EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 664 (August 2022) A&A, 664 (2022) A100 Full HTML
Open Access
Issue
A&A
Volume 664, August 2022
Article Number A100
Number of page(s) 9
Section Astrophysical processes
DOI https://doi.org/10.1051/0004-6361/202243426
Published online 10 August 2022

© G. Panizo-Espinar et al. 2022

Licence Creative CommonsOpen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

This article is published in open access under the Subscribe-to-Open model. Subscribe to A&A to support open access publication.

1. Introduction

Low mass X-ray binaries (LMXBs) are binary systems comprising a stellar-mass black hole (BH) or a neutron star (NS) that is accreting gas from a low mass donor star (≲1 M⊙). The infalling material forms an accretion disc around the compact object (Shakura & Sunyaev 1973), whose internal regions reach temperatures high enough (106–107 K) to emit in X-rays. The vast majority of LMXBs are transients. They spend most of their lives in a quiescent, low-luminosity state, showing occasional accretion episodes when their luminosity increases by several orders of magnitude: the so-called outbursts.

During outbursts, LMXBs usually evolve following a common X-ray hysteresis pattern (e.g., Muñoz-Darias et al. 2014) that is related to their accretion properties. At the beginning of the outburst, the X-ray spectrum is dominated by a hard, power-law component thought to be produced by inverse-Compton processes in a corona of hot electrons (e.g., Gilfanov 2010). This state is known as the hard state. As the outburst continues the system enters the soft state, when the spectrum becomes dominated by a soft, thermal component arising in the accretion disc. Low mass X-ray binaries can also be found in intermediate states, when they are transitioning between the above two main states (see e.g., McClintock & Remillard 2006; Done et al. 2007; Belloni et al. 2011).

Outbursts are also characterised by the presence of outflows, with observational evidence indicating that they are directly correlated with the accretion state (for a review, see e.g., Fender & Muñoz-Darias 2016). These outflows are usually observed in two flavours: jets and winds. Radio jets are ubiquitously observed in the hard (compact jet) and intermediate (discrete ejections) states, but not during the soft state (e.g., Gallo et al. 2003; Fender et al. 2004; Russell et al. 2011). Conversely, hot X-ray winds are mainly detected during the soft state as blueshifted X-ray absorptions in spectral transitions of highly ionised material, such as Fe XXV and Fe XXVI (Ueda et al. 1998; Neilsen & Lee 2009; Ponti et al. 2012, 2014; Díaz Trigo & Boirin 2016). In addition, more recent studies have also shown the presence of colder accretion disc winds, which are mainly observed in optical emission lines and can be simultaneous with the jet (e.g., Muñoz-Darias et al. 2016). These are revealed by some specific signatures: blueshifted absorptions (P-Cygni profiles or absorption troughs), broad emission line wings, flat-top line profiles, and line asymmetries. To date, they have been seen in a handful of BH (e.g., Muñoz-Darias et al. 2016, 2018, 2019; Cúneo et al. 2020b; Mata Sánchez et al. 2022) and NS transients (e.g., Muñoz-Darias et al. 2020; see also Castro Segura et al. 2022 for a detection in the ultraviolet). Furthermore, near-infrared studies show that these lower ionisation winds, also known as cold winds, are likely active during most of the outburst (Sánchez-Sierras & Muñoz-Darias 2020). Interestingly, both X-ray and optical-to-infrared (OIR) wind detections occurred in systems with relatively high orbital inclinations, which is commonly interpreted as the wind having an equatorial geometry (e.g., Ponti et al. 2012; but see Higginbottom et al. 2019).

MAXI J1348–630 (J1348 hereafter) is a new LMXB, discovered during an outburst episode on 2019 January 26 (Yatabe et al. 2019) by the Monitor of All-sky X-ray Image (MAXI) nova alert system (Matsuoka et al. 2009). The peak X-ray flux was measured on February 10 (∼1.0 × 10−7 erg cm−2 s−1; Lamer et al. 2021; Carotenuto et al. 2021), and the highest reported optical flux (g′=16.1) was measured on February 5 (Baglio et al. 2019). A hard-to-soft transition began on February 3 (Nakahira et al. 2019). X-ray studies using the Neutron Star Interior Composition Explorer (NICER) revealed type-B quasi-periodic oscillations between February 8 and 26 (Belloni et al. 2020; Zhang et al. 2021, 2022), associated with the soft-intermediate state (SIMS). The main outburst lasted ∼3 months and was followed by a few hard-state-only re-brightenings (Russell et al. 2019b; Pirbhoy et al. 2020; Negoro et al. 2020; Baglio et al. 2020; Zhang et al. 2020; Corral-Santana et al. 2016; see also Cúneo et al. 2020a). This transient is estimated to be at ∼2–3 kpc (Chauhan et al. 2021; Russell et al. 2019a; Lamer et al. 2021) and has been suggested to harbour a BH, based on its spectral and timing properties (Sanna et al. 2019; Belloni et al. 2020; Zhang et al. 2020).

In this paper we present multi-epoch spectroscopy of J1348 obtained with X-shooter at the Very Large Telescope (VLT), which covers ultraviolet, optical, and near-infrared wavelengths. We study the presence or absence of the most typical LMXB emission lines, as well as the evolution of their main properties.

2. Observations and data reduction

A total of 12 epochs of spectroscopy were obtained between February and May 2019 with X-shooter (Vernet et al. 2011) at the VLT-UT2 in Cerro Paranal, Chile. We obtained photometric magnitudes for the epochs with available acquisition images, which are presented in the observing log (Table 1). Each spectral observation included 4–16 exposures in nodding configuration with total exposure times of 1100–4500 s and covering from 3000 to 25 000 Å between the three arms of the instrument. We used slit widths of 1.0″–1.3″, 0.9″–1.2″, and 0.9″–1.2″ for the ultraviolet (UVB), visible (VIS), and infrared (NIR) arms, producing velocity resolutions of ∼55–73, ∼34–46, and ∼53–70 km s−1, respectively. Airmasses ranged from 1.28 to 1.95.

Table 1.

Summary of the observing campaign.

The spectra were reduced using the X-shooter ESO Pipeline v3.3.5. Flux calibration standard stars in epochs #3–5 and #8–9 were not bright enough in the infrared. Therefore, those spectra were calibrated with the standard star from epoch #10. Atmospheric telluric absorptions in optical and infrared ranges were corrected using MOLECFIT (Smette et al. 2015; Kausch et al. 2015), and the continuum adjacent to each spectral line of interest was individually normalised for a detailed study.

3. Analysis and results

J1348 was first detected on 2019 January 26 (MJD 58509) and it was X-ray active for ∼100 days. The upper panel of Fig. 1 shows its X-ray light curve, which follows the usual fast rise (∼10 days) and a slower decay towards quiescence. The lower panel in Fig. 1 shows the hardness-intensity diagram (HID; Homan et al. 2001) of daily averaged count rates from MAXI, where the X-ray colour is defined as the ratio between hard (4−20 keV) and soft (2−4 keV) count rates. The source displays the characteristic hysteresis pattern commonly observed in LMXBs during outbursts (Muñoz-Darias et al. 2014). According to this diagram, we consider epoch #1 to be in the hard-to-soft transition (most likely in the hard-intermediate state), #2–6 in the SIMS (type-B quasi-periodic oscillations reported in Belloni et al. 2020; Zhang et al. 2020), #7–10 in the soft state, and #11–12 in the low-luminosity hard state; in this last phase, the source was returning to quiescence. A summary of the observations and associated X-ray states is shown in Table 1.

thumbnail Fig. 1.

Light curve (upper panel) and HID (lower panel) of J1348 during its 2019 outburst (MAXI data between MJD 58509 and 58634). The small grey dots represent X-ray data, and the coloured symbols mark the interpolated position for each X-shooter epoch. For the HID we only considered data with count rates exceeding 0.025 photons cm−2 s−1 in each band. The X-ray colour is defined as the ratio between the hard (4–20 keV) and the soft (2–4 keV) count rates. The source displays the classic hysteresis loop in the anticlockwise direction.

3.1. Spectral evolution

The OIR spectrum of J1348 varied as the outburst evolved, with the most prominent emission lines observed during the last epochs (i.e., hard states; epochs #11–12). We observed several hydrogen emission lines in the broad spectral range covered, from the Balmer, Paschen, and Brackett series (as an example, see epoch #5 spectra in Fig. 2). Helium lines such as He II at 4686 Å (He II–4686), He I–5876, He I–6678, and He I–10830 are also visible. Figure 3 shows the evolution of the main emission lines across the observing campaign. All of them were individually normalised by fitting a first-order polynomial to their local continuum with the emission line masked (and the underlying absorption also masked in Balmer lines).

thumbnail Fig. 2.

Normalised OIR spectrum during epoch #5. Relevant emission lines are labelled, and prominent DIBs are shaded in grey.

thumbnail Fig. 3.

Evolution of the most relevant emission lines. The colour code is the same as in Fig. 1. The vertical dashed blue and dashed-dotted red lines mark ±1700 km s−1 and −500 km s−1, velocities of the blue wing and the absorption trough of Paβ, respectively (in epochs #2 and #6). Grey bands indicate regions contaminated by DIBs or tellurics. The emission at −2500 km s−1 in the He II–4686 column is produced by the Bowen blend.

The Hα line shows intense, double-peaked profiles in many epochs. The peak-to-peak separation increases as the outburst evolves, from 310 ± 150 km s−1 in epoch #1 to a maximum of 600 ± 70 km s−1 in the last epoch. This behaviour, revealed by two-Gaussian models fitted to the line (with all parameters free to vary), has been observed in other systems and interpreted as an indication of the disc shrinking towards the end of the outburst (e.g., Casares et al. 2019; Mata-Sánchez et al. 2015a; Torres et al. 2015; Corral-Santana et al. 2013). This line shows an asymmetric profile and broad wings reaching ∼±1500 km s−1 in epoch #1 (see Figs. 3 and 4), while a flat-top profile is visible in epoch #6. An underlying broad absorption component (from ∼–2000 to ∼1700 km s−1) is also present during most epochs, a feature that is relatively commonly observed in LMXBs in outburst (Soria et al. 2000; Casares et al. 1995; Yao et al. 2021). This is also present in Hβ and Hγ (see e.g., Fig. 2).

thumbnail Fig. 4.

Hα, He I–5876, and Paβ profiles in epochs #1, 2, 6, and 10 (re-binned by a factor of two). Vertical lines and colours have the same meanings as in previous figures.

The Hβ line shows emission profiles similar to those of Hα, although much less intense. This line also shows broad absorptions in every epoch, and they are particularly clear in epochs #5–12 (∼10% below the continuum, reaching ∼±3000 km s−1). This specially prominent and redshifted absorption has been observed in other transients in outburst (e.g., Cúneo et al. 2020b) and is most likely a combination of the aforementioned Balmer broad absorption component and an additional contribution from a broad diffuse interstellar band (DIB) at ∼4882 Å with a full width at half maximum of ∼20 Å (e.g., Kaur et al. 2012; Jenniskens & Désert 1994; Buxton & Vennes 2003).

The Paβ profiles are qualitatively similar, but broader and less intense than the Hα profiles. In addition, several lines from the Paschen series show flat-top-like profiles in epochs #4, #6, and #9. Similar boxy line profiles are also observed in high-order Brackett lines during epochs #2 and #4 (e.g., Br-10, 11, and 12, which are similar to those seen in other transitions; see Fig. 3). The Brγ line shows profiles similar to those of Paβ (Fig. 3) except for the less prominent ones in the harder epochs (#1, #11–12), as observed in other transients (Sánchez-Sierras & Muñoz-Darias 2020).

Finally, He I–10830 is generally the most intense He line. It shows line profiles very similar to those of Hα, but with more prominent double peaks. Its peak-to-peak separation also increases as the outburst evolves, from 400 ± 60 km s−1 to a maximum of 590 ± 90 km s−1 in epoch #12. Other typical He lines, such as He I–5876 and He II–4686, are also visible. The latter, which is expected to trace hotter (inner) gas, shows boxy or double-peaked profiles (characteristic of gas rotating in an accretion disc; e.g., Smak 1969) depending on the epoch (see Fig. 3).

3.2. Outflow features: blueshifted absorption troughs and broad wings

As mentioned above, during some stages of the outburst several spectral lines display features that could be interpreted as signatures of accretion disc winds. These include blueshifted absorptions, broad emission line wings, and line profiles with asymmetries or flat tops. Figures 3 and 4 show the presence of a blueshifted absorption trough centred at −500 km s−1 in epochs #2 and #6 in Hβ, He I–5876, Hα, and Paβ (dashed-dotted red line). In the first three cases, this feature resembles the blueshifted absorption of a P-Cygni profile. However, due to the broader profile of Paβ, the absorption trough is observed as a dent on its blue wing. Figure 5 shows that this feature is not visible in Paγ nor Brγ. It is worth noting that the blueshifted absorption becomes visible again in the soft state (epoch #10), but in this case only in Paβ (see Fig. 4). Interestingly, the profile of Paβ in epochs #2 and #6 also suggests the presence of an underlying broader emission component, whose blue wing reaches ∼−1700 km s−1 (blue vertical dashed line in Figs. 3–5) and the red one ∼+1000 km s−1. This velocity is similar to that of the aforementioned broad absorption components best seen in Hα in epoch #1 (∼±1700 km s−1; see Fig. 5).

thumbnail Fig. 5.

Paβ profiles (solid line) compared to Hα, Paγ, and Brγ (dashed line) in epochs #2 (upper panel) and #6 (lower panel). Spectral lines are re-binned by a factor of three for clarity. Vertical lines and colours have the same meaning as in previous figures.

3.3. The excesses diagnostic diagram

Some of the spectral features revealed by visual inspection suggest the presence of an outflow in the system (see above). In a second step, we performed a systematical inspection using the excesses diagnostic diagram. This tool was introduced by Mata Sánchez et al. (2018) and is based on studying the deviation of the spectral line wings from a pure Gaussian profile. The coordinates of each epoch in the diagram are the so-called red and blue excesses (EWr+ and EWb−), defined as the equivalent width (EW) of the line wings after subtracting the Gaussian model (see Muñoz-Darias et al. 2019; Panizo-Espinar et al. 2021 for details). Thus, an epoch with a P-Cygni profile (i.e., red emission and blue absorption, thus EWr+ >  0 and EWb− <  0) would lie in the bottom-right quadrant, while broad wings would make it fall in the top-right one (i.e., red and blue emission, EWr+ >  0 and EWb− >  0).

Although this method is generally applied to Hα, in this case the results are inconclusive due to the variable contamination by the underlying broad absorption component. We tried a multi-Gaussian fitting to model the broad absorption, but it did not provide meaningful results. The Paβ line, on the other hand, shows significant (> 5σ), positive red and blue wing residuals during epoch #2, measured in the (±)700–1500 km s−1 velocity bands (Fig. 6). This is consistent with the presence of broad wings, as suggested by the visual inspection. No P-Cygni profiles are revealed by the diagram, which is an expected outcome given that the blueshifted absorptions appear as small dents (with small EWs) on Paβ (see Sect. 3.2).

thumbnail Fig. 6.

Paβ excesses diagnostic diagram. Symbols and colour codes have the same meanings as in Fig. 1. The grey region and dotted line indicate the 3σ and 5σ contours, respectively. Epochs showing wind-related signatures are expected to lie in the right quadrants.

4. Discussion

We have presented OIR spectroscopy of J1348 during its 2019 discovery outburst. We studied the evolution of the main spectral lines throughout the entire accretion episode, paying special attention to those particularly sensitive to outflows. We find several spectral features commonly associated with the presence of an accretion disc wind.

Firstly, a blueshifted absorption trough is seen at −500 km s−1 during the bright SIMS (epoch #2 and #6) in Hβ, He I–5876, Hα, and Paβ (see Figs. 4 and 5). The fact that this narrow feature is simultaneously observed at the same velocity in four different lines rules it out as an artefact (e.g. deficient sky subtraction) or as having a DIB origin. This absorption at −500 km s−1 is present again in Paβ during the soft state (epoch #10; see Fig. 4).

Secondly, broad emission line wings are spotted in Hα during epoch #1, reaching ∼±1500 km s−1, and in Paβ during epoch #2, reaching ∼−1700 km s−1 (see Fig. 4 and Sect. 3.3). Profiles with broad wings can be interpreted as signatures of outflows (e.g., Muñoz-Darias et al. 2018; Panizo-Espinar et al. 2021; see also Prinja et al. 1996 for winds in massive stars).

Finally, several Balmer and helium lines, such as Hα, He I–5876, and He I–10830, are asymmetric with a negative skew (i.e., the emission peak appears redshifted compared to the rest wavelength) in epoch #1 (hard-intermediate state; Fig. 3). Similar profiles are commonly seen in systems that show conspicuous signatures of outflows (e.g., Muñoz-Darias et al. 2019).

Additionally, flat-top profiles are observed in epoch #2 in several hydrogen lines of the Paschen and Brackett series (Paγ, Paδ, Pa-9, Pa-10, Pa-11, Br-10, and Br-11), in epoch #6 in Hα, Paschen, and helium lines (He I–5876 and He I–10830), and epochs #9–10 in Paschen and Brackett series (see Fig. 3), suggesting the presence of the wind through the soft state. These profiles are also present (albeit with a weak central absorption) in the Balmer series and He I lines during the final hard state epochs, #11–12 (Fig. 3). Similar features are commonly detected in novae and Wolf-Rayet stars (Beals 1931; Vainu Bappu & Menzel 1954; Williams & Mason 2010) and are generally understood as a signature of expanding envelopes (i.e., outflows; e.g., Soria et al. 2000).

Overall, at least four different wind-related spectral features are visible in J1348: blueshifted absorption troughs, broad emission line wings, asymmetries, and flat-top profiles, some of which appear simultaneously in several spectral lines. We interpret these features as evidence of an OIR accretion disc wind present during most of the brightest phase of the outburst. Unfortunately, we note that we were not able to monitor the system during the initial hard state, and in particular during the hard state peak, a stage in which other systems have shown the most conspicuous optical wind signatures (e.g., MAXI J1820+070, Muñoz-Darias et al. 2019; GRS 1716−249, Cúneo et al. 2020a; MAXI J1803−298, Mata Sánchez et al. 2022). We also note that the possible presence of accretion disc winds in J1348 during previous activity phases of the system would support the hypothesis of them contributing to create a low density cavity in which the system seems to be embedded (Carotenuto et al. 2021), as suggested by other authors (Carotenuto et al. 2022).

4.1. Comparison with other systems

As summarised in Table 2, OIR accretion disc winds have been detected in a number of LMXBs during outbursts. Most cases are BH transients with conspicuous wind features present during the hard state, although there are also examples of OIR winds found in NS systems (Bandyopadhyay et al. 1999; Muñoz-Darias et al. 2020). In particular, most detections correspond to P-Cygni profiles observed in high inclination (> 60°) sources, with blue-edge velocities indicating relatively high velocity outflows (1200–3000 km s−1). This prototypical wind signature is not particularly obvious in our dataset. However, we find weak, blueshifted absorption troughs in several lines in epochs #2 and #6. In particular, the blue-edge velocity of this absorption in He I–5876 points to a terminal velocity of ∼900 km s−1, lower than the OIR wind velocities measured in other LMXBs (Table 2). There are also other (somewhat more tentative) wind features (e.g., broad emission line wings in Rahoui et al. 2014; Soria et al. 2000; Panizo-Espinar et al. 2021), which typically reach higher velocities than those inferred from the P-Cygni profiles (see e.g., Muñoz-Darias et al. 2018, 2019). This is also the case for J1348, where the emission line wings of Hα reach considerably higher values (∼1500 km s−1) than the narrow, blueshifted absorptions (500–900 km s−1). This might be explained by a dissimilar dependence of the various wind signatures on the orbital inclination, with blueshifted absorptions being particularly sensitive to the presence of outflowing material along the line-of-sight (see Sect. 4).

Table 2.

Characteristics of LMXBs with OIR winds and properties of the outflow.

Among the systems in Table 2, the comparison with MAXI J1820+070 is particularly relevant. This BH transient showed a variety of wind signatures during its 2018 outburst, which also followed a standard evolution with hard and soft states. Specifically, Paβ and Paγ showed absorption troughs with kinetic properties (wind velocity of 1200–2000 km s−1) similar to those derived from P-Cygni profiles present in other spectral lines (Sánchez-Sierras & Muñoz-Darias 2020). This is consistent with the behaviour of J1348, where the absorption features in Paβ indicate the same velocity as those found in Hα and He I–5876.

4.2. On the state dependence of the wind features

The comparison of J1348 with other LMXBs allows us to revisit the state dependence of the wind-related OIR features. In J1348, the most compelling evidence for winds is arguably found during the SIMS, while the strongest optical winds are usually found at the hard state peak. A possible exception would be the first soft observation of MAXI J1820+070 (Muñoz-Darias et al. 2019), which was obtained right after the hard-to-soft transition (i.e., similar to epoch #2 in this paper).

Our observations did not cover the bright hard state. Nonetheless, additional OIR wind features were observed during the hard-intermediate state (e.g., strong asymmetries in Hα and He I–10830) and the final (low-luminosity) hard state (flat-top profiles in the Balmer and He I lines). Wind-related features are only detected in the infrared lines (e.g., blueshifted absorptions in Paβ and flat-top profiles in the Paschen and Brackett series) during the soft state. This is consistent with the results (from MAXI J1820+070) presented by Sánchez-Sierras & Muñoz-Darias (2020). They reported on the detection of infrared wind-related features during most of the outburst, whereas the optical ones were absent during the soft state. Thus, our results reinforce a scenario in which accretion disc winds are active during the whole outburst, although they are spotted at different wavelengths depending on the X-ray state. This dependence might be related to ionisation effects that make the infrared lines more sensitive to winds during the soft state (see Sánchez-Sierras & Muñoz-Darias 2020 and references therein).

4.3. On the orbital inclination

J1348 does not show dips or eclipses, which suggests it is not a high inclination system. In fact, a mid-to-low inclination is supported by the orientation of the jet (i = 29° ± 3°; Carotenuto et al. 2022) assuming that there is not a strong misalignment between the jet and the orbital plane. Although our analysis is not focused on this issue, the HID (Fig. 1) supports this conclusion since it shows a squared q-shape evolution (with an almost horizontal hard-to-soft transition), a suggested property of BH LMXBs with mid-to-low inclinations (Muñoz-Darias et al. 2013).

In addition, some spectral lines, such as Hα and He I–10830 (Fig. 3), are double-peaked, which might be interpreted as a relatively high inclination feature. However, peak-to-peak separations for Hα seem to be narrower (300–600 km s−1; see Sect. 3) than those measured in high inclination LMXBs (e.g., ∼1900 km s−1 in MAXI J1659−152, Torres et al. 2021, ∼1200 km s−1 in XTE J1118+480 Torres et al. 2002 or 500−1100 km s−1 in MAXI J1803−298, Mata Sánchez et al. 2022).

Overall, a mid-to-low inclination is favoured by all the available observables. This might explain the peculiar observational properties of the wind in this object. For instance, a predominantly equatorial wind would be detected with a lower (projected) velocity in a low inclination system. In addition, this would make it more difficult to form blueshifted absorptions that reach fluxes below the continuum level since the contribution from the accretion disc emission lines is larger at low velocities (i.e., as the blueshifted absorption moves closer to the core of the disc line). Therefore, unless the wind features are very strong, one might naturally expect to detect them as low velocity absorption troughs qualitatively similar to those reported in this work.

5. Summary and conclusions

We have presented OIR spectroscopy of the BH candidate MAXI J1348–630 obtained during its discovery outburst in 2019. We report the detection of several spectral features that are commonly associated with the presence of outflows. In particular, we find:

  • Blueshifted absorption troughs during the SIMS (Hβ, He I–5876, Hα and Paβ) and the soft state (Paβ). They are centred at −500 km s−1.

  • Broad emission line wings (Hα and Paβ) reaching velocities of up to ±1700 km s−1, as well as asymmetric lines with a negative skew and flat-top profiles. They are seen at different stages of the outburst.

We interpret these features as signatures of a cold (OIR) accretion disc wind that is present during, at least, the brightest phases of the accretion episode. The apparently lower velocity of the blueshifted absorptions as compared to those seen in other LMXBs might be related to the mid-to-low orbital inclination of the system. Further spectroscopic observations of the system are encouraged during both quiescence and forthcoming outbursts in order to determine its fundamental parameters and better characterise the properties of the wind.

Acknowledgments

We are thankful to the anonymous referee for constructive comments that have improved this paper. DMS and MAP acknowledge support from the Consejería de Economía, Conocimiento y Empleo del Gobierno de Canarias and the European Regional Development Fund (ERDF) under grant with reference ProID2020010104 and ProID2021010132. TMD and MAPT acknowledge support via the Ramón y Cajal Fellowships RYC-2015-18148 and RYC-2015-17854, respectively. KIIK acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101002352) and from the Academy of Finland projects 320045 and 320085. GP acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 865637). This work has been supported in part by the Spanish Ministry of Science under grants AYA2017-83216-P, PID2020-120323GB-I00 and EUR2021-122010. MOLLY software developed by Tom Marsh is gratefully acknowledged. Based on observations collected at the European Southern Observatory under ESO programmes 0102.D-0309(A) and 0102.D-0799(A). This research has made use of MAXI data provided by RIKEN, JAXA and the MAXI team.

References

  1. Baglio, M. C., Russell, D. M., Bramich, D., & Lewis, F. 2019, ATel, 12491, 1 [NASA ADS] [Google Scholar]
  2. Baglio, M. C., Russell, D. M., Bramich, D. M., et al. 2020, ATel, 13710, 1 [NASA ADS] [Google Scholar]
  3. Bandyopadhyay, R. M., Shahbaz, T., Charles, P. A., & Naylor, T. 1999, MNRAS, 306, 417 [Google Scholar]
  4. Beals, C. S. 1931, MNRAS, 91, 966 [NASA ADS] [CrossRef] [Google Scholar]
  5. Beer, M. E., & Podsiadlowski, P. 2002, MNRAS, 331, 351 [NASA ADS] [CrossRef] [Google Scholar]
  6. Belloni, T. M., Motta, S. E., & Muñoz-Darias, T. 2011, Bull. Astron. Soc. India, 39, 409 [Google Scholar]
  7. Belloni, T. M., Zhang, L., Kylafis, N. D., Reig, P., & Altamirano, D. 2020, MNRAS, 496, 4366 [NASA ADS] [CrossRef] [Google Scholar]
  8. Buisson, D. J. K., Hare, J., Guver, T., et al. 2020, ATel, 13563, 1 [Google Scholar]
  9. Buisson, D. J., Altamirano, D., Armas Padilla, M., et al. 2021, MNRAS, 503, 5600 [NASA ADS] [CrossRef] [Google Scholar]
  10. Buxton, M., & Vennes, S. 2003, MNRAS, 342, 105 [NASA ADS] [CrossRef] [Google Scholar]
  11. Carotenuto, F., Corbel, S., Tremou, E., et al. 2021, MNRAS, 504, 444 [NASA ADS] [CrossRef] [Google Scholar]
  12. Carotenuto, F., Tetarenko, A. J., & Corbel, S. 2022, MNRAS, 511, 4826 [NASA ADS] [CrossRef] [Google Scholar]
  13. Casares, J., Charles, P. A., Jones, D. H. P., Rutten, R. G. M., & Callanan, P. J. 1991, MNRAS, 250, 712 [NASA ADS] [CrossRef] [Google Scholar]
  14. Casares, J., Marsh, T. R., Charles, P. A., et al. 1995, MNRAS, 274, 565 [NASA ADS] [CrossRef] [Google Scholar]
  15. Casares, J., Muñoz-Darias, T., Mata Sánchez, D., et al. 2019, MNRAS, 488, 1356 [NASA ADS] [CrossRef] [Google Scholar]
  16. Castro Segura, N., Knigge, C., Long, K. S., et al. 2022, Nature, 603, 52 [NASA ADS] [CrossRef] [Google Scholar]
  17. Chaty, S., Charles, P. A., Martí, J., et al. 2003, MNRAS, 343, 169 [NASA ADS] [CrossRef] [Google Scholar]
  18. Chauhan, J., Miller-Jones, J. C., Raja, W., et al. 2021, MNRAS, 501, 60 [Google Scholar]
  19. Chevalier, C., & Ilovaisky, S. A. 1991, A&A, 251, L11 [NASA ADS] [Google Scholar]
  20. Corral-Santana, J. M., Casares, J., Muñoz-Darias, T., et al. 2013, Sci, 339, 1048 [CrossRef] [Google Scholar]
  21. Corral-Santana, J. M., Casares, J., Munoz-Darias, T., et al. 2016, A&A, 587, A61 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  22. Cúneo, V. A., Alabarta, K., Zhang, L., et al. 2020a, MNRAS, 496, 1001 [CrossRef] [Google Scholar]
  23. Cúneo, V. A., Muñoz-Darias, T., Sánchez-Sierras, J., et al. 2020b, MNRAS, 498, 25 [CrossRef] [Google Scholar]
  24. Díaz Trigo, M., & Boirin, L. 2016, Astron. Nachrichten, 337, 368 [CrossRef] [Google Scholar]
  25. Díaz Trigo, M., Sidoli, L., Boirin, L., & Parmar, A. N. 2012, A&A, 543, A50 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  26. Done, C., Gierliński, M., & Kubota, A. 2007, A&AR, 15, 1 [NASA ADS] [CrossRef] [Google Scholar]
  27. Fender, R., & Muñoz-Darias, T. 2016, in Lect. Notes Phys., eds. F. Haardt, V. Gorini, U. Moschella, A. Treves, & M. Colpi (Cham: Springer International Publishing), 905, 65 [NASA ADS] [CrossRef] [Google Scholar]
  28. Fender, R. P., Belloni, T. M., & Gallo, E. 2004, MNRAS, 355, 1105 [NASA ADS] [CrossRef] [Google Scholar]
  29. Fomalont, E. B., Geldzahler, B. J., & Bradshaw, C. F. 2001, ApJ, 558, 283 [Google Scholar]
  30. Gallo, E., Fender, R. P., & Pooley, G. G. 2003, MNRAS, 344, 60 [Google Scholar]
  31. Gilfanov, M. 2010, Jet Paradig. Lect. Notes Phys., 794, 17 [NASA ADS] [CrossRef] [Google Scholar]
  32. Gottlieb, E. W., Wright, E. L., & Liller, W. 1975, ApJ, 195, L33 [Google Scholar]
  33. Heida, M., Jonker, P. G., Torres, M. A. P., & Chiavassa, A. 2017, ApJ, 846, 132 [Google Scholar]
  34. Higginbottom, N., Knigge, C., Long, K. S., Matthews, J. H., & Parkinson, E. J. 2019, MNRAS, 484, 4635 [NASA ADS] [CrossRef] [Google Scholar]
  35. Homan, J., Wijnands, R., van der Klis, M., et al. 2001, ApJS, 132, 377 [NASA ADS] [CrossRef] [Google Scholar]
  36. Homan, J., Neilsen, J., Allen, J. L., et al. 2016, ApJ, 830, L5 [Google Scholar]
  37. Homan, J., Gendreau, K. C., Sanna, A., et al. 2021, ATel, 14606, 1 [NASA ADS] [Google Scholar]
  38. Iaria, R., Di Salvo, T., Burderi, L., et al. 2014, A&A, 561, A99 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Jenniskens, P., & Désert, F.-X. 1994, A&AS, 106, 9 [NASA ADS] [Google Scholar]
  40. Jiménez-Ibarra, F., Muñoz-Darias, T., Casares, J., Padilla, M. A., & Corral-Santana, J. M. 2019, MNRAS, 489, 3420 [CrossRef] [Google Scholar]
  41. Kaur, R., Kaper, L., Ellerbroek, L. E., et al. 2012, ApJ, 746, L23 [NASA ADS] [CrossRef] [Google Scholar]
  42. Kausch, W., Noll, S., Smette, A., et al. 2015, A&A, 576, A78 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  43. Khargharia, J., Froning, C. S., & Robinson, E. L. 2010, ApJ, 716, 1105 [NASA ADS] [CrossRef] [Google Scholar]
  44. Lamer, G., Schwope, A. D., Predehl, P., et al. 2021, A&A, 647, A7 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  45. Lindstrøm, C., Griffin, J., Kiss, L. L., et al. 2005, MNRAS, 363, 882 [CrossRef] [Google Scholar]
  46. Macdonald, R. K., Bailyn, C. D., Buxton, M., et al. 2014, ApJ, 784, 2 [NASA ADS] [CrossRef] [Google Scholar]
  47. Mata-Sánchez, D., Muñoz-Darias, T., Casares, J., Corral-Santana, J. M., & Shahbaz, T. 2015a, MNRAS, 454, 2199 [CrossRef] [Google Scholar]
  48. Mata Sánchez, D., Muñoz-Darias, T., Casares, J., et al. 2015b, MNRAS, 449, L1 [CrossRef] [Google Scholar]
  49. Mata Sánchez, D., Muñoz-Darias, T., Casares, J., & Jiménez-Ibarra, F. 2017, MNRAS, 464, L41 [CrossRef] [Google Scholar]
  50. Mata Sánchez, D., Muñoz-Darias, T., Casares, J., et al. 2018, MNRAS, 481, 2646 [Google Scholar]
  51. Mata Sánchez, D., Muñoz-Darias, T., Cúneo, V. A., et al. 2022, ApJ, 926, L10 [CrossRef] [Google Scholar]
  52. Matsuoka, M., Kawasaki, K., Ueno, S., et al. 2009, PASJ, 61, 999 [Google Scholar]
  53. McClintock, J. E., & Remillard, R. A. 2006, Compact Stellar X-ray Sources (Cambridge, UK: Cambridge University Press), 39, 157 [NASA ADS] [CrossRef] [Google Scholar]
  54. Muñoz-Darias, T., Coriat, M., Plant, D. S., et al. 2013, MNRAS, 432, 1330 [Google Scholar]
  55. Muñoz-Darias, T., Fender, R. P., Motta, S. E., & Belloni, T. M. 2014, MNRAS, 443, 3270 [CrossRef] [Google Scholar]
  56. Muñoz-Darias, T., Casares, J., Mata Sánchez, D., et al. 2016, Nature, 534, 75 [Google Scholar]
  57. Muñoz-Darias, T., Casares, J., Mata Sánchez, D., et al. 2017, MNRAS, 465, L124 [Google Scholar]
  58. Muñoz-Darias, T., Torres, M. A. P., & Garcia, M. R. 2018, MNRAS, 479, 3987 [CrossRef] [Google Scholar]
  59. Muñoz-Darias, T., Jiménez-Ibarra, F., Panizo-Espinar, G., et al. 2019, ApJ, 879, L3 [CrossRef] [Google Scholar]
  60. Muñoz-Darias, T., Armas Padilla, M., Jiménez-Ibarra, F., et al. 2020, ApJ, 893, L19 [CrossRef] [Google Scholar]
  61. Nakahira, S., Kawai, N., Negoro, H., et al. 2019, ATel, 12469, 1 [NASA ADS] [Google Scholar]
  62. Negoro, H., Nakajima, M., Aoki, M., et al. 2020, ATel, 13994, 1 [NASA ADS] [Google Scholar]
  63. Neilsen, J., & Lee, J. C. 2009, Nature, 458, 481 [NASA ADS] [CrossRef] [Google Scholar]
  64. Orosz, J. A., Kuulkers, E., van der Klis, M., et al. 2001, ApJ, 555, 489 [NASA ADS] [CrossRef] [Google Scholar]
  65. Panizo-Espinar, G., Muñoz-Darias, T., Armas Padilla, M., et al. 2021, A&A, 650, A135 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  66. Pirbhoy, S. F., Baglio, M. C., Russell, D., et al. 2020, ATel, 13451, 1 [NASA ADS] [Google Scholar]
  67. Ponti, G., Fender, R. P., Begelman, M. C., et al. 2012, MNRAS, 422, 11 [Google Scholar]
  68. Ponti, G., Muñoz-Darias, T., & Fender, R. P. 2014, MNRAS, 444, 1829 [NASA ADS] [CrossRef] [Google Scholar]
  69. Prinja, R. K., Fullerton, A. W., & Crowther, P. A. 1996, A&A, 311, 264 [NASA ADS] [Google Scholar]
  70. Rahoui, F., Coriat, M., & Lee, J. C. 2014, MNRAS, 442, 1610 [Google Scholar]
  71. Russell, D. M., Miller-Jones, J. C. A., Maccarone, T. J., et al. 2011, A&A, 739, L19 [Google Scholar]
  72. Russell, D. M., Baglio, C. M., Lewis, F., et al. 2019a, ATel, 12439, 1 [NASA ADS] [Google Scholar]
  73. Russell, D. M., Bramich, D. M., Lewis, F., et al. 2019b, Astron. Nachr., 340, 278 [NASA ADS] [CrossRef] [Google Scholar]
  74. Sánchez-Sierras, J., & Muñoz-Darias, T. 2020, A&A, 640, L3 [EDP Sciences] [Google Scholar]
  75. Sanna, A., Uttley, P., Altamirano, D., et al. 2019, ATel, 12447, 1 [NASA ADS] [Google Scholar]
  76. Shakura, N. I., & Sunyaev, R. A. 1973, IAU Symp., 55, 155 [Google Scholar]
  77. Smak, J. 1969, AcA, 19, 155 [NASA ADS] [Google Scholar]
  78. Smette, A., Sana, H., Noll, S., et al. 2015, A&A, 576, A77 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  79. Soria, R., Wu, K., & Hunstead, R. W. 2000, ApJ, 539, 445 [NASA ADS] [CrossRef] [Google Scholar]
  80. Torres, M. A. P., Callanan, P. J., Garcia, M. R., et al. 2002, ApJ, 569, 423 [NASA ADS] [CrossRef] [Google Scholar]
  81. Torres, M. A., Jonker, P. G., Miller-Jones, J. C., et al. 2015, MNRAS, 450, 4292 [NASA ADS] [CrossRef] [Google Scholar]
  82. Torres, M. A. P., Casares, J., Jiménez-Ibarra, F., et al. 2019, ApJ, 882, L21 [NASA ADS] [CrossRef] [Google Scholar]
  83. Torres, M. A. P., Casares, J., Jiménez-Ibarra, F., et al. 2020, ApJ, 893, L37 [NASA ADS] [CrossRef] [Google Scholar]
  84. Torres, M. A., Jonker, P. G., Casares, J., Miller-Jones, J. C., & Steeghs, D. 2021, MNRAS, 501, 2174 [NASA ADS] [CrossRef] [Google Scholar]
  85. Ueda, Y., Inoue, H., Tanaka, Y., et al. 1998, ApJ, 492, 782 [NASA ADS] [CrossRef] [Google Scholar]
  86. Vainu Bappu, M. K., & Menzel, D. H. 1954, ApJ, 119, 508 [NASA ADS] [CrossRef] [Google Scholar]
  87. van der Hooft, F., Heemskerk, M. H. M., Alberts, F., et al. 1998, A&A, 329, 538 [NASA ADS] [Google Scholar]
  88. Vernet, J., Dekker, H., D’Odorico, S., et al. 2011, A&A, 536, A105 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  89. Williams, R., & Mason, E. 2010, Ap&SS, 327, 207 [NASA ADS] [CrossRef] [Google Scholar]
  90. Xu, Y., Harrison, F., Xu, Y., & Harrison, F. 2021, ATel, 14609, 1 [NASA ADS] [Google Scholar]
  91. Yao, Y., Kulkarni, S. R., Burdge, K. B., et al. 2021, ApJ, 920, 120 [NASA ADS] [CrossRef] [Google Scholar]
  92. Yatabe, F., Negoro, H., Nakajima, M., et al. 2019, ATel, 12425, 1 [NASA ADS] [Google Scholar]
  93. Zhang, L., Altamirano, D., Cúneo, V. A., et al. 2020, MNRAS, 499, 851 [NASA ADS] [CrossRef] [Google Scholar]
  94. Zhang, L., Altamirano, D., Uttley, P., et al. 2021, MNRAS, 505, 3823 [NASA ADS] [CrossRef] [Google Scholar]
  95. Zhang, W., Tao, L., Soria, R., et al. 2022, ApJ, 927, 210 [NASA ADS] [CrossRef] [Google Scholar]

All Tables

Table 1.

Summary of the observing campaign.

In the text
Table 2.

Characteristics of LMXBs with OIR winds and properties of the outflow.

In the text

All Figures

thumbnail Fig. 1.

Light curve (upper panel) and HID (lower panel) of J1348 during its 2019 outburst (MAXI data between MJD 58509 and 58634). The small grey dots represent X-ray data, and the coloured symbols mark the interpolated position for each X-shooter epoch. For the HID we only considered data with count rates exceeding 0.025 photons cm−2 s−1 in each band. The X-ray colour is defined as the ratio between the hard (4–20 keV) and the soft (2–4 keV) count rates. The source displays the classic hysteresis loop in the anticlockwise direction.
In the text
thumbnail Fig. 2.

Normalised OIR spectrum during epoch #5. Relevant emission lines are labelled, and prominent DIBs are shaded in grey.
In the text
thumbnail Fig. 3.

Evolution of the most relevant emission lines. The colour code is the same as in Fig. 1. The vertical dashed blue and dashed-dotted red lines mark ±1700 km s−1 and −500 km s−1, velocities of the blue wing and the absorption trough of Paβ, respectively (in epochs #2 and #6). Grey bands indicate regions contaminated by DIBs or tellurics. The emission at −2500 km s−1 in the He II–4686 column is produced by the Bowen blend.
In the text
thumbnail Fig. 4.

Hα, He I–5876, and Paβ profiles in epochs #1, 2, 6, and 10 (re-binned by a factor of two). Vertical lines and colours have the same meanings as in previous figures.
In the text
thumbnail Fig. 5.

Paβ profiles (solid line) compared to Hα, Paγ, and Brγ (dashed line) in epochs #2 (upper panel) and #6 (lower panel). Spectral lines are re-binned by a factor of three for clarity. Vertical lines and colours have the same meaning as in previous figures.
In the text
thumbnail Fig. 6.

Paβ excesses diagnostic diagram. Symbols and colour codes have the same meanings as in Fig. 1. The grey region and dotted line indicate the 3σ and 5σ contours, respectively. Epochs showing wind-related signatures are expected to lie in the right quadrants.
In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.