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The change in Wwe see in our simulations occurs because of changes in the physical conditions of GMCs associated with the merger. and not because the underlying star formation law is different.
The change in we see in our simulations occurs because of changes in the physical conditions of GMCs associated with the merger, and not because the underlying star formation law is different.
Finally. the concepts presented in this paper are testable in the near future with ALMA.
Finally, the concepts presented in this paper are testable in the near future with ALMA.
Our models suggest that high spatial resolution observations of nearby ULIRGs will display both large velocity dispersions in the CO gas. and larger brightness temperatures than those seen in observations of Galactic GMCs on a comparable scale.
Our models suggest that high spatial resolution observations of nearby ULIRGs will display both large velocity dispersions in the CO gas, and larger brightness temperatures than those seen in observations of Galactic GMCs on a comparable scale.
We see this when comparing the panels of Figure[|..
We see this when comparing the panels of Figure\ref{figure:iso_d3_map}.
Some observational evidence for this already exists.
Some observational evidence for this already exists.
Interferometric surveys of the central regions of nearby ULIRGs show velocity dispersions of hundreds ofLo und brightness temperatures of tens of Kelvin1998).
Interferometric surveys of the central regions of nearby ULIRGs show velocity dispersions of hundreds of, and brightness temperatures of tens of Kelvin.
. Similarly. unresolved observations of starbursts have shown gas and dust temperatures in the range of 30-50 K. in agreement with the models presented here2011).
Similarly, unresolved observations of starbursts have shown gas and dust temperatures in the range of 30-50 K, in agreement with the models presented here.
. The seminal work of investigated iin galaxies via subresolution models of GMCs— in a disc- configuration.
The seminal work of investigated in galaxies via subresolution models of GMCs in a disc-like configuration.
These authours found that wwould vary from the Galactic value in cases of high kinetic temperature. high velocity dispersion or low metallicity.
These authours found that would vary from the Galactic value in cases of high kinetic temperature, high velocity dispersion or low metallicity.
While not simultaneously modeling any of these effects. this model identitied some of the most important driving factors in setting the observed .\-factor in clouds.
While not simultaneously modeling any of these effects, this model identified some of the most important driving factors in setting the observed $X$ -factor in clouds.
A number of other studies have also investigated iin models of giant molecular clouds.
A number of other studies have also investigated in models of giant molecular clouds.
Early studies implemented ID radiative transfer calculations in spherical models of GMCs2007).
Early studies implemented 1D radiative transfer calculations in spherical models of GMCs.
.. With the increase of computational power. 3D numerical studies of GMCs in evolution have recently become feasible.
With the increase of computational power, 3D numerical studies of GMCs in evolution have recently become feasible.
Recently. and modeled aand CO formation/destruction in. magnetohydrodynamic models of GMCs.
Recently, and modeled and CO formation/destruction in magnetohydrodynamic models of GMCs.
These models were elaborated upon by who utilised radiative transfer calculations in combination with these MHD models to produce bona fide observables from the model clouds.
These models were elaborated upon by who utilised radiative transfer calculations in combination with these MHD models to produce bona fide observables from the model clouds.
These authours found that model GMC with mean densities. column densities. temperatures. and velocity dispersions comparable to the Milky Way's clouds QoLO]ü0em. Nus€107:1U7em7. To« δη. σα6kms n had average ffactors of order 2.41107em and were insensitive to
These authours found that model GMC with mean densities, column densities, temperatures, and velocity dispersions comparable to the Milky Way's clouds $n \sim 10^2-10^3 \cmthree$, $N_{\rm H_2} \sim 10^{21}-10^{22} \cmtwo$, $T\sim 10-20 \ {\rm K}$ , $\sigma\sim 1-6$ ) had average factors of order $2-4\times 10^{20}$ , and were insensitive to
of this modal modulation under DI1237|25s outer conal component pai.
of this modal modulation under B1237+25's outer conal component pair.
The top display gives the PPM profile after a πουαν segregation of the nodal power along with a curve showing the raction of this power which is modulated at the cature frequency of 2.63 0/P1: whereas the lower xuicel ooOgives the phase of this modulation.
The top display gives the PPM profile after a three-way segregation of the modal power along with a curve showing the fraction of this power which is modulated at the feature frequency of 2.63 $P_1$; whereas the lower panel gives the phase of this modulation.
As noted above. we chose a part of the pulse sequence with ew nuulls. which also had a particularly “pure” nodulation feature.
As noted above, we chose a part of the pulse sequence with few nulls, which also had a particularly “pure” modulation feature.
Clearly the phase is only reliable under the outside conal compoucut pair. where the modulation represents a large fraction of the total modal power.
Clearly, the phase is only reliable under the outside conal component pair, where the modulation represents a large fraction of the total modal power.
The lower display gives similar information for the SPM-seeregated partial sequence.
The lower display gives similar information for the SPM-segregated partial sequence.
Results for the UP partial sequence are relevant here aud thus not shown.
Results for the UP partial sequence are irrelevant here and thus not shown.
Remarkably. we see here that the PPM auc SPM power are roughly out of phase uuder the outer conal component pair.
Remarkably, we see here that the PPM and SPM power are roughly out of phase under the outer conal component pair.
The error in this phase difference is relatively σπα as evidenced by he stable SPM phase under the outer component xir.
The error in this phase difference is relatively small as evidenced by the stable SPM phase under the outer component pair.
Thus. when computed over the 256-pulse sequence. we have strong evidence that the modal power is ciuitted iu a manner which is far from “in phase.
Thus, when computed over the 256-pulse sequence, we have strong evidence that the modal power is emitted in a manner which is far from “in phase”.
This iu turn indicates that the modal yower ds systematically modulated. just as is he total power.
This in turn indicates that the modal power is systematically modulated, just as is the total power.
Furthermore. that there is SPAL »ower to scereeate implies (as cau also be seen in Fie. D)
Furthermore, that there is SPM power to segregate implies (as can also be seen in Fig. \ref{colourplot}) )
that. at times. the weaker SPM dominates he PPM.
that, at times, the weaker SPM dominates the PPM.
This behavior can be understood if both modes are. in general present in every seuple and conibine incoherentlywhich is just the situation of “superposed modes favored by. MSO0.
This behavior can be understood if both modes are, in general, present in every sample and combine incoherently—which is just the situation of “superposed modes” favored by MS00.
As discussed carlicr. conal component pairs exhibit large fractional linear polarization on their inner cdges and pronounced (often nearly conrlete) depolarization on their outer edges.
As discussed earlier, conal component pairs exhibit large fractional linear polarization on their inner edges and pronounced (often nearly complete) depolarization on their outer edges.
The three-way miode-seeregationo method provides sole vital clues to uuderstaudiug this phenomenon.
The three-way mode-segregation method provides some vital clues to understanding this phenomenon.
The power correspouding to the weaker SPM is sufficient to dominate the PPM only ou the outer “wines” of the profi5
The power corresponding to the weaker SPM is sufficient to dominate the PPM only on the outer “wings” of the profile.
The mode-segregation analyses above reveal two nuportaut characteristics of the emission bean configuration.
The mode-segregation analyses above reveal two important characteristics of the emission beam configuration.
First. the SPAL emission is generally shifted further outward. away frou the uaguetic axis. than the PPM emission.
First, the SPM emission is generally shifted further outward, away from the magnetic axis, than the PPM emission.
If this nodal radiation is euiütted (1 some average sense) * conal beams. then the enüssion conal region corresponding to the SPM beam wast have a little arecr radius than that of the PPM.
If this modal radiation is emitted (in some average sense) by conal beams, then the emission conal region corresponding to the SPM beam must have a little larger radius than that of the PPM.
Second. as we saw in Fig.
Second, as we saw in Fig.
5 the PPM aud SPM oower Is substantialle out of phase.
\ref{fig4} the PPM and SPM power is substantially out of phase.
Caven the small [/|/p for 1237|25.such that the sightline cuts the coual beams close to the magnetic axisthe phase differeuce suggests that emission elements within the respective modal beams are offset in maguctic azimuth!
Given the small $|\beta|/\rho$ for 1237+25—such that the sightline cuts the conal beams close to the magnetic axis—the phase difference suggests that emission elements within the respective modal beams are offset in magnetic azimuth!
And. iudeed. this is just the polarized-beam configuration observed m the rotating subbeam svstems of conal single pulsars DOSO9|7Ll (Rankin 22002) aud 0913|10. where systematic longitude offsets between the modes (at |Jjpo 1) also indicate offsets iu magnetic azimuth.
And, indeed, this is just the polarized-beam configuration observed in the rotating subbeam systems of conal single pulsars B0809+74 (Rankin 2002) and 0943+10, where systematic longitude offsets between the modes (at $|\beta|/\rho \sim 1$ ) also indicate offsets in magnetic azimuth.
Iu suuni. the modal conal enission patterus are offset in both magnetic colatitude aud azimuth.
In summary, the modal conal emission patterns are offset in both magnetic colatitude and azimuth.
We can begiu to conceive. given the above observational indications. how complex are the modal depolarization dyvnanuces of conal bemus.
We can begin to conceive, given the above observational indications, how complex are the modal depolarization dynamics of conal beams.
(2100051j 62s|<(pap«5lkns>1 epagc—Ὀδκαις((2011). Lin MM2 (z20M.) Lis describedthe show ο...region Surcis ct (2011) have fonued the most recent model of IRS 1. incorporating new observations of water aud methanol masers with other liue (e... Qiu et 22011) and continuum (e.g. Sandell et 22009) observations in order to delineate an outflow. torus. and cireiuustellar disk.
$\approx 100\,{\rm km}\,{\rm s}^{-1}$ $-62\,{\rm km}\,{\rm s}^{-1} < v_{\rm LSR} < -51\,{\rm km}\,{\rm s}^{-1}$ $v_{\rm LSR} \approx -58\,{\rm km}\,{\rm s}^{-1}$ $\approx 20\,M_\odot$ \ref{6cm} Surcis et (2011) have formed the most recent model of IRS 1, incorporating new observations of water and methanol masers with other line (e.g., Qiu et 2011) and continuum (e.g., Sandell et 2009) observations in order to delineate an outflow, torus, and circumstellar disk.
This model can be used to explain the line cussion in the narrow velocity range δαν|<clap5llaus5 but it does not address the details of the outflow or other sources presumnuablv responsible for the "high-velocity line emission outside of this narrow range. typified bv the water masers.
This model can be used to explain the line emission in the narrow velocity range $-62\,{\rm km}\,{\rm s}^{-1} < v_{\rm LSR} < -51\,{\rm km}\,{\rm s}^{-1}$ but it does not address the details of the outflow or other sources presumably responsible for the “high”-velocity line emission outside of this narrow range, typified by the water masers.
The (.N)=(9.6) 5NIL, maser was discovered serendipitouslv by Madden et ((1986) toward four of l1? Galactic star-forming regions suveved: Wl. W19. DR21(OID. and NGC 7538.
The $(J,K) = (9,6)$ $^{14}$ $_3$ maser was discovered serendipitously by Madden et (1986) toward four of 17 Galactic star-forming regions surveyed: W51, W49, DR21(OH), and NGC 7538.
In. 2010. we observed the uaser for the first time since its discovery. using the EVLA (Ποια Wim 2011. hereafter Paper D.
In 2010, we observed the maser for the first time since its discovery, using the EVLA (Hoffman Kim 2011, hereafter Paper I).
We coud (9.6) maser emission at new velocities. covering the rauge 6OlausLoccpagc56lans associated in vosition with IRS 1. aud cousisteut with the kinematics of the model of Surcis et (2011).
We found (9,6) maser emission at new velocities, covering the range $-60\,{\rm km}\,{\rm s}^{-1} < v_{\rm LSR} < -56\,{\rm km}\,{\rm s}^{-1}$, associated in position with IRS 1, and consistent with the kinematics of the model of Surcis et (2011).
Elsewhere in he Calas. nonietastable (7 A) απλοί mascrs are known to be variable (19: Madden et 11986 W51: Wilson. Heukel. Johustou 1990).
Elsewhere in the Galaxy, nonmetastable $J>K$ ) ammonia masers are known to be variable (W49: Madden et 1986; W51: Wilson, Henkel, Johnston 1990).
For example. Wilson IIeukel (1988) observed intensity variability of the maser in Wl bv a factor of 20 over a timescale of 10 amouths.
For example, Wilson Henkel (1988) observed intensity variability of the maser in W51 by a factor of 20 over a timescale of 10 months.
Iu a search for conuuou variability of snunionia and water masers and for other new constraints on this well studied star-formingcouples.wehave midertaken new {ας radio observations of NGC 7538
In a search for common variability of ammonia and water masers and for other new constraints on this well studied star-formingcomplex,wehave undertaken new $K$ -band radio observations of NGC 7538.
AGNs (MOJAVE-1).
AGNs (MOJAVE-1).
All the MOJAVE-I sources have J2000 declination à>—20° and a 15 GHz VLBA correlated flux density Seon21.5 Jy (2 Jy for ó«07) at any epoch between 1994.0 and 2004.0.
All the MOJAVE-1 sources have J2000 declination $\delta>-20\degr$ and a 15 GHz VLBA correlated flux density $S_\mathrm{corr}>1.5$ Jy (2 Jy for $\delta<0\degr$ ) at any epoch between 1994.0 and 2004.0.
The weaker radio blazars (Si;70.2 Jy) detected by extend the complete MOJAVE-1 sample to MOJAVE-2.
The weaker radio blazars $S_\mathrm{corr}>0.2$ Jy) detected by extend the complete MOJAVE-1 sample to MOJAVE-2.
The monitoring list currently consists of 293 sources. 186 of which are members of the First LAT catalog (IFGL.Abdoetal.2010a) that are positionally associated with AGNs.
The monitoring list currently consists of 293 sources, 186 of which are members of the First LAT catalog \citep[1FGL,][]{1FGL} that are positionally associated with AGNs.
We note that the 186 sources do not represent a complete sample selected on either parsec-scale radio flux density or 7-ray photon flux.
We note that the 186 sources do not represent a complete sample selected on either parsec-scale radio flux density or $\gamma$ -ray photon flux.
Apart from the median 5-ray photon and energy fluxes. the IFGL provides flux history data. in the form of monthly binned catalog0.1—100 GeV photon flux measurements during the first 11 months of the scientific operations. which started on 2008 August 4.
Apart from the median $\gamma$ -ray photon and energy fluxes, the 1FGL catalog provides flux history data, in the form of monthly binned $0.1-100$ GeV photon flux measurements during the first 11 months of the scientific operations, which started on 2008 August 4.
The time sampling of our VLBA radio observations 1s source-dependent: objects with more rapid structural changes (1.e.. faster apparent speeds) are observed more frequently.
The time sampling of our VLBA radio observations is source-dependent: objects with more rapid structural changes (i.e., faster apparent speeds) are observed more frequently.
There are only five sources in our sample that are monitored with a cadence more frequent than once every two months.
There are only five sources in our sample that are monitored with a cadence more frequent than once every two months.
Starting in early 2009. fifty five bright >-ray detections (7 1060) from the LAT 3-month list positionally associated with bright radio-loud blazars (Abdoetal.2009¢.a:Kovalev2009) have been incrementally added to the MOJAVE program.
Starting in early 2009, fifty five bright $\gamma$ -ray detections $>10\sigma$ ) from the LAT 3-month list positionally associated with bright radio-loud blazars \citep{Fermi3ml,LBAS,Kovalev_Fermi_assoc} have been incrementally added to the MOJAVE program.
More than half of these new LAT-detected sources have fewer than three epochs of radio observations during the era. which precludes the correlation analysis of individual light curves.
More than half of these new LAT-detected sources have fewer than three epochs of radio observations during the era, which precludes the correlation analysis of individual light curves.
Therefore. our study 1s based upon a statistical approach.
Therefore, our study is based upon a statistical approach.
Overall. we obtained 564 VLBA images and corresponding model fits for 183 bright 5-ray sources (Table 1)) within a period from June 2008 through March. 2010.
Overall, we obtained 564 VLBA images and corresponding model fits for 183 bright $\gamma$ -ray sources (Table \ref{t:sample}) ) within a period from June 2008 through March 2010.
The parsec-scale structure. typically represented by a one-sided core-jet was fitted with the procedure in the Difmap morphology.package (Shepherd1997) using a limited mode/firnumber of circular Gaussian components. às deseribed by Listerprimarilyetal.
The parsec-scale structure, typically represented by a one-sided core-jet morphology, was fitted with the procedure in the Difmap package \citep{difmap} using a limited number of primarily circular Gaussian components, as described by \cite{MOJAVE}.
(2009b).. We tested for possible correlations between the 5-raày photon fluxes and 15 GHz VLBA core flux densities using the following procedure: (1) we selected all pairs of measurements where the difference in the radio and 7-ray epochs lay within a restricted time interval. for instance. [70.5.40.5] month. where the negative sign indicates that the radio measurement precedes the 5-ray one. (1) if more than one pair of fluxes was available for à source. we selected the one with the epoch difference closest to the mean of the time interval.
We tested for possible correlations between the $\gamma$ -ray photon fluxes and 15 GHz VLBA core flux densities using the following procedure: (i) we selected all pairs of measurements where the difference in the radio and $\gamma$ -ray epochs lay within a restricted time interval, for instance, $[-0.5,+0.5]$ month, where the negative sign indicates that the radio measurement precedes the $\gamma$ -ray one, (ii) if more than one pair of fluxes was available for a source, we selected the one with the epoch difference closest to the mean of the time interval.
The procedure was then repeated iteratively by shifting the time interval by 0.5 month each time.
The procedure was then repeated iteratively by shifting the time interval by 0.5 month each time.
We performed a quantative analysis that confirmed that our data do not provide any bias towards positive pairs of radio/7-ray epoch difference.
We performed a quantative analysis that confirmed that our data do not provide any bias towards positive pairs of $\gamma$ -ray epoch difference.
We used a cutoff of SNR>3 for the 5-ray photon flux measurements to avoid a bias due to the lack of sources that are both weak in radio and 5-rays. and to exclude the influence of low-quality data points.
We used a cutoff of $\mathrm{SNR}>3$ for the $\gamma$ -ray photon flux measurements to avoid a bias due to the lack of sources that are both weak in radio and $\gamma$ -rays, and to exclude the influence of low-quality data points.
For each data set we calculated the Pearson's r and non-parametric Kendall's 7 correlation coefficients. together with a corresponding probability of a chance correlation (Table 2)).
For each data set we calculated the Pearson's $r$ and non-parametric Kendall's $\tau$ correlation coefficients, together with a corresponding probability of a chance correlation (Table \ref{t:corr_stat}) ).
A non-zero radio/~-ray time lag. clearly seen as a bump in the correlation versus delay curves (Fig. l..
A non-zero $\gamma$ -ray time lag, clearly seen as a bump in the correlation versus delay curves (Fig. \ref{f:gr_delay},
left panel). from 1 to 8 months.
left top panel), ranges from 1 to 8 months.
The smooth fitted curvestop were obtainedranges by applying a three point moving average.
The smooth fitted curves were obtained by applying a three point moving average.
To test the robustness of this result. we estimated the uncertainty value of the correlation coefficients.
To test the robustness of this result, we estimated the uncertainty value of the correlation coefficients.
Since both the radio flux densities and the 5-ray. photon fluxes are far from being normally distributed. direct. methods like the Fisher transformation or Student's t-distribution could. not be used.
Since both the radio flux densities and the $\gamma$ -ray photon fluxes are far from being normally distributed, direct methods like the Fisher transformation or Student's t-distribution could not be used.
Thus. we applied randomization techniques based on permutation tests to construct confidence intervals on the correlation coefficients.
Thus, we applied randomization techniques based on permutation tests to construct confidence intervals on the correlation coefficients.
For each data set the randomization was done in the following manner: (1) we randomly swapped the radio measurements for one source with another source. keeping the -ray fluxes the same: (11) we calculated correlation coefficients r and 7 from the randomized data.
For each data set the randomization was done in the following manner: (i) we randomly swapped the radio measurements for one source with another source, keeping the $\gamma$ -ray fluxes the same; (ii) we calculated correlation coefficients $r$ and $\tau$ from the randomized data.
We then repeated these steps 2000 times.
We then repeated these steps 2000 times.
A confidence interval (given in Table 2)) for the correlation coefficients was defined as the interval spanning from the 2.5-th to the 97.5-th percentile of the re-sampled + and 7 values.
A confidence interval (given in Table \ref{t:corr_stat}) ) for the correlation coefficients was defined as the interval spanning from the 2.5-th to the 97.5-th percentile of the re-sampled $r$ and $\tau$ values.
To estimate the null-basis level of the flux-flux correlation (which ts present due to an overall radio/7-ray correlation: see .3.2)) . we shuffled the 7-ray photon fluxes among the 11 measurements available for every source. keeping the epoch dates and radio flux densities the same.
To estimate the null-basis level of the flux-flux correlation (which is present due to an overall $\gamma$ -ray correlation; see \ref{localization}) ), we shuffled the $\gamma$ -ray photon fluxes among the 11 measurements available for every source, keeping the epoch dates and radio flux densities the same.
The resulting values were ro=0.37 and 720.26 (Fig. 1..
The resulting values were $r_0=0.37$ and $\tau_0=0.26$ (Fig. \ref{f:gr_delay},
left bottom panel).
left bottom panel).
When we randomly selected (and 80%)) of the sample the correlations remained significant. indicating that they are not driven by outliers.
When we randomly selected (and ) of the sample the correlations remained significant, indicating that they are not driven by outliers.
Additionally. we found no significant correlation between redshift and the VLBA core flux density averaged for the sample over the era.
Additionally, we found no significant correlation between redshift and the VLBA core flux density averaged for the sample over the era.
The wide range of delays in which the flux-flux correlations are significant (Fig ].. left) is presumably a result of the multiple parameters that determine the conditions in. the nucleus (black hole mass. its spin and accretion rate). and in the nearby interstellar medium.
The wide range of delays in which the flux-flux correlations are significant (Fig \ref{f:gr_delay}, left) is presumably a result of the multiple parameters that determine the conditions in the nucleus (black hole mass, its spin and accretion rate), and in the nearby interstellar medium.
The delay ts also affected by geometry. including the angle of the jets to our line of sight and the wide range of redshifts 1n our sample.
The delay is also affected by geometry, including the angle of the jets to our line of sight and the wide range of redshifts in our sample.
The redshifts are known for more than of the sources (166 out of 183).
The redshifts are known for more than of the sources (166 out of 183).
We re-did the analysis in the source's frame by dividing the radio/5-ray epoch time difference for each source by a factor of (1+z)
We re-did the analysis in the source's frame by dividing the $\gamma$ -ray epoch time difference for each source by a factor of $(1+z)$.
This gave a typical time delay of ~1.2 months in the source frame (Fig. |..
This gave a typical time delay of $\sim1.2$ months in the source frame (Fig. \ref{f:gr_delay},
right). which corresponds to ~2.5 months (for z— 1) in the observer's frame.
right), which corresponds to $\sim2.5$ months (for $z\sim1$ ) in the observer's frame.
The other sub-peaks are not significantly different from the null level of correlation. though they may indicate longer delays in à smaller number of sources.
The other sub-peaks are not significantly different from the null level of correlation, though they may indicate longer delays in a smaller number of sources.
Note that the points on the correlation curve are
Note that the points on the $\gamma$ -ray correlation curve are dependent.
We expect the smearing radio/>-rayeven in the source frame delay dependent.because the core size
We expect the smearing even in the source frame delay because the core size
by Dewev et al. (
by Dewey et al. (
1981) to find the ninimuua detectable flux deusitv a pulsar has to have in order to be detectable: Tere the coustaut factor (ap takes iuto account losses in the hardware aud the tlireshold. signal-to-noise ratio above which a detection 1s €ousidered signuificaut (4)2LO In our case). To. is the system teniperatire (see below). G is the exin of the telesco] rome ON ! for Effelshere operating at 21-c13). Av is the ¢)bserviug xaidwidth (16-AIIIz for this survey). the factor of 2 uxicates that two »olarisation cinel were sunined. 7 is the iutegration iue per telescope pointing (35 min). P is the period of he pulsar iux T is the observed width o the pulse.
1984) \nocite{dss+84} to find the minimum detectable flux density a pulsar has to have in order to be detectable: Here the constant factor $\eta$ takes into account losses in the hardware and the threshold signal-to-noise ratio above which a detection is considered significant $\eta \approx 10$ in our case), $T_{\rm sys}$ is the system temperature (see below), $G$ is the gain of the telescope (1.5 K $^{-1}$ for Effelsberg operating at 21-cm), $\Delta \nu$ is the observing bandwidth (16-MHz for this survey), the factor of $\sqrt{2}$ indicates that two polarisation channels were summed, $\tau$ is the integration time per telescope pointing (35 min), $P$ is the period of the pulsar and $W$ is the observed width of the pulse.
The system temperature To. is essentially the sui of he noise tenrovature of the receiver TL. the spillover roise into the beau side-lobes from the ground Ti, iu he excess backeround teurorature Tug. caused lareecly wi svuclrotron radiating cletrous in the Galactic plane itself.
The system temperature $T_{\rm sys}$ is essentially the sum of the noise temperature of the receiver $T_{\rm rec}$, the spillover noise into the beam side-lobes from the ground $T_{\rm spill}$ and the excess background temperature $T_{\rm sky}$ caused largely by synchrotron radiating electrons in the Galactic plane itself.
From regular calibration measurements we fotπι Jui to be 35 IK. The spilover contribution Tij was estimated to be 5 IX for typi‘al telescope elevations duriug survey observations.
From regular calibration measurements we found $T_{\rm rec}$ to be 35 K. The spillover contribution $T_{\rm spill}$ was estimated to be 5 K for typical telescope elevations during survey observations.
We estinate Zij by scaling the AIIIz all-sky survey of Hasla net al. (
We estimate $T_{\rm sky}$ by scaling the 408-MHz all-sky survey of Haslam et al. (
1982). to Llo0 MITIz assundue a spectral index of 2.7 (Lawson ct al.
1982) \nocite{hssw82} to 1400 MHz assuming a spectral index of –2.7 (Lawson et al.
1987). finding a typical value in tlic! direction /=29 aud 5=0.0 to be 15 I. With these vaues in Eq. (1)).
1987), \nocite{lmop87} finding a typical value in the direction $l=29$ and $b=0.0$ to be 15 K. With these values in Eq. \ref{equ:smin}) ),
we find the niunuuni flux «ensitv for detecting a 0.5 s musar with a duty evele of to be ayout 0.3 12Js.
we find the minimum flux density for detecting a 0.5 s pulsar with a duty cycle of to be about 0.3 mJy.
We caulon that this seusitivity estimate should be viewed as odd "best Case SCenario. valid for relatively lone-period pulsars wi nv dispersion iueasures and narrow pulses observed at the Dear centre.
We caution that this sensitivity estimate should be viewed as a “best case scenario”, valid for relatively long-period pulsars with low dispersion measures and narrow pulses observed at the beam centre.
The effects of saniplug aie dis]sersion and pulse scattering sigUficautly degrade 1o search sensitivity at short periods.
The effects of sampling and dispersion and pulse scattering significantly degrade the search sensitivity at short periods.