Accretion Flow Properties of GRS 1716-249 during its 2016-17 'failed' Outburst
Kaushik Chatterjee, Dipak Debnath, Debjit Chatterjee, Arghajit Jana, Sujoy Kumar Nath, Riya Bhowmick, Sandip K. Chakrabarti
aa r X i v : . [ a s t r o - ph . H E ] F e b Accretion Flow Properties of GRS 1716-249 during its − ‘failed’ Outburst Kaushik Chatterjee , Dipak Debnath ∗ • Debjit Chatterjee • Arghajit Jana • Sujoy Kumar Nath , Riya Bhowmick , Sandip K. Chakrabarti Abstract
In 2016 −
17, the Galactic transient black hole candidateGRS 1716-249 exhibited an outburst event after a long pe-riod of quiescence of almost 23 years. The source remainedin the outbursting phase for ∼ / XRT and As-troSat / LAXPC data. From the nature of the variation ofthe spectral and temporal properties, we find the source re-mains in hard state during the entire outburst. It never hada transition to other states which makes this event a ‘failed’outburst. An absence of the softer spectral states is consis-tent with the class of short orbital period objects, where the
Kaushik Chatterjee, Dipak DebnathIndian Centre For Space Physics, 43 Chalantika, Garia Station Road,Kolkata, 700084, Indiaemail (Dipak Debnath): [email protected] ChatterjeeIndian Institute of Astrophysics, Koramangala, Bengaluru, Karnataka560034Arghajit JanaPhysical Research Laboratory, Navrangpura, Ahmedabad 380009, IndiaSujoy Kumar Nath, Riya Bhowmick, Sandip K. ChakrabartiIndian Centre For Space Physics, 43 Chalantika, Garia Station Road,Kolkata, 700084, India Indian Centre For Space Physics, 43 Chalantika, Garia Station Road,Kolkata, 700084, India Indian Institute of Astrophysics, Koramangala, Bengaluru, Karnataka560034 Physical Research Laboratory, Navrangpura, Ahmedabad 380009, India source belongs to. From the spectral fit, we also estimatethe probable mass of GRS 1716-249 to be in the range of4 . − . M ⊙ or 5 . + . − . M ⊙ . Keywords
X-rays: binaries – stars: black holes – stars: individual(GRS 1716-249) – accretion, accretion disc – shock – radi-ation
Stellar-mass black holes (SBHs) are one of the most fas-cinating astronomical objects to study especially in X-ray, γ -ray. Black holes (BHs) are considered to be identifiedwhen the accretion flows around them emit radiations withspectra consistent with the black hole boundary conditions.Accretion disk are formed around the BHs when they ac-crete matter from the binary companion(s) through Roche-lobe overflow or wind. High energy radiation bears moreinformation about the compact objects as they are emittedfrom closer radius of the accretion disk. Some of the stel-lar mass BHs are transient in nature, and show outbursts ina gap of months to years. An outburst is generally consid-ered to be triggered, when rise in viscosity at the outer-edgeof the disk occurs (Chakrabarti 1996; Ebisawa et al. 1996).According to Chakrabarti and his collaborators (Chakrabartiet al. 2019; Bhowmick et al. 2020), accreted matter fromthe companion first piles up at the far location (within La-grange point L1), known as the pile-up radius ( X p ) insidethe Roche lobe. Due to the accumulation of large amountof matter at X p , viscosity rises and crosses its critical valueto trigger an outburst. During an outburst, a BH generallypasses through four di ff erent spectral states. They are hardstate (HS), hard intermediate state (HIMS), soft intermediatestate (SIMS) and soft state (SS) (see, Remillard & McClin-tock 2006; Nandi et al 2012). Normally, when an outburststarts, it begins in the HS. Then as the luminosity increases, it goes to the HIMS and then to SIMS. Finally it moves tothe SS when luminosity of the source is the maximum. Thisis known as the rising phase of the outburst. Then, the lu-minosity starts to decrease slowly to the minimum and thesource transits back to the HS in the reverse cycle. Thisis known as the declining phase of the outburst. In short,the spectral state transition of a BH takes place in the fol-lowing sequence to form a hysteresis loop: HS (rising) → HIMS (rising) → SIMS (rising) → SS → SIMS (declining) → HIMS (declining) → HS (declining).Depending upon the nature of outbursts, transient blackhole candidates (BHCs) show two types of outburst, such astype-I and type-II (Debnath et al. 2017). Those outbursts,where all four canonical spectral states are observed in theabove mentioned sequence, are known as type-I or classicaloutburst. If any outburst does not go to softer states (SIMS,SS), it is termed as type-II or harder type of outburst. Thelater outbursts are also known as ‘failed’ outbursts. Each ofthese states are defined based on the spectral and temporalproperties. Hardness intensity diagram (HID; Belloni et al.2005) and accretion rate ratio intensity diagram (ARRID;Jana et al. 2016) correlate the spectral and temporal proper-ties during various spectral states. The radiation spectrum ofa BH is defined by a multicolor thermal black body or diskblack body (DBB) and a non-thermal power-law (PL) com-ponent. While harder states (HS, HIMS) are dominated bythe non-thermal high energy radiations, the softer (SIMS,SS) states are dominated by thermal black body radiation.Quasi periodic oscillations (QPOs) are one of the most com-mon features of a stellar mass black hole (SBH). Low fre-quency type C QPOs (van der Klis 2005) are most commonwhich are generally observed in HS and HIMS (McClintock& Remillard 2005). There are also the existence of sporadictype (A and B; Casella et al. 2005; van der Klis 2005) lowfrequency QPOs (LFQPOs). They generally show mono-tonic increase and decrease in frequency in rising and de-clining phases respectively. In SS, generally no QPOs areseen (Nandi et al. 2012; Debnath et al. 2010, 2013).Over the years, various models were introduced to un-derstand physics of accretion around the BHs. Bondi flow(Bondi 1952), Standard disk model (Shakura & Sunyaev1973), Thick disk model (Paczynski & Witta 1980) are a fewof them. These models could explain the radiation spectraof a BHC successfully to some extent. However, they allwere more of a special solution of a general picture. Thesoft component in the BH spectra is, as mentioned before,the black body radiation that comes from the Keplerian disk(Shakura & Sunyaev 1973) and the PL component comesfrom the hot Compton cloud (Sunyaev & Titarchuk 1980).In 1995, Chakrabarti and his collaborators came up with ageneral picture of accretion disk, namely the two componentadvective flow (TCAF) solution (Chakrabarti & Titarchuk1995, hereafter CT95; Chakrabarti 1997), which is a so- lution of radiation transfer equation considering both heat-ing and cooling e ff ects. In this TCAF model, there are twotypes of accretion flows: one is the high viscous, high an-gular momentum Keplerian matter, another one is the lowviscous, lower angular momentum sub-Keplerian compo-nent. According to this model, the sub-Keplerian compo-nent, being less viscous, moves faster than the Keplerianone and forms an axisymmetric shock close to black holewhen the centrifugal force roughly becomes comparable tothe gravitational force acting on it. In the post-shock loca-tion as matter slows down and moves in a sub-sonic speed,matter starts to pile up and becomes hot. This post-shockpu ff ed-up matter acts a ‘hot’ Compton cloud as of Sunyaev& Titarchuk (1980), known as the CENtrifugal pressure sup-ported BOundary Layer (CENBOL). The soft photons fromthe Keplerian disk contribute to the soft multicolor thermalDBB part of the spectra. A fraction of these soft photons areintercepted by the CENBOL and are inverse-Comptonizedmultiple times by the ‘hot’ electrons to become higher en-ergy photons before they emit from the CENBOL. TheseComptonized photons contribute to the non-thermal hard PLtail of the spectra.In general, at the beginning of an outburst, we see highdominance of the PL component. When an outburst is trig-gered due to a sudden rise in viscosity at the pile up radiusi.e., at the outer disk, both types of matter start to move to-wards the BH after forming accretion disk (Ebisawa et al.1996; Chakrabarti et al. 2019). As discussed before, beinglow viscous and low angular momentum, the sub-Keplerianmatter moves closer to the BH much faster (roughly in afree fall time) than Keplerian component (moves in viscoustime), and dominates at the beginning of an outburst. We seepresence of a larger CENBOL. The source stays in HS dur-ing this phase of the outburst as sub-Keplerian matter dom-inates. The Keplerian component is referred to as the diskrate ( ˙ m d ) while the sub-Keplerian component is referred toas the halo rate ( ˙ m h ) in the TCAF model. As outburst pro-gresses, more and more Keplerian matter comes into the pic-ture to increase cooling rate, resulting shrinking of the CEN-BOL size. In this phase, we see the presence of the interme-diate (HIMS and SIMS) spectral states. We observe softspectral state, when CENBOL cools down completely dueto higher dominance of the Keplerian matter. The decliningphase starts, when viscous e ff ect at the outer edge is turnedo ff . This reduces supply of matter from the pile-up radius.In this phase, we see spectral states in the reverse sequence(SS → SIMS → HIMS → HS) as supply from the ˙ m d reduces ina faster rate compared to the ˙ m h . Debnath and his collabo-rators have successfully implemented this TCAF solution asa local additive table model in HEASARC’s spectral analy-sis software package xspec to fit BH spectra (Debnath et al.2014; 2015a). The model requires supply of initial guess ofthe four basic flow parameters: (i) Keplerian disk rate ( ˙ m d in ˙ m Edd ), (ii) sub-Keplerian halo rate ( ˙ m h in ˙ m Edd ), (iii) shocklocation ( X s in Schwarzschild radius r s ), which is the bound-ary of the CENBOL, (iv) compression ratio ( R ), which is theratio of the matter densities of the post to pre shock flows( R = ρ + /ρ − ), other than (v) mass of the BH ( M BH in M ⊙ )and (vi) normalization ( N ).In the HS, we generally see presence of a strong shock(higher R ) at a larger X s . Since the QPO frequency is in-versely proportional to the location of the shock ( ν qpo ∝ X − / s ; Chakrabarti & Manickam 2000), we observe lowerfrequency QPOs in the HS. In the rising phase, as theoutburst progresses, shock moves inward with reducingstrength as post-shock cooling rate increases with increasing˙ m d . We see monotonically increasing frequency of the gen-erally observed type-C QPOs. On the HIMS to SIMS tran-sition day, shock becomes weaker ( R ∼
1) and we see high-est frequency of the evolving type-C QPOs. These evolvingQPOs are generally formed due to the resonance shock os-cillation when cooling time scale roughly matches with theinfall time scale (Molteni, Sponholtz & Chakrabarti 1996;Chakrabarti et al. 2015). In the SIMS, generally type-B or AQPOs are observed sporadically on and o ff . The origin of theSIMS QPOs are (i) due to the weak resonance of a weaklyresonating CENBOL (for type-B) or a shockless centrifu-gal barrier (for type-A); or (ii) due to non-satisfaction of theRankine-Hugoniot (R-H) conditions to form a stable shock(all types). Recently, Chatterjee et al. (2020) observedpresence of type-C QPOs in the SIMS of MAXI J1535-571 (using AstroSat LAXPC data), originating due to non-satisfaction of the R-H conditions. No QPOs are observedin SS. In declining intermediate and hard spectral states, wealso see presence of the low frequency QPOs. Similar to therising HS and HIMS, in the declining HS and HIMS, mono-tonically evolving type-C QPOS (with reducing frequenciesas shock moves outward) are also generally seen. Jets areassociated with the hard and intermediate spectral states.CENBOL acts as the base of the jets. Jets are more active inthe intermediate spectral states. Compact jets are generallyobserved in the harder spectral states (HS and HIMS), whilediscrete or blobby jets could be seen in the SIMS. Due to thequenching of the CENBOL in the SS, similar to no QPOs,no jet is observed (Chakrabarti & Nandi 2000 and referencestherein).Analysis with TCAF model provides us a great under-standing about the source’s intrinsic property (i.e., mass)along with its spectral and temporal properties. Spectral fitwith the TCAF model, directly provide us information aboutthe flow dynamics via two accretion rates and two shock pa-rameters. If mass of the BH is not well known, one canalso estimate its probable value from spectral fit by keepingit as a free parameter. The normalization depends on thesource’s distance and inclination, which does not changesignificantly during an outburst. That is why N generally stays almost constant, or, varies in a narrow range during anoutburst. Because of the non-inclusion of the jet phenom-ena in the current version of the TCAF model fits file, N varies in a broad range in presence of jets. It can vary ina broad range if other phenomena like disk precision, bulkmotion Comptonization, etc. are present. Recently, afterits (TCAF) inclusion as an additive table model in XSPEC(Debnath et al. 2014, 2015a), spectra of many BHC havebeen successfully fitted and described by our group (Deb-nath et al. 2015a,b,2017,2020; Mondal et al. 2014, 2016;Chatterjee et al. 2016,2019; Jana et al. 2016,2020a,b; Chat-terjee et al. 2020, Shang et al. 2019). Estimation of massof these sources has also been done using the TCAF model.In our group’s recent papers, X-ray contribution only fromjets / outflows are also estimated using the method as de-scribed by Jana, Chakrabarti & Debnath (2017, hereafterJCD17).The well known Galactic transient BHC GRS 1716-249 (also known as GRO J1719-24; Bharali et al. 2019)is an X-ray transient, which was discovered in 1993 byCGRO / BATSE and Granat / SIGMA telescopes (Ballet et al.1993; Harmon et al. 1993). This source is located at a dis-tance of 2 . ± . ∼ . M ⊙ . According to them,it has a K-type companion star of mass ∼ . M ⊙ with anorbital period of ∼ . ∼ . × cm − (Tanaka 1993). Since itslast outburst in 1993, it was in a quiescence phase. In 2016,it became active and showed an outburst. On 2016 Decem-ber 18, it was detected by MAXI (Masumitsu et al. 2016;Negoro et al. 2016). According to Negoro et al. (2016),during December 2016, the source had a photon index ( Γ ) ∼ . ± .
06, which suggests that the source was in harderstates during that time. Using Chandra satellite data, Milleret al. (2017) reported that during February 2017, Γ still had alow value ( ∼ . −
17 outburst ofGRS 1716-249 as ‘failed’ outburst.In this paper, we intend to study the accretion flow prop-erties of the BHC GRS 1716-249 during its recent 2016 − + PL) and physicalTCAF models. The paper is organized in the following way.In §2, we discuss about the data reduction and data analy-sis method. In §3, we show the results from the spectral and temporal analysis. Finally, in §4, we make discussions aboutthe results and try to draw some conclusions from our workin §5.
Swift monitored the 2016 −
17 outburst of the BHC GRS1716-279 roughly on a daily basis, starting from 2016 Jan-uary 28, ( ∼ MJD 57781.00) till the end of the outburst. How-ever, the outburst actually started in December. On 2016 De-cember 18, MAXI detected this outburst (Masumitsu et al.2016; Negoro et al. 2016). For our work, we make use of thearchival Swift / XRT (1 −
10, 0 . −
8, 0 . − −
10 keV),MAXI / GSC (2 −
10 and 6 −
20 keV) and Swift / BAT (15 − −
30 keV) data. Since we did not find the archival(both in the HEASARC and ASDC) Swift data before 2017January 28, we make use of the on demand MAXI / GSCdata from 2016 January 28. For broadband analysis, wealso make use of the AstroSat / LAXPC data from the ISSDCarchive and NuSTAR data from HEASARC archive. Thedata reduction for di ff erent satellites / instruments are doneusing the methods mentioned in the following sub-section.2.1 Data Reduction Swift / XRT
We make use of the windowed timing (WT) mode datafor XRT instrument. We use the xrtpipeline command toproduce cleaned event files from the level-1 uncleaned data.For each cleaned event file, we select and save a circular re-gion of 30 arcsec around the source in ds // / analysis / xrt). After producing thespectra, we make use of the grppha task with a minimum of10 counts / bin. The default time bin in the XRT event filesis 1 sec . For our analysis to find LFQPOs, we extract lightcurves of bin size 0 . sec and for that, we use the ‘ set bin-size 0.01 ’ command in XSELECT. Swift / BAT
For the reduction of BAT archival data, we follow themethods mentioned in BAT analysis thread (https: // / analysis / bat).At first, we use bateconvert to make proper energy conver-sion from the already present event file. Next, batbinevt is used to produce proper detector plane image (DPI). Af-ter that, we use bathotpix to define hot pixels and bat-maskwtevt to apply mask weighting. With inclusion of themask weighting file to the batbinevt command again, weproduce the spectra files. Then, we use batphasyserr to add systematic error to the spectra files. After that, ray tracingcorrection is done by using the batupdatephakw command.At last, we use batdrmgen to generate the response file. Wehave not made any light curves from the BAT data. MAXI / GSC
The MAXI / GSC spectra files are available on demand inthe website (http: // maxi.riken.jp / mxondem) and we down-loaded suitable spectra files which are close to or on the XRTdata dates. The on-demand process is described in Matsuokaet al. (2009). AstroSat / LAXPC
For extracting LAXPC data, we use publicly availablecode (http: // / ∼ antia / laxpc.html). We performthe data reduction process to generate level-2 files to cre-ate source and background spectra for LAXPC10 unit (unit1) using all anode layers. First, we run the ‘ laxpcl1.f ’ pro-gram to process multiple orbits of the level-1 data and pro-duce event files, light curves, spectra, good time intervals(GTI) in both the ASCII and FITS format. Then we runthe ‘ backshiftv3.f ’ program to make background correctionto the light curves and spectra and also to identify the re-sponse file, to be used in the spectral analysis. We also ex-tract 0 .
01 sec light curves for QPO analysis.
NuSTAR / FPMA
For getting broad energy information (3 −
79 keV), weuse FPMA instrument data of the NuSTAR satellite. Thedata reduction process is done using the NuSTAR data anal-ysis software
NuSTARDAS (version 1.4.1). We first run theNuSTAR pipeline using nupipeline command using the un-cleaned stage-I data providing input, output directories andsteminputs. It produces stage-II cleaned event files. Us-ing XSELECT, we read the cleaned event files and save thesource and background region files. Now, using those re-gion files, we use the nuproducts command to extract stage-III data to produce background subtracted spectra. We alsomade use of the grppha task for grouping the data with aminimum of 30 counts / bin.2.2 Data Analysis The daily average MAXI / GSC (2 −
10 keV) and Swift / BAT(15 −
50 keV) light curves are downloaded from the re-spective public archives. Those light curves are convertedin mCrab unit using proper conversion factors. For GSC,1 mCrab is equal to 0.00282 photons cm − s − in 2 −
10 keV,while for BAT, 1 mCrab equals 0.000220 counts cm − s − in15 −
50 keV. We also estimate the count rates in 0 . − −
10 keV energy bands from XRT light curves.
For QPO analysis, we generate the power density spectra(PDS) by running the powspec task of the XRONOS pack-age. We extract QPO information from both the XRT andthe LAXPC data using 0 . sec time binned light curves.For XRT, we use 1 −
10 keV light curves, while for LAXPC,we use 3 −
80 keV light curves. Geometrical rebinning con-stants of ‘ − .
02’ or ‘ − .
05’ (as needed) has been used. Tofit the QPO profiles, we make use of the Lorentzian model.This gives us the fitted value of QPO frequencies ( ν qpo ), itswidth ( △ ν ) and power. With these, we calculate the qual-ity factor ( Q = ν qpo / △ ν ), rms (%) value, which help us toclassify the nature (type) of the QPOs.We have also produced LAXPC light curves’ data in fourdi ff erent energy bands, which are 3 −
20 keV, 20 −
40 keV,40 −
60 keV and 60 −
80 keV respectively. By generating thelight curves in the mentioned energy bands, we have pro-duced PDS for those ranges to see the energy dependence ofQPOs.
We have fitted spectra using XRT, GSC, BAT, LAXPC, andNuSTAR data in di ff erent energy ranges. Data of a totalof 39 observations are fitted using both the phenomenologi-cal disk blackbody plus power-law (DBB + PL) and physicalTCAF model. 10 observations are fitted using only XRTdata in 0 . − . −
20 keV andonly 2 observations are fitted using XRT, GSC and BATdata in the energy range of 0 . −
30 keV. Since, there is asignificant noise in the BAT data beyond 30 keV, we haveonly taken them in the 15 −
30 keV range. For broadbandfitting, we have used LAXPC and NuSTAR and combinedthem with the XRT data (of same MJDs). Using combinedXRT-LAXPC data, we have fitted 2 observations (out of thetotal 39 studied observations) in 0 . −
80 keV energy band onMJDs ∼ . −
77 keV energy band on MJDs ∼ TBABS (Wilms, Allen & McCray 2000) model to account for theabsorption in the interstellar medium. We use
TCAF as anadditive table model along with the multiplicative
TBABS model. 1% systematic error is used for all our spectral anal-ysis except for the AstroSat / LAXPC data, for which we use2% systematic error (Antia et al. 2017; Sreehari et al. 2019).
We have studied the accretion flow properties of the sourcebased on the temporal and spectral analysis. Because ev-ery spectrum is fundamentally dependent on the mass of the black hole which controls the thermodynamic quantities ofa disk, it is possible to estimate the mass of the black holefrom each spectrum if the fit is proper. TCAF fits the data inabsolute sense up to a normalization (a function of distance).Thus we have also obtained the probable mass of the sourcefrom TCAF model while fitting of the spectra. Our resultsare presented below.3.1 Temporal PropertiesHere, we discuss about the timing properties (light curves,hardness-ratios, QPOs) and their evolution over the durationof the outburst.
In Figure 1, we show the entire duration of the 2016 − ∼ ∼ −
10 keV MAXI / GSC (online red)and 15 −
50 keV Swift / BAT (online blue) fluxes from MJD ∼ fast rise slow decay (FRSD) and slow rise slow decay (SRSD). From GSC andBAT light curve profiles in Fig. 1(a), we notice that boththe fluxes increase significantly in a very short time of theinitial rising phase of the outburst. For BAT flux (onlineblue), it was ∼ ∼ ∼ ∼ ∼ ∼ ∼ ∼ ∼ ∼ ∼ . − −
10 keV (online blue). The 4 − . − to show the full variation of XRT count rates. The countrates are estimated from those observations for which wehave performed spectral analysis. Hardness ratio (HR) is defined as F H / F S , where F H and F S represent the hard and soft X-ray fluxes (or the count rates)respectively. It provides us with a quick look on evolution ofthe flow dynamics of the source, as it is assumed that originof the F H is non-thermal and F S is thermal processes. But,from the physical point of view, there is always a chanceof mixing up of the thermal and non-thermal photons while F H and F S are defined as photon flux or count rates into twofixed energy bands. In the harder states (HS & HIMS), theHR is generally high, when the contribution from the hard(non-thermal) component dominates over the soft (thermal)component. In softer states (SIMS & SS) it becomes lowwhen the soft component takes over hard component.In Figure 1, we have shown two HRs using the ratio of15 −
50 keV BAT hard flux to 2 −
10 keV GSC flux (HR1;panel b) and 4 −
10 keV XRT to 0 . − ∼ ∼ ∼ As described in §2, we have made use of the 0.01 sec timebinned Swift / XRT (in 1 −
10 keV) and AstroSat / LAXPC (in3 −
80 keV) light curves to produce PDS using XRONOSpackage. We show a PDS (in 0 . −
10 Hz) in Fig. 2.The continuum of PDS (Fig. 2) is fitted using combina-tion of Lorentzian and power-law profiles. Using Lorentzianmodel, we have fitted all the light curves’ data which showQPO nature and extracted their frequencies. We have founda total of 6 days (from both the XRT and LAXPC data)on which QPO was present. In Fig. 3, we show the QPOfrequencies of these 6 days along with their evolution with time during the outburst. We see monotonic increase ofQPO frequency during the outburst’s rising phase. On MJD57781.00 (2017 January 28), we see the presence of the firstQPO with ν qpo = .
633 Hz. Then, ν qpo increases to 0.675Hz on MJD 57799.68 (2017 February 15). On this day, dueto noise (i.e., low signal to noise ratio), we have not foundany QPO nature in the XRT data. Then ν qpo kept on increas-ing to reach to a value of 1.213 Hz. This is also from theLAXPC data. We have not found any sign of QPOs in thedeclining phase of the outburst. The evolution is shown inFigure 3. The detailed QPO information is provided in Table1. According to Chakrabarti et al. (2015), in the TCAFmodel, when the cooling timescale (time, the soft disk pho-tons take to cool the CENBOL in the process of inverse-Comptonization or by synchrotron cooling if magnetic fieldis strong) roughly ( ∼ Using the AstroSat / LAXPC data of 2017 February 15 (MJD57799.68) and 2017 April 06 (MJD 57849.69), we studiedenergy dependent nature of the observed QPOs. We haveproduced the power density spectra (PDS) in four energybands: 3 −
20, 20 −
40, 40 −
60 and 60 −
80 keV to checkthe energy dependence of the QPOs. In Fig. 4, we showmodel fitted PDS in between 0 . −
10 Hz in the above fourenergy bands for the data observed on 2017 April 06 (MJD57849.69; obs id = = ∼ . ∼ . −
20 keV and 20 −
40 keV) energy bands (see, Fig. 4(a-b)),whereas in 40 −
60 keV band, we see only the primary QPO.In the 60 −
80 keV band, signatures of the primary QPObecomes weaker. But, in the the two higher energy bands( >
40 keV), we see the signature of another low frequencyQPO at ∼ .
62 Hz. This low frequency QPO is more promi-nent in the 60 −
80 keV band. From the Lorentzian fittedQPOs in the PDS, we have estimated the rms of the primaryQPO in the 3 −
20, 20 −
40 and 40 −
60 keV energy bands. Adecreasing trend of the rms of the primary QPO is observedas we moved toward higher energy bands, this means that
QPO becomes fainter as we move towards the higher energyband. The QPO rms is found ∼
12 percent in 3 −
20 keV, ∼
11 percent in 20 −
40 keV, and ∼ −
60 keV.These results are presented in Table 1 (bottom panel).3.2 Spectral PropertiesThe study of the spectral properties of an outburst is an im-portant aspect to get an idea about the source and its evo-lution during the outburst. First, we have fitted 39 obser-vations with the
DBB + PL model, using mainly Swift / XRT,MAXI / GSC and Swift / BAT data. The
DBB + PL fitting givesa rough approximation about the spectral states. To un-derstand the physical picture of accretion flow properties,we have refitted those same observations with the physical TCAF model. This shows us the evolution of the accretionflow parameters and also gives us the estimation of the massof the source. This will be discussed in a di ff erent subsec-tion. To check consistency of our result, we have fitted twoobservations in broader bands with each of NuSTAR / FPMAand AstroSat / LAXPC data by combining them with simul-taneous Swift / XRT data. We have fitted XRT + NuSTAR andXRT + LAXPC data in 0 . −
77 keV and 0 . −
80 keV energybands respectively. We show detailed spectral analysis re-sults in the following section. In Fig. 5, we show four
TCAF model fitted spectra using di ff erent spectral data in di ff er-ent energy bands. In panel (a), we show the spectra usingXRT + GSC + BAT instruments in the 0 . −
30 keV band, in (b)XRT + GSC spectra in 0 . −
20 keV is shown. In Fig. 5(c-d),we show the fitted spectra in the broader bands using simul-taneous XRT + NuSTAR (0 . −
77 keV) and XRT + LAXPC(0 . −
80 keV) data respectively.We show the variation of
TCAF and
DBB + PL model fit-ted parameters in Figs. 6 and 7. In Figure 6, we showthe variations of TCAF model fitted (a) total accretion rate( ˙ m d + ˙ m h ), (b) disk rate ( ˙ m d ), (c) halo rate ( ˙ m h ) and (d) ac-cretion rate ratio (ARR), which is defined as the ratio of halorate to discrete ( ˙ m h / ˙ m d ). Both of these rates are in the unitof Eddington rate ( ˙ m Edd ). We show the shock parameters( X s and R ) of TCAF model in Fig. 7(a-b). The
DBB + PL model fitted inner-disk temperature ( T in ) and photon indexof power-law ( Γ ) are shown in panel c-d of Fig. 7.We notice that from the beginning of our analysis date upto MJD 57827.78 (2017 March 15), ˙ m h remained at a nearlyconstant value of ∼ .
48. Then it decreased by a very smallamount to reach to a value of 0 .
45 on MJD 57878.74 (2017May 05) and then it gradually decreased and reached a valueof 0.20 on MJD 57975.27 (2017 August 11). From the be-ginning, ˙ m d was gradually increasing from a value of 0.23and reached its maximum value of 0.37 on MJD 57857.02(2017 April 14). The total flow rate ( ˙ m d + ˙ m h ) also showedsimilar variation with ˙ m d . The total rate was 0 .
72 on the firstday of our observation and after that it gradually increased, and reached its peak on MJD 57857.02. After that, both thedisk rate and total rate started decreasing and reached theirminimum ( ∼ .
12 & 0 .
32) on MJD 57975.27. The shocklocation was far away (Fig. 7a) at a distance of ∼ r s on the first day of our observation on MJD 57781.00 (2017January 28). After MJD 57786.73 (2017 February 02; onwhich it became ∼ r s ), and it started decreasing gradu-ally and attained its minimum of ∼ r s on MJD 57796.55(2017 February 12). It remained at this minimum distancefor some time till MJD 57857.02 (2017 April 14) before in-creasing gradually. On the last day (MJD 57975.27; 2017August 11) of our analyzed period, the shock ( X s ) movedaway to a distance of ∼ r s . The compression ratio (ratioof post to pre shock density; ρ + /ρ − ; Fig. 7b) has varied be-tween 2 . − .
4. The inner-disk temperature ( T in ) was ∼ . ∼ .
84 keV onMJD 57790.46 (2017 February 06) and then gradually de-creased to ∼ .
53 keV on MJD 57857.02. Then it againincreased to ∼ .
70 keV on MJD 57884.06 (2017 May 11)after which it decreased gradually. The power-law photonindex ( Γ ) varied between 1 . − .
76. On first observation Γ was low ( ∼ . ∼ .
76) on MJD 57857.02, the day onwhich the total rate was maximum. It then started decreas-ing and became ∼ .
42 on MJD 57975.27 (2017 August 11).As we discussed before, from our temporal results onecould conclude that the source might have gone through theHS and HIMS. However, our spectral results do not stronglysupport the presence of the HIMS. We see a complete dom-inance of the halo rate ( ˙ m h ) over the disk rate ( ˙ m d ) through-out the entire duration of our analysis. The photon index( Γ ) never became > . −
17 outburst.We also show the variations of the hydrogen column den-sity ( n H ) (Fig. 8a), which is found to be between 0 .
37 and0 . × cm − using the TBABS model. This result is ingood agreement with Tanaka (1993).As we mentioned earlier that the normalization parameter( N ) of the TCAF model is a constant multiplicative factor, tooverlay the observed spectra to the theoretical spectra of theTCAF model fits (Molla et al. 2016, 2017). In our analysis,the variation of normalization ( N ) is shown in Fig. 8(b),which varied in a range of 12 . − .
70. There is report onthe presence of radio jet during this outburst by Bassi et al.(2019). So, this broad range of variation of N is due to thepresence of radio jet. + PL’ model fits the spectral shape, there is no infor-mation about the mass. A physical model such as TCAF iscapable of extracting the mass, though the accuracy is re-stricted as the observed spectrum is a sum of radiation con-tributed from a large region of varied density and tempera-ture.To fit black hole spectrum, TCAF model needs to supplysix input parameters including mass ( M BH ) and normaliza-tion and the rest are related to the flow parameters. Whenwe fit a spectrum the TCAF model parameters after keepingall parameters as free, we get an estimation of the best fit-ted values for all those parameters. We keep mass as a freeparameter when it is unknown. While fitting the spectra ofGRS 1716-249, we obtained it to lie between 4 . − . M ⊙ from the fits. The uncertainty arises from non-uniformity inthe quality of the data and errors due to fitting. Our estima-tion of the probable mass of the source from the TCAF anal-ysis is 5 . + . − . M ⊙ (since 5 . M ⊙ is average of the modelfitted mass values). This is in good agreement with the pre-vious finding of Masetti et al. (1996), who estimated themass of the source as 4 . M ⊙ . In Figure 8(c), we show ourmodel fitted mass values throughout the entire analysis pe-riod of the outburst. The Galactic transient BHC GRS 1716-249 was monitoredin multi-wave band by Swift roughly on a daily basis start-ing from MJD 57781.00 (2017 January 28). The data ofthe initial rising phase of the 2016-17 outburst is missing asSwift started pointing the source few days after its discov-ery. MAXI also monitored the outburst. We have performedspectral analysis of GRS 1716-249 during its 2016 − / XRT (0 . − / GSC (6 −
20 keV) and Swift / BAT (15 −
30 keV).To study in the higher energy bands, we use two observa-tions of NuSTAR (on MJD 57850.60; 2017 April 07 and57853.69; 2017 April 10) and also two observations of As-troSat / LAXPC (on MJD 57799.68; 2017 February 15 and57849.69; 2017 April 06). Combining NuSTAR or LAXPCdata with simultaneous XRT observations, a broad energystudy is done in the range of 0 . −
77 keV and 0 . −
80 keV bands respectively. The spectral analysis is done usingboth phenomenological (DBB + PL) and physical (TCAF)models. The timing analysis is done mainly using XRT(1 −
10 keV) and LAXPC (3 −
80 keV) data.Low frequency QPOs are one of the most common phe-nomena in hard and intermediate spectral states of stel-lar mass BHCs. For QPO analysis, we have made useof 0 .
01 sec time binned light curves from both XRT andLAXPC data in 1 −
10 keV and 3 −
80 keV energy bands re-spectively. With Lorentzian model fitting, we have extractedthe centroid frequencies of the QPOs. Using XRT data,we have found QPOs in 4 observations on MJDs 57781.00(2017 January 28; obs. Id. = = = = . −
10 Hz. ThisFigure shows a QPO with a harmonic, which are fitted usingthe combination of Lorentzian and power-law models. Us-ing all the QPO information from both set of data, we showthat ν qpo increased monotonically in the rising phase (see,Fig. 3). We have not found the existence of QPOs in the de-clining phase. To find the origin of these QPOs i.e., they aredue to satisfaction of the resonance oscillation of the shockor not (see, Molteni et al. 1996; Chakrabarti et al. 2015),we calculated cooling time ( t c )and infall time ( t i ) scales ofthe post shock matter and found that their ratio ( t c / t i ) devi-ates largely from the unity. So, we conclude that during theboth rising and declining phases of the outburst, resonanceshock condition was not satisfied. Possibly due to this, inthe declining phase of the outburst, we have not observedany QPO.We have also shown the energy dependence of powerdensity spectrum using AstroSat / LAXPC data. We have ob-served the presence of both the fundamental QPO and theharmonic appear in energies <
40 keV, while there is nosign of harmonic above 40 keV. The QPO signature becomesweaker in the PDS above 60 keV. It is evident from the Fig-ure 4(a-d) that as the energy is increasing the QPO shapeis changing along with reducing rms. With increasing en-ergy, the QPO rms is decreasing while the broadband noiseis increasing. The disappearance of QPO shape in high en-ergy (above 60 keV here) in the LAXPC data could be dueto the reason that there is presence of low number of pho-tons in high energy. It also could be due to the fact that the detector e ff ective area decreases to 4100 − cm (Antiaet al. 2017) in the energy range of 60 −
80 keV. This wasalso reported by Sreehari et al. (2019) for the BHC MAXIJ1535-571. Interestingly, we see one more low frequencyQPO ∼ .
62 Hz in the energy range above 40 keV. ThisQPO becomes more significant in the 60 −
80 keV band ascompared to 40 −
60 keV band. This has an rms of ∼ . −
80 keV band.This could be one more local oscillationin the higher radius.From the spectral analysis with the TCAF model, we seethat at the beginning of the outburst, the supply of both thehigh viscous Keplerian and low viscous sub-Keplerian mat-ter stays low. According to the TCAF model, due to higherradial velocity of the sub-Keplerian component, it movesmuch faster than the Keplerian component (moves in vis-cous timescale). The Keplerian component, having high an-gular momentum forms the disk, with sub-Keplerian mat-ter residing over it, forming the halo. This halo compo-nent forms the hot Compton cloud or CENBOL at the post-shock region. Due to inverse Comptonization, the soft pho-tons from the disk gains energy and produced the power-law tail in the observed spectrum. At the beginning of theoutburst, the shock was located far away ( ∼ r s ) and thecooling was ine ffi cient. As a result the shock was strong.The shock then gradually moved closer and reached ∼ r s after MJD ∼ + halo) rate was increased. Although the halo rate was decreas-ing from the start, it did not decrease that much during thisperiod of observations (from ∼ .
49 to ∼ . Γ ) was also on the lower side (1 . − .
66) ofits values, with T in decreasing from 0 .
74 keV to 0 .
58 keVgradually. The ARR (Fig. 6d) was also higher ( ∼ . − . ∼ r s after2017 April 07 (MJD 57850.37) for some days until 2017April 21 (MJD 57864.07). From MJD = = ffi ciency of cooling of the CEN-BOL decreased and the boundary i.e., X s started to moveoutward. On 2017 May 05 (MJD 57878.74), X s became ∼ r s and then moved away rapidly from the source. OnMJD = Γ ) of power-law modelwas on its highest value ( ∼ . ∼ . = X s continued to moveoutside and reached to a similar value ( ∼ r s ) as in thebeginning of the outburst. After MJD = Γ againbecame < . m d and ˙ m h further decreased,as the source progressed towards the quiescence. ARR didnot increase that much except only at the back end of theoutburst when it became ∼ . = −
17 outburst of GRS 1716-249 can be referred toas a harder type (type-II) or ‘failed’. According to Bharaliet al. (2019), the orbital period of the source is 14 . +
480 (Chatterjee etal. 2019). A similar presence of only HS during 2000 &2005 outbursts of the short orbital period ( ∼ . +
480 was noticed (see, Chatterjee etal. 2019; Debnath et al. 2020).We also estimated the probable mass of the BH ( M BH ),from our spectral analysis with the TCAF model. In TCAF, M BH is a model input parameter. Since, mass of GRS 1716-249 is not well known, while fitting spectra we kept M BH as free. We observed M BH in the range of the source in be-tween 4 . − . M ⊙ . The observed variation of our esti-mated mass is mainly due to instrumental and fitting errors.The flux from black body emission depends on the fourthpower of the temperature ( T ) of the Keplerian disk. So anysmall change in the value of T while fitting the black bodycomponent (which is possible due to poorly understood ab-sorption due to intervening medium) can lead to a significantchange in the estimated mass. Taking the average, we con-clude that the most probable mass of the BHC GRS 1716-249 is 5 . + . − . M ⊙ , which is in good agreement with theearlier findings (Masetti et al. 1996). We have done spectral and temporal analysis of the BHCGRS 1716-249 during its recent 2016 −
17 outburst. Tostudy outburst profile in di ff erent energy bands and hard-ness ratios, we used MAXI / GSC, Swift / BAT and Swift / XRTdata. The temporal analysis of the QPOs is done usingthe Swift / XRT and AstroSat / LAXPC data using powspec of XRONOS package. We have also studied energy de-pendent QPOs using the LAXPC data. The spectral analy-sis is done using Swift / XRT, MAXI / GSC, Swift / BAT, As-troSat / LAXPC and NuSTAR / FPMA data, using both the phenomenological DBB + PL and physical TCAF modelsseparately in
XSPEC . Depending on our detailed analysis ofGRS 1716-249 during 2016-17 outburst, we may summarizefollowing results -(i) The source showed low frequency QPOs during therising phase of the outburst. These QPO frequencies werefound to rise monotonically. QPOs were not originated dueto the resonance shock oscillation of the CENBOL.(ii) The nature of the QPOs are found to be energy de-pendent. We found that the fundamental QPO is absentabove 60 keV, while the harmonic is non-detectable above40 keV in the case of AstroSat / LAXPC data. As the energyincreases the rms decreases along with the increment of thebroadband noise.(iii) The 2016 −
17 is a ‘failed’ or harder type of outburstwhich did not go through the usual soft and intermediatespectral states. The source was observed only in the hardstate (HS) during entire period of the outburst. This non-observation of the softer spectral states is similar to whatwas observed in other short orbital period sources.(iv) The probable mass of the black hole was estimatedto lie in the range of 4 . − . M ⊙ or 5 . + . − . M ⊙ , from ourspectral analysis with the TCAF model. Acknowledgements
This work has made use of the archival XRT and BAT dataprovided by UK Swift Science Data Centre at the Universityof Leicester, MAXI GSC data provided by RIKEN, JAXA,and the MAXI team. We have also made use of LAXPCdata from Indian Space Research Organization’s (ISRO’s)successful operation of AstroSat mission. We have usedFPMA data from NuSTAR mission, a project led by Cal-tech, funded by NASA and managed by NASA / JPL. Wehave utilised the NuSTARDAS software package, jointly de-veloped by the ASDC, Italy and Caltech, USA.K.C. acknowledges support from DST / INSPIRE Fellow-ship (IF170233). Research of D.D. and S.K.C. is supportedin part by the Higher Education Dept. of the Govt. ofWest Bengal, India. D.C. and D.D. acknowledge supportfrom DST / SERB sponsored Extra Mural Research project(EMR / / / RES / / / References
Antia, H. M., et al. 2017, ApJS, 231, 10Armas Padilla, M., Munoz-Darias, T., 2017, ATel, 10236, 1Bhowmick, R., Debnath, D., Chatterjee, K., et al. 2020, ApJ (inpress) (arXiv:2102.02030)Ballet, J., Denis, M., Gilfanov, M., et al. 1993, IAU Circ., 5874Bassi, T., Del Santo, M., Motta, S. E., 2017, ATel, 10371, 1Bassi, T., Del Santo, M., et al. 2019, MNRAS, 482, 1587Belloni, T., Homan, J., Casella, P., et al. 2005, A&A, 440, 207Bharali, P., Chandra, S., Chauhan, J., et al. 2019, MNRAS, 487,3150Bondi, H., 1952, MNRAS, 112, 195Casella, P., Belloni, T., Stella L., 2005, ApJ, 629, 403Chakrabarti, S. K., Titarchuk, L., 1995, ApJ, 455, 623Chakrabarti, S. K. 1996, ApJ, 464, 664Chakrabarti, S. K., 1997, ApJ, 484, 313Chakrabarti, S. K., Manickam, S. G., 2000, ApJ, 531, L41Chakrabarti, S. K., Nandi, A., 2000, InJPB, 75, 1Chakrabarti, S. K., Mondal, S. Debnath, D., 2015, MNRAS, 452,3451Chatterjee, D., Debnath, D., Chakrabarti, S. K., Mondal, S., JanaA., 2016, ApJ, 827, 88Chatterjee, D., Debnath, D., Jana, A., Chakrabarti, S. K., 2019,Ap&SS, 364, 14Chatterjee, K., Debnath, D., Chatterjee, D., Jana, A., Chakrabarti,S. K., 2020, MNRAS, 493, 2452Debnath, D., Chakrabarti, S. K., Nandi, A., 2010, A&A, 520, A98Debnath, D., Chakrabarti, S. K., Nandi, A., 2013, ASR, 52, 2143Debnath, D., Chakrabarti, S. K., Mondal, S., 2014, MNRAS, 440,L121Debnath, D., Mondal, S., Chakrabarti, S. K., 2015a, MNRAS, 447,1984Debnath, D., Molla, A. A., Chakrabarti, S. K., Mondal, S., 2015b,ApJ, 803, 59Debnath, D., Jana, A., Chakrabarti, S. K., Chatterjee, D., Mondal,S., 2017, ApJ, 850, 52Debnath, D., Chatterjee, D., Jana, A., Chakrabarti, S. K., Chatter-jee, K., 2020, RAA, 20, 175della Valle, M., Mirabel, I. F., Rodriguez, L. F., 1994, A&A, 290,803Ebisawa, K., Titarchuk, L., Chakrabarti, S. K., 1996, PASJ, 48, 59Frank, J., King, A., Raine, D., Accretion Power in Astrophysics,2002, Cambridge University PressHarmon, B. A., Fishman, G. J., Paciesas, W. S., Zhang, S. N., 1993,IAU Circ., 5900Jana, A., Debnath, D., Chakrabarti, S. K., et al. 2016, ApJ, 819,107Jana, A., Chakrabarti, S. K., Debnath, D., 2017, ApJ, 850, 91Jana, A., Debnath, D., Chakrabarti, S. K., Chatterjee, D., 2020a,RAA, 20, 3Jana, A., Debnath, D., Chatterjee, D., Chatterjee, K., et al. 2020b,ApJ, 897, 3Lasota, J. P., 2001, The disc instability model of dwarf novae andlow-mass X-ray binary transients. NewAR, 45, 449Leahy, D. A., Darbro, W., Elsner, R. F., et al. 1983, ApJ, 266, 160Masetti, N., Bianchini, A., Bonibaker, J., della Valle, M. Vio R.,1996, A&A, 314, 123Masumitsu, T. et al., 2016, ATel, 9895, 1McClintock, J. E., Remillard, R. A. 2005, in Compact Stel-lar X-Ray Sources, ed. W. H. G. Lewin, & M. van der Klis(arXiv:astro-ph / This manuscript was prepared with the AAS L A TEX macros v5.2.2 F l ux ( m C r a b ) GSC (2-10 keV)BAT (15-50 keV) H R BAT/GSC C oun t s / s ec XRT (0.6-4 keV)XRT 4 × (4-10 keV) Day (MJD) H R (a)(b)(c)(d) Fig. 1
Variation of (a) mCrab converted 15 −
50 keV Swift / BAT (online blue) and 2 −
10 keV MAXI / GSC (online red) fluxes, (b) hardnessratio (HR) of BAT and GSC fluxes, (c) XRT count rate in 0 . − −
10 keV (online blue) and (d) hardness ratio of4 −
10 keV to 0 . − −
17 outburst of GRS 1716-249. Note that to scale with the 0 . − −
10 keV flux with a factor of 4. − . × − × − × − . P o w e r Frequency (Hz)
Fig. 2
Continuum (0 . −
10 Hz) fitted power density spectrum (PDS) using 0.01 s time binned 3 −
80 keV AstroSat / LAXPC light curvedata from the orbit 8238 on MJD 57849.69 (2017 April 6). Primary QPO with frequency 1.21 Hz is seen along with its harmonic at 2.42Hz. Day (MJD) Q P O F r e qu e n c y XRT LAXPC
Fig. 3
Evolution of QPO frequencies with time (Day in MJD). The black circular points are the ones estimated using Swift / XRT data andred diamond points are from AstroSat / LAXPC data. The ‘y’ axis is in units of ‘Hz’. − . × − × − × − . P o w e r Frequency (Hz) (a) − . × − × − × − . P o w e r Frequency (Hz) (b)20−40 keV − − . P o w e r Frequency (Hz) (c)40−60 keV − − − . P o w e r Frequency (Hz) (d)60−80 keV
Fig. 4
AstroSat / LAXPC Continuum (0 . −
10 Hz) fitted energy dependent power density spectra (PDS) in (a) 3 −
20 keV, (b) 20 − −
60 keV and (d) 60 −
80 keV energy bands respectively. These PDS are shown for the LAXPC data on 2017 April 06 (MJD57849.69; obs id = = k e V ( pho t on s c m - s - k e V - ) XRTGSCBAT1 10
Energy (keV) -4-2024 R e s i du a l s (a) k e V ( pho t on s c m - s - k e V - ) XRTGSC1 10
Energy (keV) -4-2024 R e s i du a l s (b) k e V ( pho t on s c m - s - k e V - ) XRTNuSTAR1 10
Energy (keV) -4-2024 R e s i du a l s (c) k e V ( pho t on s c m - s - k e V - ) XRTLAXPC1 10
Energy (keV) -4-2024 R e s i du a l s (d) Fig. 5
TCAF model fitted spectra of di ff eret observations. (a) shows the 0 . −
30 keV XRT + GSC + BAT fitted spectra of the obs. X11(MJD 57793.56). (b) is the 0 . −
20 keV XRT + GSC fitted spectra for obs. X20 (MJD 57808.37). (c) and (d) show broadband spectra usingcombined XRT + NuSTAR (in 0 . −
77 keV) and XRT + LAXPC (in 0 . −
80 keV) data respectively for XRT obs. X29 (MJD 57850.37). m d + m h m d m h Day (MJD) A RR HS (a)(b)(c)(d) ....
Fig. 6
Variation of TCAF model fitted (a) total accretion rate ( ˙ m d + ˙ m h ), (b) disk rate ( ˙ m d ), (c) halo rate ( ˙ m h ) and (d) accretion rate ratio(ARR = ˙ m h / ˙ m d ). The accretion rates are in the unit of Eddington rate ˙ m Edd . X S R Γ Day (MJD) T i n HS (a)(b)(c)(d)
Fig. 7
Variations of (a) TCAF model fitted shock location ( X s ), (b) compression ratio ( R ), (c) DBB + PL fitted photon index ( Γ ) and(d) inner disk temperature ( T in ) as functions of time (Day in MJD). X s and T in are in the units of Schwarzschild radius ( r s ) and keVrespectively. n H N Day (MJD) M (a)(b)(c) Fig. 8
Variations of (a) hydrogen column density ( n H ), TCAF model fitted (b) normalization ( N ) and mass of the BH ( M BH in M ⊙ ) areshown. Table 1
QPO properties UT [1]
Day [1] ν qpo [2] ∆ ν [2] Q [3] rms (%) [4] Date MJD (Hz) (HZ) ( ν qpo / ∆ ν )(1) (2) (3) (4) (5) (6)2017-01-28 57781.00 0 . ± .
027 0 . ± .
136 2.26 14.952017-02-15 57799.68 0 . ± .
028 0 . ± .
137 1.81 11.602017-02-22 57806.57 0 . ± .
034 0 . ± .
178 1.94 15.312017-02-24 57808.37 0 . ± .
028 0 . ± .
142 4.03 12.432017-03-09 57821.53 1 . ± .
038 0 . ± .
144 2.53 13.532017-04-06* 57849.69 1 . ± .
015 0 . ± .
081 2.49 9.131Energy (keV) * L AX P C . ± .
026 0 . ± .
155 1.98 12.0320-40 1 . ± .
014 0 . ± .
071 2.54 11.1440-60 1 . ± .
028 0 . ± .
087 5.55 6.8260-80 0 . ± .
019 0 . ± .
078 10.66 3.66 [1]
Column 1 and 2 represent the universal time and MJD of the data used. The 2nd and 6th row are the observations, taken using LAXPC data.The 2nd data is from the orbit 7498 and last one is from orbit 8238. The 1st, 3rd, 4th and 5th data are from XRT data on MJD 57781.00(obs id = = = = [2] ν qpo and ∆ ν represent observed QPO frequency and its full width at half maximum (FWHM), obtained by fitting PDS with Lorentzian profiles. [3] Q ( = ν qpo /∆ ν ) is the coherence factor that indicates sharpness of the QPOs. [4] Column 7 represents the percentage rms amplitude of the QPOs.In the lower panel we show the parameters ( ν qpo , ∆ ν , Q and rms) for di ff erent energy ranges. The results are shown for the LAXPC data on 2017April 06 (orbit = Table 2
Properties of spectral model fitted parametersObs [1] UT [2] MJD [2] n H [3] T in [4] Γ [4] χ / dof [6] ˙ m d [5] ˙ m h [5] X s [5] R [5] M BH [5] N [5] χ / dof [6] (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)X01 Y-01-28 57781.00 0 . ± . . ± . . ± . /
756 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
748 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
747 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
750 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
742 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
740 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
739 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
743 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
775 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
753 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
738 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
751 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
756 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
739 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
753 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
762 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
739 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
740 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
742 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
742 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
738 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
745 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
739 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
748 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
751 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
740 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
734 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
728 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
694 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
739 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
739 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . /
719 0 . ± . . ± . . ± . . ± . . ± . . ± . / [1] represents observation IDs of the data. Here, ‘X’ marks initial part of the observation IDs: 000349240. [2] ‘Y’ marks the year of the UT dates, which is 2017. UT dates are in mm / dd format. Column 3 represents the respective MJDs of column 2’s dates. [3] represents the model fitted values of hydrogen column density ( n H ). [4] DBB + PL model fitted inner-disk temperature T in (in keV), and PL index ( Γ ) are mentioned in Cols. 5-6. [5] TCAF model fitted parameters: disk rate ( ˙ m d in Eddington rate ˙ M Edd ), halo rate ( ˙ m h in ˙ M Edd ), shock location, X s in Schwarzschild radius ( r s ),compression ratio ( R ), mass of the black hole ( M BH in solar mass M ⊙ ) and normalization ( N ) are mentioned in Cols. 8-13. [6] DBB + PL and TCAF model fitted χ red values are mentioned in column 7 and 14 respectively as χ / do f , where ‘dof’ represents degrees of freedom.Note: we present average values of 90% confidence ± parameter error values, which are obtained using ‘err’ task in XSPEC.Note: we use the ± error as the superscript to save space in the Table Table 3
TCAF model fitted parameters for broadband analysisObs Id [1] UT [2] MJD [2]
Obs Id [3] UT [4 MJD [4] ˙ m d [5] ˙ m h [5] X s [5] R [5] M BH [5] N [5] χ / dof [6] (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)XRT NuSTARX29 Y-04-07 57850.36 90202055002 2017-04-07 57850.60 0 . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . . ± . . ± . . ± . / . ± . . ± . . ± . . ± . . ± . . ± . / = . ± . . ± . . ± . . ± . . ± . . ± . / = [1] represents the XRT observation Ids. Here ‘X’ marks the initial part of the obs. Ids: 000349240 [2] represent XRT obs. Ids’ respective dates in universal time (yyyy / mm / dd format) and MJDs. ‘Y’ represents the year in each UT. [3] represents the NuSTAR (row 1 and 2) and LAXPC (row 3 and 4) observation Ids. [4] represent NuSTAR (row 1 and 2) and LAXPC (row 3 and 4) obs. Ids’ respective dates in universal time (yyyy / mm / dd format) and MJDs. [5] TCAF model fitted parameters: disk rate ( ˙ m d in Eddington rate ˙ M Edd ), halo rate ( ˙ m h in ˙ M Edd ), shock location, X s in Schwarzschild radius ( r s ),compression ratio ( R ), mass of the black hole ( M BH in solar mass M ⊙ ) and normalization ( N ) are mentioned in Cols. 7-12. [6] TCAF model fitted χ red values are mentioned in column 13 as χ / do f , where ‘dof’ represents degrees of freedom.Note: we present average values of 90% confidence ± parameter error values, which are obtained using ‘err’ task in XSPEC.Note: we use the ±±