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A&A
Volume 532, August 2011
Article Number A23
Number of page(s) 41
Section Interstellar and circumstellar matter
DOI https://doi.org/10.1051/0004-6361/201015399
Published online 14 July 2011

© ESO, 2011

1. Introduction

The chemical composition of the gas from which the star forms is well known to influence the process of the star formation and be, in turn, influenced by the process itself. The first obvious example is that the Jeans mass depends on the gas temperature, which, in turn, is set by the molecular line cooling accross a large range of densities and temperatures. The chemical composition of the gas is of paramount importance because the cooling is dominated by different species as a function of the gas temperature and density and the elemental abundance (Goldsmith 2001). A second classical example is the slow contraction of the prestellar cores, which is governed by ambipolar diffusion. Since only ions feel the magnetic field that counteracts the gravitational force, the chemical composition of the gas, which determines the ion abundance, is crucial. In addition to this, since the gas chemical composition is largely affected by the star formation process, its study in star forming regions is a powerful diagnostic tool to identify the various processes at work. Finally, the study of the chemical composition in regions forming solar-type stars is of particular importance, as it helps us to understand the formation history of our own Solar System. For example, the comparison of the chemical composition of comets with that of solar-type protostars or protoplanetary disks is used to help ascertain the origin of the former (Crovisier et al. 2004). The same applies to the studies of the molecular content of meteorites. In particular, the claim that the amino acids found in carbonaceous meteorites may have formed during the first phases of the life of the Solar System is based on the measured large deuteration in the meteoritic amino acids and in the protostellar environment (Pizzarello & Huang 2005). In this context, unbiased spectral surveys at millimeter and submillimeter wavelengths are particularly relevant as they allow us to detect heavy and large molecules, and, specifically, complex organic molecules. In summary, unbiased spectral surveys at the millimeter to submillimeter wavelengths are a powerful method to characterize the molecular content of astrophysical objects, and the only way to obtain a complete census of the chemical species.

There are at least two other aspects that make unbiased spectral surveys precious tools for studying the star formation process. First, in general they provide multiple lines from the same molecule, allowing multi-frequency analysis and modeling. Since different lines from transitions with different upper level energies and Einstein coefficients are excited at different temperatures and densities, they probe different regions in the line of sight. A careful analysis can, therefore, distinguish between the various physical components in the beam. If one also adds the kinematic information provided by the line profiles, the method can be so powerful that it can identify sub-structures along the line of sight, even if the spatial resolution of the observations is inadequate. In the present article, we provide an example of this capability of unbiased spectral surveys.

Given their powerful diagnostic ability, several unbiased spectral surveys in the millimeter and sub-millimeter bands accessible from ground have been obtained in the past in the direction of star forming regions. A complete list of these surveys can be found in Herbst & van Dishoeck (2009). By far the most targeted sources are hot cores, the regions of high-mass protostar formation, where the dust temperature exceeds the sublimation temperature of the water-ice grain mantles,  ~100 K. The combined effect of the mantle sublimation and the high gas temperature triggers a singular and rich chemistry. At the same time, the relatively high densities (≥ 107 cm-3) and temperatures (≥ 100 K) are favorable for the excitation of several high lying transitions. The result is that extremely rich spectra are observed towards the hot cores. About a dozen hot cores have been targeted in different bands (Schilke et al. 1997; Helmich & van Dishoeck 1997; Hatchell et al. 1998; Schilke et al. 2001; Tercero et al. 2010). One of the most studied hot cores is the Orion-KL source. Spectral surveys covering almost all the bands accessible from the ground have been obtained, from about 80 to 900 GHz, detecting thousands of lines from hundreds of species and relative isotopologues (see for instance Schilke et al. 1997; Lee et al. 2001; Comito et al. 2005; Olofsson et al. 2007; Demyk et al. 2007; Carvajal et al. 2009; Margulès et al. 2009; Tercero et al. 2010, and references therein). In addition, the 500–2000 GHz range is observed with the HIFI spectrometer (de Graauw et al. 2010) on board the recently launched Herschel1 satellite (Pilbratt et al. 2010), in the Key Program HEXOS2. Similarly, the 500–2000 GHz range is observed in other hot cores, as part of the Key Program CHESS3 (Chemical Herschel Surveys of Star forming regions). Preliminary results of the surveys performed in these two Herschel Key Programs can be found in Bergin et al. (2010) and Ceccarelli et al. (2010), respectively.

Although being both less massive and less luminous, solar-type protostars also possess regions where the dust mantles sublimate, yielding similar properties as those of hot cores (see Ceccarelli 2007, and references therein). These regions have been baptized hot corinos, to highlight that they share similarities with hot cores but are not just scaled-down versions of them (see also Bottinelli et al. 2007). The interest in observing hot corinos, whose sizes are comparable to the Solar System sizes, is amplified by there being likely to resemble the Solar Nebula. In other words, their study corresponds to an archeological study of the ancestor of our Solar System.

So far, only one (partial) spectral survey has been obtained towards a solar-type protostar (Blake et al. 1994; van Dishoeck et al. 1995). The targeted source was IRAS 16293-2422 (hereinafter IRAS 16293), in the L1689N cloud (d = 120 pc, Loinard et al. 2008). This survey partially covered the two windows in the 200 GHz and 350 GHz bands accessible from the ground, and was obtained with the JCMT and CSO telescopes. The sensitivity achieved (~40 mK) allowed the detection of 265 lines from 24 species, namely the most abundant molecules CO, H2CO, CH3OH, SO, SO2 etc. Later, more sensitive observations have demonstrated that the IRAS 16293 line spectrum is rich in complex organic molecules (Ceccarelli et al. 2000b; Cazaux et al. 2003), and doubly (Ceccarelli et al. 1998) and triply (Parise et al. 2004) deuterated molecules. Additional support for an unbiased spectral survey towards IRAS 16293 is provided by the Herschel/HIFI data in the 555–636 GHz range which shows that, while IRAS 16293 has much fewer lines than the 2 × 106   L⊙ source NGC 6334I, the same number of species is detected in both sources (Ceccarelli et al. 2010).

Several studies have been carried out towards IRAS 16293, with both single dish telescopes and interferometers. The emerging overall picture is that IRAS 16293 is a protobinary system (Wootten 1989; Mundy et al. 1992) surrounded by an envelope of about 2 M⊙ (Crimier et al. 2010). The structure of the envelope has been the target of several studies (Ceccarelli et al. 2000a; Schöier et al. 2002; Jørgensen et al. 2005). Crimier et al. (2010) concludes that the envelope density follows a r-2 power law at distances larger than about 1300 AU and r − 3/2 innerwards. The grain mantles are predicted to sublimate at a distance of 75 AU, where the density is equal to 2 × 108 cm-3. The envelope extends from about 25 AU to about 6000 AU from the center. Inside the envelope, the two sources, A (south-east) and B (north-west), of the binary system are separated by about 4′′ (separation being measured from interferometer observations at a spatial resolution of about 1′′), which is equivalent to a linear distance of 480 AU. The source B is brighter than the source A in the millimeter continuum and in several “cold envelope” molecular lines, whereas the source A seems to be brighter in several hot-corino-like molecular lines (Kuan et al. 2004; Bottinelli et al. 2004; Chandler et al. 2005). Finally, Chandler et al. (2005) have claimed that source A might be a multiple system and the observations of Pech et al. (2010) suggest that A is itself a binary system of 0.5 M⊙ and 1.5 M⊙, respectively.

Despite its relatively complex structure at arcsec scales, IRAS 16293 remains the brightest and most appropriate source to carry out a detailed study of the gas chemical composition in the first phases of the formation of a solar-type star. As discussed above, the best way for that is to obtain unbiased spectral surveys, that are as sensitive as possible. In this paper, we present the results of the most sensitive unbiased spectral survey of the bands between 80 and 366 GHz observable from ground-based telescopes obtained so far in the direction of IRAS 16293. This study is part of a more general project to also observe the 500–2000 GHz frequency range with the spectrometer HIFI on board the Herschel satellite, in the context of the Herschel Key Program CHESS4 (Ceccarelli et al. 2010).

2. Observations

The observations were obtained at the IRAM-30 m (frequency range 80–280 GHz) and JCMT-15 m (frequency range 328–366 GHz) telescopes during the period between January 2004 and August 2006. Overall, the observations required a total of about 300 h (~200 h at IRAM and  ~100 h at JCMT) of observing time. The beam of the survey varied between 9″ and 33″, depending on the telescope used and the frequency, and the spectral resolution ranged between 0.3 and 1.25 MHz, corresponding to velocity resolutions between 0.51 and 2.25 km s-1. The achieved rms varied between 4 and 14 mK in 1.5 km s-1 bins. The observations were centered on the B (north-west) component at α(2000.0) = 16h32m22.6m, δ(2000.0) =  − 24°28′33′. The A and B components, separated by 4″, are both inside the beam of our observations at all frequencies. However, at the highest frequencies observed with the IRAM 30 m telescope (i.e. the 1 mm band), the attenuation of emission from source A is not negligible as we discuss in Sect. 5. All observations were performed in DBS (Double-Beam-Switch) observing mode, with a 90″ throw. The pointing and focus were checked every two hours on planets or on continuum radio sources (1741-038 or 1730-130). Table 1 summarizes the observed bands and the details of the observations. Because of the different weather conditions during the different runs, the system temperatures widely varied. However, during the data processing, scans with too high system temperatures were removed before averaging.

Table 1

Parameters of the observations at IRAM-30 m and JCMT-15 m telescopes.

2.1. IRAM observations

The following three bands were almost fully covered by observations at the IRAM-30 m telescope: 3 mm band (80–115.5 GHz), 2 mm band (129–177.5 GHz), and 1 mm band (198–281.5 GHz).

In all IRAM-30 m observations, two frequency ranges were observed simultaneously, with two SIS receivers with orthogonal polarizations for each frequency range, in the following configuration: 3 mm receivers (A100 & B100) in parallel with 1 mm receivers (A230 & B230), and 2 mm receivers (C150 & D150) in parallel with 1 mm receivers (C270 & D270). Because of the limitation (at the time of the observations) of the IRAM-30 m backend capabilities in terms of instantaneous frequency bandwidth and spectral resolution, we chose the largest possible spectral bandwidth to cover the IRAM-30 m bands in the smallest observing time. For simultaneous observations in the 3 mm and 1 mm bands, the VESPA autocorrelator was split into four parts, two of them covering the whole IF band of the A&B100 receivers (0.5 GHz) with 320 kHz spectral resolution and the two others covering half of the IF band of the A&B230 receivers (1 GHz) with 1250 kHz spectral resolution. The second half of the IF band of the A&B230 receivers was covered with the 1 MHz filter banks (FB). For simultaneous observations in the 2 mm and upper 1 mm bands, the VESPA autocorrelator was split into four parts, two of them covering half of the IF band of the C&D150 receivers (0.5 GHz) with 320 kHz sampling and the two others covering half of the IF band of the C&D270 receivers (1 GHz) with 1250 kHz sampling. The second half of the IF band of the C&D150 receivers was covered with the 1 MHz FB.

The configuration for observations in the 2 mm band resulted in different spectral resolutions for each half of the IF band of the receivers (320 kHz  ~  0.65 km s-1 and 1 MHz  ~  2 km s-1). Therefore, we shifted the tuning frequency of the receivers by only 0.5 GHz from one tuning to the next one to cover the entire 2 mm band at the highest and at the lowest spectral resolution, respectively. As a consequence, two different datasets were obtained, one at high resolution (generally used for studying brighter lines), and one at low resolution (for the faint lines).

2.2. JCMT observations

The JCMT-15 m observations covered the 328 to 366 GHz frequency range. They were obtained with a 345 GHz SIS receiver RxB3 used in dual-channel single-sideband (SSB) mode. Each polarization of the receiver was connected to a unit of the ACSIS autocorrelator providing a bandwidth of 0.5 GHz for a spectral resolution of 625 kHz. At 345 GHz, this yields a velocity resolution of about 0.5 km s-1.

3. Calibration

3.1. Method

At the IRAM-30 m telescope, the calibration was performed with a cold and a warm absorbers, and the atmospheric opacity was obtained using the ATM program (Cernicharo 1985, IRAM internal report). At the JCMT-15 m, line strengths were calibrated via the chopper wheel method (Kutner & Ulich 1981).

Our spectral survey does not allow us to estimate the calibration uncertainties from line observation redundancy: each spectral range was observed only once and there is only negligible frequency overlap between adjacent spectra. From our simultaneous observations with two receivers in the 1 mm range, we may estimate the receiver contribution, but to derive the total calibration uncertainties of the survey, we performed a detailed comparison between our own and previous observations. As our comparisons rely only on observations obtained with the same telescopes towards the same position (namely source B), no bias is caused by the different source dilution in the beams and our results are unaffected by the underestimate of source A contribution at high frequency. The comparison includes virtually all the published data towards IRAS 16293 obtained with the IRAM-30 m and the JCMT-15 m telescopes, as well as unpublished data obtained with the IRAM-30 m telescope. The list of the articles used for this comparison is the following: a) IRAM-30 m bands: Ceccarelli et al. (1998), Loinard et al. (2000), Cazaux et al. (2003), Wakelam et al. (2004), Parise et al. (2002), and Parise et al. (2005b); b) JCMT-15 m band: Blake et al. (1994), van Dishoeck et al. (1995), Loinard et al. (2000), Schöier et al. (2002), and Parise et al. (2004). Table 1 reports the percentage of the survey spectra that could be cross-checked and calibrated against previously published data for each band. In addition, we cross-checked the calibration in the 2 mm band by comparing the data obtained with 1 MHz and 320 kHz resolution. Finally, we estimated the calibration uncertainty produced by the receivers by comparing lines in the 1 mm band observed with the two receivers A230 and B230.

To quantify the differences, we obtained Gaussian fits of the lines and compared their characteristics (integrated intensity, peak intensity, and full width at half maximum FWHM), with the previously published values. The comparison was performed in the main beam brightness scale (Tmb) based on the /Tmb beam efficiency factors given in Table1. This method provides two types of check: i) the average uncertainty for each band; and ii) possible specific calibration problems on single settings.

3.2. Calibration uncertainties

With the method described above to quantify the calibration uncertainty in the survey, we obtained the following results.

FWHM: In all the frequency ranges, except 1mm, the agreement between the survey and the published FWHM values is within 15–20% and no systematic trend is observed. In contrast, in the 1 mm band the FWHM of the survey lines appears to be systematically broader by  ≃ 1 km s-1 than the published values. This is likely due to the relatively poorer spectral resolution of our survey in this range (0.8 to 1.9 km s-1) compared to the linewidths (on average  ≃ 4–5 km s-1).

Integrated and peak intensity: The comparison of the integrated and peak intensity of the lines of the survey with published values yields the same results, when the difference due to the spectral resolution described above is taken into account. In addition, since the derivation of the integrated intensities does not depend on the line shape, we choose to quantify the calibration uncertainties by comparing the integrated line intensities.

thumbnail Fig. 1

Distribution of integrated intensity ratios of this survey’s 1 mm lines compared to published observations obtained with the IRAM 30 m telescope. The curve is a Gaussian fit to the histogram ruling out the “anomalous” ratios (≤ 0.5 or  ≥ 1.5). It can be noticed that the 12 “anomalous” ratios correspond to only 7 “anomalous spectra” among the 165 spectra observed in the 1 mm range.

Derived uncertainties: We can derive an estimate of the calibration uncertainty from the distribution of the integrated intensity ratios. Figure 1 shows the result for the 1 mm band. If one excludes the two extremes at  ≤ 0.5 and  ≥ 1.5, which correspond to spectra with “anomalous intensity”, the ratio distribution can be fitted by a Gaussian with a mean value of R, very close to one and a standard deviation σratio. On the basis of the assumption that the relative uncertainties in the published intensities, σpub, and on the survey line intensities, σcal, are independent variables, the error propagation formula implies that: (1)Most publications report calibration uncertainties of 15% (or do not report any estimate). Except in the 3 mm frequency range, where our comparisons suggest that the calibration uncertainty is probably somewhat smaller than 15%, we obtain consistent uncertainties assuming either that σpub = 15% for all the frequency ranges or that our observations are representative of average observation conditions in each frequency range, i.e., σpub    =    σcal and thus . Table 1 reports the resulting calibration uncertainties for each observed band.

We note that at 2 mm, the “external” comparisons with published spectra, which include all uncertainty factors, lead to higher values than “internal” comparisons between the VESPA and 1 MHz FB simultaneous observations, which take into account only the contribution of the backends. Similarly, at 1 mm, a comparison of the line intensities observed simultaneously with the two receivers A230 and B230 shows that the receivers’ contribution to the calibration uncertainties is approximately 10%, whereas the total calibration uncertainty is 17%.

thumbnail Fig. 2

The IRAS 16293 spectra in the four bands of the survey. Upper panels: IRAM-30 m 3 mm and 2 mm bands. Lower panels: IRAM-30 m 1 mm and JCMT-15 m 0.9 mm bands. The middle panels are zoomed views of sample frequency ranges in the four bands respectively. These panels include lines identification based on the publicly available spectral databases (see text for details).

Finally, the full list of lines used for the calibration comparison is reported in the on line material, in Table 2 for a comparison between the survey lines and previous observations obtained with the same telescopes and in Table 3 for a comparison between the survey lines observed simultaneously with VESPA and the 1 MHz filter bank at the IRAM-30 m telescope.

4. Data release

The data are made publicly available on the TIMASSS web site5. The site provides the files with the IRAM-30 m and JCMT-15 m data in CLASS format6. The intensities are in TA ∗ . On the basis of the discussion of the previous section, the potential user is highly recommended to verify the calibration uncertainty in the data that she/he wants to use by looking at Tables 2 and 3. We emphasize that we did not apply any “rescaling” factor to the survey data because the difference may be caused by an incorrect calibration of the published rather than the survey data. Only a very careful scientific analysis can assess what is the most likely explanation. It is, therefore, the user’s responsibility to verify that the data are correctly used, based on the information provided at the web site.

5. Results

5.1. Overall survey

Figure 2 shows the full survey in the four bands and the richness of the IRAS 16293 line spectrum. About 20 lines per GHz on average have been detected with a signal-to-noise ratio S/N higher than three in the 220 GHz frequency range covered by the survey. The line density seems to increase slightly with frequency: there are 17 lines/GHz in the 3 mm band, 19 and 23 lines/GHz in the 2 mm and 1 mm ranges respectively, and as many as 26 lines/GHz in the 0.9 mm range.

To quantify more rigorously the lines and species detected in the survey, we made Gaussian fits and line identification using the CASSIS7 package. The spectroscopic data come from the CDMS and JPL databases (Müller et al. 2001, 2005; Pickett et al. 1998, and references quoted on the databases to data producers for each species). In a few cases (ortho and para H2CO for instance), a specific database with each form separated has been used (see the CASSIS7 web site). For the D-bearing isotopologues of methanol, only the lines reported by Parise et al. (2002, 2004) are included in this paper.

Hereinafter we only consider lines identified according to the following criteria: i) lines belonging to species included in the JPL and CDMS databases or to the D-bearing isotopologues of methanol, ii) lines detected with a certainty of more than 3σ in the integrated line intensity, iii) unblended lines, and iv) lines with upper level energies Eup lower than 250 K. This last condition only limits the number of methanol lines in this analysis, since lines of other molecules with Eup higher than 250 K are in any case too weak to be detected by our survey. When applying these criteria, we end up with  ~ 1000 lines listed in Table 5. In the table, we report the line identification together with the result of the Gaussian fit of each line (see also Sect. 5.3).

Figure 3 shows the line densities, which are limited to the lines satisfying the above criteria, in each of the four survey frequency ranges, for various signal-to-noise ratios. In the 3 mm and 2 mm ranges, these densities are a factor of between two and three smaller than the estimates of the total densities including blended lines. This effect is even stronger in the 1 mm and 0.9 mm ranges, where the lack of weak lines () is particularly striking in Fig. 3. This is a bias due to our selection criterion of non-blended lines, as these frequency ranges are rich in lines from large molecules, which emit many weak lines, so that our unblended line criterion filters out a large fraction of these lines of moderate S/N. In contrast, the 2 mm range, which benefits from a better spectral resolution compared to the 3 mm and 1 mm ranges, is less affected by this selection effect.

Most of the lines retained in the 1 mm and 0.9 mm ranges and a large fraction (≃ 2/3) of the lines retained in the 3 mm and 2 mm ranges have a high S/N (10). The density of lines with such high S/N is relatively constant in frequency and equal to  ≃ 4 − 5 GHz.

When comparing with the line density quoted at the beginning of the section, namely about 20 lines per GHz, obtained considering lines with S/N ≥ 3 but no other filter, clearly the introduction of the other criteria, unblended lines and, to a lesser degree, identified lines and Eup ≤ 250 K, severely underestimates the line content.

The line intensity spans more than three orders of magnitude, from 10 mK to 24 K. The number of lines showing an integrated intensity higher than a given threshold is given in Fig. 4. For integrated intensity ranging between 1 and 30 K km s-1, the distribution roughly follows a power law of slope –0.9. The power law breaks down in the high and low end of the distribution. This slope is identical to those observed by Schilke et al. (2001), White et al. (2003), and Comito et al. (2005), in their submillimeter surveys of Orion-KL. As found by these surveys, this slope does not provide a good fit for the brightest and the weakest lines.

5.2. Detected lines and species

thumbnail Fig. 3

Distribution of the density (averaged over 10 GHz intervals) of identified lines (see text) in each of the four frequency ranges. The upper panel corresponds to lines with , the central panel is restricted to lines with and the lower panel corresponds to lines with .

Table 5 lists the species detected and identified in the survey, (see below).

In the framework of a survey analysis restricted to the four line criteria mentioned above, 69 different molecules (including ions) have been detected. They correspond to 32 distinct chemical species and include 37 rare isotopologues. They are listed in Table 5 which gives the number of lines detected for each species, the range of upper level energy of the lines and observational quantities. Among the  ~ 1000 lines in Table 5, about half belong to only three species: CH3HCO, HCOOCH3, and CH3OH.

Most of the 4000 lines detected in our survey belong to species already identified in this source (see Table 5), among which a few molecules display extremely rich spectra, including many weak and/or blended lines that are not included in the present study. Although we anticipate the presence of unidentified lines, their assignment will require a careful analysis and even probably modeling of these spectra. The Eup ≤ 250 K selection criterion used in this work also prevent us from identifying any vibrationally excited lines. We postpone these considerations to a future article.

Table 5 also lists the sum of the line flux in each species. For species displaying rich and complex spectra and/or numerous lines with upper energy levels  ≥ 250 K, this value is a lower limit because of the numerous weak and blended lines that are not included in the present analysis.

As noted by the previous studies (Blake et al. 1994; van Dishoeck et al. 1995), the millimeter and submillimeter spectrum of IRAS 16293 is dominated by simple O-rich species such as CO, SO, H2CO, SO2, and CH3OH (the three first families alone constitute more than two-thirds of the total flux). In the frequency range covered by our survey, the total flux emitted in the CO main and isotopic lines is about 800 K km s-1,  ~ 30% smaller than the flux emitted in the SO, H2CO, SO2, and CH3OH lines together (~1100 K km s-1). Thus, CO is not the major cooling agent in this frequency range. In addition, our survey detects thousands of weaker lines from heavier and more complex molecules that had not been found in the previous surveys. The zoomed figures of Fig. 2 illustrate the situation, with several lines from CH3CCH, CH3CN, HCOOCH3 etc. To roughly estimate the contribution of this “grass” of lines to the total cooling of the gas (in this range of frequencies), we consider a line density of about 15 lines per GHz (see above) and a line integrated intensity of  ~0.3 K km s-1. This gives approximatively an integrated line intensity of 900 K km s-1, which is comparable to the contribution of CO and its isotopologues.

thumbnail Fig. 4

Number of lines showing an integrated intensity larger than a given threshold. The solid line shows the single index power-law best fit to the distribution.

5.3. Line parameters

A Gaussian fit was performed for each of the lines of Table 5. The parameters of the fit (integrated intensity, line width FWHM, and rest velocity vLSR) are reported in the same table. The uncertainties in the integrated line intensity are based on the spectra noise and the calibration uncertainties reported in Table 1. We verified that even when the line profile differs from a simple Gaussian (for example in self-absorbed lines, or lines with broad wings) the Gaussian fit area is very close to the true integrated line intensity and, therefore, reliable. The uncertainties in the line width FWHM and rest velocity vLSR take into account the statistical errors (from the fit) and the uncertainty due to the limited spectral resolution, which indeed dominates the error. The cases where the line profiles are clearly not Gaussian are marked in Table 5. The average  ⟨ FWHM ⟩  and  ⟨ vLSR ⟩  for each species and isotopologues are reported in Table 5, except for those that show severe blending caused by unresolved or partially resolved hyperfine structure (CH3CN, HNCO, NH2D, NS).

In the following, we analyze the information derived from the Gaussian FWHM and vLSR of the lines.

Figure 5 shows the FWHM versus vLSR for each species. In the plots, we have regrouped the isotopologues of the same species and, in a few cases, species with a small number of lines. In these cases, we verified that the species have similar FWHM and vLSR to avoid introducing artificial trends in the plot. Figure 5 shows a remarkable and unexpected behavior: the FWHM and vLSR distributions are not the same but, in contrast depend on the species.

Table 5

Detected species ordered by decreasing fluxes of the main isotopologue.

On the basis of the different FWHM and vLSR distributions, four types of “kinematical behaviors”t can be identified:

  • 1.

    Type I (first row of Fig. 5): ⟨ vLSR ⟩  ~ 4.0 km s-1 and  ⟨ FWHM ⟩  ~ 2.5 km s-1. The lines show very little dispersion in terms of both rest velocities and line widths. Small carbon chains and rings, and “small molecules” belong to this group.

  • 2.

    Type II (second row):  ⟨ vLSR ⟩  ~ 3.7 km s-1 with very little dispersion, FWHM from  ~2 km s-1 to  ~8 km s-1. All species in this group are S- or N-bearing molecules. We note that HCO+ and C3H2 (in the first row) have properties which are in-between type I and type II.

  • 3.

    Type III (third row):  ⟨ vLSR ⟩  ~ 2.5–3.0 km s-1,  ⟨ FWHM ⟩  ≤ 4.0 km s-1. Four complex organic molecules display this behavior.

  • 4.

    Type IV (fourth row): vLSR and FWHM have mixed behaviors, with characteristics belonging to the two last groups. CH3OH lines have vLSR and FWHM ranging from 2 to 9 km s-1; H2CO and CH3CCH lines have moderate FWHM (4–5 km s-1) and vLSR ranging from 2.5 to 4 km s-1; lines from the rare isotopes of OCS have vLSR ~ 2.5 km s-1 and FWHM ≤ 4 km s-1.

We note that the FWHM averaged over each of the four frequency bands of the survey is similar, between 2 and 5 km s-1, there being a slight increase in the 1 mm band caused by the poorer spectral resolution. We verified that none of the four kinematical behaviors are produced by this instrumental effect. Table 6 summarizes the situation. To more clearly understand the physical meaning of the plots in Fig. 5 (and the four identified types), we plotted in Fig. 6 the values of the FWHM as function of the upper level energy Eup of the transition. The species were grouped as in Fig. 5; it is striking that the distinction between the four types defined by the (FWHM, vLSR) distribution is also visible in this plot.

Table 6

Distribution of the detected species in four kinematical types.

Type I species have lines with Eup lower than 50 K. We note that this is not an observational bias: except for a few very light molecules, such as C2H, the species associated with type I have high energy transitions in the survey frequency range, but the line intensities decrease abruptly when Eup becomes higher than 50 K. In contrast, type II, III, and IV species have lines with Eup up to 200 K but different behaviors. For type II species, the FWHM increases with Eup, whereas for type III and IV the FWHM is constant and does not depend on Eup. In contrast, analogous plots of vLSR versus Eup indicate that the lines’ velocity does not depend on Eup in any species. A related effect was discovered by Schöier et al. (2002), who noted a correlation between the linewidths and the excitation temperatures derived by Blake et al. (1994) and van Dishoeck et al. (1995). These properties are used to give a physical meaning to the four types in Sect. 6. Finally, we note that when detected, the deuterated species show the same behavior as the main isotopomers, except the D-isotopomers of type III species that have too weak lines to be detected in our survey.

6. Discussion

6.1. Comparison with previous surveys

When compared to the previous survey toward IRAS 16293 (Blake et al. 1994; van Dishoeck et al. 1995), the present one not only enlarges the covered frequency range (~200 GHz versus  ~40 GHz) but also the number of detected species, thanks to the higher sensitivity (~10 mK versus  ~40 mK). The average line density of the previous unbiased survey of IRAS 16293 was 7 lines per GHz, which should be compared with 20 lines per GHz for the present one. Several species detected in our survey were not detected in the previous one: complex organic molecules (HCOOCH3, HCOOCH3 and CH3OCH3), carbon chains and rings (C2S, C4H, c-C3H), N-bearing species (NO, PN, NS), and several D-bearing molecules.

Towards hot cores, numerous surveys have been performed. They have covered the whole range of frequencies reachable from the ground, from the 3 mm range observed with IRAM, SEST, NRAO, or JCMT to the submillimeter windows observable with the CSO and JCMT (MacDonald et al. 1996; Schilke et al. 1997; Helmich & van Dishoeck 1997; Nummelin et al. 1998; Thompson & MacDonald 1999; Kim et al. 2000; Nummelin et al. 2000; Lee et al. 2001; Schilke et al. 2001; White et al. 2003; Comito et al. 2005; Kim et al. 2006; Belloche et al. 2007; Olofsson et al. 2007; Tercero et al. 2010). The line densities usually range from 10 to 20 lines per GHz, i.e. have value comparable to the present survey. SgrB2 appears as a noticeable exception, displaying significantly higher line densities, as high as 100 lines per GHz in the 3 mm range observed with IRAM (Belloche et al. 2007) or 40 lines per GHz in the 1 mm range observed with SEST (Nummelin et al. 1998, 2000). Interestingly, the slope of –0.9 that we observe for the cumulative number of lines versus flux threshold is identical to the slopes observed by Schilke et al. (2001), White et al. (2003), and Comito et al. (2005) in their submillimeter surveys of Orion-KL.

In conclusion, our survey in terms of molecular content has a richness comparable to that of hot cores and confirms that the high abundance of deuterated isotopologues, which are easily detected for a number of species, is a distinctive characteristic of low mass protostars.

6.2. Kinematical types and associated components

As mentioned in the Introduction, IRAS 16293 is formed by a proto-binary system surrounded by an infalling envelope. In addition, multiple outflows originate in the system (e.g. Castets et al. 2001). Before attempting to interpret the observations of Sect. 5.3 and, specifically, the meaning of the four kinematical types of Table 6, based on the line rest velocities and widths, we review what is known so far about the envelope and the proto-binary system.

6.2.1. Envelope

The envelope extends for 6000–7000 AU in radius, equivalent to about 100′′ in diameter, and is relatively massive (~2   M⊙) (Crimier et al. 2010). At the border of the envelope, the dust temperature is  ~ 13 K and the density is  ~105 cm-3. The dust temperature reaches 100 K at a radius 75–86 AU, where the density is (2–3)  ×    108 cm-3, creating the region called hot corino. The rest velocity of the cold envelope has been measured in several studies and is  ~3.9 km s-1 (Mizuno et al. 1990; Bottinelli et al. 2004; Takakuwa et al. 2007). Molecules probing the cold envelope have  ~2 km s-1 line widths.

thumbnail Fig. 5

Plots of the rest velocity vLSR versus the FWHM, derived from the Gaussian fits of the lines (Table 5). All the detected species and the relevant isotopologues of Table 5 are plotted, except those in which the lines have obviously non-Gaussian profiles (see text). In particular, the labels HCN* and OCS* mean that the main isotopologues of these species are not included, because of their non-Gaussian profiles. The one-σ error bars include fit and spectral resolution uncertainties. The vertical lines at vLSR = 2.7 and 3.9 km s-1 correspond to the velocity of the components B and A, respectively (see Sect. 6). The horizontal line at 5 km s-1 corresponds approximatively to the average of the line FWHM range.

Table 7

Correspondence between kinematical types and spatial distributions derived from interferometric observations.

6.2.2. Proto-binary system

Several interferometric studies have been carried out in the past to characterize the nature of the two sources, A (south-east) and B (north-west), forming the binary system (Kuan et al. 2004; Bottinelli et al. 2004; Chandler et al. 2005; Bisschop et al. 2008; see also references in Table 7). Some species are associated only or predominantly with one of the two sources A and B, and others are observed in both sources. All studies agree in measuring broader lines towards A (~8 km s-1) than B (~3 km s-1). However, the rest velocity of the molecular emission in the two objects is more uncertain: there is some evidence that the two objects have different rest velocities (higher in source A than in source B), but this difference might also be due to absorption by the envelope according to Chandler et al. (2005) or self-absorption in optically thick lines from source B according to Bottinelli et al. (2004); Kuan et al. (2004) also report velocities that are somewhat higher in source A than source B, with a dispersion larger than 2.5 km s-1 in the values for all species. According to Bisschop et al. (2008), both sources A and B show emission at velocities between 1.5 and 2.5 km s-1; Huang et al. (2005) mention two velocity components at 1.5 and 4.5 km s-1 for source A and show emission from B peaking at  ~2 km s-1. We note that all these studies use moderate spectral resolutions (~1 km s-1), deal with a small number of lines (often only one) for each species and, in some cases, suffer from poor S/N for the weakest lines.

Table 7 summarizes, for each of the species classified according to their kinematical type in Table 6, the results of interferometric observations towards the three components of IRAS 16293 (sources A and B and the envelope).

thumbnail Fig. 6

Plots of the linewidth, FWHM, versus the energy of the upper level of the transition, Eup. The species are grouped as in Fig. 5. All the detected species and the relevant isotopologues of Table 5 are plotted, except those in which the lines obviously have non-Gaussian profiles (see text). In particular, the labels HCN* and OCS* mean that the main isotopologues of these species are not included, because of their non-Gaussian profiles. The one-σ error bars include fit and spectral resolution uncertainties. The horizontal line at 5 km s-1 corresponds approximatively to the average of the line FWHM range.

6.2.3. Interpretation of the kinematical types

On the basis of published interferometric observations, each species is assigned to one or two of the three components (source A, B, and the envelope). For example, CN displays type I kinematical characteristics (vLSR ~ 4 km s-1 and FWHM ~ 2 km s-1) and has only found to be associated with the envelope and was not detected in any of the two sources A and B. In contrast, CH3CHO has the characteristics of the type III behavior (vLSR = 2.5–3 km s-1 and FWHM ≤ 4 km s-1) and has only been detected in the direction of source B. Some species of Table 6 (C2H, C3H, C4H, C2S, NO, HNC, HCS+, and CS) have not been observed with interferometers, to the best of our knowledge, so are not reported in Table 7. The correspondence between the four types of Table 6 and the interferometric observations presented in Table 7 suggests that the species belonging to the same kinematical type are associated with a spatially different source: envelope (type I), source A (type II), source B (type III), and a mix of the three previous components (type IV). We note that the distribution of molecules in four kinematical types is not an artifact or a bias caused by the survey pointing, which detects more emission from source B than source A at higher frequencies. Even excluding all lines observed at IRAM-30 m or JCMT-15 m telescopes with a HPBW larger than 14′′, i.e. all lines with frequencies higher than 200 GHz, the vLSR versus FWHM plots and the FWHM versus Eup plots show the same behavior.

  • 1.

    Type I corresponds to molecules abundant inthe cold envelope of IRAS 16293. We cannotexclude that these species also emit in the densest parts of sourcesA and B but that this emission is strongly absorbed by the gas in theenvelope. NO, which shows two broad and relatively bright lineswith Eup = 36 K, bright narrow lines with Eup = 7 K and barely detected lines with Eup = 19 K (not included in this paper), might be an example of this situation, which deserves a detailed excitation study to come. The 343.8 GHz line associated with source B was identified by Kuan et al. (2004) as the C3H2 2313,10–2312,11 transition(Elow = 790 K) but the CH3CHO 182,17–172,16 transition (with Eup = 166 K) seems a more reasonable identification.

  • 2.

    Type II identifies molecules prevalently associated with source A. A few exceptions, for which emission from source B is mentioned in the literature, deserve some attention. The identification by Huang et al. (2005) of a line to SO2(v2 = 1) associated with source B is also questionable given the very high upper energy level (Elow = 1800 K) of the transition, as is the attribution by Huang et al. (2005) of H2CS emission to source B, as no map is shown for this species. Finally, SO emission is rather extended and associated with both sources A and B (Chandler et al. 2005). It is possible that part of the line broadening is due to wings associated with the outflow, whereas the bulk of the emission is associated with the cold envelope (which would instead make SO a species of type I). In addition, without detailed excitation models to be presented in subsequent studies, it is not possible to exclude that, for some type II species, the cold envelope contributes to the emission observed at low Eup and small FWHM.

  • 3.

    Type III species have lines that are prevalently emitted by source B. HCOOCH3, which has been observed in both source A and B appears as a notable exception. Excitation modeling of this species will be discussed in detail in a subsequent paper. Several qualitative arguments may already explain why no lines with type II characteristics are present in this study: (i) as the lines emitted by the source A are much broader than the lines emitted by the source B, whose lines display a higher percentage of blending with nearby lines excluding them from this study; (ii) in our large beam observations, emission from sources A and B are superposed; the narrow lines emitted from the source B appear “on top of the” broad lines emitted by the source A and are, thus, more easily detected; (iii) this second effect is enhanced by the pointing towards the source B.

  • 4.

    Type IV species are a mixed bag. The species are present in both sources A and B and, sometimes, even in the envelope. Depending on the intensity contribution, the lines can have a low or high vLSR and FWHM. Therefore, type IV species are not associated with any specific component.

Using the kinematic properties of the lines, we were able to identify general trends depending on whether the emission of the species originates in source A or B, although both sources are included in our single dish observations. Despite the kinematic differences being small, for example a difference in the vLSR of not more than 1.5 km s-1, we were able to draw a general picture thanks to the large number of detected lines.

6.3. The dynamics of sources A and B

Identified where the emission from the various species originates helps us to clarify the nature of sources A and B. As noted in several previous works, A and B have apparently different chemical compositions: source B is brighter in complex organic molecules, while source A is brighter in simpler S- and N-bearing molecules (see Table 7). Furthermore, the FWHM of the lines arising in source A are broader than in source B.

Our analysis established two additional properties that had previously not been recognized (see discussion in Sect. 6.1): i) the two sources have different velocities (vLSR) and ii) in the source A, the FWHM of the lines increases with increasing upper level energy (Fig. 6) whereas it remains constant in the source B.

For the linewidth behavior, a related effect, the increase in FWHM with the excitation temperature, had already been observed by Schöier et al. (2002), but this represents a less direct probe of the gas kinematics, as it relied on modeling assumptions to derive the excitation temperatures. The increase in the line FWHM with increasing excitation has been interpreted in two ways: either it is caused by infalling gas onto the accreting protostellar object (Ceccarelli et al. 2003), or shocks caused by jet/wind interaction with the inner dense envelope (Schöier et al. 2002; Jørgensen et al. 2002). The two interpretations predict different molecular emission distributions. However, the existing maps do not allow us to distinguish these interpretations. In addition, to reliably differentiate between these two interpretations we would need to perform a detailed modeling of the source that is beyond the scope of this paper. At this stage, it can simply be said that the interpretation of the infalling gas (Ceccarelli et al. 2000b) would lead to reasonable estimates of source A and B central masses: for optically thin emission, the free-fall velocity may be estimated from the linewidth, assuming that the FWHM includes quadratically a turbulent width δth and the free-fall broadening; its analytic expression yields the following expression of the core mass, where the widths are expressed in km s-1 and the radius r in AU. (2)Assuming that the turbulent width in the A and B core external layers is close to that of the envelope static gas, we derive δth ~ 2 km s-1 from the type I species linewidths. According to the interferometric observations of type II and type III species reported in Table 7, both sources show a radius of  ~1.5′′ (i.e. 180 AU at a distance of 120 pc). For core A, typical FWHM larger than  ~6 km s-1 lead to a central mass of at least 0.8 M⊙, whereas for core B, where the FWHM is smaller than  ~3 km s-1, the central mass cannot exceed 0.1 M⊙. This assumes that the linewidths are due to collapsing envelopes rather than rotating disks. If they were, in contrast, due to rotating disks, one would have to take into account the (unknown) inclination angle. The available interferometer observations, which are barely able to spatially resolve the core A only (Bottinelli et al. 2004), do not allow us to distinguish between these two possibilities. In the following, we restrict the discussion to the infalling envelopes, for simplicity, but our conclusions are also largely applicable to the disk case.

The difference between the vLSR of both sources can be interpreted in the following way: the source B rotates around its companion, source A; for a distance of 480 AU between cores A and B, and a core A mass of 0.8 M⊙, the rotation velocity of core B is 1.2 km s-1. The observed difference between A and B velocities (vLSR of 3.9 and 2.7 km s-1 respectively) is thus perfectly consistent with this picture. Bottinelli et al. (2004) already discussed this possibility but did not have enough evidence to state that it was more likely than another hypothesis where the line kinematical properties reflect opacity effects. The large number of lines and species observed in our survey allows us to investigate the source dynamics.

7. Conclusions

We have presented an unbiased spectral survey of the 3, 2, 1, and 0.9 mm bands accessible from ground towards the class 0 source IRAS 16293. We used the IRAM-30 m and JCMT-15 m telescopes, performing about 300 h of observations. This is the most sensitive survey ever published in these bands towards a solar-type protostar.

The data have been released for public use in two CLASS files, which can be retrieved on the TIMASSS web site8. The site also contains two accompanying files (reported in the on line material) providing information about the calibration of the single receiver settings, obtained by comparing the survey lines with previously obtained observations.

The line density,  ~20 lines/GHz, appears to be as high as in comparable surveys obtained towards high mass protostars (with the exception of SgrB2). More than one thousand unblended lines with S/N ≥ 3 and upper energy levels lower than 250 K have been identified by comparing with the JPL and CDMS catalogs. They correspond to 32 chemically distinct species, a chemical richness comparable to those of hot cores. The identification of 37 additional rare isotopologues and, specifically, numerous D-bearing molecules confirm that IRAS 16293 has a remarkably high abundance of deuterated species. The 3 mm – 0.9 mm spectra are dominated by relatively simple molecules (CO, SO, H2CO, SO2, and CH3OH). However, the numerous weaker lines emitted by larger molecules account to at least as much as the CO integrated line intensities.

The analysis of the profiles of this large set of identified lines, and specifically the central velocities and widths, provides clues to help us identify where each emission predominantly originates: cold envelope (narrow lines at VLSR ≃ 3.9 km s-1), source A (broader lines at VLSR ≃ 3.9 km s-1), and source B (narrow lines at VLSR ≃ 2.7 km s-1). Furthermore, in source A, the line widths increase with the upper energy level of the transition. If this behavior is interpreted as being caused by gas infalling towards a central object, the core A mass is  ~1   M⊙ and the smaller line widths observed towards source B set an upper limit to the mass of this source,  ≤ 0.1   M⊙. The observed difference in the VLSR,  ~ 1.2 km s-1), is consistent with the source B rotating around the more massive source A. From a chemical point of view, the source B shows predominant emission from O-bearing complex molecules whereas N- and S-bearing molecules are strong emitters in the source A. To derive reliable estimates of the corresponding chemical abundances, it will be necessary to carry out careful radiative transfer modeling, which we intend to present in future articles.

1

Herschel is an ESA space observatory with science instruments provided by European-led principal Investigator consortia and with important participation from NASA.

7

CASSIS has been developed by IRAP-UPS/CNRS, see http://cassis.cesr.fr.

Acknowledgments

We are deeply thankful to the IRAM staff and the successive TACs, and particularly to Clemens Thum, for his help in preparing and programming the observations at the IRAM-30 m telescope. We gracefully thank the JCMT staff, particularly Remo Tilanus and Jim Hogh, who were always able to quickly resolve problems. We thank Laurent Pagani for fruitful discussions about calibration problems. We are very thankful to the molecular databases JPL and CDMS, which were largely used for the work presented here as to the spectroscopic groups providing the data. This work has been supported by l’Agence Nationale pour la Recherche (ANR), France (contracts ANR-08-BLAN-022) and by the Ministère de la Recherche Scientifique et Université J. Fourier de Grenoble, France (PPF WAGOS). Finally, we warmly thanks the referee, Dr, J. Cernicharo, and the editor, Dr. M. Walmsley, who contributed to improve a lot this paper with numerous helpful comments.

References

  1. Belloche, A., Comito, C., Hieret, C., et al. 2007, in Molecules in Space and Laboratory [Google Scholar]
  2. Belov, S. 1995, J. Mol. Spect., 173, 380 [Google Scholar]
  3. Belov, S. P., Tretyakov, M. Y., Kozin, I. N., et al. 1998, J. Mol. Spect., 191, 17 [Google Scholar]
  4. Bergin, E. A., Phillips, T. G., Comito, C., et al. 2010, A&A, 521, L20 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Bisschop, S. E., Jørgensen, J. K., Bourke, T. L., Bottinelli, S., & van Dishoeck, E. F. 2008, A&A, 488, 959 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Blake, G. A., van Dishoek, E. F., Jansen, D. J., Groesbeck, T. D., & Mundy, L. G. 1994, ApJ, 428, 680 [NASA ADS] [CrossRef] [Google Scholar]
  7. Bogey, M., Demuynck, C., & Destombes, J. L. 1985, A&A, 144, L15 [NASA ADS] [Google Scholar]
  8. Bogey, M., Demuynck, C., Destombes, J. L., & Dubus, H. 1987, J. Mol. Spect., 122, 313 [Google Scholar]
  9. Bocquet, R., Demaison, J., Cosléou, J., et al. 1999, J. Mol. Spect., 195, 345 [Google Scholar]
  10. Bogey, M., Civiš, S., Delcroix, B., et al. 1997, J. Mol. Spect., 182, 85 [NASA ADS] [CrossRef] [Google Scholar]
  11. Bottinelli, S., Ceccarelli, C., Neri, R., et al. 2004, ApJ, 617, L69 [NASA ADS] [CrossRef] [Google Scholar]
  12. Bottinelli, S., Ceccarelli, C., Williams, J. P., & Lefloch, B. 2007, A&A, 463, 601 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  13. Brown, R. D., Godfrey, P. D., McNaughton, D., & Yamanouchi, K. 1987, Mol. Phys., 62, 1429 [NASA ADS] [CrossRef] [Google Scholar]
  14. Brünken, S., Fuchs, U., Lewen, F., et al. 2004, J. Mol. Spect., 225, 152 [Google Scholar]
  15. Brünken, S., Müller, H. S. P., Thorwirth, S., Lewen, F., & Winnewisser, G. 2006, J. Mol. Struct., 780, 3 [NASA ADS] [CrossRef] [Google Scholar]
  16. Butner, H. M., Charnley, S. B., Ceccarelli, C., et al. 2007, ApJ, 659, L137 [NASA ADS] [CrossRef] [Google Scholar]
  17. Camy-Peyret, C., Flaud, J., Lechuga-Fossat, L., & Johns, J. W. C. 1985, J. Mol. Spect., 109, 300 [Google Scholar]
  18. Carvajal, M., Margulès, L., Tercero, B., et al. 2009, A&A, 500, 1109 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Castets, A., Ceccarelli, C., Loinard, L., Caux, E., & Lefloch, B. 2001, A&A, 375, 40 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  20. Cazaux, S., Tielens, A. G. G. M., Ceccarelli, C., et al. 2003, ApJ, 593, L51 [NASA ADS] [CrossRef] [Google Scholar]
  21. Cazzoli, G., & Puzzarini, C. 2005, J. Mol. Spect., 233, 280 [Google Scholar]
  22. Cazzoli, G., & Puzzarini, C. 2008, A&A, 487, 1197 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Cazzoli, G., Puzzarini, C., & Lapinov, A. V. 2004, ApJ, 611, 615 [NASA ADS] [CrossRef] [Google Scholar]
  24. Cazzoli, G., Puzzarini, C., & Gauss, J. 2005, ApJS, 159, 181 [NASA ADS] [CrossRef] [Google Scholar]
  25. Cazzoli, G., Cludi, L., & Puzzarini, C. 2006, J. Mol. Struct., 780, 260 [NASA ADS] [CrossRef] [Google Scholar]
  26. Ceccarelli, C. 2007, in Molecules in Space and Laboratory [Google Scholar]
  27. Ceccarelli, C., Castets, A., Loinard, L., Caux, E., & Tielens, A. G. G. M. 1998, A&A, 338, L43 [NASA ADS] [Google Scholar]
  28. Ceccarelli, C., Castets, A., Caux, E., et al. 2000a, A&A, 355, 1129 [NASA ADS] [Google Scholar]
  29. Ceccarelli, C., Loinard, L., Castets, A., Tielens, A. G. G. M., & Caux, E. 2000b, A&A, 357, L9 [NASA ADS] [Google Scholar]
  30. Ceccarelli, C., Maret, S., Tielens, A. G. G. M., Castets, A., & Caux, E. 2003, A&A, 410, 587 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  31. Ceccarelli, C., Bacmann, A., Boogert, A., et al. 2010, A&A, 521, L22 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  32. Chandler, C. J., Brogan, C. L., Shirley, Y. L., & Loinard, L. 2005, ApJ, 632, 371 [NASA ADS] [CrossRef] [Google Scholar]
  33. Chen, W., Novick, S. E., McCarthy, M. C., Gottlieb, C. A., & Thaddeus, P. 1995, J. Chem. Phys., 103, 7828 [NASA ADS] [CrossRef] [Google Scholar]
  34. Cho, S., & Saito, S. 1998, ApJ, 496, L51 [NASA ADS] [CrossRef] [Google Scholar]
  35. Clouthier, D. J., Huang, G., Adam, A. G., & Merer, A. J. 1994, J. Chem. Phys., 101, 7300 [NASA ADS] [CrossRef] [Google Scholar]
  36. Comito, C., Schilke, P., Phillips, T. G., et al. 2005, ApJS, 156, 127 [NASA ADS] [CrossRef] [Google Scholar]
  37. Crimier, N., Ceccarelli, C., Maret, S., et al. 2010, A&A, 519, A65 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. Crovisier, J., Biver, N., Bockelée-Morvan, D., et al. 2004, in Planetary Systems in the Universe, ed. A. Penny, IAU Symp., 202, 178 [Google Scholar]
  39. de Graauw, T., Helmich, F. P., Phillips, T. G., et al. 2010, A&A, 518, L6 [Google Scholar]
  40. Demyk, K., Mäder, H., Tercero, B., et al. 2007, A&A, 466, 255 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Dore, L., Puzzarini, C., & Cazzoli, G. 2001, Can. J. Phys., 79, 359 [NASA ADS] [CrossRef] [Google Scholar]
  42. Fusina, L., di Lonardo, G., Johns, J. W. C., & Halonen, L. 1988, J. Mol. Spect., 127, 240 [Google Scholar]
  43. Goldsmith, P. F. 2001, ApJ, 557, 736 [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  44. Golubiatnikov, G. Y., Lapinov, A. V., Guarnieri, A., & Knöchel, R. 2005, J. Mol. Spect., 234, 190 [Google Scholar]
  45. Guarnieri, A., & Huckauf, A. 2003, Z. Naturforsch, 58, 275 [Google Scholar]
  46. Hatchell, J., Thompson, M. A., Millar, T. J., & MacDonald, G. H. 1998, A&AS, 133, 29 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  47. Helmich, F. P., & van Dishoeck, E. F. 1997, A&AS, 124, 205 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  48. Herbst, E., & van Dishoeck, E. F. 2009, ARA&A, 47, 427 [NASA ADS] [CrossRef] [Google Scholar]
  49. Huang, H., Kuan, Y., Charnley, S. B., et al. 2005, Adv. Space Res., 36, 146 [NASA ADS] [CrossRef] [Google Scholar]
  50. Johns, J. W. C. 1985, J. Opt. Soc. Am. B Opt. Phys., 2, 1340 [NASA ADS] [CrossRef] [Google Scholar]
  51. Jørgensen, J. K., Schöier, F. L., & van Dishoeck, E. F. 2002, A&A, 389, 908 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  52. Jørgensen, J. K., Lahuis, F., Schöier, F. L., et al. 2005, ApJ, 631, L77 [NASA ADS] [CrossRef] [Google Scholar]
  53. Kim, E., & Yamamoto, S. 2003, J. Mol. Spect., 219, 296 [Google Scholar]
  54. Kim, H., Cho, S., Chung, H., et al. 2000, ApJS, 131, 483 [NASA ADS] [CrossRef] [Google Scholar]
  55. Kim, S., Kim, H., Lee, Y., et al. 2006, ApJS, 162, 161 [NASA ADS] [CrossRef] [Google Scholar]
  56. Klapper, G., Lewen, F., Gendriesch, R., Belov, S. P., & Winnewisser, G. 2001, Zeitschrift Naturforschung Teil A, 56, 329 [Google Scholar]
  57. Klapper, G., Surin, L., Lewen, F., et al. 2003, ApJ, 582, 262 [NASA ADS] [CrossRef] [Google Scholar]
  58. Klaus, T., Saleck, A. H., Belov, S. P., et al. 1996, J. Mol. Spect., 180, 197 [Google Scholar]
  59. Kleiner, I., Lovas, F. J., & Godefroid, M. 1996, J. Phys. Chem. Ref. Data, 25, 1113 [CrossRef] [Google Scholar]
  60. Klisch, E., Klaus, T., Belov, S. P., Winnewisser, G., & Herbst, E. 1995, A&A, 304, L5 [NASA ADS] [Google Scholar]
  61. Kuan, Y., Huang, H., Charnley, S. B., et al. 2004, ApJ, 616, L27 [NASA ADS] [CrossRef] [Google Scholar]
  62. Kutner, M. L., & Ulich, B. L. 1981, ApJ, 250, 341 [NASA ADS] [CrossRef] [Google Scholar]
  63. Lapinov, A. V., Golubiatnikov, G. Y., Markov, V. N., & Guarnieri, A. 2007, Astron. Lett., 33, 121 [NASA ADS] [CrossRef] [Google Scholar]
  64. Lattanzi, V., Walters, A., Drouin, B. J., & Pearson, J. C. 2007, ApJ, 662, 771 [NASA ADS] [CrossRef] [Google Scholar]
  65. Lee, C. W., Cho, S., & Lee, S. 2001, ApJ, 551, 333 [NASA ADS] [CrossRef] [Google Scholar]
  66. Leguennec, M., Demaison, J., Wlodarczak, G., & Marsden, C. J. 1993, J. Mol. Spect., 160, 471 [Google Scholar]
  67. Lohilahti, J., & Horneman, V. 2004, J. Mol. Spect., 228, 1 [Google Scholar]
  68. Loinard, L., Castets, A., Ceccarelli, C., et al. 2000, A&A, 359, 1169 [NASA ADS] [Google Scholar]
  69. Loinard, L., Torres, R. M., Mioduszewski, A. J., & Rodríguez, L. F. 2008, ApJ, 675, L29 [NASA ADS] [CrossRef] [Google Scholar]
  70. Lovas, F. J., & Suenram, R. D. 1982, J. Mol. Spect., 93, 416 [NASA ADS] [CrossRef] [Google Scholar]
  71. Lovas, F. J., & Suenram, R. D. 1987, J. Chem. Phys., 87, 2010 [NASA ADS] [CrossRef] [Google Scholar]
  72. Lovas, F. J., Suenram, R. D., Ogata, T., & Yamamoto, S. 1992, ApJ, 399, 325 [NASA ADS] [CrossRef] [Google Scholar]
  73. MacDonald, G. H., Gibb, A. G., Habing, R. J., & Millar, T. J. 1996, A&AS, 119, 333 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  74. Maeda, A., De Lucia, F. C., & Herbst, E. 2008, J. Mol. Spect., 251, 293 [Google Scholar]
  75. Margulès, L., Lewen, F., Winnewisser, G., Botschwina, P., & Müller, H. S. P. 2003, Phys. Chem. Chem. Phys. (Incorporating Faraday Transactions), 5, 2770 [NASA ADS] [Google Scholar]
  76. Margulès, L., Motiyenko, R., Demyk, K., et al. 2009, A&A, 493, 565 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  77. Meerts, W. L., & Dymanus, A. 1972, J. Mol. Spect., 44, 320 [Google Scholar]
  78. Minowa, H., Satake, M., Hirota, T., et al. 1997, ApJ, 491, L63 [NASA ADS] [CrossRef] [Google Scholar]
  79. Mizuno, A., Fukui, Y., Iwata, T., Nozawa, S., & Takano, T. 1990, ApJ, 356, 184 [NASA ADS] [CrossRef] [Google Scholar]
  80. Mollaaghababa, R., Gottlieb, C. A., Vrtilek, J. M., & Thaddeus, P. 1993, J. Chem. Phys., 99, 890 [NASA ADS] [CrossRef] [Google Scholar]
  81. Müller, H. S. P., Farhoomand, J., Cohen, E. A., et al. 2000a, J. Mol. Spect., 201, 1 [Google Scholar]
  82. Müller, H. S. P., Gendriesch, R., Lewen, F., & Winnewisser, G. 2000b, Zeitschrift Naturforschung Teil A, 55, 486 [NASA ADS] [Google Scholar]
  83. Müller, H. S. P., Gendriesch, R., Margulès, L., et al. 2000c, Phys. Chem. Chem. Phys. (Incorporating Faraday Transactions), 2, 3401 [NASA ADS] [Google Scholar]
  84. Müller, H. S. P., Winnewisser, G., Demaison, J., Perrin, A., & Valentin, A. 2000d, J. Mol. Spect., 200, 143 [Google Scholar]
  85. Müller, H. S. P., Thorwirth, S., Roth, D. A., & Winnewisser, G. 2001, A&A, 370, L49 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  86. Müller, H. S. P., Menten, K. M., & Mäder, H. 2004, A&A, 428, 1019 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  87. Müller, H. S. P., Schlöder, F., Stutzki, J., & Winnewisser, G. 2005, J. Mol. Struct., 742, 215 [NASA ADS] [CrossRef] [Google Scholar]
  88. Müller, H. S. P., Drouin, B. J., & Pearson, J. C. 2009, A&A, 506, 1487 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  89. Mundy, L. G., Wootten, A., Wilking, B. A., Blake, G. A., & Sargent, A. I. 1992, ApJ, 385, 306 [NASA ADS] [CrossRef] [Google Scholar]
  90. Neustock, W., Guarnieri, A., & Demaison, G. 1990, Z. Naturforsch, 45, 702 [Google Scholar]
  91. Nummelin, A., Bergman, P., Hjalmarson, A., et al. 1998, ApJS, 117, 427 [NASA ADS] [CrossRef] [Google Scholar]
  92. Nummelin, A., Bergman, P., Hjalmarson, Å., et al. 2000, ApJS, 128, 213 [NASA ADS] [CrossRef] [Google Scholar]
  93. Olofsson, A. O. H., Persson, C. M., Koning, N., et al. 2007, A&A, 476, 791 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  94. Padovani, M., Walmsley, C. M., Tafalla, M., Galli, D., & Müller, H. S. P. 2009, A&A, 505, 1199 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  95. Parise, B., Ceccarelli, C., Tielens, A. G. G. M., et al. 2002, A&A, 393, L49 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  96. Parise, B., Castets, A., Herbst, E., et al. 2004, A&A, 416, 159 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  97. Parise, B., Caux, E., Castets, A., et al. 2005a, A&A, 431, 547 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  98. Parise, B., Ceccarelli, C., & Maret, S. 2005b, A&A, 441, 171 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  99. Pech, G., Loinard, L., Chandler, C. J., et al. 2010, ApJ, 712, 1403 [NASA ADS] [CrossRef] [Google Scholar]
  100. Pickett, H. M., Poynter, I. R. L., Cohen, E. A., et al. 1998, J. Quant. Spect. Rad. Transf., 60, 883 [Google Scholar]
  101. Pilbratt, G. L., Riedinger, J. R., Passvogel, T., et al. 2010, A&A, 518, L1 [CrossRef] [EDP Sciences] [Google Scholar]
  102. Pizzarello, S., & Huang, Y. 2005, Geochim. Cosmochim. Acta, 69, 599 [Google Scholar]
  103. Remijan, A. J., & Hollis, J. M. 2006, ApJ, 640, 842 [NASA ADS] [CrossRef] [Google Scholar]
  104. Schilke, P., Groesbeck, T. D., Blake, G. A., & Phillips, T. G. 1997, ApJS, 108, 301 [NASA ADS] [CrossRef] [Google Scholar]
  105. Schilke, P., Benford, D. J., Hunter, T. R., Lis, D. C., & Phillips, T. G. 2001, ApJS, 132, 281 [NASA ADS] [CrossRef] [Google Scholar]
  106. Schmid-Burgk, J., Muders, D., Müller, H. S. P., & Brupbacher-Gatehouse, B. 2004, A&A, 419, 949 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  107. Schöier, F. L., Jørgensen, J. K., van Dishoeck, E. F., & Blake, G. A. 2002, A&A, 390, 1001 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  108. Schöier, F. L., Jørgensen, J. K., van Dishoeck, E. F., & Blake, G. A. 2004, A&A, 418, 185 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  109. Spahn, H., Müller, H. S. P., Giesen, T. F., et al. 2008, Chem. Phys., 346, 132 [NASA ADS] [CrossRef] [Google Scholar]
  110. Takakuwa, S., Ohashi, N., Bourke, T. L., et al. 2007, ApJ, 662, 431 [NASA ADS] [CrossRef] [Google Scholar]
  111. Tercero, B., Cernicharo, J., Pardo, J. R., & Goicoechea, J. R. 2010, A&A, 517, A96 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  112. Thompson, M. A., & MacDonald, G. H. 1999, A&AS, 135, 531 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  113. Thorwirth, S., Müller, H. S. P., Lewen, F., Gendriesch, R., & Winnewisser, G. 2000a, A&A, 363, L37 [NASA ADS] [Google Scholar]
  114. Thorwirth, S., Müller, H. S. P., & Winnewisser, G. 2000b, J. Mol. Spect., 204, 133 [NASA ADS] [CrossRef] [Google Scholar]
  115. Thorwirth, S., Müller, H. S. P., Lewen, F., et al. 2003, ApJ, 585, L163 [NASA ADS] [CrossRef] [Google Scholar]
  116. van der Tak, F. F. S., Müller, H. S. P., Harding, M. E., & Gauss, J. 2009, A&A, 507, 347 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  117. van Dishoeck, E. F., Blake, G. A., Jansen, D. J., & Groesbeck, T. D. 1995, ApJ, 447, 760 [NASA ADS] [CrossRef] [Google Scholar]
  118. Wakelam, V., Castets, A., Ceccarelli, C., et al. 2004, A&A, 413, 609 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  119. White, G. J., Araki, M., Greaves, J. S., Ohishi, M., & Higginbottom, N. S. 2003, A&A, 407, 589 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  120. Winnewisser, G., Belov, S. P., Klaus, T., & Schieder, R. 1997, J. Mol. Spect., 184, 468 [NASA ADS] [CrossRef] [Google Scholar]
  121. Wootten, A. 1989, ApJ, 337, 858 [NASA ADS] [CrossRef] [Google Scholar]
  122. Xu, L., & Lovas, F. J. 1997, J. Phys. Chem. Ref. Data, 26, 17 [NASA ADS] [CrossRef] [Google Scholar]
  123. Yamamoto, S., & Saito, S. 1994, J. Chem. Phys., 101, 5484 [NASA ADS] [CrossRef] [Google Scholar]

Online material

Table 2

Comparison of the spectral survey lines with previous observations.

Table 3

Comparison of the strong spectral survey lines simultaneously observed with different backends.

Table 4

Identified non-blended lines. The line characteristics are derived from Gaussian fits.

All Tables

Table 1

Parameters of the observations at IRAM-30 m and JCMT-15 m telescopes.

In the text
Table 5

Detected species ordered by decreasing fluxes of the main isotopologue.

In the text
Table 6

Distribution of the detected species in four kinematical types.

In the text
Table 7

Correspondence between kinematical types and spatial distributions derived from interferometric observations.

In the text
Table 2

Comparison of the spectral survey lines with previous observations.

In the text
Table 3

Comparison of the strong spectral survey lines simultaneously observed with different backends.

In the text
Table 4

Identified non-blended lines. The line characteristics are derived from Gaussian fits.

In the text

All Figures

thumbnail Fig. 1

Distribution of integrated intensity ratios of this survey’s 1 mm lines compared to published observations obtained with the IRAM 30 m telescope. The curve is a Gaussian fit to the histogram ruling out the “anomalous” ratios (≤ 0.5 or  ≥ 1.5). It can be noticed that the 12 “anomalous” ratios correspond to only 7 “anomalous spectra” among the 165 spectra observed in the 1 mm range.
In the text
thumbnail Fig. 2

The IRAS 16293 spectra in the four bands of the survey. Upper panels: IRAM-30 m 3 mm and 2 mm bands. Lower panels: IRAM-30 m 1 mm and JCMT-15 m 0.9 mm bands. The middle panels are zoomed views of sample frequency ranges in the four bands respectively. These panels include lines identification based on the publicly available spectral databases (see text for details).
In the text
thumbnail Fig. 3

Distribution of the density (averaged over 10 GHz intervals) of identified lines (see text) in each of the four frequency ranges. The upper panel corresponds to lines with , the central panel is restricted to lines with and the lower panel corresponds to lines with .
In the text
thumbnail Fig. 4

Number of lines showing an integrated intensity larger than a given threshold. The solid line shows the single index power-law best fit to the distribution.
In the text
thumbnail Fig. 5

Plots of the rest velocity vLSR versus the FWHM, derived from the Gaussian fits of the lines (Table 5). All the detected species and the relevant isotopologues of Table 5 are plotted, except those in which the lines have obviously non-Gaussian profiles (see text). In particular, the labels HCN* and OCS* mean that the main isotopologues of these species are not included, because of their non-Gaussian profiles. The one-σ error bars include fit and spectral resolution uncertainties. The vertical lines at vLSR = 2.7 and 3.9 km s-1 correspond to the velocity of the components B and A, respectively (see Sect. 6). The horizontal line at 5 km s-1 corresponds approximatively to the average of the line FWHM range.
In the text
thumbnail Fig. 6

Plots of the linewidth, FWHM, versus the energy of the upper level of the transition, Eup. The species are grouped as in Fig. 5. All the detected species and the relevant isotopologues of Table 5 are plotted, except those in which the lines obviously have non-Gaussian profiles (see text). In particular, the labels HCN* and OCS* mean that the main isotopologues of these species are not included, because of their non-Gaussian profiles. The one-σ error bars include fit and spectral resolution uncertainties. The horizontal line at 5 km s-1 corresponds approximatively to the average of the line FWHM range.
In the text

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