EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 677 (September 2023) A&A, 677 (2023) A186 Full HTML
Open Access
Issue
A&A
Volume 677, September 2023
Article Number A186
Number of page(s) 17
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/202346797
Published online 27 September 2023

© The Authors 2023

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 stellar systems composed of a black hole or a neutron star accreting material from a Roche lobe filling low-mass (≲1 M⊙) companion, the donor star. A few hundred of these systems have been already discovered in our galaxy (e.g. Liu et al. 2007), including both persistently active X-ray sources and transient objects (e.g. Casares et al. 2017). However, thousands more are expected to exist, mainly as transient objects with recurrence periods longer than ~50 yr, the timescale sampled by X-ray astronomy (e.g. Corral-Santana et al. 2016; Tetarenko et al. 2016; Bahramian & Degenaar 2023).

The orbital period (Porb) is arguably the most important parameter of a binary system. Among other things, it is a proxy for its size, and thus the physical properties of its components. Regardless of their persistent or transient nature, classical LMXBs can be defined as those with hydrogen-burning donors (e.g. main-sequence stars). They have Porb in the range from 80 min to tens of days. Contrastingly, systems with Porb shorter than ~60–80 min are thought to harbour hydrogen-poor companions, which do not burn hydrogen in their cores and may contain electron-degenerate matter (Paczynski & Sienkiewicz 1981; Rappaport et al. 1982). LMXBs harbouring this kind of donor are known as ultra-compact X-ray binaries (UCXBs; see also Solheim 2010, for similar compact binaries with WD accre-tors). By hosting two ultra-dense objects in a close binary orbit, UCXBs are expected to play a crucial role in the new era of gravitational wave astronomy as they will be among the loudest persistent sources (Nelemans 2018; Tauris 2018; Chen et al. 2021). In addition, UCXBs are ideal targets to investigate and test some fundamental stages of binary evolution, such as the common-envelope phase, and are also unique laboratories to study accretion processes in hydrogen-deficient environments (Nelemans et al. 2009). We can distinguish three main UCXB evolutionary channels (see e.g. Nelemans et al. 2010 for a more extended description).

The white dwarf (WD) channel. In this scenario, the binary system is formed by a black hole or a neutron star, and a WD. The loss of angular momentum driven by gravitational wave emission shortens the binary period to a very compact configuration. At some point (generally at Porb of a few minutes), the WD overflows its Roche lobe and starts to transfer matter onto the more massive compact object, giving rise to a persistent UCXB. This also results in an expansion of the orbit. As Porb increases, the mass transfer rate decreases, making the system less luminous. The UCXB eventually becomes a transient source as the accretion disc becomes not fully ionised and no longer stable (Yungelson et al. 2002; Sengar et al. 2017; van Haaften et al. 2012b).

The helium star channel. The companion star is a low-mass helium star, which is still burning helium in its core at the time of filling its Roche lobe. Mass transfer occurs as the orbit shrinks, due to angular momentum loss via gravitational wave emission. A minimum Porb is reached (~ 10–60 min) when the helium core of the ≲0.2 M⊙ donor becomes semi-degenerate and its mass-radius relation inverts. This makes the companion star radius increase with further mass loss (Savonije et al. 1986; Iben & Tutukov 1987; Yungelson 2008; Nelemans et al. 2010). At this point, the orbit evolution reverses and the system expands as gravitational wave radiation cannot counteract the effect of mass transfer.

The evolved main-sequence star channel. The donor star is an evolved main-sequence star that started mass transfer near or just after the point of central hydrogen exhaustion. The orbit shrinks due to angular momentum loss via gravitational wave emission and magnetic braking, reaching orbital periods as short as ~10 min. Then, the growing helium core becomes semidegenerate and the system follows a similar path to that of the helium channel (e.g. Tutukov et al. 1985; Nelson et al. 1986; Podsiadlowski et al. 2002; Nelson & Rappaport 2003; Sengar et al. 2017).

Interestingly, the final outcome of these three channels is the same: an UCXB with a WD donor that is evolving towards longer orbital periods. The binary expansion is driven by conservation of angular momentum, as the less massive star (the WD) transfers mass to a heavier object. This slow evolutionary process could, in principle, increase Porb up to ~120 min in a Hubble time (van Haaften et al. 2012b,c). Thus, while Porb ≲ 80 min is a common observational diagnostic to separate UCXBs from the classic LMXB population (see e.g. Nelemans & Jonker 2010 and Heinke et al. 2013 for previous compilations of UCXBs), the former class might also include very old members with Porb up to 2 h. These long-period UCXBs are, however, difficult to detect because of their much lower accretion rates and luminosities.

Globular clusters (GCs) have been proposed to host a significant fraction of the UCXB population. The LMXB formation rate (per unit mass) in GCs is a hundred times higher than in the Galactic field (assuming that GCs account for ~0.01% of the Galactic stellar mass; Katz 1975). This overabundance is thought to be due to the fact that LMXB formation in GCs is strongly enhanced by dynamical encounters, such as tidal captures, direct collisions, and exchange interactions (Fabian et al. 1975; Hills 1976; Verbunt 1987; Rasio et al. 2000; Ivanova et al. 2005). As a consequence, the populations of UCXBs formed in GCs through each of the above evolutionary pathways may be different from those in the Galactic field. Therefore, the properties of the current (i.e. observable) populations of UCXBs in GCs and the Galactic field can be significantly different (e.g. distribution of Porb ; Zurek et al. 2009; Heinke et al. 2013).

Measuring Porb in UCXB systems is often difficult because of the short timescales and low luminosities involved. Therefore, the UCXB classification sometimes relies on a number of additional observational properties. The most direct ones, albeit not necessarily the most robust, are based on inferring the degenerate nature of the donor star from the chemical composition of the accreted material. These include (i) the lack of hydrogen features in the optical spectra (Nelemans et al. 2004; in ’t Zand et al. 2008; Hernández Santisteban et al. 2019; Armas Padilla et al. 2020; Stoop et al. 2021) together with the presence of helium and metallic lines (e.g. nitrogen and carbon; Nelemans et al. 2004; see also Homer et al. 2002; Tudor et al. 2018 for UV examples); (ii) the presence of X-ray features attributed to overabundances (i.e. non-solar composition) in the accreted material or the local interstellar medium (Schulz et al. 2001; Juett et al. 2001; Krauss et al. 2007, but see Juett & Chakrabarty 2005), and enhanced fluorescent lines (e.g. O VIII Lyα) due to X-ray reprocessing in an oxygen-rich accretion disc (see e.g. Madej et al. 2010; Schulz et al. 2010); and (iii) the properties of thermonuclear bursts, such as duration, recurrence time, and radiated energy, which can provide hints on the composition of the accreted fuel (e.g. Cumming 2003; Falanga et al. 2008; Galloway et al. 2020; see also Juett & Chakrabarty 2003). Additional diagnostics for identifying UCXBs are related to the small size of their accretion discs. First, UCXBs can be persistent sources at low X-ray luminosities (LXpers ≲1036 erg s−1) since smaller accretion discs can be entirely ionised at lower accretion rates (Lasota 2001; in ’t Zand et al. 2007). Second, given that the region of the disc emitting in the optical (via X-ray reprocessing) is also smaller, UCXBs show very low optical–to–X-ray flux ratios (van Paradijs & McClintock 1994).

In this paper we present a comprehensive catalogue of UCXBs, which we named UltraCompCAT, and that is available online1. Given the overall importance and very distinct features of the UCXB family, the main goal of this catalogue is to keep a complete and updated compilation of the current and future members of this LMXB subgroup, together with their observational properties. UltraCompCAT includes systems with a measured Porb shorter than 120 min and those without a solid Porb measurement, but which exhibit some of the UCXB-related features described above. The first version of the catalogue includes 49 LMXBs and is presented in Sect. 2. The most direct results derived from this compilation are presented in Sect. 3 and discussed in Sect. 4.

2 The catalogue

2.1 The sample

We searched the literature, collecting sources that can be divided in three main categories: ultra-compact, ultra-compact candidates, and short orbital period LMXBs. Each category is described below.

Ultra-compact X-ray binaries (UCXBs). These are LMXBs with orbital periods shorter than ~80 min. This category includes LMXBs with confirmed orbital period determinations (e.g. derived from Doppler shifts in X-ray pulsars) and systems for which strong constraints, such as those inferred from periodic flux modulations, are available. The latter group might include systems where the orbital period is not known with high precision, as modulations often reflect periodicities that may deviate slightly from the orbital period (e.g. those resulting from super-humps are a few per cent longer than Porb). A good example is 4U 0614+091, for which Shahbaz et al. (2008) reported a clear modulation and several candidate periods in the range of ~40–60 min, the strongest being ~51 min. Other authors (e.g. Nelemans et al. 2006; Hakala et al. 2011; Zhang et al. 2012; Baglio et al. 2014) have confirmed the presence of this modulation, reporting slightly different periods within the same range. Thus, while a precise value is still missing, we believe that the UCXB classification for this source is robust. Another example (albeit less extreme) is 4U 1820-303 for which clear X-ray and UV modulations at 11.41 and 11.5 min, respectively, have been found (Stella et al. 1987 and Wang & Chakrabarty 2010). This group currently includes 20 systems.

Ultra-compact X-ray binary candidates. LMXBs with suggestive UCXB properties (see above) are labelled candidates (cUCXBs in Tables B.1–B.3). These systems might (or might not) have weak or contradictory constraints on the orbital period. This category currently counts 25 systems, including one object with no particularly suggestive UCXB properties, but a proposed orbital period shorter than 80 min (NGC 6652 B, 43 min; Deutsch et al. 2000). We also include in this category 4U 1728–34, which has a suggested Porb of 10.7 min (3σ detection of an X-ray periodic signal) and thermonuclear bursts characteristic of hydrogen-poor fuel (Galloway et al. 2010). Alternatively, the observation of an infrared counterpart to a thermonuclear Type I X-ray burst points to Porb>1 h (Vincentelli et al. 2020).

Short-period LMXBs. This category is equivalent to that of UCXBs, but for systems with Porb in the range of ~80–120 min (spLMXBs in Tables B.1–B.3). The reason for having this category, currently including four sources, is twofold: (i) to retain old UCXBs that currently evolve towards long Porb > 80 min and (ii) to also include close progenitors of UCXBs via the helium star and evolved main-sequence star channels (see e.g. van Haaften et al. 2012a; Armas Padilla et al. 2022). We acknowledge that our choice for the Porb interval for this category is somewhat arbitrary. However, it should be mentioned that the LMXB with the shortest known orbital period not included in UltraCompCAT (i.e. with Porb > 120 min) is the accreting millisecond pulsar (AMXP) SAX J1808.4-3658 with Porb=120.82 min. This is a very well-studied source with observational properties that do not match those of UCXBs (e.g. it shows a classic hydrogen-rich optical spectrum; Cornelisse et al. 2009).

2.2 UltraCompCAT

The full catalogue is available online1 and was built according to the criteria described here.

Table B.1 presents the basic astrometric properties. The column distribution is as follows:

(1) ID number;

(2) Source type: UCXB for confirmed UCXBs, cUCXB for candidate UCXBs, and spLMXB for short-period LMXBs;

(3) Year of discovery;

(4) Preferred name of the system (GC if located in one);

(5–7) Right ascension (RA) and declination (Dec) in equinox J2000. The accuracy in the astrometry and source of the coordinates are also reported;

(8–9) Galactic longitude (ℓ) and latitude (b) in degrees;

(10–11) Estimated distance (d) and height above the Galactic plane (z) in kpc. We use the notation (H) and (He) for distances estimated using thermonuclear burst, assuming hydrogen-rich and pure helium, respectively. (G) distances from Gaia parallaxes. For systems located in GCs, we report the distance to their host GC (see Sect. 3.1);

(12) References for the above parameters.

Table B.2 summarizes the main properties for all the systems presented in Table B.1. The column distribution is:

(1) ID number;

(2) Source type: UCXB for confirmed UCXBs, cUCXB for candidate UCXBs, and spLMXB for short-period LMXBs;

(3) Preferred name of the system (GC if located in one);

(4) Type of accretion, persistent (P) or transient (T). LO is specified for those transients with very long outbursts, and QP for persistent systems with very short periods of inactivity (see Sect. 3);

(5) Confirmed nature of the accretor: black hole (BH) or neutron star (NS). If the NS is an accreting X-ray millisecond pulsar, AMXP is added;

(6) Reported Porb in min;

(7) Unabsorbed peak X-ray flux in erg cm−2 s−1, standardised to the 2–10 keV band. To do so, we begin with the X-ray flux published in the literature. We assume a power-law spectrum with a photon index Γ = 2 (Belloni et al. 2011) and the published total neutral Galactic hydrogen column density (NH), derived from direct X-ray spectral analysis (in Col. 9);

(8) Peak optical or IR apparent magnitude (and quiescence [q], if the system is transient). To document the original observed band, we provide its name in its original photometric system;

(9) Total neutral Galactic hydrogen column density (NH), published in the literature derived from direct X-ray spectral analysis;

(10) Optical Galactic extinction E(B – V) reported in the literature for host GCs;

(11) References for the above parameters.

Table B.3 shows the main multi-wavelength phenomenology supporting short orbital periods for the systems presented in Table B.1. The column distribution is:

(1) ID number;

(2) Source type: UCXB for confirmed UCXBs, cUCXB for candidate UCXBs, and spLMXB for short-period LMXBs;

(3) Preferred name of the system (GC if located in one); (4–6) Detection of bursts and their types: short–normal burst (short-B), intermediate long burst (IB), or superburst (SB);

(7–9) Spectral information, in the X-ray, optical, and UV bands; (10–11) Small accretion disc size indirect diagnostic properties: Lo/LX<<, for systems with low optical-to-X-ray luminosity ratio, and LXPers <<, for systems persistently accreting at very low X-ray luminosities;

(12) References for the above parameters.

3 Results

UltraCompCAT currently includes 49 systems. A dozen of them were discovered at the dawn of X-ray astronomy in the 1970s. This number steadily increased as new and more sensitive X-ray facilities were launched, such as the ROSAT observatory in 1990, followed by the Chandra and XMM-Newton missions in 1999 (see Fig. 1). It took ten years for the first UCXB to be confirmed with the measurement of Porb = 41.5 min in 4U 1626-67 using optical pulsations (Middleditch et al. 1981). The number of confirmed UCXBs increased significantly with the launch of missions with enhanced timing capabilities, such as RXTE (1996) and, more recently, NICER (2017). This led to the discovery of AMXPs (Wijnands & Van Der Klis 1998; Chakrabarty & Morgan 1998; see Campana et al. 2008; Patruno & Watts 2021 for reviews), whose orbital periods can be efficiently measured with these facilities. To date, AMXPs account for half of the confirmed UCXB population (10 out of 20; see Table B.2). In addition, there are two other AMXPs in our sample that belong to the short-period LMXB category (i.e. Porb in the range of 80 to 120 min).

Looking at the long-term behaviour, we find that 22 systems are transient (5 of them experience outbursts that last several years), while the remaining 27 systems are persistent. The latter group includes four systems that can be classified as quasi-persistent; these are sources that are active, but sporadically switch into short periods of low luminosity. An illustrative example is AX J1754.2-2754, which has always been observed in active state, except for one occasion, when it was not detected for a brief period of time (≲11 months; Bassa et al. 2008; Jonker & Keek 2008; Degenaar et al. 2012b).

The accretor is a NS in the vast majority of the systems (45 out of 49). This is known through the detection of thermonuclear bursts and/or pulsations, with 36 sources showing the former events. In particular, 18 sources have displayed intermediate-long bursts and four superbursts, with only two targets showing different burst durations compatible with the three categories (short, intermediate long, and superburst): 4U 0614+091 and SLX 1735-269 (see Table B.3). Finally, two of the targets that have not displayed NS signatures have been instead been proposed to harbour BHs through indirect evidence. This is based on their position in the X-ray–radio, optical–X-ray, and X-ray– photon-index planes (47 Tuc X-9; Miller-Jones et al. 2015 and IGR J17285–2922; Stoop et al. 2021). We note that this low fraction of BH systems is consistent with synthetic population models, which predict a very low number of BHs in UCXBs (less than 20%, van Haaften et al. 2013; Belczynski & Taam 2004). These would be mostly formed by accretion-induced collapse of accreting NSs (Belczynski & Taam 2004; Chen et al. 2023) rather than a BH directly formed in the collapse of a massive star (but see Qin et al. 2023).

thumbnail Fig. 1

Cumulative histogram of ultra-compact and short orbital period LMXBs detected since the beginning of the X-ray astronomy era. The black bars represent the confirmed UCXBs.

3.1 Galactic distribution

The Galactic distribution of our sample is represented in Fig. 2. Half of them (24 out of 49), are located in the central 20 deg in longitude (the Galactic bulge). The density of sources decreases drastically as we move away from the centre, with only a few targets scattered between 300 and 180 deg, and none between 70 and 180 deg (see also Fig. 3). In the same way, UCXBs and candidates are concentrated in the Galactic plane, with 92% of them comprised between −20 and 20 deg (77% between −10 and 10 deg; see Fig. 2).

In Fig. 3 we plot the objects with their estimated distances projected onto a face-on view of the Milky Way. About 35% of the sources are located within 8 kpc of the Sun, 50% between 8 and 10 kpc, and only 10% beyond 10 kpc (see also the distribution of distances in Fig. A.1). We note that these numbers should be taken with caution since some distances are not well constrained. Half of the distances are derived from thermonuclear bursts assuming Eddington limit luminosity peaks. Here we used helium fuel distances for the UCXBs and candidates, and hydrogen for the four short-period LMXBs (i.e. we do not assume their UCXB nature). In addition, we note that the peak at 8– 10 kpc includes nine systems, whose distances were assumed to be ~8 kpc (~10 kpc in one case) based on their coordinates (i.e. consistent with the Galactic centre) and neutral hydrogen equivalent column densities. For those systems located in GCs, we used the distance to the host GC. We used (meaningful) distances from Gaia parallaxes when the Gaia (candidate) counterpart was positively cross-matched to that of our X-ray binary system (e.g. those listed in the work of Arnason et al. 2021).

A total of 11 sources are located in GCs, eight confirmed UCXBs and three candidates (represented by yellow and orange stars, respectively, in Figs. 2 and 3). Most of them correspond to those systems scattered away from the Galactic bulge and plane (see Fig. 2). Attending to their long-term variability, six of the sources are persistent systems (five in the case of the confirmed UCXBs; see Table B.2).

3.2 Orbital period distribution

The orbital period is known for 24 of the 49 sources included in the catalogue. Figure 4 (top panel) shows the Porb distribution using bins of 5 and 10 min. The sources are grouped in two populations: one with Porb between 10 and 40 min (eight sources; peaking at ~20 min), and a second group with Porb between 40 and 60 min (ten sources; peaking at 45 min). Only three systems are scattered within the range of 60 to 85 min, while none is found between 85 and 110 min. From there, the number of sources is observed to increase again, a trend that is known to be followed by classical LMXBs beyond the 120 min limit of Ultra-CompCAT (see e.g. Bahramian & Degenaar 2023). It is worth noting that the ratio of the GC to field UCXB populations is very different in the two main peaks. While the 20 min group is dominated by systems in GCs (5 out of 8), the 45 min peak only includes three (out of 10), and thus is dominated by UCXBs formed in the field (i.e. Galactic plane and bulge).

The lower panel in Fig. 4 provides the percentage of systems that are persistent for each 5 min Porb bin. The objects within the ~20 min peak are all persistent. As a matter of fact, every UCXB below 40 min is persistent. This drops sharply to below ~50% for Porb > 40 min, and then to zero for systems with Porb longer than 60 min. This number increases again to ~60% for systems with Porb longer than 110 min.

Out of the eight GC sources with a Porb measurement, five are persistent (those with Porb < 40 min), while the remaining three sources in the 45 min group are transient. In the case of the 16 field systems, half of them are persistent: the three systems with Porb < 40 min, three of the seven systems in the 45 min peak, and two short-period LMXBs (with Porb ~ 110 min).

4 Discussion

UCXBs are a distinctive subset of the LMXB family. In the past this has given rise to several compilations that list its members and basic characteristics (e.g. in ’t Zand et al. 2007; Nelemans & Jonker 2010; van Haaften et al. 2012a; Heinke et al. 2013). In this paper we take another step forward, and present UltraCompCAT.

The UCXB properties compiled in the catalogue have allowed us to discuss their orbital period distribution, which is key to understanding their origin and evolution, as well as their Galactic distribution.

thumbnail Fig. 2

Distribution for all the sources included in the catalogue. Top: galactic distribution for the 20 confirmed UCXBs (yellow), 25 candidates (orange) and four short-period LMXBs (green) in Galactic coordinates. Systems located in GCs are marked with stars rather than circles. (Background image credit: ESA/Gaia/DPAC.) Bottom: histogram of the distribution of all sources in Galactic longitude (left) and latitude (right). Blue is used for all systems (field + GC), and green for those located in GCs. A bin size of 10 deg has been applied in both plots.

4.1 UltraCompCAT: present and future

UltraCompCAT is the first comprehensive catalogue of ultracompact and short orbital period X-ray binaries. It is available online and includes 49 sources, whose (known) properties have been carefully revised and listed. Among the hundreds of reported LMXBs, both transient and persistent, we selected those with Porb or spectral properties compatible with the UCXB family. This was done by thoroughly searching in the literature, aiming at providing accurate information that can be used in UCXB research. We cannot be totally certain that all the sources included in UltraCompCAT are bona fide UCXBs. First, we extended the sample to systems with Porb > 80 min, which we refer to as short-period LMXBs. We find it is important to include this category because the UCXB nature of a given LMXB is not strictly defined by Porb, but by the nature of the donor (systems with Porb > 80 min may in fact be UCXBs that have evolved past the minimum Porb) and because even if they are not UCXBs, this subset of LMXBs can be useful for UCXB studies (since they might be UCXB progenitors; e.g. Armas Padilla et al. 2022). In any case, only four out of the 49 systems belong to this Porb range. Second, we decided to follow an inclusive approach by building the UCXB-candidates group, although it could be the case that new Porb measurements end up disproving the UCXB nature of some of the current members. However, previous studies have shown that a significant fraction of the candidates are eventually confirmed (e.g. Zurek et al. 2009; Zhong & Wang 2011; Strohmayer et al. 2018a).

Likewise, UltraCompCAT is necessarily affected by observational biases related to the instrumentation employed, cadence, and completeness. In addition to the ample theoretical support behind the idea that the vast majority of the Galactic UCXBs are yet to be discovered, it is also possible that some known LMXBs are unclassified UCXBs. Similarly, there is a large number of faint, unclassified X-ray sources detected by the most sensitive X-ray surveys (e.g. Webb et al. 2020; Bahramian et al. 2021). While the dominant population is expected to be made up of (magnetic) accreting WDs, the large number of Galactic UCXBs predicted to exist by theoretical studies (Belczynski & Taam 2004; van Haaften et al. 2013) suggest the UCXB nature of some of these faint sources.

Despite the above biases, UltraCompCAT represents the current observational view of UCXBs, and the most complete ever compiled. UltraCompCAT will be continuously updated, growing in size as more systems are discovered and characterised, and more orbital periods are measured.

thumbnail Fig. 3

Galactic distribution of UCXBs and short-period LMXB systems with estimated distances following the same colours and symbols as in Fig. 2 (Background image credit: NASA/JPL-Caltech/R. Hurt (SSC/Caltech)).
thumbnail Fig. 4

Orbital period distribution. Top panel: Histogram of the orbital period of UCXBs and short-period LMXB systems, plotted in 10 min bins (grey) and 5 min bins [blue for all systems (field + GC) and green for those located in GCs]. The canonical 80 min that defines the bona fide UCXBs limit is shown as a dotted black line. Lower panel: Percentage of systems accreting persistently.

4.2 Different populations of UCXBs

The Galactic distribution of UCXBs (see Fig. 2) shows an accumulation of objects in the Galactic bulge (although several distances are not well constrained) and along the disc plane, with only a few scattered sources placed further away (located mostly in GCs). This is in agreement with UCXBs being mostly Population II stars (Tauris & van den Heuvel 2006). About a quarter of our sources are located in GCs: eight of the 20 confirmed UCXBs and three of the candidates. This is not unexpected since UCXBs are predicted to be overproduced in these dense conglomerations of stars via dynamical collisions. It has even been suggested that UCXBs formed in GCs are one of the dominant populations of X-ray binaries (Verbunt 1987; Bildsten & Deloye 2004; Ivanova et al. 2008).

The histogram representing the Porb distribution (Fig. 4) shows three main groups, which might be related to different UCXBs populations: one group with Porb~20 min (10 to 40 min); a second group with Porb~45 min (40 to 60 min); and a third, less populated group with periods longer than 110 min. According to binary synthesis models, the population of UCXBs in the Galaxy is expected to be ~ 0.1 − 1 × 105. Most of them are predicted to have already evolved to Porb longer than ~60 min, and are thus characterised by low accretion rates. Taking this into account, together with the disc instability model, only a few tens of UCXBs are expected to have shown activity during the X-ray astronomy era (Belczynski & Taam 2004; Zhu et al. 2012). However, systems formed in GCs via dynamical interactions (i.e. at any time) may modify this picture.

van Haaften et al. (2013) explored the formation of UCXBs in the Galactic bulge (i.e. the oldest Galactic field population). They predict a peak of sources below 30 min dominated by persistent systems formed through the WD channel, most of them with He or C/O WD donors. Contrastingly, the helium-burning channel is expected to contribute (at most) a few transients with longer Porb (60–80 min). Hence, the observed 20 min peak formed by persistent systems (Fig. 4) could in principle be associated with the WD channel. However, Fig. 4 shows that it is dominated by GC systems (75%), while very short Porb (≲40 min) UCXBs formed in the field are scarce. The histogram also includes three transient field UCXBs with Porb in the range of 60–80 min that could be identified with the helium-burning channel according to van Haaften et al. (2013), but this work does not specifically account for the observed peak at 40–60 min.

In a different study, Zhu et al. (2012) predicted that systems formed via the helium star channel in the Galactic field might be observed over a wider range in Porb (between ~1 –80 min), peaking at ~40 min. These systems would be persistent, while the observed 40–60 min population is mostly transient. In this model, transient UCXBs would have longer periods (33 < Porb < 130 min), but only a few (i.e. far fewer than persistent ones) would be detected. This does not seem to be consistent with the current (i.e. observed) Galactic field populations, in which half of UCXBs are transient sources. The evolved main-sequence star channel is predicted to produce a much lower number of UCXBs (e.g. only 0.3 %according to van Haaften et al. 2013), and thus its contribution to the observable population should be negligible.

In general, UCXBs population synthesis models, which are mostly focused on systems in the Galactic field, predict that the vast majority of the sources should have evolved towards relatively long orbital periods. Therefore, they would be transients characterised by low accretion rates (and thus long recurrence times). However, our study shows that the transient UCXB population (i.e. those that have displayed at least one outburst in ~60 years) is not as low as predicted. Transients actually account for almost half of the sample (22 out of 49 systems, 9 out of the 20 confirmed UCXBs). This becomes even more striking if we only consider UCXBs in the Galactic field (19 persistent and 19 transients). On the other hand, the population of UCXBs and candidates in GCs is formed by 11 sources, most of them persistent with Porb < 30 min (five of the eight with a Porb measurement). In fact, there is a dearth of (longer period) transients formed in GCs. This might be consistent with most of them being produced by dynamical interactions (i.e. at any time) via the WD evolutionary channel, as suggested in Heinke et al. (2013).

To elucidate the evolutionary channel of a given UCXB based on observational constraints is challenging. Optical, X-ray, and UV spectroscopy, together with the properties of type I X-ray bursts can be used to infer the abundances of the accreted material. For instance, Cumming (2003) propose that 4U 1820–303 has a helium-rich companion based on its type I X-ray bursts. However, tight constraints on more than one element would be required to single out the evolutionary channel (see e.g. Nelemans et al. 2010). In addition, one might also consider the observed accretion rate (i.e. luminosity) for a given Porb together with the disc instability model (i.e. persistent or transient behaviour). Based on this, the three persistent systems of the 45 min group may have formed through the helium star channel (Nelemans et al. 2010; Heinke et al. 2013). Nevertheless, its worth noting that there are several cases where it is difficult to reconcile all the above into a single picture (e.g. 4U 0614+091 and 2S 0918-549; see e.g. Kuulkers et al. 2010; Heinke et al. 2013; Armas Padilla et al. 2020).

5 Conclusions

We have presented the first comprehensive catalogue of ultracompact and short orbital period X-ray binaries, which currently includes 49 sources. This compilation is available online1 and includes a carefully revised collection of observational properties for each source. UltraCompCAT will grow as more systems are discovered and more orbital periods are measured. Thus, we expect that it will become a powerful tool for the study of this key subgroup of LMXBs, particularly in the new era of gravitational wave astrophysics, since UCXBs are expected to be among the loudest persistent sources. We have shown that the orbital period distribution of the current sample presents two main groups. One mainly formed by persistent systems in GCs with orbital periods shorter than 30 min, and a second one with transient objects (70%), periods in the range of 40–60 min and dominated by UCXBs in the Galactic field. These two groups might be the result of two different evolutionary channels that dominate in the GC and field populations. Future observations of known and newly discovered UCXBs will allow UltraCompCAT to grow and hopefully shed light on these open problems.

Acknowledgements

This work is supported by the Spanish Ministry of Science under grants PID2020-120323GB-I00, PID2021-124879NB-I00, and EUR2021-122010. We 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 ProID2021010132.

Appendix A Histogram

thumbnail Fig. A.1

Histogram of the distribution of all the objects with known distances (left) and their scale height (z) from the Galactic plane (right).

Appendix В Tables

Table B.1

Astrometry and location.

Table B.2

Main observational properties.

Table B.3

Additional multi-wavelength properties.

References

  1. Alizai, K., Chenevez, J., Brandt, S., & Lund, N. 2020, MNRAS, 494, 2509 [NASA ADS] [CrossRef] [Google Scholar]
  2. Altamirano, D., Patruno, A., Heinke, C., et al. 2010, ApJ, 712, 58 [Google Scholar]
  3. Anderson, G. E., Gaensler, B. M., Kaplan, D. L., et al. 2014, ApJS, 212, 13 [CrossRef] [Google Scholar]
  4. Angelini, L., White, N. E., Nagase, F., et al. 1995, ApJ, 449, L41 [NASA ADS] [CrossRef] [Google Scholar]
  5. Armas Padilla, M., & López-Navas, E. 2019, MNRAS, 488, 5014 [NASA ADS] [CrossRef] [Google Scholar]
  6. Armas Padilla, M., Degenaar, N., & Wijnands, R. 2013a, MNRAS, 434, 1586 [NASA ADS] [CrossRef] [Google Scholar]
  7. Armas Padilla, M., Wijnands, R., & Degenaar, N. 2013b, MNRAS, 436, L89 [NASA ADS] [CrossRef] [Google Scholar]
  8. Armas Padilla, M., Ponti, G., De Marco, B., Muñoz-Darias, T., & Haberl, F. 2018, MNRAS, 473, 3789 [NASA ADS] [CrossRef] [Google Scholar]
  9. Armas Padilla, M., Muñoz-Darias, T., Jiménez-Ibarra, F., et al. 2020, A & A, 644, A63 [Google Scholar]
  10. Armas Padilla, M., Rodríguez-Gil, P., Muñoz-Darias, T., et al. 2022, ApJ, 931, L9 [NASA ADS] [CrossRef] [Google Scholar]
  11. Arnason, R. M., Papei, H., Barmby, P., Bahramian, A., & Gorski, D. M. 2021, MNRAS, 502, 5455 [NASA ADS] [CrossRef] [Google Scholar]
  12. Asai, K., Mihara, T., Serino, M., et al. 2016, ATel, 8769, 1 [NASA ADS] [Google Scholar]
  13. Auriere, M., & Koch-Miramond, L. 1992, A & A, 263, 82 [NASA ADS] [Google Scholar]
  14. Baglio, M. C., Mainetti, D., D’Avanzo, P., et al. 2014, A & A, 572, A99 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  15. Baglio, M. C., D’Avanzo, P., Campana, S., et al. 2016, A & A, 587, A102 [Google Scholar]
  16. Bahramian, A., & Degenaar, N. 2023, in Handbook of X-ray and Gamma-ray Astrophysics, eds. C. Bambi & A. Santangelo (Springer Living Reference Work), 120 [Google Scholar]
  17. Bahramian, A., Heinke, C. O., Tudor, V., et al. 2017, MNRAS, 467, 2199 [Google Scholar]
  18. Bahramian, A., Heinke, C. O., Kennea, J. A., et al. 2021, MNRAS, 501, 2790 [NASA ADS] [CrossRef] [Google Scholar]
  19. Barlow, E. J., Bird, A. J., Clark, D. J., et al. 2005, A & A, 437, L27 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  20. Barret, D., Olive, J. F., & Oosterbroek, T. 2003, A & A, 400, 643 [Google Scholar]
  21. Bassa, C. G., Jonker, P. G., In ’t Zand, J. J. M., & Verbunt, F. 2006, A & A, 446, L17 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  22. Bassa, C., Jonker, P. G., Nelemans, G., et al. 2008, ATel, 1575 [Google Scholar]
  23. Baumgardt, H., & Vasiliev, E. 2021, MNRAS, 505, 5957 [NASA ADS] [CrossRef] [Google Scholar]
  24. Bazzano, A., Cocchi, M., Ubertini, P., et al. 1997, IAUC, 6668 [Google Scholar]
  25. Becker, R. H., Smith, B. W., Swank, J. H., et al. 1977, ApJ, 216, L101 [NASA ADS] [CrossRef] [Google Scholar]
  26. Belczynski, K., & Taam, R. E. 2004, ApJ, 603, 690 [NASA ADS] [CrossRef] [Google Scholar]
  27. Belloni, T. M., Motta, S. E., & Muñoz-Darias, T. 2011, Bull. Astron. Soc. India, 39, 409 [Google Scholar]
  28. Bhattacharyya, S., Strohmayer, T. E., Markwardt, C. B., & Swank, J. H. 2006, ApJ, 639, L31 [NASA ADS] [CrossRef] [Google Scholar]
  29. Bildsten, L., & Deloye, C. J. 2004, ApJ, 607, L119 [NASA ADS] [CrossRef] [Google Scholar]
  30. Boissay, R., Chenevez, J., Bozzo, E., et al. 2012, ATel, 3984, 1 [NASA ADS] [Google Scholar]
  31. Boller, T., Haberl, F., Voges, W., et al. 1997, IAUC, 6546, 1 [NASA ADS] [Google Scholar]
  32. Bozzo, E., Grinberg, V., Wilms, J., et al. 2017, ATel, 10880, 1 [NASA ADS] [Google Scholar]
  33. Brandt, S., Budtz-Jørgensen, C., & Chenevez, J. 2006a, ATel, 778, 1 [NASA ADS] [Google Scholar]
  34. Brandt, S., Budtz-Jorgensen, C., Chenevez, J., et al. 2006b, ATel, 970, 1 [NASA ADS] [Google Scholar]
  35. Brown, A. G. A., Vallenari, A., Prusti, T., et al. 2021, A & A, 649, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  36. Bult, P., Altamirano, D., Arzoumanian, Z., et al. 2021, ApJ, 920, 59 [NASA ADS] [CrossRef] [Google Scholar]
  37. Cackett, E. M., Wijnands, R., & Remillard, R. 2006, MNRAS, 369, 1965 [NASA ADS] [CrossRef] [Google Scholar]
  38. Cackett, E. M., Miller, J. M., Raymond, J., et al. 2008, ApJ, 677, 1233 [NASA ADS] [CrossRef] [Google Scholar]
  39. Campana, S., Ravasio, M., Israel, G. L., Mangano, V., & Belloni, T. 2003, ApJ, 594, L39 [NASA ADS] [CrossRef] [Google Scholar]
  40. Campana, S., Ferrari, N., Stella, L., & Israel, G. L. 2005, A & A, 434 [Google Scholar]
  41. Campana, S., Stella, L., Israel, G., & D'Avanzo, P. 2008, ApJ, 689, L129 [NASA ADS] [CrossRef] [Google Scholar]
  42. Casares, J., Jonker, P. G., & Israelian, G. 2017, in Handbook of Supernovae (Springer), 1499 [CrossRef] [Google Scholar]
  43. Chakrabarty, D. 1998, ApJ, 492, 342 [NASA ADS] [CrossRef] [Google Scholar]
  44. Chakrabarty, D., & Jonker, P. G. 2020, ATel, 14146, 1 [NASA ADS] [Google Scholar]
  45. Chakrabarty, D., & Morgan, E. H. 1998, Nature, 394, 346 [NASA ADS] [CrossRef] [Google Scholar]
  46. Chakrabarty, D., Jonker, P. G., & Markwardt, C. B. 2016, ATel, 9591, 1 [NASA ADS] [Google Scholar]
  47. Chelovekov, I. V. V., & Grebenev, S. A. A. 2007, Astron. Lett., 33, 807 [Google Scholar]
  48. Chelovekov, I. V., & Grebenev, S. A. 2010, Astron. Lett., 36, 895 [Google Scholar]
  49. Chelovekov, I. V., Grebenev, S. A., & Sunyaev, R. A. 2006, Astron. Lett., 32, 456 [Google Scholar]
  50. Chelovekov, I. V., Grebenev, S. A., Mereminskiy, I. A., & Prosvetov, A. V. 2017, Astron. Lett., 43, 781 [NASA ADS] [CrossRef] [Google Scholar]
  51. Chen, H. L., Tauris, T. M., Han, Z., & Chen, X. 2021, MNRAS, 503, 3540 [NASA ADS] [CrossRef] [Google Scholar]
  52. Chen, H.-L., Tauris, T. M., Chen, X., & Han, Z. 2023, ApJ, 951, 91 [NASA ADS] [CrossRef] [Google Scholar]
  53. Chenevez, J., Falanga, M., Kuulkers, E., et al. 2007, A & A, 469, L27 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Chenevez, J., Kuulkers, E., Brandt, S., et al. 2012, ATel, 4050, 1 [NASA ADS] [Google Scholar]
  55. Chenevez, J., Beeck, S., Brandt, S., et al. 2017, ATel, 10195, 1 [NASA ADS] [Google Scholar]
  56. Cherepashchuk, A. M., Molkov, S. V., Lutovinov, A. A., & Postnov, K. A. 2015, ATel, 7506, 1 [NASA ADS] [Google Scholar]
  57. Chevalier, C., & Ilovaisky, S. A. 1987, A & A, 172, 167 [NASA ADS] [Google Scholar]
  58. Chevalier, C., Ilovaisky, S. A., & Charles, P. A. 1985, A & A, 147, L3 [NASA ADS] [Google Scholar]
  59. Chevalier, C., Ilovaisky, S. A., Chevalier, C., & Ilovaisky, S. A. 1990, A & A, 228, 115 [Google Scholar]
  60. Christian, D. J., & Swank, J. H. 1997, ApJS, 109, 177 [NASA ADS] [CrossRef] [Google Scholar]
  61. Churazov, E., Sunyaev, R., Revnivtsev, M., et al. 2007, A & A, 467, 529 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  62. Clark, G. W., Kwok Li, F., Canizares, C., et al. 1977, MNRAS, 179, 651 [NASA ADS] [CrossRef] [Google Scholar]
  63. Cocchi, M., Bazzano, A., Natalucci, L., et al. 1998, ApJ, 508, L163 [NASA ADS] [CrossRef] [Google Scholar]
  64. Cocchi, M., Natalucci, L., in ’t Zand, J., et al. 1999, IAUC, 7247, 3 [NASA ADS] [Google Scholar]
  65. Coomber, G., Heinke, C. O., Cohn, H. N., Lugger, P. M., & Grindlay, J. E. 2011, ApJ, 735, 95 [NASA ADS] [CrossRef] [Google Scholar]
  66. Cornelisse, R., Verbunt, F., In’t Zand, J. J., Kuulkers, E., & Heise, J. 2002, A & A, 392, 931 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  67. Cornelisse, R., D’Avanzo, P., Muñoz-Darias, T., et al. 2009, A & A, 495, L1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  68. Corral-Santana, J. M., Casares, J., Muñoz-Darias, T., et al. 2016, A & A, 587, A61 [Google Scholar]
  69. Costantini, E., Pinto, C., Kaastra, J. S., et al. 2012, A & A, 539, A32 [Google Scholar]
  70. Coti Zelati, F., De Ugarte Postigo, A., Russell, T. D., et al. 2021, A & A, 650, A69 [Google Scholar]
  71. Cumming, A. 2003, ApJ, 595, 1077 [NASA ADS] [CrossRef] [Google Scholar]
  72. Curran, P. A., Chaty, S., & Heras, J. A. Z. 2011, A & A, 533, A3 [Google Scholar]
  73. D’Avanzo, P., Campana, S., Casares, J., et al. 2009, A & A, 508, 297 [Google Scholar]
  74. Davison, P., Burnell, J., Ives, J., Wilson, A., & Carpenter, G. 1976, IAUC, 2925, 2 [NASA ADS] [Google Scholar]
  75. de Marchi, G., & Paresce, F. 1994, ApJ, 422, 597 [NASA ADS] [CrossRef] [Google Scholar]
  76. Degenaar, N., Krauss, M., Maitra, D., et al. 2007, ATel, 1136, 1 [NASA ADS] [Google Scholar]
  77. Degenaar, N., Jonker, P. G. G., Torres, M. A. P. A. P., et al. 2010, MNRAS, 1602, 1591 [Google Scholar]
  78. Degenaar, N., Wijnands, R., & Kaur, R. 2011, MNRAS, 414, L104 [NASA ADS] [CrossRef] [Google Scholar]
  79. Degenaar, N., Altamirano, D., & Wijnands, R. 2012a, ATel, 4219 [Google Scholar]
  80. Degenaar, N., Starling, R. L. C. L. C., Evans, P. A. A., et al. 2012b, A & A, 540, A22 [Google Scholar]
  81. Degenaar, N., Wijnands, R., & Miller, J. M. 2013, ApJ, 767, L31 [Google Scholar]
  82. Degenaar, N., Altamirano, D., Parker, M., et al. 2016, MNRAS, 461, 4049 [NASA ADS] [CrossRef] [Google Scholar]
  83. Degenaar, N., Pinto, C., Miller, J. M., et al. 2017, MNRAS, 464, 398 [NASA ADS] [CrossRef] [Google Scholar]
  84. Deller, A., Degenaar, N., Hessels, J., et al. 2015, ATel, 7255, 1 [NASA ADS] [Google Scholar]
  85. Del Santo, M., Sidoli, L., Mereghetti, S., et al. 2007, A & A, 468, L17 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  86. Del Santo, M., Romano, P., Ferrigno, C., et al. 2012, ATel, 4017, 1 [NASA ADS] [Google Scholar]
  87. Deutsch, E. W., Anderson, S. F., Margon, B., & Downes, R. A. 1996, ApJ, 472, L97 [NASA ADS] [CrossRef] [Google Scholar]
  88. Deutsch, E. W., Margon, B., & Anderson, S. F. 1998, AJ, 116, 1301 [NASA ADS] [CrossRef] [Google Scholar]
  89. Deutsch, E. W., Margon, B., & Anderson, S. F. 2000, ApJ, 530, L21 [NASA ADS] [CrossRef] [Google Scholar]
  90. Díaz Trigo, M., Migliari, S., Miller-Jones, J. C., et al. 2017, A & A, 600 [Google Scholar]
  91. Dieball, A., Knigge, C., Zurek, D. R., et al. 2005, ApJ, 634, L105 [NASA ADS] [CrossRef] [Google Scholar]
  92. Di Salvo, T., Iaria, R., Burderi, L., & Robba, N. R. 2000, ApJ, 542, 1034 [NASA ADS] [CrossRef] [Google Scholar]
  93. Downes, R. A., Anderson, S. F., & Margon, B. 1996, PASP, 108, 688 [NASA ADS] [CrossRef] [Google Scholar]
  94. Elebert, P., Callanan, P. J., Filippenko, A. V., et al. 2007, MNRAS, 383, 1581 [Google Scholar]
  95. Emelyanov, A. N., Aref’ev, V. A., Churazov, E. M., Gilfanov, M. R., & Sunyaev, R. A. 2001, Astron. Lett., 27, 781 [Google Scholar]
  96. Evans, P. A., Tohuvavohu, A., & Neil Gehrels Swift Observatory Team 2020, GRB Coordinates Network, 26982, 1 [Google Scholar]
  97. Fabian, A. C., Pringle, J. E., & Rees, M. J. 1975, MNRAS, 172, 15 [Google Scholar]
  98. Falanga, M., Chenevez, J., Cumming, A., et al. 2008, A & A, 484, 43 [Google Scholar]
  99. Fiocchi, M., Bazzano, A., Ubertini, P., & De Cesare, G. 2008, A & A, 477, 239 [Google Scholar]
  100. Fiocchi, M., Bazzano, A., Natalucci, L., Landi, R., & Ubertini, P. 2011, MNRAS, 414, 41 [Google Scholar]
  101. Forman, W., & Jones, C. 1976, ApJ, 207, L177 [NASA ADS] [CrossRef] [Google Scholar]
  102. Futamoto, K., Mitsuda, K., Takei, Y., Fujimoto, R., & Yamasaki, N. Y. 2004, ApJ, 605, 793 [NASA ADS] [CrossRef] [Google Scholar]
  103. Galloway, D. K., Chakrabarty, D., Morgan, E. H., & Remillard, R. A. 2002, ApJ, 576, L137 [NASA ADS] [CrossRef] [Google Scholar]
  104. Galloway, D. K., Yao, Y., Marshall, H., Misanovic, Z., & Weinberg, N. 2010, ApJ, 724, 417 [NASA ADS] [CrossRef] [Google Scholar]
  105. Galloway, D. K., in ’t Zand, J., Chenevez, J., et al. 2020, ApJS, 249, 32 [Google Scholar]
  106. Gambino, A. F., Iaria, R., Di Salvo, T., et al. 2019, A & A, 625 [Google Scholar]
  107. Gavriil, F. P., Strohmayer, T. E., & Bhattacharyya, S. 2012, ApJ, 753, 2 [NASA ADS] [CrossRef] [Google Scholar]
  108. Giacconi, R., Murray, S., Gursky, H., et al. 1972, ApJ, 178, 281 [NASA ADS] [CrossRef] [Google Scholar]
  109. Giacconi, R., Murray, S., Gursky, H., et al. 1974, ApJS, 27, 37 [NASA ADS] [CrossRef] [Google Scholar]
  110. Gierliński, M., & Poutanen, J. 2005, MNRAS, 359, 1261 [Google Scholar]
  111. Giles, A. B., Greenhill, J. G., Hill, K. M., & Sanders, E. 2005, MNRAS, 361, 1180 [NASA ADS] [CrossRef] [Google Scholar]
  112. Gioia, I. M., Maccacaro, T., Schild, R. E., et al. 1990, ApJS, 72, 567 [NASA ADS] [CrossRef] [Google Scholar]
  113. Goodwin, A. J., Galloway, D. K., in ’t Zand, J. J. M., et al. 2019, MNRAS, 486, 4149 [NASA ADS] [CrossRef] [Google Scholar]
  114. Gottwald, M., Steinle, H., Graser, U., et al. 1991, A & AS, 89, 367 [NASA ADS] [Google Scholar]
  115. Grindlay, J. E. 1981, Astrophys. Space Sci. Lib., 87, 79 [NASA ADS] [CrossRef] [Google Scholar]
  116. Grindlay, J. E., Cohn, H., & Schmidtke, P. 1987, IAUC, 4393 [Google Scholar]
  117. Guver, T., Ak, T., Urgup, H., et al. 2015, ATel, 8149, 1 [NASA ADS] [Google Scholar]
  118. Hakala, P., Ramsay, G., Muhli, P., et al. 2005, MNRAS, 356, 1133 [NASA ADS] [CrossRef] [Google Scholar]
  119. Hakala, P. J., Charles, P. A., & Muhli, P. 2011, MNRAS, 416, 644 [NASA ADS] [Google Scholar]
  120. Harris, W. E. 1996, AJ, 112, 1487 [Google Scholar]
  121. Harris, W. E. 2010, ArXiv e-prints [arXiv:1012.3224] [Google Scholar]
  122. Haurberg, N. C., Lubell, G. M. G., Cohn, H. N., et al. 2010, ApJ, 722, 158 [NASA ADS] [CrossRef] [Google Scholar]
  123. Heinke, C. O., Edmonds, P. D., & Grindlay, J. E. 2001, ApJ, 562, 363 [NASA ADS] [CrossRef] [Google Scholar]
  124. Heinke, C. O., Grindlay, J. E., Edmonds, P. D., et al. 2005, ApJ, 625, 796 [NASA ADS] [CrossRef] [Google Scholar]
  125. Heinke, C. O., Altamirano, D., Cohn, H. N., et al. 2009, ApJ, 714, 894 [Google Scholar]
  126. Heinke, C. O., Ivanova, N., Engel, M. C., et al. 2013, ApJ, 768, 184 [NASA ADS] [CrossRef] [Google Scholar]
  127. Hemphill, P. B., Schulz, N. S., Marshall, H. L., & Chakrabarty, D. 2021, ApJ, 920, 142 [NASA ADS] [CrossRef] [Google Scholar]
  128. Hernández Santisteban, J. V., Cúneo, V., Degenaar, N., et al. 2019, MNRAS, 488, 4596 [CrossRef] [Google Scholar]
  129. Hertz, P., & Grindlay, J. E. 1984, ApJ, 282, 118 [NASA ADS] [CrossRef] [Google Scholar]
  130. Hills, J. G. 1976, MNRAS, 175, 1 [Google Scholar]
  131. Hoffman, J. A., Lewin, W. H. G., Doty, J., et al. 1976, ApJ, 210, L13 [NASA ADS] [CrossRef] [Google Scholar]
  132. Hoffman, J. A., Lewin, W. H. G., Doty, J., et al. 1978, ApJ, 221, L57 [NASA ADS] [CrossRef] [Google Scholar]
  133. Hoffman, J. A., Cominsky, L., & Lewin, W. H. G. 1980, ApJ, 240, L27 [NASA ADS] [CrossRef] [Google Scholar]
  134. Homan, J., Sivakoff, G., Pooley, D., et al. 2016, ATel, 8971, 1 [NASA ADS] [Google Scholar]
  135. Homer, L., Charles, P. A., Naylor, T., et al. 1996, MNRAS, 282, L37 [NASA ADS] [CrossRef] [Google Scholar]
  136. Homer, L., Anderson, S. F., Margon, B., Deutsch, E. W., & Downes, R. A. 2001, ApJ, 550, L155 [NASA ADS] [CrossRef] [Google Scholar]
  137. Homer, L., Anderson, S. F., Wachter, S., & Margon, B. 2002, AJ, 124, 3348 [NASA ADS] [CrossRef] [Google Scholar]
  138. Iaria, R., Di Salvo, T., Lavagetto, G., Robba, N. R., & Burderi, L. 2006, ApJ, 647, 1341 [NASA ADS] [CrossRef] [Google Scholar]
  139. Iaria, R., Sanna, A., Di Salvo, T., et al. 2021, A & A, 646, A120 [Google Scholar]
  140. Iben, Icko, J., & Tutukov, A. V. 1987, ApJ, 313, 727 [NASA ADS] [CrossRef] [Google Scholar]
  141. in ’t Zand, J. J. M., Verbunt, F., Heise, J., et al. 1998, A & A, 329, L37 [Google Scholar]
  142. in ’t Zand, J., Heise, J., Bazzano, A., Cocchi, M., & Smith, M. J. S. 1999a, IAUC, 7243 [Google Scholar]
  143. in ’t Zand, J. J. M., Heise, J., Muller, J. M., et al. 1999b, Nuclear Phys. B Proc. Suppl., 69, 228 [CrossRef] [Google Scholar]
  144. in ’t Zand, J. J. M., Verbunt, F., Kuulkers, E., et al. 2002, A & A, 389, 43 [Google Scholar]
  145. in ’t Zand, J., Verbunt, F., Heise, J., et al. 2004, Nuclear Phys. B Proc. Suppl., 132, 486 [CrossRef] [Google Scholar]
  146. in ’t Zand, J. J. M., Cornelisse, R., & Méndez, M. 2005, A & A, 440, 287 [CrossRef] [EDP Sciences] [Google Scholar]
  147. in ’t Zand, J. J. M., Jonker, P. G., & Markwardt, C. B. 2007, A & A, 465, 953 [CrossRef] [EDP Sciences] [Google Scholar]
  148. in ’t Zand, J. J. M., Bassa, C. G. G., Jonker, P. G. G., et al. 2008, A & A, 485, 183 [Google Scholar]
  149. in ’t Zand, J., Linares, M., & Markwardt, C. 2014, ATel, 5972, 1 [Google Scholar]
  150. in ’t Zand, J. J. M., Kries, M. J. W., Palmer, D. M., & Degenaar, N. 2019, A & A, 621, A53 [Google Scholar]
  151. Israel, G. L., Krimm, H. A., Rea, N., et al. 2008, ATel, 1528 [Google Scholar]
  152. Ivanova, N., Rasio, F. A., Lombardi, J. C. Jr., Dooley, K. L., & Proulx, Z. F. 2005, ApJ, 621, L109 [NASA ADS] [CrossRef] [Google Scholar]
  153. Ivanova, N., Heinke, C. O., Rasio, F. A., Belczynski, K., & Fregeau, J. M. 2008, MNRAS, 386, 553 [NASA ADS] [CrossRef] [Google Scholar]
  154. Jonker, P. G., & Keek, L. 2008, ATel, 1643 [Google Scholar]
  155. Jonker, P. G., & Nelemans, G. 2004, MNRAS, 354, 355 [Google Scholar]
  156. Jonker, P. G., van der Klis, M., Homan, J., et al. 2001, ApJ, 553, 335 [NASA ADS] [CrossRef] [Google Scholar]
  157. Jonker, P. G., Mendez, M., Nelemans, G., Wijnands, R., & van der Klis, M. 2003a, MNRAS, 341, 823 [NASA ADS] [CrossRef] [Google Scholar]
  158. Jonker, P. G., Nelemans, G., Wang, Z., et al. 2003b, MNRAS, 344, 201 [NASA ADS] [CrossRef] [Google Scholar]
  159. Jonker, P. G., van der Klis, M., Kouveliotou, C., et al. 2003c, MNRAS, 346, 684 [NASA ADS] [CrossRef] [Google Scholar]
  160. Jonker, P. G., Galloway, D. K., McClintock, J. E., et al. 2004, MNRAS, 354, 666 [Google Scholar]
  161. Jonker, P. G., Bassa, C. G., & Wachter, S. 2007, MNRAS, 377, 1295 [NASA ADS] [CrossRef] [Google Scholar]
  162. Juett, A. M. M., & Chakrabarty, D. 2003, ApJ, 599, 498 [NASA ADS] [CrossRef] [Google Scholar]
  163. Juett, A. M., & Chakrabarty, D. 2005, ApJ, 627, 926 [NASA ADS] [CrossRef] [Google Scholar]
  164. Juett, A. M., Psaltis, D., & Chakrabarty, D. 2001, ApJ, 560, 59 [Google Scholar]
  165. Juett, A. M., Galloway, D. K., & Chakrabarty, D. 2003, ApJ, 587, 754 [NASA ADS] [CrossRef] [Google Scholar]
  166. Kaaret, P., Morgan, E. H., Vanderspek, R., & Tomsick, J. A. 2006, ApJ, 638, 963 [CrossRef] [Google Scholar]
  167. Kaptein, R. G. G., in’t Zand, J. J. M. J. M., Kuulkers, E., et al. 2000, A & A, 358, L71 [Google Scholar]
  168. Kashyap, U., Chakraborty, M., & Bhattacharyya, S. 2022, MNRAS, 512, 6180 [NASA ADS] [CrossRef] [Google Scholar]
  169. Katz, J. I. 1975, Nature, 253, 698 [NASA ADS] [CrossRef] [Google Scholar]
  170. Kaur, R., Wijnands, R., Kamble, A., et al. 2017, MNRAS, 464, 170 [NASA ADS] [CrossRef] [Google Scholar]
  171. Keek, L., Iwakiri, W., Serino, M., et al. 2017, ApJ, 836, 111 [NASA ADS] [CrossRef] [Google Scholar]
  172. King, I. R., Stanford, S. A., Albrecht, R., et al. 1993, ApJ, 413, L117 [NASA ADS] [CrossRef] [Google Scholar]
  173. Knigge, C., Dieball, A., Maíz Apellániz, J., et al. 2008, ApJ, 683, 1006 [NASA ADS] [CrossRef] [Google Scholar]
  174. Koliopanos, F., Peaúlt, M., Vasilopoulos, G., et al. 2021, MNRAS, 501, 548 [Google Scholar]
  175. Krauss, M. I., Schulz, N. S., Chakrabarty, D., Juett, A. M., & Cottam, J. 2007, ApJ, 660, 605 [NASA ADS] [CrossRef] [Google Scholar]
  176. Krimm, H. A., Markwardt, C. B., Deloye, C. J., et al. 2007, ApJ, 668, L147 [NASA ADS] [CrossRef] [Google Scholar]
  177. Kuulkers, E. 2005, ATel, 483 [Google Scholar]
  178. Kuulkers, E. 2009, ATel, 2141, 1 [NASA ADS] [Google Scholar]
  179. Kuulkers, E., den Hartog, P. R., in ’t Zand, J. J. M., et al. 2003, A & A, 399, 663 [Google Scholar]
  180. Kuulkers, E., in ’t Zand, J. J. M., Atteia, J.-L., et al. 2010, A & A, 514, A65 [Google Scholar]
  181. Lasota, J.-P. 2001, New Astron. Rev., 45, 449 [Google Scholar]
  182. Lehto, H. J., Machin, G., McHardy, I. M., & Callanan, P. 1990, Nature, 347, 49 [NASA ADS] [CrossRef] [Google Scholar]
  183. Lewin, W. H. G. 1976, IAUC, 2914 [Google Scholar]
  184. Lewin, W. H. G., Li, F. K., Hoffman, J. A., et al. 1976, MNRAS, 177, 93 [Google Scholar]
  185. Lin, J., & Yu, W. 2018, MNRAS, 474, 1922 [NASA ADS] [CrossRef] [Google Scholar]
  186. Lin, J., & Yu, W. 2020, ApJ, 903, 37 [NASA ADS] [CrossRef] [Google Scholar]
  187. Lin, D., Webb, N. A., & Barret, D. 2012, ApJ, 756, 27 [NASA ADS] [CrossRef] [Google Scholar]
  188. Liu, Q. Z., Van Paradijs, J., & Van Den Heuvel, E. P. 2007, A & A, 469, 807 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  189. Ludlam, R. M., Miller, J. M., Cackett, E. M., et al. 2016, ApJ, 824, 37 [NASA ADS] [CrossRef] [Google Scholar]
  190. Ludlam, R. M., Miller, J. M., Cackett, E. M., Degenaar, N., & Bostrom, A. C. 2017, ApJ, 838, 79 [NASA ADS] [CrossRef] [Google Scholar]
  191. Machin, G., Callanan, P. J., Charles, P. A., et al. 1990, MNRAS, 247, 205 [NASA ADS] [Google Scholar]
  192. Madej, O. K., Jonker, P. G., Fabian, A. C., et al. 2010, MNRAS, 407, L11 [NASA ADS] [Google Scholar]
  193. Madej, O. K., Jonker, P. G., Groot, P. J., et al. 2013, MNRAS, 429, 2986 [NASA ADS] [CrossRef] [Google Scholar]
  194. Malesani, D. B., Izzo, L., Palmerio, J., et al. 2020, GRB Coordinates Network, 26989, 1 [Google Scholar]
  195. Markert, T. H., Bradt, H. V., Clark, G. W., et al. 1975, IAUC, 2765, 1 [NASA ADS] [Google Scholar]
  196. Markert, T. H., Backman, D. E., & McClintock, J. E. 1976, ApJ, 208, L115 [NASA ADS] [CrossRef] [Google Scholar]
  197. Markwardt, C. B., Swank, J. H., Strohmayer, T. E., in ’t Zand, J. J. M., & Marshall, F. E. 2002, ApJ, 575, L21 [NASA ADS] [CrossRef] [Google Scholar]
  198. Markwardt, C. B., Juda, M., & Swank, J. H. 2003a, IAUC, 8095 [Google Scholar]
  199. Markwardt, C. B., Smith, E., & Swank, J. H. 2003b, ATel, 122, 1 [NASA ADS] [Google Scholar]
  200. Martí, J., Mirabel, I. F., Rodríguez, L. F., & Chaty, S. 1998, A & A, 332, 45 [Google Scholar]
  201. Mata Sánchez, D., Charles, P. A., Armas Padilla, M., et al. 2017, MNRAS, 468, 564 [Google Scholar]
  202. McClintock, J. E., Canizares, C. R., Bradt, H. V., et al. 1977, Nature, 270, 320 [NASA ADS] [CrossRef] [Google Scholar]
  203. Melandri, A., Covino, S., Fugazza, D., D’Avanzo, P. I., & REM Team 2020, GRB Coordinates Network, 26986, 1 [Google Scholar]
  204. Middleditch, J., Mason, K. O., Nelson, J. E., & White, N. E. 1981, ApJ, 244, 1001 [NASA ADS] [CrossRef] [Google Scholar]
  205. Migliari, S., Tomsick, J. A. A., Miller-Jones, J. C. A. C. A., et al. 2010, ApJ, 710, 117 [NASA ADS] [CrossRef] [Google Scholar]
  206. Miller-Jones, J. C. A., Strader, J., Heinke, C. O., et al. 2015, MNRAS, 453, 3918 [Google Scholar]
  207. Molkov, S., Revnivtsev, M., Lutovinov, A., & Sunyaev, R. 2005, A & A, 434, 1069 [Google Scholar]
  208. Monelli, M., Fiorentino, G., Burderi, L., et al. 2005, AIPC, 797, 565 [NASA ADS] [Google Scholar]
  209. Mori, H., Maeda, Y., Pavlov, G. G., Sakano, M., & Tsuboi, Y. 2005, Adv. Space Res., 35, 1137 [NASA ADS] [CrossRef] [Google Scholar]
  210. Morris, S. L., Liebert, J., Stocke, J. T., et al. 1990, ApJ, 365, 686 [NASA ADS] [CrossRef] [Google Scholar]
  211. Mukai, K., Smale, A. P., Stahle, C. K., Schlegel, E. M., & Wijnands, R. 2001, ApJ, 561, 938 [NASA ADS] [CrossRef] [Google Scholar]
  212. Muno, M. P., Belloni, T., Dhawan, V., et al. 2005, ApJ, 626, 1020 [NASA ADS] [CrossRef] [Google Scholar]
  213. Murakami, T., Inoue, H., Koyama, K., et al. 1983, PASJ, 35, 537 [Google Scholar]
  214. Nakajima, M., Sugita, S., Serino, M., et al. 2020, ATel, 13754, 1 [NASA ADS] [Google Scholar]
  215. Negoro, H., Serino, M., Mihara, T., et al. 2015a, ATel, 7504, 1 [NASA ADS] [Google Scholar]
  216. Negoro, H., Serino, M., Sasaki, R., et al. 2015b, ATel, 8241, 1 [NASA ADS] [Google Scholar]
  217. Nelemans, G. 2018, ArXiv e-prints [arXiv: 1807.01060] [Google Scholar]
  218. Nelemans, G., & Jonker, P. G. 2010, New Astron. Rev., 54, 87 [Google Scholar]
  219. Nelemans, G., Jonker, P. G., Marsh, T. R., & Van Der Klis, M. 2004, MNRAS, 348, L7 [NASA ADS] [CrossRef] [Google Scholar]
  220. Nelemans, G., Jonker, P. G., & Steeghs, D. 2006, MNRAS, 370, 255 [Google Scholar]
  221. Nelemans, G., Wood, M., Groot, P., et al. 2009, Astro2010: The Astronomy and Astrophysics Decadal Survey, Science White Papers, 221 [Google Scholar]
  222. Nelemans, G., Yungelson, L. R., Sluys, M. V. D., & Tout, C. A. 2010, MNRAS, 401, 1347 [NASA ADS] [CrossRef] [Google Scholar]
  223. Nelson, L. A., & Rappaport, S. 2003, ApJ, 598, 431 [NASA ADS] [CrossRef] [Google Scholar]
  224. Nelson, L. A. A., Rappaport, S. A. A., & Joss, P. C. C. 1986, ApJ, 304, 231 [NASA ADS] [CrossRef] [Google Scholar]
  225. Ng, M., Ray, P. S., Bult, P., et al. 2021, ApJ, 908, L15 [NASA ADS] [CrossRef] [Google Scholar]
  226. Paczynski, B., & Sienkiewicz, R. 1981, ApJ, 248, L27 [NASA ADS] [CrossRef] [Google Scholar]
  227. Paduano, A., Bahramian, A., Miller-Jones, J. C., et al. 2021, MNRAS, 506, 4107 [NASA ADS] [CrossRef] [Google Scholar]
  228. Papitto, A., D’Aì, A., Di Salvo, T., et al. 2013, MNRAS, 429, 3411 [NASA ADS] [CrossRef] [Google Scholar]
  229. Paresce, F., de Marchi, G., & Ferraro, F. R. 1992, Nature, 360, 46 [NASA ADS] [CrossRef] [Google Scholar]
  230. Patruno, A., & Watts, A. L. 2021, in Timing Neutron Stars: Pulsations, Oscillations and Explosions (Springer), 143 [NASA ADS] [CrossRef] [Google Scholar]
  231. Pavlinsky, M. N., Grebenev, S. A., & Sunyaev, R. A. 1994, ApJ, 425, 110 [Google Scholar]
  232. Piro, L., Heise, J., Jager, R., et al. 1997, IAUC, 6538, 2 [NASA ADS] [Google Scholar]
  233. Podsiadlowski, P., Rappaport, S., & Pfahl, E. D. 2002, ApJ, 565, 1107 [NASA ADS] [CrossRef] [Google Scholar]
  234. Qin, K., Jiang, L., & Chen, W.-C. 2023, ApJ, 944, 83 [NASA ADS] [CrossRef] [Google Scholar]
  235. Rappaport, S., Joss, P. C., & Webbink, R. F. 1982, ApJ, 254, 616 [NASA ADS] [CrossRef] [Google Scholar]
  236. Rasio, F. A., Pfahl, E. D., & Rappaport, S. 2000, ApJ, 532, L47 [NASA ADS] [CrossRef] [Google Scholar]
  237. Ravi, V. 2017, ApJ, 851, 114 [NASA ADS] [CrossRef] [Google Scholar]
  238. Remillard, R., & RXTE ASM Team 2002, ATel, 92, 1 [NASA ADS] [Google Scholar]
  239. Revnivtsev, M. G., Trudolyubov, S. P., & Borozdin, K. N. 2002, Astron. Lett., 28, 237 [Google Scholar]
  240. Revnivtsev, M. G., Kniazev, A., Karasev, D. I., Berdnikov, L., & Barway, S. 2013, Astron. Lett., 39, 523 [NASA ADS] [CrossRef] [Google Scholar]
  241. Ricci, C., Beckmann, V., Carmona, A., & Weidenspointner, G. 2008, ATel, 1840, 1 [Google Scholar]
  242. Rupen, M. P., Dhawan, V., & Mioduszewski, A. J. 2003, ATel, 210, 1 [NASA ADS] [Google Scholar]
  243. Rupen, M. P., Mioduszewski, A. J., Dhawan, V., et al. 2005, ATel, 530, 1 [NASA ADS] [Google Scholar]
  244. Sakano, M., Koyama, K., Murakami, H., et al. 2002, ApJS, 138, 19 [NASA ADS] [CrossRef] [Google Scholar]
  245. Salaris, M., Held, E. V., Ortolani, S., Gullieuszik, M., & Momany, Y. 2007, A & A, 476, 243 [Google Scholar]
  246. Sanna, A., Papitto, A., Burderi, L., et al. 2017, A & A, 598, A34 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  247. Sanna, A., Bahramian, A., Bozzo, E., et al. 2018a, A & A, 610, A2 [Google Scholar]
  248. Sanna, A., Bozzo, E., Papitto, A., et al. 2018b, A & A, 616, L17 [Google Scholar]
  249. Sanna, A., Pintore, F., Riggio, A., et al. 2018c, MNRAS, 481, 1658 [NASA ADS] [CrossRef] [Google Scholar]
  250. Sanna, A., Bult, P., Ng, M., et al. 2022, MNRAS, 516, L76 [NASA ADS] [CrossRef] [Google Scholar]
  251. Savonije, G. J., de Kool, M., & van den Heuvel, E. P. J. 1986, A & A, 155, 51 [NASA ADS] [Google Scholar]
  252. Schulz, N. S., Chakrabarty, D., Marshall, H. L., et al. 2001, ApJ, 563, 941 [CrossRef] [Google Scholar]
  253. Schulz, N. S., Nowak, M. A., Chakrabarty, D., & Canizares, C. R. 2010, ApJ, 725, 2417 [NASA ADS] [CrossRef] [Google Scholar]
  254. Sengar, R., Tauris, T. M., Langer, N., & Istrate, A. G. 2017, MNRAS, 470, L6 [NASA ADS] [CrossRef] [Google Scholar]
  255. Serino, M., Tanaka, K., Negoro, H., et al. 2016, ATel, 8872, 1 [NASA ADS] [Google Scholar]
  256. Serino, M., Hidaka, K., Negoro, H., et al. 2018, ATel, 1302, 1 [Google Scholar]
  257. Seward, F. D., Page, C. G., Turner, M. J. L., & Pounds, K. A. 1976a, MNRAS, 175, 39 [Google Scholar]
  258. Seward, F. D., Page, C. G., Turner, M. J. L., & Pounds, K. A. 1976b, MNRAS, 177, 13 [Google Scholar]
  259. Shahbaz, T., Watson, C. A., Zurita, C., Villaver, E., & Hernandez-Peralta, H. 2008, PASP, 120, 848 [NASA ADS] [CrossRef] [Google Scholar]
  260. Shaw, A. W., Heinke, C. O., Degenaar, N., et al. 2017, MNRAS, 471, 2508 [NASA ADS] [CrossRef] [Google Scholar]
  261. Shidatsu, M., Iwakiri, W., Negoro, H., et al. 2021, ApJ, 910, 144 [NASA ADS] [CrossRef] [Google Scholar]
  262. Sidoli, L., & Mereghetti, S. 2003, ATel, 147, 1 [NASA ADS] [Google Scholar]
  263. Sidoli, L., Parmar, A. N., Oosterbroek, T., et al. 2001, A & A, 368, 451 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  264. Sidoli, L., Paizis, A., Bazzano, A., & Mereghetti, S. 2006, A & A, 460, 229 [Google Scholar]
  265. Sidoli, L., Paizis, A., Mereghetti, S., Götz, D., & Del Santo, M. 2011, MNRAS, 415, 2373 [NASA ADS] [CrossRef] [Google Scholar]
  266. Skinner, G. K., Willmore, A. P., Eyles, C. J., et al. 1987, Nature, 330, 544 [NASA ADS] [CrossRef] [Google Scholar]
  267. Skinner, G. K., Foster, A. J., Willmore, A. P., & Eyles, C. J. 1990, MNRAS, 243, 72 [NASA ADS] [Google Scholar]
  268. Smale, A. P. 2001, ApJ, 562, 957 [NASA ADS] [CrossRef] [Google Scholar]
  269. Solheim, J.-E. S. E. 2010, PASP, 122, 1133 [NASA ADS] [CrossRef] [Google Scholar]
  270. Stacey, W. S., Heinke, C. O., Cohn, H. N., Lugger, P. M., & Bahramian, A. 2012, ApJ, 751, 62 [NASA ADS] [CrossRef] [Google Scholar]
  271. Steeghs, D., Torres, M. A. P., Garcia, M. R., et al. 2005, ATel, 543, 1 [NASA ADS] [Google Scholar]
  272. Stella, L., White, N. E., & Priedhorsky, W. 1987, ApJ, 312, L17 [NASA ADS] [CrossRef] [Google Scholar]
  273. Stoop, M., van den Eijnden, J., Degenaar, N., et al. 2021, MNRAS, 507, 330 [NASA ADS] [CrossRef] [Google Scholar]
  274. Strohmayer, T. E., & Brown, E. F. 2002, ApJ, 566, 1045 [NASA ADS] [CrossRef] [Google Scholar]
  275. Strohmayer, T. E., Arzoumanian, Z., Bogdanov, S., et al. 2018a, ApJ, 858, L13 [NASA ADS] [CrossRef] [Google Scholar]
  276. Strohmayer, T. E., Ray, P. S., Gendreau, K. C., et al. 2018b, ATel, 11507, 1 [NASA ADS] [Google Scholar]
  277. Sugizaki, M., Mitsuda, K., Kaneda, H., et al. 2001, ApJS, 134, 77 [NASA ADS] [CrossRef] [Google Scholar]
  278. Suzuki, M., & Kawai, N. 2005, ATel, 539 [Google Scholar]
  279. Swank, J. H., Becker, R. H., Pravdo, S. H., Saba, J. R., & Serlemitsos, P. J. 1976, IAUC, 3010 [Google Scholar]
  280. Swank, J. H., Becker, R. H., Boldt, E. A., et al. 1977, ApJ, 212, L73 [NASA ADS] [CrossRef] [Google Scholar]
  281. Tarana, A., Bazzano, A., Ubertini, P., et al. 2006, A & A, 448, 335 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  282. Tauris, T. M. 2018, Phys. Rev. Lett., 121, 131105 [NASA ADS] [CrossRef] [Google Scholar]
  283. Tauris, T. M., & van den Heuvel, E. P. J. 2006, in Compact Stellar X-ray Sources, eds. W. H. G. Lewin, & M. van der Klis (Cambridge University Press), 39, 623 [NASA ADS] [CrossRef] [Google Scholar]
  284. Tawara, Y., Kii, T., Hayakawa, S., et al. 1984, ApJ, 276, L41 [NASA ADS] [CrossRef] [Google Scholar]
  285. Tetarenko, B. E., Sivakoff, G. R., Heinke, C. O., & Gladstone, J. C. 2016, ApJS, 222, 15 [Google Scholar]
  286. Tetarenko, A. J., Bahramian, A., Wijnands, R., et al. 2018, ApJ, 854, 125 [NASA ADS] [CrossRef] [Google Scholar]
  287. Tomsick, J. A., Walter, R., Kaaret, P., et al. 2007, ATel, 1189 [Google Scholar]
  288. Torres, M. A. P., Steeghs, D., Jonker, P. G., & Ross, N. R. 2010, ATel, 2870, 1 [NASA ADS] [Google Scholar]
  289. Tudor, V., Miller-Jones, J. C. A., Knigge, C., et al. 2018, MNRAS, 476, 1889 [NASA ADS] [CrossRef] [Google Scholar]
  290. Tutukov, A. V., Fedorova, A. V., Ergma, E. V., & Yungelson, L. R. 1985, Pisma Astron. Zh., 11, 123 [NASA ADS] [Google Scholar]
  291. Valenti, E., Ferraro, F. R., & Origlia, L. 2010, MNRAS, 402, 1729 [NASA ADS] [CrossRef] [Google Scholar]
  292. van den Eijnden, J., Degenaar, N., Pinto, C., et al. 2018a, MNRAS, 475, 2027 [NASA ADS] [CrossRef] [Google Scholar]
  293. van den Eijnden, J., Degenaar, N., Russell, T., et al. 2018b, ATel, 11487, 1 [NASA ADS] [Google Scholar]
  294. Van Den Eijnden, J., Degenaar, N., Russell, T. D., et al. 2021, MNRAS, 507, 3899 [NASA ADS] [CrossRef] [Google Scholar]
  295. van Haaften, L. M., Voss, R., & Nelemans, G. 2012a, A & A, 543, A121 [Google Scholar]
  296. van Haaften, L. M. M., Nelemans, G., Voss, R., Wood, M. A. A., & Kuijpers, J. 2012b, A & A, 537, A104 [Google Scholar]
  297. van Haaften, L. M., Nelemans, G., Voss, R., & Jonker, P. G. 2012c, A & A, 541, A22 [Google Scholar]
  298. van Haaften, L. M., Nelemans, G., Voss, R., et al. 2013, A & A, 552, A69 [Google Scholar]
  299. van Paradijs, J., & McClintock, J. E. E. 1994, A & A, 290, 133 [Google Scholar]
  300. van Paradijs, J., Dotani, T., Tanaka, Y., & Tsuru, T. 1990, PASJ, 42, 633 [NASA ADS] [Google Scholar]
  301. Vanderspek, R., Morgan, E., Crew, G., Graziani, C., & Suzuki, M. 2005, ATel, 516, 1 [NASA ADS] [Google Scholar]
  302. Verbunt, F. 1987, ApJ, 312, L23 [NASA ADS] [CrossRef] [Google Scholar]
  303. Villa, G., Page, C. G., Turner, M. J. L., et al. 1976, MNRAS, 176, 609 [NASA ADS] [CrossRef] [Google Scholar]
  304. Vincentelli, F. M., Cavecchi, Y., Casella, P., et al. 2020, MNRAS, 495, 37 [Google Scholar]
  305. Voges, W., Aschenbach, B., Boller, T., et al. 1999, A & A, 349, 389 [NASA ADS] [Google Scholar]
  306. Walter, F. M., Bowyer, S., Mason, K. O., et al. 1982, ApJ, 253, 67 [Google Scholar]
  307. Walter, R., Bodaghee, A., Barlow, E. J., et al. 2004, ATel, 229, 1 [NASA ADS] [Google Scholar]
  308. Wang, Z., & Chakrabarty, D. 2004, ApJ, 616, L139 [NASA ADS] [CrossRef] [Google Scholar]
  309. Wang, Z. M., & Chakrabarty, D. 2010, ApJ, 712, 653 [NASA ADS] [CrossRef] [Google Scholar]
  310. Wang, Y., Méndez, M., Altamirano, D., et al. 2019, MNRAS, 484, 3004 [NASA ADS] [CrossRef] [Google Scholar]
  311. Webb, N. A., Coriat, M., Traulsen, I., et al. 2020, A & A, 641, A136 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  312. Werner, K., Nagel, T., Rauch, T., Hammer, N. J., & Dreizler, S. 2006, A & A, 450, 725 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  313. White, N. E., & Swank, J. H. 1982, ApJ, 253, L61 [NASA ADS] [CrossRef] [Google Scholar]
  314. White, N. E., & Angelini, L. 2001, ApJ, 561, L101 [NASA ADS] [CrossRef] [Google Scholar]
  315. Wiersema, K., Russell, D. M., Degenaar, N., et al. 2009, MNRAS, 397, L6 [NASA ADS] [CrossRef] [Google Scholar]
  316. Wijnands, R., & Van Der Klis, M. 1998, Nature, 394, 344 [CrossRef] [Google Scholar]
  317. Wijnands, R., Parikh, A. S., Altamirano, D., Homan, J., & Degenaar, N. 2017, MNRAS, 472, 559 [NASA ADS] [CrossRef] [Google Scholar]
  318. Wilson, C. A., Patel, S. K., Kouveliotou, C., et al. 2003, ApJ, 596, 1220 [NASA ADS] [CrossRef] [Google Scholar]
  319. Yungelson, L. R. 2008, Astron. Lett., 34, 620 [Google Scholar]
  320. Yungelson, L. R., Nelemans, G., & Van Den Heuvel, E. P. 2002, A & A, 388, 546 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  321. Zhang, Y., Hynes, R. I., & Robinson, E. L. 2012, MNRAS, 419, 2943 [NASA ADS] [CrossRef] [Google Scholar]
  322. Zhong, J., & Wang, Z. 2011, ApJ, 729, 8 [Google Scholar]
  323. Zhu, C. H., Lü, G. L., & Wang, Z. J. 2012, Res. Astron. Astrophys., 12, 1526 [CrossRef] [Google Scholar]
  324. Zolotukhin, I. Y., & Revnivtsev, M. G. 2011, MNRAS, 411, 620 [NASA ADS] [CrossRef] [Google Scholar]
  325. Zurek, D. R., Knigge, C., MacCarone, T. J., Dieball, A., & Long, K. S. 2009, ApJ, 699, 1113 [NASA ADS] [CrossRef] [Google Scholar]

All Tables

Table B.1

Astrometry and location.

In the text
Table B.2

Main observational properties.

In the text
Table B.3

Additional multi-wavelength properties.

In the text

All Figures

thumbnail Fig. 1

Cumulative histogram of ultra-compact and short orbital period LMXBs detected since the beginning of the X-ray astronomy era. The black bars represent the confirmed UCXBs.
In the text
thumbnail Fig. 2

Distribution for all the sources included in the catalogue. Top: galactic distribution for the 20 confirmed UCXBs (yellow), 25 candidates (orange) and four short-period LMXBs (green) in Galactic coordinates. Systems located in GCs are marked with stars rather than circles. (Background image credit: ESA/Gaia/DPAC.) Bottom: histogram of the distribution of all sources in Galactic longitude (left) and latitude (right). Blue is used for all systems (field + GC), and green for those located in GCs. A bin size of 10 deg has been applied in both plots.
In the text
thumbnail Fig. 3

Galactic distribution of UCXBs and short-period LMXB systems with estimated distances following the same colours and symbols as in Fig. 2 (Background image credit: NASA/JPL-Caltech/R. Hurt (SSC/Caltech)).
In the text
thumbnail Fig. 4

Orbital period distribution. Top panel: Histogram of the orbital period of UCXBs and short-period LMXB systems, plotted in 10 min bins (grey) and 5 min bins [blue for all systems (field + GC) and green for those located in GCs]. The canonical 80 min that defines the bona fide UCXBs limit is shown as a dotted black line. Lower panel: Percentage of systems accreting persistently.
In the text
thumbnail Fig. A.1

Histogram of the distribution of all the objects with known distances (left) and their scale height (z) from the Galactic plane (right).
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.