Interpreting the Spectro-Temporal Properties of the Black Hole Candidate Swift J151857.0-572147 during its First Outburst in 2024 (2024)

1 Introduction

X-ray binaries (XRBs) are quite common and important astronomical binary systems. Since accretion serves as the power source in these systems, it is crucial to understand them (Frank, King & Raine 2002).The primary object in XRBs is a compact object, and the secondary object is a companion star. The compact object may be a neutron star or a black hole, which are both the remnants of stellar bodies. There aremultiple categories for XRBs. They fall into two main categories based on the companion’s mass: low-mass X-ray binaries (LMXRBs) and high-mass X-ray binaries (HMXRBs) (Remillard & McClintock 2006).Transient and persistent sources are the other categories into which XRBs are divided, based on the type of variability in their outbursts. While transient sources occasionally exceed detection levels andprimarily remain in quiescence, or the dormant state ($L<10^{32}$ erg/s; Hannikainen et al. 2005), flux or counts of persistent sources remain higher than just the detection level most of the time ($L>10^{36}$ erg/s; Chen et al. 1997). These transients experience outbursts that can endure for several weeks or even months (Tetarenko et al. 2016). Though the population of transient HMXBs is increasing,the majority of reported transients are LMXBs (McClintock et al. 2013; Remillard & McClintock 2006 for a review as well). As per Debnath et al. (2010), there are two main categories ofBH outbursts based on their nature: slow rise slow decay (SRSD) and fast rise slow decay (FRSD). Zhang et al. (2019) divided outbursts into many types, such as glitter, reflare, multipeak, mini-outburst,or new-outburst, based on their rebrightening characteristics.

The soft multi-color thermal black body and the hard non-thermal power-law components combine to form the spectrum of a black hole. The hard component can be explained by physical scenario in the Comptonizingregion, also referred to as the ‘Compton Cloud’, which is the repository of hot electrons (Sunyaev & Titarchuk 1980, 1985). The soft component is modeled as the radiation of the standard Keplerian disk (Shakura& Sunyaev 1973, hereafter SS73). Over time, numerous models have been proposed to describe the hard component of the composite spectrum of a stellar-mass black hole, e.g., the thick disk model (Paczynski &Witta 1980). Even though they did a good job of explaining it, they all made some very specific assumptions. In 1995, Chakrabarti and his collaborators developed the two-component advective flow (TCAF, Chakrabarti& Titarchuk 1995) system, which provided a more comprehensive solution.

A transient black hole experiences many phases and spectral types during an outburst (Remillard & McClintock 2006). Generally speaking, during an outburst, we witness four distinct BH spectral states, whichare hard state (HS), hard intermediate state (HIMS), soft intermediate state (SIMS), and soft state (SS), respectively. An outburst usually starts in the HS. After that, it moves to the HIMS and the SIMS asbrightness increases. At last, when the source’s brightness peaks, it shifts to the SS. This is referred to as the outburst’s rising phase. The source then transits back to the HS in the opposite cycle as thebrightness gradually drops to its minimum. This is referred to as the outburst’s declining phase. To put it briefly, a BH’s spectral state transition forms a hysteresis loop in the order listed below: HS (rising)$\rightarrow$ HIMS (rising) $\rightarrow$ SIMS (rising) $\rightarrow$ SS $\rightarrow$ SIMS (declining) $\rightarrow$ HIMS (declining) $\rightarrow$ HS (declining). A source that experiences all four of theaforementioned often observed spectral states during some outbursts is known as type-I outbursts. In type-II or failed outburst, the source does not go to soft state (Tetarenko et al. 2016).

Understanding temporal aspects is just as critical to comprehending the dynamics of the accreting flow around the BHs as rich spectrum features and variabilities. It has been noted that the light curvesexhibit extremely tiny timescale variabilities during an outburst, particularly in the high-energy bands. Variabilities like broadband noise and narrow characteristics in the power density spectrum, or PDS,are imprinted by the Fourier transformation of the light curve (van der Klis 1989). A power-law function is used to describe the broadband noise, which is dispersed over a wide frequency range. Lorentzianprofiles can be used to describe the quasi-periodic oscillation (QPO), which is a power peak in restricted frequency ranges. Because of their geometrical origin, low-frequency QPOs (LFQPOs) are frequentlydetected in BHXRBs. Types A, B, and C are the three categories into which LFQPOs are divided, based on characteristics such as frequency ($\nu$), $Q$-value ($=\nu/\delta\nu$, where $\delta\nu$ is the fullwidth at half maximum, or FWHM), (%) RMS, etc. (Casella et al. 2005). High-frequency QPOs can also be seen in BHXRBs, although it is quite rear. Shock oscillation model (Molteni et al. 1996; Chakrabarti etal. 2005, 2008, 2015), magneto-acoustic waves (Titarchuk et al. 1998), accretion-ejection instability (Tagger & Pellat 1999), Lense-Thirring precession (Stella et al. 1999; Ingram et al. 2009), and othertheories have been proposed, though their origin is still up for debate. Shock oscillation model seems to be a more complete one since it can simultaneously describe the temporal and spectral features.

It is thought that spectral and timing properties are related since they originate from the same system and because variations in spectral states can also affect the kinds of QPOs. When examining the twosolely in terms of the features of the light curve, such as the hardness ratio, or HR, and the hardness intensity diagram, or HID, a strong association is seen (Homan et al. 2001). Accretion rate ratiointensity diagrams, or ARRIDs, can be used to understand how variations in viscosity or different mass accretion rates interact, as some model-fitted approaches also demonstrated (Chatterjee et al. 2020).Links between spectral and temporal features from pure observational ground can also be established using the RMS-intensity diagram, or RID (Munoz-Darias et al., 2011), and the hardness ratio-intensitydiagram, or HRD (Belloni et al., 2005).

First identified by Swift/XRT as a GRB (GRB 20240303A; Kennea et al. 2024), the new Galactic transient Swift J151857.0-572147 was found in Swift Trigger 1218452(GCN 35849). But thereafter, it was determined to be a Galactic transient due to its constant brightness and location in the Galactic plane. The RA andDec of the source were determined to be RA(J2000) = $15h18m57.00s$ and Dec(J2000) = $-57d21^{{}^{\prime}}47.9^{{}^{\prime\prime}}$ based on the optimal source localization utilizing XRT instantaneous on-board localization(Kennea et al. 2024). On March 4, 2024, during 15 minutes, from 02:13:13.3 to 02:28:08.9 (MJD 60373.1), follow-up radio observations were conducted using the MeerKAT telescope at $1.28GHz$ (L-band)with a bandwidth of $856$ MHz at flux density of $10$ mJy (Carotenuto et al., 2024; Cowie et al., 2024). The source’s nature was identified as consistent with an X-ray binary in the hard state by usingthe inverted radio spectrum ($f(\nu)\propto\nu^{\alpha}$, where $\nu\sim+0.5$) in conjunction with the photon index. This suggested that the source might be a black hole or a neutron star. On March 9,2024, from UT 10:35:10 to UT 11:06:20 (MJD 60378.45), the Australia Telescope Compact Array (ATCA) simultaneously recorded radio observations at frequencies of $5.5$ and $9$ GHz (Saikia et al., 2024).Additionally, their investigation confirmed the source to be a Galactic black hole. Target of opportunity (ToO) was carried out on this source with an exposure of 1000s by Swift/XRT following the ATCA.According to Del Santo et al. (2024), it was discovered that the combination of the phenomenological disk black body (diskbb) and power-law (po) model models describes the spectrum quite well. Thesediscoveries also confirmed that the source is a black hole. The source was detected by INTEGRAL serendipitously on March 8, 9, 10, and 11 of 2024 (Sguera 2024). The 60cm Robotic Eye Mount (REM) telescopeobserved the source in both optical and near-infrared wavelengths as part of the monitoring program of GRBs (Baglio et al. 2024). Optical measurements of the source were also carried out by the Las CumbersObservatory (LCO) network (Saikia et al. 2024).

From their Swift/XRT spectral modeling, Kennea et al. (2024) found a column density of $N_{H}=5.6\pm 0.06\times 10^{22}$ cm^-2. Additionally, they observed a power-law photon index of $\Gamma=1.78\pm 0.02$. While Burridge et al. (2024) reported that the source’s distance was $4.48^{+0.67}_{-0.47}$ kpc, with an HI absorption towards it, the absence of positive velocity absorption lines towards othersources in the field of the HI absorption for this source puts an upper limit on the distance as $15.64^{+0.77}_{-0.60}$ kpc. The mass and spin parameters of the source are reported to be $\sim 9.2\pm 1.6-10.5\pm 1.8M_{\odot}$ and $\sim 0.65$, while the possible inclination is $\sim 38^{\circ}\pm 8^{\circ}-47^{\circ}\pm 15^{\circ}$ and $0.65$ (Mondal et al. 2024).

2 Observation and Data Reduction and Analysis

This source has recently been observed by Swift satellite. It is currently being monitored at the time of this manuscript writing by various other X-ray satellites, e.g., NICER, NuSTAR, IXPE, etc.We use X-ray data from China’s first X-ray mission Insight-HXMT (Zhang et al. 2020). After the onset of the outburst, 7 observation IDs were available publicly when we started our analysis.We list the data in Table 1 below.

Each of these observation IDs has multiple exposures (up to 14 for some). While listing our analysis results, we will list all those exposure IDs with MJD. Using raw data from all these obs IDs,we first produced science-analyzable, cleaned data and then performed our analysis. We discuss data reduction and analysis in the following subsections.

3 Results

We discuss our results from the timing and spectral analysis in the following subsections. However, before going into the analysis results, we discuss the variation of the flux of the source during theoutburst first below.

3.1 Timing Properties

First, we will discuss the outburst evolution from the light curve profiles and hardness ratio, and then we will discuss our analysis of QPOs.

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3.1.1 Outburst Profile, and Hardness Ratio

The BHC Swift J151857.0-572147 was not observed by the MAXI/GSC instrument. The source is located at $\sim 0.2^{\circ}$ from the source Cir X-1. Although the facility could identify the brightening of thesource, the two sources could not be resolved seperately. In Figure 1, we show the location of the two sources in the upper panel. It can be noticed that the two sources are located very close to eachother. The lower panel of the figure shows increased activity due to the outburst of Swift J151857.0-572147.

Evolution of LC, and HR

In Figure 2, we show the variation of the count rates for around 15 days. The count rates are extracted using LE, ME, and HE light curves of HXMT in the $2-10$, $10-35$, and $27-250$keV energy bands.In panel (a), we show the variation of those source and background count rates for the three bands (in respective colors). Red is for LE, while green and blue colors are used to represent ME and HE bands.The filled circle (of each color) lines represent the source counts, whereas the triangle-shaped lines represent the background count rates. As can be noticed, the HE background count rate was quite highand was almost comparable to the source count rate. The other two bands showed a significant difference in count levels between source and background. In Table 2, we list the start, end, and average MJDsof all our analyzed exposures. We also list the source and background count rates for LE, ME, and HE in Table 2. In panel (b) of Figure 2, we show the count rates in $2-4$, $4-10$keV energy bands, whichare extracted using LE light curves. In panel (c), the hardness ratio (HR) is plotted using the ratio of the LE count rates of $4-10$ to $2-4$keV.

From the light curves, we see that the source is quite bright during the outburst. The LE count rate shows a smoother variation than the ME and HE bands, which can also be noticed in the (b) panel. Fromthe variation, HR gives a rough idea that the source had already moved past its hard state as Insight-HXMT started monitoring the source. As time progressed, spectral nature progressed from intermediateto softer states. However, we need timing and spectral analysis results to designate this firmly. We discuss them in the next two subsections.

3.1.2 Low-Frequency Quasi Periodic Oscillations

Model fitted PDS continuum

We created the PDS to analyze QPOs using the $0.01$ sec time-binned light curves from all three bands (LE, ME, and HE), as stated in §2. In Figure 3, we show the best model-fitted PDS continuum for thethree bands (a) LE, (b) ME, and (c) HE for the observation ID P0614374001 (exposure ID: P061437400101-20240304-01-01). While, both the QPO and harmonic were present in the LE band, the harmonic nature wasabsent in ME and was not very prominent in HE. The QPO and harmonic have a 1:2 ratio in frequency with the $\nu_{harmonic}\sim 6.43\pm 0.04$Hz. The harmonic in this exposure has an FWHM of $0.39\pm 0.13$and normalization of $0.57\pm 0.14$. We discover that each of the three energy bands’ light curves has a fundamental QPO nature. We first checked all the exposures for the observation IDP0614374001. From our fitting, we first extracted the basic QPO information, which are QPO frequency ($\nu_{qpo})$, full-width at half-maximum (FWHM or LW), and QPO normalization(LN).

We found that QPO was present in most of the exposures of this observation ID. It was present for all exposures in the ME band and was absent in the last LE band and second and fifth HE band. Also, the QPO frequencyevolved within the short period of the duration of this observation ID. Thus, we checked for QPOs for all the exposures. At the start of our analysis period, fundamental QPO was present in almost most of the exposures.The $\nu_{qpo}$ was $\sim$ 3.2 for all three bands on MJD 60373.9, and it increased as the outburst progressed. Then after some days, it decreased, and then again showed an increasing trend. Then, it again decreased andincreased and decreased and continued this way. The highest frequency in the LE band was 8.1 Hz on MJD 60376.9, on which both the light curves in the ME and HE bands were not created by the hpipeline command. The highest frequency in the ME band was 8.97 Hz on MJD 60377.9, on which the LE and ME light curves were not produced. In the HE band, $\nu_{qpo}$ was the highest on MJD 60379.3 with a value of 6.82Hz. We show the variations of the QPO frequency during our full analysis period in Figure 4(a-c) for (a) LE, (b) ME, and (c) HE. In Table 3, we listed the values of $\nu_{qpo}$ in columns 2, 3, & 4 for LE, ME, and HE.Although for the exposure P061437400103-20240305-02-01, there was a presence of a harmonic nature in the HE band, we did not fit it as the noise was high and the harmonic was like a broad Lorentzian feature. We did notfind harmonic for any other exposures of any other observation ID in any of the three bands.

Energy Dependent PDS

We were able to extract certain information about QPOs, such as full-width at half maximum (FWHM) and Normalization (LN) by the use of PDS fitting. For the exposures, we additionally retrieved the source andbackground count rates. Using the formula from Bu et al. (2015), we estimated the fractional RMS as $RMS=\sqrt{\frac{P}{S+B}}\frac{S+B}{S}$, which denotes the fractional variability in the PDS. Here, $S$,and $B$ represent the count rates of the source and the background, respectively. $P$ is the Leahy normalized power. We also estimated the $Q$-factor ($\nu/\delta\nu$), which measures the sharpness of the QPO.Table 3 lists these values for LE, ME, and HE in columns 5–7 ($Q$-value) and 8–10 (RMS), respectively. This is shown in Figure 5. The variations of the $Q$ factor were consistent in the three different bands.To check if there is any correlation between the QPO RMS and QPO frequency, we plotted those two properties against each other in Figure 6. We have not found any correlation between them for this sourcein all three energy bands.

As explained before, we also checked the energy dependence of QPOs using the HE light curve in 7 different energy bands. These energy ranges were chosen to maintain similarity with Ma et al. (2023). The PDScontinuums for the observation ID P0614374001 (exposure ID: P061437400101-20240304-01-01) are given in Figure 7(a-g) for respective energy bands. For this exposure, we find that the fundamental QPO was prominentlypresent at 3.274 Hz in the $27-35$ keV energy band, while it is also present in the $35-48$ keV with a little change of frequency of 3.222 Hz. However, the nature of QPO was not as strong as in the $27-35$ keV.Above 48 keV, we did not find any nature of fundamental QPO. We notice a sharp fall of QPO strength above 48 keV. Chatterjee et al. (2021) studied QPO energy dependence for the BHC GRS 1716-249 using AstroSat data.Although the fundamental QPO nature got weaker in high energies in that report, it did not show this type of sharp fall of QPO nature after some energy band. A possible weak harmonic nature was noticed in the$35-48$ keV band, which was not present in the $27-35$ keV. However, it looks very weak and we did not model it. Harmonic nature was also not observed above 48 keV. We checked this for all the 31 exposures forwhich fundamental LFQPO was present in the HE light curve. We find that for all of these exposures, QPO was absent above 48 keV. For some exposures, we found that LFQPO was absent in the 35-48 keV band, althoughit was present in the 27-35 keV band.

Using the formulas, as mentioned above, we estimated $Q$-values and RMS (%) for all these exposures in both these bands. In Figure 8, we show the variation of QPO frequency, $Q$-value, and RMS (%) for all theseexposures with time. We notice that the $\nu_{qpo}$ varied in a very narrow range between these two energy bands, which is within the error range. The $Q$-value shows a random variation for both the bands, where itwas sometimes higher for 27-35 keV bands and sometimes for 35-48 keV. The overall variation of RMS (%) was higher in case of 27-35 keV band, compared to the higher band. The values of the variation of QPO propertiesin case of energy dependence is given in the Table 4.

We also show the variation of QPO RMS with energy in Figure 9. We noticed that the QPO RMS was lowest in the LE band. It was the highest in the ME band. Then it started to decrease. Above 48 keV, we did notfind the presence of any QPO.

Apart from this, we also searched for QPOs in the $48-250$keV energy band light curve. Since above $48$keV, no QPO was found, we wanted to check if the energy range was higher, it could show QPO nature or not.In all of the exposures, except one, we did not find the presence of QPO in this energy band. This is for the observation ID. P0614374001 (exposure ID. P061437400103-20240305-02-01). We found that there was thepresence of a fundamental QPO in this exposure at $3.06\pm 0.05$Hz. This is shown in the Figure 10.

3.1.3 High Frequency QPOs

PDS Continuum for HFQPO

Apart from looking for low-frequency QPOs, we also searched for high-frequency QPOs (HFQPOs) in all the light curves for the three bands in all 62 exposures. In Figure 11(a-c), we show the PDS continuum for$0.001$ sec time-binned (Nyquist frequency = 500 Hz) curve for (a) LE, (b) ME, and (c) HE. However, we did not find any signature of HFQPOs in any of our light curves. The frequency in the PDS in LE, ME, andHE in Figure 11, are similar to those in Figure 3. Those are the LFQPOs present in those light curves during that exposure.

3.2 Spectral Properties

Studying the spectrum features sheds additional light on the nature of the outburst in addition to the temporal properties. We examined the source using the Insight-HXMT data that was accessible, for 14exposures in total. The exposure IDs in Table 2’s first column have a ‘*’ symbol next to them. We perform a thorough spectral study using HXMT data on this source for every consecutive days for the available data.Our spectrum investigation was initiated with MJD 60373.9. For spectral fitting, we have simultaneously analyzed LE+ME+HE in the $2-100$ keV energy band (LE in 2–10, ME in 10–35,and HE in 27–100 keV) for all of the chosen exposure IDs.

Model Fitted Insight-HXMT Spectra

First, we tried to model the spectrum with simple additive models diskbb andpower-law. We also used the multiplicativetbabs (with wilm abundance, Wilms et al. (2000)) model to account for the interstellar absorption.The model fitted unfolded spectrum is given in the Appendix section in Figure A.15. Although, the $\chi^{2}/DOF$ value was acceptable, we noticed that the spectrum changes its slope above $\sim 20$keV. Thus, wereplaced the power-law with the broken power-law model, which accounts for thechange of slope after certain energy, called break energy ($E_{b}$). In XSPEC, our model was expressed as constant*tbabs(diskbb + broken powerlaw).The three distinct instruments (LE, ME, and HE) are normalized using the constant. This model could fit the spectra for an acceptable $\chi^{2}/DOF$ value ($\sim 1$). These valuescan be found in column 11 of Table 5. Although this model fit was acceptable, there was a reflection nature in the spectrum. To account for that, we replaced the broken power-lawmodel with the reflection model in neutral medium pexrav. With this model, using the model combination asconstant*tbabs(diskbb + pexrav), we also achieved the best fit. The $\chi^{2}/DOF$ values can be found in column 11 of Table 6. We also checked the reflection component byusing the reflection model pexriv which takes ionization into account. Thus constant*tbabs(diskbb + pexriv) is our Model-3 combination inXSPEC. We also achieved best fit using this combination. Here, we like to point out our approach using the Model 3. Except for 2 parameters, all the parameters of this modelare the same as the pexrav model. While fitting with this model, we fixed the cut-off energy ($E_{cut}$) of this model to the pexrav model. Also,we found while fitting that the disk temperature parameter (in units of Kelvin) was always taking its highest value, which is $10^{6}$Kelvin. Thus, for all the spectral fitting using this model, we freeze thevalue of this parameter to this highest value. The extra parameter that this model has over pexrav is the disk ionization parameter ($\xi$), which is given as $\xi=4\pi F_{ion}/n$,where $n$ is the density of the reflector (Done et al. 1992) and $F_{ion}$ is the irradiating flux in the 5eV to 20keV energy band. The best fitted parameters are given in Table 7 along with the fittingstatistics. We find that the parameter variation of the pexriv model is similar to the pexrav model. In Figure 12(a-c), we show the model fittedbest unfolded spectra using (a) Model-1, (b) Model-2, and (c) Model-3.

In Figure 13, we show the variations of some of the spectrally analyzed properties from both models. In panel (a), we show the variations of the hydrogen column density ($N_{H}$) for both the model fittings (redfilled-square for Model-1 and blue filled-square for Model-2). We notice that they show close variations within the error range throughout. While for Model-1, $N_{H}$ varied between $(4.3-6.5)\times 10^{22}$cm^-2, it varied in the range of $(5.1-6.3)\times 10^{22}$ cm^-2 for Model-2 and in the range of $(5-6.9)\times 10^{22}$ for Model-3. In panel (b), we show the variations in the inner-disk temperature($T_{in}$ in keV) for both models. $T_{in}$ shows variation in the range of $0.95-1.6$ keV for Model-1, $1.3-2.1$ keV for Model-2, and $0.9-2.1$keV for Model-3. Since, the last exposure could not be fittedusing Model-2, we think we have got the narrower variation using Model-2. In panel (c), we show the variations of photon indices. The red filled-square and hollow square represent $\Gamma 1$ and $\Gamma 2$ forthe broken power-law model, where the blue and filled squares represent the $\Gamma$ of the pexrav and the pexriv models. The energy break ($E_{b}$) of the broken power-lawmodel was $19.2\pm 0.3$ at the starting day and it decreased to $8.54\pm 0.3$ at the end of the analysis period. All the spectral parameters are given in Table 5, including fitting constants, needed to normalizesimultaneous data in three bands. Similarly, all the spectral parameters are listed in Table 6 and 7, for the analysis using Model-2 and Model-3. For analysis with Model-2 and Model-3, we fixed the abundances tosolar abundance and also varied the value of the inclination to a narrow range around $30^{\circ}$ as reported by Mondal et al. (2024). However, on the last date of our analysis period, we found that althoughthe fitting statistics were acceptable, the parameter space was unphysical. We tried to adjust the parameter space. However, the best fit was not achieved then. Thus we have left it blank in Table 6.

4 Discussions

The Galactic black hole Swift J151857.0-572147 started an outburst recently in March 2024. We have used Insight-HXMT data for our both timing and spectral studies from 2024 March 04 to 2024 March 17. Usingthe $0.01$sec time-binned light curves from the three instruments of HXMT (LE, ME, and HE), we studied the source’s timing properties. We also searched for the energy dependence of LFQPOs by producing light curvesin 7 different energy ranges within the HE band. Along with these, we searched for HFQPOs from all the light curves from LE, ME, and HE by making $1$ms time-binned light curves. We then examined the combined LE+ME+HEspectra in the $2-100$keV broad energy band to learn more about the spectral characteristics of this source using the spectra files from these three instruments.

For stellar-mass black holes, quasi-periodic oscillation is one of the most significant and frequent occurrences. We examined 186 exposures in total for this recently found source (62 for each of LE, ME, and HE).Nevertheless, incorrect light curve production occurred in 2 LE exposures. A total of 184 light curves for LE, ME, and HE were obtained. The details are listed in Table 2. We discovered that QPO was not presentin each of these light curves. The details on QPO properties are listed in Table 3. Over this brief analysis period, the QPO frequency has rapidly changed. Even in a single day, there was an increase in the QPOfrequency ($\nu_{qpo}$). The results section contains a general discussion of the QPO frequency’s evolution. Type-C QPO nature is identified from the fluctuation of QPO frequency, (%)RMS, and $Q$-factor. One thingwe would like to discuss here that the difference in RMS value (in Table 3) for LE, ME, and HE is due to the large variation in background counts in these three bands. As we can notice in Table 2, the backgroundcount in the HE band is almost equivalent to the source count in the HE band for this source. We recently studied the outburst properties of the BHC Swift J1727.8-1613 using HXMT data (Chatterjee et al. 2024).However, there was a great difference between the source and background count rates in all three bands. This is the case here for the LE and ME bands. For both sources, the same reduction method is used.

Even though the QPOs have been thoroughly examined in the literature, further modeling is necessary to understand their origin. Here, we want to concentrate on the physical scenario that explains how shock instabilitiesin advective flows near black holes (BHs) give rise to QPOs. According to Chakrabarti (1989), accretion onto BH is a transonic flow with the potential for numerous sonic locations. The companion’s matter doesn’t needto be exclusively Keplerian. A supply of matter with an angular momentum distribution that differs from the Keplerian one may exist. This is the sub-Keplerian component. Infalling matter with a smaller angular momentumcomponent accretes over a free-fall timescale. At a certain distance from the black hole, this matter might nearly stop due to the counterbalance between the centrifugal force and gravitational force, undergo a shocktransition, and form a post-shock region. Standing shocks form according to the flow properties (Chakrabarti 1989; Singh et al. 2022 and references therein). The spectral and temporal properties of BHs that have beenseen can be effectively described by this method (Debnath et al. 2014; Mondal et al. 2014, Chatterjee et al. 2020, 2021, 2023). This shock may not be stable at the outer edge over time. There could be oscillations inthe CENBOL boundary, which can be caused due to either of two reasons:

(i) According to Chakrabarti (1989), the satisfaction of the Rankine-Hugoniot condition makes the boundary of the shock stable and steady. However, if this condition is not satisfied, the shock could oscillate at theouter boundary to find local equilibrium. This could produce variabilities in the light curves.

(ii) Molteni et al. (1996) state that the presence of cooling may cause the shock to oscillate. QPOs emerge during the oscillation when the heating timescale and the cooling timescale caused by the Comptonization processmatch (see Chakrabarti et al. 2015).

The QPO frequency is given by,

where the following are represented, respectively: $c$, $G$, $M_{BH}$, $X_{s}$, and $R$; these are the gravitational constant, the speed of light, the mass of the BH, the shock location, and the ratio of matterdensities in post-shock to pre-shock regions ($\rho_{+}/\rho_{-}$).

We have already retrieved the QPO frequency ($\nu_{qpo}$) from our timing analysis. We calculated the shock location during the outburst using therelation mentioned above. Chakrabarti et al. (2005) state that depending on the flow parameters causing shocks, $X_{s}$ can be anywhere over $10~{}r_{s}$. When the spectral nature of an outburst is hard, the shockforms far away $\sim 1000~{}r_{s}$, and it gradually becomes small in the following days as cooling increases (Mondal et al. 2015). Based on Eq. 1, we discovered that during the beginning of the outburst, the shockwas located at a distance of $\sim 100~{}r_{s}$ from the BH (see Figure 14b). Then, as $\nu_{qpo}$ increased, the shock moved inwards, suggesting cooling was in progress. After a few days, the shock became stable.Table 3 provides the values for the shock location (columns 11–13).

The light curve from MAXI/GSC was absent due to the proximity of another source in Cir X-1. Thus, from the HXMT extracted light curves and HR variations, we can roughly say that the source transitioned past itshard state at the start of our analysis period. It was at the end of its harder state (HS and HIMS). Our spectral analysis result also confirms this. From the variation of the photon index, we can say that thesource was already in the end phase of its HIMS state and was transitioning towards its SIMS state. Our estimated shock location also agrees with this designation. At the start of our analysis period, shock wasat a distance, which suggests the source has already transitioned past its hard state and may be at the end of its hard intermediate state. Then the shock moved inward, suggesting now the source is making atransition towards the softer states via SIMS and SS. On several days, we did not notice any QPO signature from the start of our analysis to the end in any of the three bands. This could be because the infalland cooling timescales did not match for the shock. However, this could be also due to the data. For several days, QPO is only present in one of the three bands, whereas on some days it is present in two bands.We find that on the last day of our analysis period, the $\Gamma$ became quite high, which suggests that the source transitioned into the soft state (SS) that day. Thus, we did not find QPO in any band on thatday. The absence of QPOs and high $\Gamma$ confirms the SS as inferred in Mondal et al. (2024) using IXPE and NuSTAR observations of the source.

We also found that high-frequency QPO was absent during the entire analysis duration of the outburst. Although the HFQPO phenomenon is not very common, its absence could be because the disk did not proceed veryclose to the compact object to produce variabilities with high frequency. Or, it could be due to the reason that the photon detection by HXMT instruments is not sufficient for this phenomenon. We also checkedthe energy dependence of LFQPOs in the HE band for those exposures in which LFQPO was present in the full energy band. The energy dependence of QPOs could give valuable insight into the origin of the QPO. In Maet al. (2023) paper, they reported that LFQPO was present till very high energy, which suggested that the origin of the QPO could be from the precession of the jet. Examining all of those 31 exposures, we findthat LFQPO was present till $48$keV, above which there is no prominent or weak QPO nature, either. In the $27-35$keV band, the nature of LFQPOs was stronger than in the $35-48$keV band. The shock was quitestrong in the case of the BHC Swift J1727.8-1613 (Chatterjee et al. 2024), which could produce variabilities up to higher energies. However, for this source, the shock was not very big, which suggests that ithas already cooled down by the process of inverse-Comptonization. Thus, it could only produce variabilities in hard photons up to $48$keV. This also supports our claim about the origin of the quasi-periodicoscillations, observed in the light curves.

Unlike the BHC Swift J1727.8-1613, this source has shown a very high value of hydrogen column density ($N_{H}$), using both combinations of models. $N_{H}$ varied in the range of $(4.3-6.5)\times 10^{22}$cm^-2and $(5.1-6.3)\times 10^{22}$cm^-2 for Model-1 and Model-2, respectively. This is very high, considering Galactic black holes. This indicates some absorption local to the source, which could be due to theoutflows from the disk or the presence of some blobs along the line of sight (see Neilsen & Homan, 2012; Mondal & Jithesh, 2023). To confirm this, we need a detailed study of the outflow/jet properties of thesource.

5 Summary and Conclusions

We have studied the timing and spectral properties of the very first outburst of BHC Swift J1727.8-1613 in 2024. Using Insight-HXMT LE, ME, and HE exposure average light curve data, we present the evolutionof the light curve and its hardness ratio across our full analysis period. For our investigation, we selected the 7 observation IDs using the Insight-HXMT data, publicly available during the analysis. Fortiming analysis, we employed all of the exposures from those observation IDs, and for spectrum analysis, we employed selective exposures, respectively. We produced a power density spectrum and used $0.01~{}s$time-binned light curves from the three HXMT instruments, i.e., LE, ME, and HE, to study the QPO properties. We used the Lorentzian model to obtain the QPO properties. We also studiedenergy-dependent QPO by producing HE light curves in seven different energy bands. We extracted the energy-dependent QPO properties in the same way we did for the LE, ME, and HE light curves in the full band. Apartfrom these, we also produced $0.001$s time-binned light curve to search for high-frequency QPOs. We employ LE + ME + HE spectrum files in the broad $2-100$keV energy band for spectralanalysis. We found that the models i) constant*tbabs*(diskbb + broken power-law) and ii) constant*tbabs*(diskbb + pexrav) fit the spectra for the beststatistics. Based on our investigation, we cdiskonclude that:

i) The source was present in the intermediate state at the start of our analysis period and proceeded toward the soft state as the outburst progressed.

ii) It was in the soft state at the last observation ID of our analysis period.

iii) Type-C QPO was present in the intermediate state, which could be produced by the shock instability in the transonic accretion flow.

iv) As the source transited to the soft state, we did not find any QPOs.

v) LFQPOs were present up to 48 keV, above which we did not find the presence of LFQPO for all the exposures.

vi) HFQPOs were absent during this analysis period.

vii) As the shock was of intermediate strength, it could not produce variabilities up to very high energies. Thus, we only found QPOs up to 48 keV.

viii) The hydrogen column density varied in the range of $N_{H}\sim(4.3-6.9)\times 10^{22}$cm^-2 in accord with the estimation by Mondal et al. (2024). This could be due to the presence of outflows from the disk or some blobsalong the line of sight.

6 Data Availability

This work has made use of public data from several satellite/instrument archives and has made use of software from the HEASARC, which is developed and monitored by the Astrophysics Science Division at NASA/GSFC andthe High Energy Astrophysics Division of the Smithsonian Astrophysical Observatory. This work made use of the data from the Insight-HXMT mission, a project funded by the China National Space Administration (CNSA) andthe Chinese Academy of Sciences (CAS).

7 Acknowledgements

We thank Dr. Lian Tao of the Institute of High Energy Physics (IHEP), Chinese Academy of Sciences (CAS) for publicizing the Insight-HXMT data by request. We also thank Prof. Mutsumi Sugizaki of the National AstronomicalObservatory, Chinese Academy of Sciences (NAOC) for providing fruitful information about the absence of MAXI/GSC daily average light curve on the source. We sincerely thank Prof. John A. Tomsick of the Space Sciences Lab,University of California, Berkeley, USA for providing suggestions in the draft.

KC acknowledges support from the SWIFAR postdoctoral fund of Yunnan University. SPS and SM acknowledge the Ramanujan Fellowship (# RJF/2020/000113) by SERB-DST, Govt. of India for this research. CBS is supportedby the National Natural Science Foundation of China under grant no. 12073021.

References

• (1)
• (2)[] Baglio, M. C., D’Avanzo, P., Ferro, M., Campana, S., Covino, S., 2024, ATel, 16506, 1
• (3)[] Belloni, T., Homan, J., Casella, P., van der Klis, M., et al., 2005, A&A, 440, 207
• (4)[] Bondi, H., 1952, MNRAS, 112, 195
• (5)[] Bu, Q.-C., Li, Z.-S., Qu, J.-L., Belloni, T. M., Zhang, L., 2015, ApJ, 799, 2
• (6)[] Burridge, B. J., Miller-Jones, J. C. A., Bahramian, A., Prabu, S., Carotenuto, F., et al., 2024, ATel, 16538, 1
• (7)[] Carotenuto, F., Russell, T. D., JACKPOT Collaboration, 2024, ATel, 16518, 1
• (8)[] Casella, P., Belloni, T., & Stella, L., 2005, ApJ, 629, 403
• (9)[] Chakrabarti, S. K., 1989, MNRAS, 340, 7
• (10)[] Chakrabarti, S. K., & Titarchuk, L. G., 1995, ApJ, 455, 623
• (11)[] Chakrabarti, S. K., & Manickam, S. G., 2000, ApJ, 531, L41
• (12)[] Chakrabarti, S. K., Acharya, K., & Molteni, D., 2004, A&A, 421, 1
• (13)[] Chakrabarti, S. K., Nandi, A., Debnath, D., Sarkar, R., & Datta, B. G., 2005, preprint (arXiv:astro-ph/0508024)
• (14)[] Chakrabarti, S. K., Debnath, D., Nandi, A., & Pal, P. S., 2008, A&A, 489, L41
• (15)[] Chakrabarti, S. K., Mondal, S., & Debnath, D., 2015, MNRAS, 452, 3451
• (16)[] Chatterjee, K., Debnath, D., Chatterjee, D., Jana, A., Chakrabarti, S. K., 2020, MNRAS, 493, 2452
• (17)[] Chatterjee, K., Debnath, D., Chatterjee, D., Jana, A., et al., 2021, Ap&SS, 366, 63
• (18)[] Chatterjee, K., Debnath, D., Nath, S. K., & Chang, H. -K., 2023, ApJ, 965, 55
• (19)[] Chatterjee, K., Mondal, S., Singh, C. B., Sugizaki, M., 2024, ApJS (preprint: arXiv:2405.01498)
• (20)[] Chen, Y., Cui, W., Li, W., et al. 2020, Science China Physics, Mechanics, and Astronomy, 63, 249505
• (21)[] Cowie, F. J., Carotenuto, F., Fender, R. P., Heywood, I., Hughes, A. K., et al., 2024, ATel, 16503, 1
• (22)[] Dauser, T., Garcia, J., Walton, D. J., et al., 2016, A&A, 590, A76
• (23)[] Debnath, D., Chakrabarti, S.K., & Nandi, A., 2010, A&A, 520, A98
• (24)[] Debnath, D., Chakrabarti, S. K., & Mondal, S., 2014, MNRAS, 440, L121
• (25)[] Del Santo, M., Russell, T. D., Marino, A., & Motta, S., 2024, ATel, 16519, 1
• (26)[] Done, C., Mulchaey, J. S., Mushotzky, R. F., & Arnaud, K. A., 1992, ApJ, 395, 275
• (27)[] Frank, J., King, A., Raine, D., Accretion Power in Astrophysics, 2002, Cambridge University Press
• (28)[] Hannikainen, D. C., Charles, P. A., van Zyl, L., et al. 2005, MNRAS, 357, 325
• (29)[] Homan, J., Wijnands, R., van der Klis, M., Belloni, T., van Paradijs, J., KleinWolt, M., Fender, R., & Mendez, M., 2001, ApJS, 132, 377
• (30)[] Ingram, A., Done, C., & Fragile, P. C., 2009, MNRAS, 397, L101
• (31)[] Kennea, J. A., Lien, A. Y., D’Elia, V., Melandri, A., Page, K. L., et al., 2024, ATel, 16500, 1
• (32)[] Leahy, D. A., et al., 1983, ApJ, 266, 160L
• (33)[] Ma, X., Zhang, L., Bu, Q. C., Qu, J. L., Zhang, S. N., et al., 2023, ApJ, 948, 116
• (34)[] McClintock, J.E., Narayan, R., & Steiner, J.F., 2013, The Physics of Accretion onto Black Holes, Space Sciences Series of ISSI, 49, 295
• (35)[] Molteni, D., Sponholz, H., & Chakrabarti, S. K., 1996, ApJ, 457, 805
• (36)[] Mondal, S., Debnath, D., & Chakrabarti, S. K., 2014, ApJ, 786, 4
• (37)[] Mondal, S., Chakrabarti, S. K., & Debnath, D., 2015, ApJ, 798, 57
• (38)[] Mondal, S., & Jithesh, V. 2023, MNRAS, 522, 2065
• (39)[] Mondal, S., Suribhatla, S. P., Chatterjee, K., & Singh, C. B., 2024, (preprint: arXiv:2404.09643)
• (40)[] Munoz-Darias, T., Motta, S., & Belloni, T. M., 2011, MNRAS, 410, 679
• (41)[] Nandi, A., Debnath, D., Mandal, S., Chakrabarti, S. K., 2012, A&A, 542, 56
• (42)[] Neilsen, J., & Homan, J. 2012, ApJ, 750, 27
• (43)[] Paczynski, B., & Wiita, P., 1980, A&A, 88, 23
• (44)[] Remillard, R. A., & McClintock, J. E., 2006, ARA&A, 44, 49
• (45)[] Saikia, P., Russell, D. M., Baglio, M. C., Alabarta, K., Rout, S., et al., 2024, ATel, 16516, 1
• (46)[] Sguera, V., 2024, ATel, 16524, 1
• (47)[] Shakura, N. I., & Sunyaev, R. A., 1973, A&A, 24, 337
• (48)[] Singh, C. B., Mondal, S., & Garofalo, D., 2022, MNRAS, 510, 807
• (49)[] Stella, L., Vietri, M., & Morsink, S. M., 1999, ApJ, 524, L63
• (50)[] Sunyaev, R. A., & Titarchuk, L. G., 1980, A&A, 500, 167
• (51)[] Sunyaev, R. A., & Titarchuk, L. G., 1985, A&A, 143, 374
• (52)[] Tagger, M., & Pellat, R., 1999, A&A, 349, 1003
• (53)[] Tetarenko, B. E., Sivakoff, G. R., Heinke, C. O., & Gladstone, J. C., 2016, ApJS, 222, 15
• (54)[] Titarchuk, L., Lapidus, I., & Muslimov, A., 1998, ApJ, 499, 315
• (55)[] van der Klis, M., 1989, Annu. Rev. Astron. Astrophys., 27, 517
• (56)[] Wilms, J., Allen, A., & McCray, R., 2000, ApJ, 542, 914
• (57)[] Zhang, S. -N., et al., 2020, Science China Physics, Mechanics, and Astronomy 63, 249502
• (58)[] Zhang, G. B., Bernardini, F., Russell, D. M., Gelfand, J. D., Lasota, J.-P. et al., 2019, ApJ, 876, 5
• (59)