray Telescope (SXT) observation on board AstroSat. The source was  detected  in  the  soft  state  during  the  observation,  which results in a disk dominating energy spectrum within the energy range of 0.7-25.0 keV. We carried out the analysis at different flux  levels.  In  the  temporal  analysis,  LAXPC  data  in  all  flux levels  showed  the  presence  of  noise  components,  describing broad  Lorentzian  components.  We  modeled  the  energydependent temporal properties of the source in order to identify the radiative origin of the observed variability. This source is not a  well-studied  source;  hence  we  attempt  to  estimate  various source characteristics like inner-disk radius, flux, and inner-disk temperature.  \nKeywords-x-ray binary, GX 9+9, neutron star.', 'I. INTRODUCTION': "GX 9+9  is  a  neutron  star  low-mass  X-ray  binary  (NSLMXB)  that  was  identified  during  the  Galactic  center's sounding rocket mission [1, 2]. It is an established atoll source since it traces a 'C'-pattern in the hardness-intensity diagram (HID).  Atoll  sources  primarily  have  two  states:  (i)  the hard/island state (IS), which is observed in lower luminosities; and (ii) the soft/banana state (BS), which is observed in higher luminosities [3]. BS is further classified into upper and lower banana states. In hard state, the Comptonization component is more dominant, while the accretion disk's thermal emission is more prominent in  soft  spectra.  On  durations  ranging  from days  to  weeks,  the  atoll  sources  show  significant  spectral changes [4, 5, 6, 7]. The rate of accreting mass in such sources is believed to be increasing from island to upper banana state [3, 8].  \nThe source GX 9+9 has 4.2-hour X-ray and optical waveband modulation [2, 9, 10]. Its distance is asummed to be in between 5 kpc and 10 kpc [10, 11]. The estimated values for the mass and radius of the compact NS in the XRB system are 0.2-0.45 M ⨀ and 0.3-0.6R ⨀ , respectively [2, 9]. It is often detected in a luminous soft state with a ~220 mCrab of X-ray flux in the 220  keV  band  [12].  The  source  spectrum  has  been  modeled using  various  spectral  descriptions,  including  a  power  law [13],  a  blackbody  and  Comptonization  model  [14],  a  disk component with a Comptonized blackbody [11], and a double blackbody  with  a  broad  iron  line  [15].  Recent  studies emphasize  the  role  of  spectral  modeling  in  understanding coronal plasma, though these models often have geometric and locational  ambiguities  [12].  Chatterjee  et  al.  [16]  presented Imaging X-ray Polarimetry Explorer (IXPE) data along with AstroSat  spectral  data  from  2020,  showing  the  spectropolarimetric studies inferring coronal geometry. A simultaneous X-ray and optical band timing investigation for GX  9+9  was  conducted  using  the      South  African  \nAstronomical  Observatory  (SAAO)  and  Rossi  Timing Explorer (RXTE) [14]. Over RXTE, LAXPC has a number of benefits, such as, larger effective area, wider energy coverage, etc.  Hence,  more  precise  information  on  the  time  delays, spectral distribution for a wider energy band, and other timing aspects can be anticipated from AstroSat data.  \nIn this work, we study the specto-temporal properties of the source using AstroSat data and we compare the constancy between the spectral and temporal analysis. We also estimate the  characteristics  values  of  the  source  with  the  help  of  the obtained spectral parameters and compare with the previously reported results.", 'II. OBSERVATION AND DATA REDUCTION': "AstroSat  is  India's  first  multi-wavelength  observatory.  For this  work,  we  used  the  Large  Area  X-ray  Proportional Counter  (LAXPC)  and  Soft  X-ray  Telescope  (SXT) instruments of AstroSat. There is a single AstroSat archival observation available for this source (Obs. ID: A09\\_018T01\\_9000003774),  which  was  taken  on  July  25, 2020. The SXT and LAXPC data were utilized for spectral analysis. For timing analysis, we considered only the LAXPC data  due  to  its  high  timing  resolution  (in  order  of microseconds) [17, 18, 19].  \nLAXPC has three identical counters, of which the LAXPC counters  10  and  30  suffered  abnormal  gains  from  2018 onwards [20]; hence, we only considered the LAXPC 20 data for our analysis. LAXPC operates over a wide energy band from  3-80  keV  [17,  18,  19].  We  used  the  South  Atlantic Anomaly and Earth occultation-free good time interval data to extract the scientific level-2 data [18], using the standard pipeline  of  LAXPCsoftware  (version:  Oct.  13,  2022).  The corresponding  subroutine  of  the  software  has  been  used  to extract  the  scientific  products  like  light  curves,  spectrums, background spectrums, and response files.  \nSXT is an imaging instrument of AstroSat working in the low energy range of 0.3-8.0 keV [21, 22]. The level-1 SXT data for  the  source  has  been  processed  through  the  standard AS1SXTLevel2-1.4b  SXTpipeline  to  generate  the  cleaned level-2 event files. The standard background (SkyBkg\\_comb\\_EL3p5\\_Cl\\_Rd16p0\\_v01.pha) and response file (sxt\\_pc\\_mat\\_g0to12.rmf) have been used as provided by the SXT payload operational center (POC) to carry out the analysis.  During  the  observation,  the  SXT  count  rate exceeded the pileup threshold of 40 counts/sec. In order to limit  the  counts/sec  below  the  pileup  limit,  we  utilized  an annular zone with an outer radius of 13 arcmin and an inner radius of 2 arcmin to extract the light curves and the spectrum utilizing  XSELECT  (V2.5b). Ancillary  response  files  were created using the task sxtARFModule. We incorporated 2%  \nmodel  systematic  error  for  the  background  uncertainty estimation [19].  A gain fit has been applied to the SXT data,  \nFig.1.  HID of the source using the AstroSat data, with a binning time of 32s. Each color represents the different flux levels as indicated in the plot.  \n<!-- image -->  \nwith a slope of 1 and keeping the offset parameter free, whose value usually lies within 0.02-0.09 [23, 24]. Both the LAXPC and  SXT  spectrums  are  optimally  grouped  using  the  ftool ftgrouppha.", 'III. FLUX-RESOLVED SPECTRAL ANALYSIS': "This work combines the SXT and LAXPC spectra, utilizing the  broad-band  spectral  coverage  from  soft  to  hard  X-ray energy range. The HID of the source is displayed in Fig. 1, where the overall count rate in the 3-20 keV band is plotted against the X-ray photon count ratio in the energy ranges of 6-20 keV and 3-6 keV. We may infer that the source was in BS at the time of observation based on the form of HID. As shown in Fig. 1,  we segregated the flux of the  source  into three distinct flux levels (FLs): FL1-450 to 570 counts/s, FL2570 to 650 counts/s, and FL3-650 to 770 counts/s, in order to conduct  the  flux-resolved  spectral  analysis.  We  have independently undertaken the spectral analysis in each of the FLs  within  the  energy  range  of  0.7-25  keV  in  order  to investigate the spectral parameter variations with the rise in X-ray flux. For the purpose of the spectral fitting, we use the XSPEC  (version:  12.13.0c)  [25]  package  of  HEASOFT (6.31.1).  \nWe used the strict simultaneous data from LAXPC and SXT,  \ni.e., when both instruments were observing the source at the same  time,  for  spectrum  analysis.  First,  we  consider  the blackbody  surface  (bbodyrad)  to  be  the  source  of  seed photons. However, with a reduced χ 2 value > 2, this scenario was  unable  to  explain  the  observational  data.  Next,  we proceeded  with  the  assumption  that  the  soft  photon  was emitting from the accretion disk (diskbb),  which  gave  us a good-fit  with  physical  spectral  parameters.  Therefore,  we obtain const*tbabs*(thcomp*diskbb) as the best-fit model for analysis. To calibrate the different instruments utilized for the joint  spectral  fitting,  we  incorporate  a  cross-calibration component 'const' in the model. We considered the LAXPC 20 spectra as the base spectra, so we kept its constant fixed at 1, leaving the SXT constant free for the calibration. The bestfit model is comparable to the one employed by Chatterjee et al. [16]; however, we have used the thermal Comptonization model (ThComp) [26], an improved version of the nThComp. We extend the energy range with 1000 log bins by 'energies 0.01  500  1000  log'  for  the  convolution  model ThComp.  \nCovering fraction, a model parameter of ThComp, indicates the amount of seed photons that will be Comptonized.  \nFig.2. Best-fit spectrum of FL1, FL2, and FL3 from top to bottom, in the energy range 0.7-25 keV. The red and black points represent the SXT and LAXPC 20 data, respectively.  \n<!-- image -->  \nEnoray (kev)  \nThe  best-fit  spectrum  is  shown  in  Fig.  2,  while  Table  1 displays  the  best-fit  parameters  for  each  FL.  The  level  of confidence for the parametric errors is 90%. To constrain the other parameters, we freeze the source's optical depth at 9. We require edge models (instrumental features) at energy 2.4 keV in order to obtain a better fit [16].  \nBased on the best-fit parameters from the spectral fitting, we estimated  the  average  inner-disk  radius  ( 𝑅 in)  of  the  source during the observation to be ~ 16.57±1.29 km. It is calculated using the relation,  \n𝑅 in= k 2 ( 𝑁 dbb / 𝑐𝑜𝑠 θ ) 1/2 ∗ 𝐷 10 (1)  \nwhere, k is the color-correction factor, having a value of 1.7 [27]. 𝑁 dbb  is  the  disk-normalization, θ is  the  source's  diskinclination angle, which is considered as 60 degrees [2, 9, 11]. D represents the source distance, which is considered as 10 kpc [11] while D10 refers the source distance in the units of 10 kpc.  Additionally,  using  the  XSPEC  model  'cflux'  we estimated  the  total  unabsorbed  flux  along  the  FLs  in  the extended energy range of 0.01-100 keV, which came out to be ~5.94 × 10 -9 ergs s -1 cm -2 , 6.51 × 10 -9 ergs s -1 cm -2 , 7.30 × 10 -9 ergs s -1 cm -2 in FL1, FL2, and FL3 respectively.", 'IV. TIMING ANALYSIS': "There  are  two  types  of  variability  that  LMXBs  generally show:  quasi-periodic  oscillations  (QPOs)  and  broad-band noise (BBN) features. A power density spectrum (PDS) plot is used to detect the variability of the source during the course of observation. We checked for the variability in different flux levels  (FL1,  FL2  and  FL3)  by  using  the  multi-lorentzian approach to the PDS.  We didn't detect any hint of QPOs or prominent BBN feature. Further, we decided to look for any statistics as compared to discrete FLs. We generated PDS of full flux in an energy range of 3-20 keV in a frequency range  \nof 0.003 Hz to 1 Hz because of very low statistics beyond 1Hz and below 0.003 Hz. We observed a BBN like feature in a wide centered region as shown in Figure 3 (left). We required two Lorentzians to fit the PDS. We obtained the rms and time lag spectra using LAXPC subroutine 'laxpc\\_find\\_freqlag' at the centroid frequency ( ν o) as obtained from the fitting which is ~0.04 Hz. The characteristic frequency ( ν c) thus obtained is ~0.1 Hz (see Figure 3 (left)) on applying ν c= √ ( ν o 2 +HWHM) [28]. Here, HWHM, is the value indicating the half width of the spectral feature at half its maximum  height,  is approximately 0.09 Hz. Hence, the peak in the spectra does not align with the ν₀ of the Lorentzian; rather, it is equal to or greater than ν₀. While this difference is minimal for QPOs, which  have  typically  narrow  width.  But  it  becomes  more pronounced  in  cases  involving  BBN  features  as  it  spreads over a certain range of frequency [28].  \nFrom the Figure 3 (right), we can see that the rms at ~0.1 Hz is increasing as the energy is increasing whereas the phase lag is showing a decreasing trend with energy. But we cannot rely on the phase lag here as the error-bar are consistent  within data points. To understand the radiative origin of the observed variability,  we used the model as formalized by Garg et al. [29].  It  is  one  of  the  propagative  models  based  on  the assumption of the truncated disk and a hot electron plasma (corona) in between the  inner radius and ISCO in a binary system. Where the coronal region is a Comptonizing medium and the soft seed photons originate from the truncated disk. It relates the spectral parameters with the physical parameters, which  helps  in  understanding  the  factor  leading  to  such stochastic variability in the system.  \nWith this model we were able to obtain a reduced χ 2 value of ~0.80. We further introduced the combination of heating rate, optical depth to check the better fit in rms and lag but we end up  getting  insignificant χ 2 values  (>2).  Hence,  the  best-fit model from this formalism was the variation in kTin and fs with some time delay (phase lag)  w.r.t  fs, as shown in black solid  line  in  Figure  3  (right). The  parameters  values  of  the best-fit are shown in Table 1. As per the analysis, we can infer that the variation responsible for this observed variability was initially introduced as a variation in the inner-disk temperature  and  the  perturbation  moved  towards  coronal region as the variation in the fraction of seed photons that is being Comptonized which can be seen as the positive value of  the  phase  lag.  We  didn't  consider  further  additional variations  of  parameter  because  of  bad χ 2 values.  So  we obtained variability observed in Ktin w.r.t. f s .  \nOn the basis of radiative mechanisms, Garg et al. [29] tries to understand the origin of the variability, like QPOs and   BBN. It  has  been  successfully  incorporated  in  sources  like  GRS 1915+105 [29], MAXI 1535-571 [30], H 1743-322 [31] and the 4U 1608-52 [32] to explain the energy variability in these sources. χ 2 /dof  \nIn  order  to  incorporate  this  technique,  we  fit  the  model  as formalized by [29] in rms and phase lag spectra. The relation between the phase lag and the time lag can be given as: time lag  is  equal  to  phase  lag/2πf,  where  f  is  the  peak/central frequency which is usually in millisecond (ms).  \nWe started with the simple scenario where we are changing the  inner-disk  temperature  (kTin)  and  fractional  scattering (fs) with some time-delay with respect to the fs.  \nFig.3. (left): PDS fit and (right): the energy dependent temporal modelling of fractional r.m.s. and phase lag of the representative segment FL1 in top and bottom panel, respectively.  \n<!-- image -->  \nTABLE  1.  BEST-FIT  PARAMETERS  OF  SPECTRAL  ANALYSIS  AND  ENERGYDEPENDENT TEMPORAL MODELING", 'V. CONCLUSION': "In  this  work,  we  have  used  the  AstroSat  observation  to comprehend  the  source  GX  9+9's  timing  and  spectral characteristics, which are as follows:  \n- 1)  We perform spectral analysis using the SXT and LAXPC simultaneous  data.  We  determined  the  source's  total unabsorbed  flux  in  the  0.01-100  keV  band,  observing  an increase from FL1 to FL3. The maximum flux reached 7.30 × 10⁻⁹ ergs s⁻¹ cm⁻², and is comparable to 7.8 × 10⁻⁹ ergs s⁻¹ cm⁻² reported by [12] in the 0.1-100 keV range.\n- 2)  Based  on  the  best-fit  spectral  parameters,  the  source's average  estimated  Rin  is  around  16.54±1.78  km.  Which  is relatively  consistent  to  the  previously  reported  estimated value of 27±4 km by Iaria et al [12], where they considered θ as ~43 ° and a distance of 5 kpc.\n- 3)  Based  on  the  variation  in  spectral  parameters  with increasing  X-ray  flux,  it  is  suggested  that  the  source  is transitioning  towards  a  softer  state.  This  is  indicated  by  a slight decrease in kTe and an increase in Tin across the FLs.\n- 4)  We  also  conducted  the  timing  analysis  using  the  high timing  resolution  of  LAXPC.  We  detected  BBN-like variability in the PDS centering at ~0.1 Hz, and we further modeled  the  energy-dependent  temporal  properties  to investigate the radiative origin of the obtained variability.\n- 5) Based on the formalism presented by Garg et al. [29], we find  that  fractional  scattering  and  the  change  in  inner-disk temperature are the causes of the obtained broad-band noise variability.  \nThis  work  is  constrained  due  to  poor  data  quality  of  the source. GX 9+9 is not a well-studied source; accordingly, further  research  into  the  source  is  necessary,  and  a  variety  of mission observations will be beneficial in order to get a better understanding of the source.", 'ACKNOWLEDGMENT': 'This work has used the LAXPC and SXT instruments data of AstroSat mission of ISRO. We thank the LAXPC and the SXT POC at TIFR, Mumbai, for providing the data via the ISSDC data  archive  and  the  necessary  software  tools.  Authors acknowledges the academic visits to Inter-University Centre for  Astronomy  and  Astrophysics  (IUCAA),  Pune  for  its hospitality and fruitful discussion with the eminent scientists and  researcher.  B.  Sarkar  also  acknowledge  the  visiting associateship programme of IUCAA. Author S. Bhattacherjee acknowledge the financial support of DST-INSPIRE (Grant. No.: DST/INSPIRE  Fellowship/[IF220164]) fellowship, Ministry  of  Science  and Technology,  Government  of  India. Finally, we would like to acknowledge the anonymous referee for their valuable feedback, which significantly enhanced the quality of the paper.', 'REFERENCES': "- [1] Bradt, H., Naranan, S., Rappaport, S., and Spada, G., 'Celestial Positions of X-Ray Sources in Sagittarius', The Astrophysical Journal, vol. 152, IOP, p. 1005, 1968. doi:10.1086/149613.\n- [2] Hertz, P. and Wood, K. 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