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Cataclysmic variables (CVs) are strong interacting binaries. They are systems with an accreting white dwarf (WD, the primary) and a red dwarf (the donor). The donor star is on a late-type main sequence, or sometimes in a slightly evolved state. An accretion disc forms and accreted material reaches the WD in the case in which the magnetic field of the primary is too weak to interrupt the accretion flow (B  0.01 MG): such systems are referred to as non-magnetic CVs, characterized by their eruptive behaviour (Warner 1995). Mass and angular momentum transfer from the donor star to the WD drive a rich variety of variability, as well as the evolution of these systems (Knigge, Baraffe & Patterson 2011). Nova-like variables (NLs) and dwarf novae (DNs) are subtypes of non-magnetic CVs: in addition to the more frequent eruption of DNs, there are many differences between them. NLs have high accretion rates (∼10−8 M⊙ yr−1), so are in a persistent high state, and they gather above the period gap in the period distribution of CVs (Thorstensen et al. 1991); while the accretion rates of DNs are lower than those of NLs by one or two orders of magnitude (≤10−9 M⊙ yr−1), their luminosities only match those of NLs during DN outbursts and their periods are more commonly below the period gap. The possible evolutionary links between the two classes were discussed by Shara et al. (1986) as part of the hibernation scenario, in which systems are NLs immediately after a nova burst and then metamorphose into DNs if their luminosity becomes sufficiently low within several centuries. The hibernation hypothesis also predicts that CVs will experience novae, NLs, and DNs within 104−105 yr and repeat the cycle during their lifetimes. The NL system V1315 Aql was estimated to experience a nova outburst about 500–1200 yr earlier (Sahman et al. 2018): this is consistent with nova-induced cycles in hibernation theory. Kovetz, Prialnik & Shara (1988) estimated that the mass-transfer rate declines at a rate of 0.012 mag yr−1 for the century following outburst. Despite enhanced interest in long-term observations of post-novae and their final decline inspired by the hibernation hypothesis, analysis of the secular evolution of NLs is not yet well known.
Citation: Thorstensen et al. 1991
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Depending on the specific driver, the characteristics of turbulence will then be imprinted within the ISM mainly as three-dimensional density and velocity fluctuations, and these fluctuations have been traditionally studied via correlation functions such as the spatial power spectrum (SPS) (e.g., Crovisier & Dickey 1983), Δ-variance (e.g., Stutzki et al. 1998), and structure function (e.g., Padoan et al. 2002; Burkhart et al. 2015b). In particular, the SPS approach has been applied to observations of various Galactic and extragalactic environments (e.g., Plume et al. 2000; Dickey et al. 2001; Elmegreen et al. 2001; Burkhart et al. 2010; Combes et al. 2012; Zhang et al. 2012; Pingel et al. 2013), showing power spectral slopes β roughly ranging from −2.7 to −3.7 depending on the tracers used (e.g., H i, carbon monoxide (CO), and dust). These slopes essentially provide information on the relative amount of structure as a function of spatial scale and can be compared with theoretical models of turbulence (mainly numerical simulations) to characterize turbulence cascade (e.g., Burkhart et al. 2010), to determine the influence of shocks (e.g., Beresnyak et al. 2005), to reveal the injection and dissipation scales of turbulent energy (e.g., Kowal & Lazarian 2007; Federrath & Klessen 2013; Chen et al. 2015), and to trace the evolution of MCs (e.g., Burkhart et al. 2015a). The proximity and abundance of multi-wavelength observations make MCs in the solar neighborhood an ideal laboratory for probing the impact of turbulence on their formation and evolution. In this paper, we focus on the Perseus MC, which is a nearby (∼300 pc; e.g., Herbig & Jones 1983; Černis 1990), low-mass (∼2 × 104 M⊙; e.g., Sancisi et al. 1974; Lada et al. 2010) cloud. Its star formation activities, as well as atomic and molecular gas content, have been extensively examined over the past decade (e.g., Ridge et al. 2006; Jørgensen et al. 2007; Pineda et al. 2008; Lee et al. 2012, 2014, 2015; Mercimek et al. 2017), revealing that the cloud consists of several individual dark and star-forming regions (e.g., B5, B1, B1E, IC 348, and NGC 1333) and is actively forming low- to intermediate-mass stars (see Bally et al. 2008 for a review).
Citation: Burkhart et al. 2010
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Citation: Burkhart et al. 2010
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Citation: Pingel et al. 2013
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The catalogue represents a luminosity-complete sample of galaxies with r-band absolute magnitude Mr ≤ −19 in a (300h−1Mpc)3 comoving volume at z = 0. The mock contains both central and satellite galaxies, populated in dark matter haloes identified in an N-body simulation having 10243 particles with a flat ΛCDM WMAP7 cosmology (Komatsu et al. 2011; Ωm = 0.276, h = 0.7). To achieve the luminosity completeness threshold of Mr ≤ −19, haloes containing ≥40 particles are considered. Since the halo concentration cannot be reliably measured for haloes with fewer than about ∼400 particles, we use the method presented by Ramakrishnan, Paranjape & Sheth (2021) to assign concentrations cvir (assuming Navarro, Frenk & White 1996, NFW profiles) conditioned on the mass and local tidal environment of individual haloes.2 The galaxies were populated using a halo occupation distribution (HOD) model and H i-optical scaling relations calibrated by Paul, Choudhury & Paranjape (2018) and Paul, Pahwa & Paranjape (2019) using luminosity- and colour-dependent clustering measurements from the Sloan Digital Sky Survey (SDSS; York et al. 2000; Zehavi et al. 2011) and H i-dependent clustering measurements from the Arecibo Legacy Fast ALFA survey (ALFALFA; Giovanelli et al. 2005; Guo et al. 2017). Each galaxy in the mock is assigned absolute magnitudes in SDSS u, g, and r bands (with a threshold Mr ≤ −19 imposed by the SDSS clustering measurements) and a stellar mass m* using a colour-dependent mass-to-light ratio. The H i-optical scaling relation additionally leads to a fraction ${\sim}60{{\ \rm per\ cent}}$ of galaxies to be assigned an H i mass $m_{\rm{H}\,{\small I}}$. PCS21 presented extensive tests of this algorithm. We focus in this work on the population of mock central galaxies containing massive H i discs, with $m_{\rm{H}\,{\small I}}\ge 10^{9.7}h^{-2}M_{\odot }$; the resulting ∼50 000 such objects in our catalogue form a volume-complete sample of H i-selected galaxies.
Citation: Navarro, Frenk & White 1996
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Over time, the data releases have treated the Balmer line regions in different ways. The presence of the artificial curvature was first reported by Busca et al. (2013) in the context of the DR9 data release. To minimize this effect, a different scheme was used in DR12 (Alam et al. 2015, see their table 2) by using a linear function (instead of an iterative b-spline procedure) to interpolate the flux over the masked regions. Surprisingly, we observe that this data reduction change was only applied to the Balmer β, γ, and δ lines but not applied to the Balmer α line. For the latter one, the original iterative spline interpolation scheme has been used all along. As a result, an absorption-like feature at the location of Balmer α is found in SDSS data releases 9 up to now, i.e. the latest data release 14 (Abolfathi et al. 2018). To illustrate this, we show examples of calibration vectors for SDSS BOSS DR9 (Ahn et al. 2012; Dawson et al. 2013), DR12 (Alam et al. 2015), eBOSS DR14 (Dawson et al. 2016; Abolfathi et al. 2018) data release as well as calibration vectors for the MaNGA survey (Bundy et al. 2015) DR14 data release (Abolfathi et al. 2018) in Fig. 6. In the upper panel, we show small-scale features in calibration vectors from the same plate (number 3647) processed by the DR9 (blue), DR12 (green), and DR14 (red) pipelines. The spectra are obtained by normalizing the large-scale features in calibration vectors with a cubic b-spline with break points separated by 50 Å. The three spectra are mostly identical while the smooth curving features at the wavelengths of Balmer series in DR9 disappear in DR12 and DR14. From DR12, the pipeline corrects the features with linear interpolation across wavelength regions with Balmer β, γ, and δ lines (Alam et al. 2015). One can also observe the change in the median residual spectra of DR9 and DR12 in Fig. 1. However, the Hα feature remains uncorrected from DR9 to DR14. We also show a DR7 calibration vector (black) in which most of the wiggles are absent. As pointed previously, this is due to the fact that the DR7 pipeline interpolates the calibration vectors using an effective scale larger than that used in subsequent data releases.
Citation: Abolfathi et al. 2018
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Citation: Abolfathi et al. 2018
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Citation: Abolfathi et al. 2018
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The new sample of HSPs gave us an opportunity to see the optical IDVs of HSPs and compare its properties with optical IDVs of LSPs. We started a dedicated project to search for optical IDV in HSPs and after doing 62 nights of IDV observations of HSPs which gave us 144 LCs (41 in B band, 62 in R band, and 41 in B−R colour) of five HSPs (Mrk 421, 1ES 1426+428, 1ES 1553+113, 1ES 1959+650, and 1ES 2344+514). Interestingly, we found that, four HSPs did not show any IDV (Gaur, Gupta & Wiita 2012a; Gaur et al. 2012b,c), but only one HSP 1ES 1426+428 for which we have the least observations have shown IDV in six LCs out of eight LCs (Gaur et al. 2012c). Our this pilot project gave us 6 IDV LCs out of 144 LCs searched for IDV i.e ∼4 per cent LCs have shown IDV. We explained it by density inhomogeneities and bends in the bases of the jets by Kelvin–Helmholtz instabilities (Romero, Cellone & Combi 1999). We gave an alternative explanation i.e. since in HSPs, the optical band lies below the SED peak, hence, we should see changes in the efficiency of acceleration of, and/or in the rates at which energy is radiated by, the highest energy electrons available for synchrotron emission would have a more retarded effect on optical variability in HSPs (Gaur et al. 2012b). In LSPs, the optical band is dominated by highest energy electrons emitting synchrotron radiation and probably the X-ray emission is dominated by the comparatively lower energy electrons emitting the inverse Compton radiation, hence their X-ray variability is less pronounced than optical variability. If SED peak is really responsible for IDV properties, then we suspected that X-ray IDV LCs in LSPs should not show any IDV at all or show on rare occasions. With this motivation, here we present the X-ray IDV study of almost complete sample of 10 LSPs and 2 ISPs observed by XMM–Newton since its launch and we found that the LSPs show very less IDV 2 out of 50 LC i.e. 4 per cent in X-ray bands. We have reported above the similar finding for HSPs in optical bands.
Citation: Gaur et al. 2012; c
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The distances to planetary nebulae (PNe) have always faced the difficulty that nearby targets were lacking that could be reached well by direct methods. Trigonometric parallaxes have been obtained in a homogeneous long time-line campaign by the US Naval Observatory (USNO; Harris et al. 2007) and from the Hubble Space Telescope (HST; Benedict et al. 2009). Other studies (Acker et al. 1998; Smith 2015) showed that Hipparcos spacecraft parallaxes do not seem to be reliable. It was assumed that contamination by the emission of the surrounding nebulae caused these problems. Another model-independent method for distances to PNe are a cluster membership, as studied extensively by Majaess et al. (2007, 2014), and as discussed in Frew et al. (2016). In addition to these model-independent methods, a wide variety of statistical, model-dependent individual distance scales have been derived. The most frequently used of these are certainly those that are based on surface brightness versus angular sizes. They sometimes include optical depth corrections. All these methods have to be calibrated against a data set of nebulae with known distances. The older, widely used method is based on the 6 cm radio continuum flux, either using the ionized mass concept of Daub (1982) in the calibrations of Cahn et al. (1992) and Stanghellini et al. (2008), or by means of the radio continuum brightness temperature as used by van de Steene & Zijlstra (1994) and calibrated with a Galactic bulge sample. The newest model developed by Frew et al. (2016) is based on similar ideas, but makes use of the optical Hα surface brightness and a wide set of various calibrators. Moreover, they use a completely homogeneous data set for the brightness data derived earlier by themselves (Frew et al. 2013). Smith (2015) and Frew et al. (2016) described the underlying physics and assumptions for all these methods in detail. With the upcoming Gaia project (Gaia Collaboration 2016), a new era was expected to start for many classes of objects. The first step into this was described by Stanghellini et al. (2017) based on the combined Tycho + Gaia DR1 solution called TGAS (Michalik et al. 2015). With the second Data Release of Gaia (hereafter GDR2; Gaia Collaboration 2018), a complete homogeneous data set based only on Gaia measurements is available now for the first time. We present here the comparison of this new data set with common previous calibrations of PNe distances. Moreover, we compare it to the preliminary TGAS results in Stanghellini et al. (2017). Finally, we discuss possible caveats using the current GDR2.
Citation: Frew et al. (2016)
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Citation: Frew et al. (2016)
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Water ice is ubiquitous in the cold regions of the Universe, owing to the fact that hydrogen and oxygen are the two most abundant elements to form a solid such as icy dust particles and comets. It is, therefore, commonly accepted that the essential component of dust particles and planetesimals in protoplanetary discs is water ice beyond the so-called snow line, at which the temperature of gas is low enough for water vapour to condense into ices (e.g. Cyr, Sears & Lunine 1998). Reactive accretion of water ice from hydrogen and oxygen atoms on the surface of dust particles takes place in the dense core of molecular clouds where the growth of dust particles has been observed by scattering of stellar radiation (Steinacker et al. 2010). It is worthwhile noting that laboratory experiments on the coagulation growth of water-ice particles have a long history outside astronomy and planetary science, since coagulation is observed in daily life and is a plausible route to the formation of snowflakes (e.g. Faraday 1860; Hosler, Jensen & Goldshlak 1957). Recent works on laboratory measurements of cohesion between crystalline water-ice particles at vacuum conditions provided encouraging results that dust particles composed of water ice might be much more cohesive than previously believed (Gundlach et al. 2011; Gundlach & Blum 2015; Jongmanns et al. 2017). Form a theoretical point of view, Chokshi, Tielens & Hollenbach (1993) demonstrated that the JKR theory of elastic contact formulated by Johnson, Kendall & Roberts (1971) is a powerful tool for better understanding of dust coagulation. Numerical simulations incorporating the JKR theory have shown that dust aggregates consisting of submicrometre-sized water-ice particles proceed with coagulation growth even at a collision velocity of 50 m s−1 (Wada et al. 2009, 2013). As a result, the majority of recent studies on dust coagulation and planetesimal formation assume that silicate aggregates are disrupted by mutual collision at a velocity of vdisrupt ∼ 1 m s−1, but icy aggregates at vdisrupt ∼ 10 m s−1 (e.g. Birnstiel, Dullemond & Brauer 2010; Vericel & Gonzalez 2019). Such a trendy assumption led Drążkowska & Alibert (2017) to propose planetesimal formation by the ‘traffic jam’ effect at the snow line, provided that sticky water-ice particles grow faster and thus drift toward the central star faster than less-sticky bare silicate particles, implying that aggregates of the former catch up the latter at the snow line, which results in a traffic jam. However, we argue that the importance of water ice to dust coagulation is still open to debate, since water ice is not necessarily stickier than other materials such as silicates and complex organic matter (Kimura et al. 2015, 2020a; Musiolik & Wurm 2019).
Citation: Gundlach et al. 2011
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Citation: Hosler, Jensen & Goldshlak 1957
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The PN central white dwarf generates a significant ultraviolet (UV) radiation field during its transition from the proto-PN stage to the PN stage, typically ∼105 times that of the general interstellar medium (ISM), but decreasing to 10–100 as the remnant envelope expands and the luminosity of the white dwarf declines (Cox 1997). The copious amount of UV photons penetrating the nebula is predicted to photodissociate the remnant molecular material from the AGB stage within a thousand years (e.g., Redman et al. 2003). Indeed, the first molecular searches of PNe turned up negative (e.g., Penzias et al. 1971; Wilson et al. 1974). Subsequently, both CO and H2 have been detected in numerous PNe (e.g., Huggins & Healy 1989; Huggins et al. 1996, 2005; Hora et al. 1999; Likkel et al. 2006). More recent studies have identified other molecules in planetary nebulae with ever increasing complexity. Toward the young PNe NGC 7027 and NGC 6537, for example, HCN, HNC, CCH, CS, SO, H2CO, HCO+, and N2H+ have been identified (Zhang et al. 2008; Edwards & Ziurys 2013). In more evolved nebulae, species such as HCN, HNC, HCO+, CS, and CN have been found (e.g., Cox et al. 1992; Bachiller et al. 1997; Edwards et al. 2014). The very old Helix Nebula (age ∼12,000 years.) has an assortment of interesting molecules, including HCO+, CN, HCN, H2CO, CCH, c-C3H2, and HNC (Bachiller et al. 1997; Tenenbaum et al. 2009), and mapping data have shown that the molecular material is distributed throughout the PN (Zack & Ziurys 2013; Zeigler et al. 2013). SiO, SO, and SO2 have recently been found in M2-48 (age ∼5000 years.) as well (Edwards & Ziurys 2014). Perhaps even more striking is the identification of C60 in several PNe with low central star temperatures (Cami et al. 2010; García-Hernández et al. 2010, 2011, 2012; Otsuka et al. 2013). The presence of long-lived molecular material is believed to arise from shielding by high-density clumps (Howe et al. 1994), as seen in images of the Helix and the Ring (e.g., Meaburn et al. 1992; Speck et al. 2003; Meixner et al. 2005).
Citation: Wilson et al. 1974
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As of 2018, three multimeasurement catalogues including a substantial amount of redshift-independent extragalactic distance measurements have been released: HyperLEDA (Makarov et al. 2014), NED-D (Mazzarella & Team 2007; Steer et al. 2017), and Cosmicflows-3 (Tully, Courtois & Sorce 2016). HyperLEDA includes a homogenized catalogue for extragalactic distances in the nearby universe, with 12 866 distance measurements for 518 galaxies to date. NED-D is the NASA/IPAC Extragalactic Distance catalogue of redshift-independent distances, which compiles 326 850 distance measurements for 183 062 galaxies in its 2018 version. Here, ∼1800 galaxies (∼1 per cent) have more than 13 distance measurements, and 180 galaxies (∼0.1 per cent) have distance measurements using more than six different methods. Cosmicflows-3 is the most up-to-date catalogue, which reports distance measurements for 10 616 galaxies (all of which include errors) using up to four distance determination methods, calibrated with supernova luminosities. However, unlike HyperLEDA or NED-D, Cosmicflows-3 only reports the latest distance measurement for each method. In HyperLEDA, NED-D, and Cosmicflows-3 errors are reported as one standard deviation from the reported distance modulus. Treatment of errors for combining distance moduli across methods or across measurements is suggested by Mazzarella & Team (2007) and Tully et al. (2016) to be based on weighted estimates such as the uncertainty of the weighted mean, albeit with caution partly due to the heterogeneous origin of the compiled data and partly due to Malmquist bias. In the case of NED-D, this is additionally complicated by the fact that many errors are not reported or are reported as zero. In fact, the TF relation method has the largest number of galaxies with non-reported distance modulus errors (884 to date). Even though extragalactic distances measured using the TF relation were originally reported to have a relative error in distance modulus of 10–20 per cent (Tully & Fisher 1977), we consider that this conservative estimate can be improved upon by using a predictive model based on the distance error of galaxies that use the same distance determination method. This requires a robust estimation of the variance of extragalactic distances based on the available data.
Citation: Mazzarella & Team (2007)
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The emission from both types of sources contaminates measurements of the Cosmic Microwave Background (CMB), which contains information on cosmological parameters. The measurement of the CMB polarization, particularly the E-mode damping tail, can help break some of the degeneracies between cosmological parameters. Measurements of the polarization damping tail are expected to become foreground-limited at a smaller angular scale (higher ℓ) than the temperature damping tail, because of the expected low polarization of dusty point sources (see below). Further, the higher contrast of the acoustic features in EE power spectrum compared to astrophysical foregrounds (Calabrese et al. 2014; Galli et al. 2014) will ultimately provide independent and tighter constraints on the standard cosmological parameters, such as the scalar spectral index ns, than those from the temperature data alone. High-resolution measurements of the E-mode polarization will improve the delensing of the primordial B-modes (Seljak & Hirata 2004), ultimately tightening the constraint on the tensor-to-scalar ratio r. As measurements of the small angular-scale fluctuations in the CMB are attaining higher sensitivity and finer resolution, ongoing and planned ground-based CMB surveys, such as Advanced ACTPol (Henderson et al. 2016), SPT-3G (Benson et al. 2014), Simons Observatory (Ade et al. 2019 (SO)), CCAT-prime (Stacey et al. 2018), and CMB Stage 4 (Abazajian et al. 2016; Abitbol et al. 2017) will be capable of extracting information from the E-mode damping tail out to ℓ ≈ 9000. However, the contribution of the extragalactic point sources to the CMB power spectrum increases towards smaller angular scales, and it is expected to be a significant fraction of the CMB polarization power. For example, extragalactic foreground sources are expected to be the predominant contaminant for angular scales smaller than 30′ (ℓ≳ 400) in the 70–100 GHz frequency range (Toffolatti et al. 1998). Hence, characterization of these sources in terms of their spectral and spatial distributions is essential for separating foregrounds from the CMB.
Citation: Galli et al. 2014
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