ReadingTimeMachine/rtm-sgt-ocr-v1 · Datasets at Hugging Face

source stringlengths 1 2.05k ⌀	target stringlengths 1 11.7k
Since in starburst environments the aand eemission lines are expected to be driven mainly by ionization (e.g.,?),, the lower ratios found along the southwest axis are likely due to a eemission enhanced by the starburst ring.	Since in starburst environments the and emission lines are expected to be driven mainly by photo-ionization \citep[e.g.,][]{ho07}, the lower ratios found along the northeast-southwest axis are likely due to a emission enhanced by the starburst ring.
Although, these low ratios are also consistent with a ratio II] €O.1 found in shocks (?) where the low ionization line ccan also be enhanced (2).	Although, these low ratios are also consistent with a ratio $\leq$ 0.1 found in shocks \citep{binette85} where the low ionization line can also be enhanced \citep{voit92}.
. On the other hand, the highest rratios found above and below the starburst ring are larger than those typically found in shocks.	On the other hand, the highest ratios found above and below the starburst ring are larger than those typically found in shocks.
These higher ratios could actually be tracing an additional contribution to the [NellI] emission by a conically shaped narrow line region (NLR).	These higher ratios could actually be tracing an additional contribution to the [NeIII] emission by a conically shaped narrow line region (NLR).
Previously, no evidence was found for the existence of such a NLR, given the absence of emission in the central 800pcx800pc (?)..	Previously, no evidence was found for the existence of such a NLR, given the absence of emission in the central $\times$ 800pc \citep{moorwood96a}.
Instead the conical cavity traced by optical and near-infrared line and continuum tracers (??) was associated with a starburst super wind.	Instead the conical cavity traced by optical and near-infrared line and continuum tracers \citep{moorwood96a, marconi00} was associated with a starburst super wind.
However, given the high extinction implied by our observations, optical eemission can be easily attenuated; mid-infrared eemission less so.	However, given the high extinction implied by our observations, optical emission can be easily attenuated; mid-infrared emission less so.
A hypothetical conical NLR would be	A hypothetical conical NLR would be
Since in microlensing experiments the event durations are found by photometric fitüng and since the optical depth is proportional to the sum of the fit /zs. when making corrections [or blending it is important to properly relate the lens-light lraction of each event to the underlying event duration.	Since in microlensing experiments the event durations are found by photometric fitting and since the optical depth is proportional to the sum of the fit $\te$ 's, when making corrections for blending it is important to properly relate the lens-light fraction of each event to the underlying event duration.
and ((1997) (WP) studied the degeneracy of blend fits and concluded that in many cases blended and unblended lightcurves cannot be distinguished by photometric fitüng.	and (1997) (WP) studied the degeneracy of blend fits and concluded that in many cases blended and unblended lightcurves cannot be distinguished by photometric fitting.
They described areas of parameter space where blend fits would be useful and areas where they would not.	They described areas of parameter space where blend fits would be useful and areas where they would not.
While we think that WP did an accurate and very useful caleulation, and we agree with their conclusion that blend fits are usually not very useful, we wanted to repeat their analysis for several reasons.	While we think that WP did an accurate and very useful calculation, and we agree with their conclusion that blend fits are usually not very useful, we wanted to repeat their analysis for several reasons.
First, WP did not include the baseline magnitude in their fits. reasoning that since many measurements are taken before and aller the event, the error in baseline magnitude was not significant.	First, WP did not include the baseline magnitude in their fits, reasoning that since many measurements are taken before and after the event, the error in baseline magnitude was not significant.
In fact, we find that error in the baseline magnitude is one of the most severe problems in blend fits.	In fact, we find that error in the baseline magnitude is one of the most severe problems in blend fits.
We find that errors even at the few percent level can drasucally alter the parameter values extracted [rom the fit.	We find that errors even at the few percent level can drastically alter the parameter values extracted from the fit.
Second, WP considered only evenly spaced observations and we wanted to consider whether different [ollow-up strategies could improve the ability to extract the parameters.	Second, WP considered only evenly spaced observations and we wanted to consider whether different follow-up strategies could improve the ability to extract the parameters.
In our studies, we find the error in fit parameters three ways.	In our studies, we find the error in fit parameters three ways.
First we create artificial lightcurves using the theoretical formula and add Gaussian random noise to each measurement.	First we create artificial lightcurves using the theoretical formula and add Gaussian random noise to each measurement.
We perform blended and unblended fits on these lghtcurves using Minuit (CERN Lib.	We perform blended and unblended fits on these lightcurves using Minuit (CERN Lib.
2003).	2003).
Second we calculate the error matrix by inverting the Hessian matrix as discussed in Gould (2003).	Second we calculate the error matrix by inverting the Hessian matrix as discussed in Gould (2003).
Finally to understand the e[Iect of the non-Gaussianity of the errors in real microlensing experiments we create. artificial lensing lighteurves by adding microlensing signal into actual non-microlensing lightcurves obtained by the MACHO collaboration, and then fit these.	Finally to understand the effect of the non-Gaussianity of the errors in real microlensing experiments we create artificial lensing lightcurves by adding microlensing signal into actual non-microlensing lightcurves obtained by the MACHO collaboration, and then fit these.
Since the method of calculating the error matrix is closest to what WP did, we first give these results.	Since the method of calculating the error matrix is closest to what WP did, we first give these results.
Briefly, we calculate the Hessian matrix (the matrix of second derivatives of the light curve residuals with respect to each parameter) then invert it.	Briefly, we calculate the Hessian matrix (the matrix of second derivatives of the light curve residuals with respect to each parameter) then invert it.
The square root of the diagonal elements of the resulting matrix are then the one sigma errorbars of the parameters.	The square root of the diagonal elements of the resulting matrix are then the one sigma errorbars of the parameters.
This accounts for correlations in the parameters, but not any nonlineariues.	This accounts for correlations in the parameters, but not any nonlinearities.
WP used a very similar method, but used it to calculate the ο of the error bars.	WP used a very similar method, but used it to calculate the $\Delta \chi^2$ instead of the error bars.
In figure 3. we show that our method brackets WP's.	In figure \ref{fig:wp} we show that our method brackets WP's.
We show limits calculated as both the one sigma lower limit on. { for an unblended hghtcurve and the value of fy that gives fj,ση= 1.	We show limits calculated as both the one sigma lower limit on $f_{ll}$ for an unblended lightcurve and the value of $f_{ll}$ that gives $f_{ll}+\sigma_{f_{ll}} = 1$
In the case of narrow line or edge features. in different combinations of spectral order. data reduction method aud binning size. we identify possible structure in residuals al 26.5. 21.6. 34.4. 32.4. and 35.9 (emission like features). and at 28.2. 39.1. and 86.5 (absorption like features). that might be tempting to attribute to the source.	In the case of narrow line or edge features, in different combinations of spectral order, data reduction method and binning size, we identify possible structure in residuals at 26.5, 27.6, 34.4, 32.4, and 35.9 (emission like features), and at 28.2, 39.1, and 86.5 (absorption like features), that might be tempting to attribute to the source.
ILowever. we cannot exclude the possibility that anv are chance fluctuations at the level.	However, we cannot exclude the possibility that any are chance fluctuations at the level.
The issue is complicated by possible calibration uncertainties on smaller scales. believed to be at a level of about oor less. that should be largely smoothed out by dither.	The issue is complicated by possible calibration uncertainties on smaller scales, believed to be at a level of about or less, that should be largely smoothed out by dither.
We have also used a 60ks observation (ObsID 331) of2155-304. currently thought to be a featureless continuum in the speclral range we are concerned wilh here (Marshall οἱ al..	We have also used a 60ks observation (ObsID 331) of, currently thought to be a featureless continuum in the spectral range we are concerned with here (Marshall et al.,
in preparation). as a flat field source lo aid in feature identification.	in preparation), as a flat field source to aid in feature identification.
This spectrum comprises about eight limes (he number of first order counts of the combined ddata.	This spectrum comprises about eight times the number of first order counts of the combined data.
Moreover. we have imposed a constraint that features must appear in both positive and negative orders in the sspectrum.	Moreover, we have imposed a constraint that features must appear in both positive and negative orders in the spectrum.
We examined deviations [rom the model on scales up to 3 aad find only the expected normal distribution of residuals after allowing [for smooth departures resulting [rom calibration.	We examined deviations from the model on scales up to 3 and find only the expected normal distribution of residuals after allowing for smooth departures resulting from calibration.
The Ixolmogorov-5Smürnov. test applied to deviations on different scales also revealed no evidence for significant features (hese scales.	The Kolmogorov-Smirnov test applied to deviations on different scales also revealed no evidence for significant features these scales.
In summary. all significant deviations in the residuals (hat have been found can reasonably be explained bv instrumental effects.	In summary, all significant deviations in the residuals that have been found can reasonably be explained by instrumental effects.
Equivalent width upper limits were derived by applying counting statistics to a convolution of the spectrum with a triangular kernel (Figure 2)).	Equivalent width upper limits were derived by applying counting statistics to a convolution of the spectrum with a triangular kernel (Figure \ref{f:ew}) ).
The distance of 62 pe derived by Walter (2001) seems at odds with the neutral HE column density. Vj). of LO?" ? derived [rom the Chandra spectra: measured Vy, values for objects al this distance based on different techniques are typically in the range 107-10?) 7 FFruscione οἱ 1994).	The distance of 62 pc derived by Walter (2001) seems at odds with the neutral H column density, $N_H$ , of $10^{20}$ $^{-2}$ derived from the Chandra spectra: measured $N_H$ values for objects at this distance based on different techniques are typically in the range $10^{18}$ $10^{19}$ $^{-2}$ Fruscione et 1994).
Walter (2001) indeed remarked on (his. citing reddening values Epv olf up to 0.1 derived by Ixnude Hog (1998) in support of the distance.	Walter (2001) indeed remarked on this, citing reddening values $E_{B-V}$ of up to 0.1 derived by Knude g (1998) in support of the distance.
However. these redclening values show considerable scatter at low reddening and are based only on a relalively coarse attribution of spectral twpe to the stars considered.	However, these reddening values show considerable scatter at low reddening and are based only on a relatively coarse attribution of spectral type to the stars considered.
We have estimated Ny, and the mean local neutral hvdrogen number density. 2,;. in the line-of-sight. toward aas a [unetion of distance by spatial interpolation in (he measurements compiled by Fruscione et ((1994) ancl Diplas Savage(1994) using a technique developed by P. Jelinsky	We have estimated $N_H$ and the mean local neutral hydrogen number density, $n_H$, in the line-of-sight toward as a function of distance by spatial interpolation in the measurements compiled by Fruscione et (1994) and Diplas Savage(1994) using a technique developed by P. Jelinsky
Ou the large scale (Figure 2)) we can see extremely faint. diffuse ciuission that exteuds for ~675 (20 kpc} in the east-west direction.	On the large scale (Figure \ref{fig:1549ls}) ) we can see extremely faint, diffuse emission that extends for $\sim6\farcs5$ (20 kpc) in the east-west direction.
The north-south exteusion. as noted bv Prestage&Peacock(1983).. cam be seen.	The north-south extension, as noted by \citet{pandp83}, can be seen.
This Figure shares simul features to the deep Very Large Telescope Comm rk image of IT06 (their Figure 1).	This Figure shares similar features to the deep Very Large Telescope Gunn $r$ image of H06 (their Figure 1).
The authors note that the north-south extended features appear to contain knots of enuüssiou.	The authors note that the north-south extended features appear to contain knots of emission.
Πας we cau see poiut-like sources im similar positious to these knots. which could be foreground stars but may also be super star clusters associated with the tidal tails of PISSIS19-το,	Here we can see point-like sources in similar positions to these knots, which could be foreground stars but may also be super star clusters associated with the tidal tails of PKS1549-79.
The radio15 source PISS 1315112 las also hac wach previous work carried out on it.	The radio source PKS 1345+12 has also had much previous work carried out on it.
Again. a brief outline of its main properties will be given before the new data are presented.	Again, a brief outline of its main properties will be given before the new data are presented.
Readers iuterested iu a more thorough review are directed toward ITALO3.	Readers interested in a more thorough review are directed toward HTM03.
PISS 1315)12 (1€ 12.50) is one of the closest GPS sources.	PKS 1345+12 (4C 12.50) is one of the closest GPS sources.
This allows the compact double jet and core structure. noted frou, VLBI (δα) and VLBA (Gein) radio observatious. to preseut proportions of ~0715.	This allows the compact double jet and core structure, noted from VLBI (2cm) and VLBA (6cm) radio observations, to present proportions of $\sim0\farcs15$.
The more pronünent S-shaped jet componcut extends to the south-cast before beudiug aud expanding into a diffuse lobe.	The more prominent S-shaped jet component extends to the south-east before bending and expanding into a diffuse lobe.
Protruding to the north-west of the core (the core being identified from the relative fatness of the radio spectimm) weak radio cussion is detected.	Protruding to the north-west of the core (the core being identified from the relative flatness of the radio spectrum) weak radio emission is detected.
On larger scales. diffuse radio cussion is detected exteudiue 35700 (NU kpe) to the north. aud 25700 (~55 kpc) to the south (Stanghellinietal.2005).	On larger scales, diffuse radio emission is detected extending 0 $\sim$ 80 kpc) to the north, and 0 $\sim$ 55 kpc) to the south \citep{stang05}.
. Optically. PISS 1315\|12 shows a couples morphology characterized by two nuclei; the western most of which. identified as a 17.5(V) magnitude elliptical. possessing an extended curved tail.	Optically, PKS 1345+12 shows a complex morphology characterized by two nuclei, the western most of which, identified as a 17.5(V) magnitude elliptical, possessing an extended curved tail.
PreviousAST studies. which are unable to resolve structure down to the scale of the radio mmorphology. have shown the western nucleus to be associated with the radio source (Axonetal.2000).	Previous studies, which are unable to resolve structure down to the scale of the radio morphology, have shown the western nucleus to be associated with the radio source \citep{axon00}.
. From the ACS data presented here we find optical radio offsets (Table 2)) similar to those fouud by Axonetal. (2000).. which coufizius the western nucleus as the host of the radio source.	From the ACS data presented here we find optical – radio offsets (Table \ref{tab:astro}) ) similar to those found by \citet{axon00}, which confirms the western nucleus as the host of the radio source.
The double nuuceus and distorted appearance of PISS 1315\|12 shows tha tagnereer event Is taking place.	The double nucleus and distorted appearance of PKS 1345+12 shows that a merger event is taking place.
As with the other source in this study; PISS 1315\|12 shows a voung stellar populaion (Tadluuteretal. 2005).. a FIR excess (ULIRG) and near-UV cussion (Evansctal.1999.Labianoetal..inprep).. mdicatiug the presence of considerable star formation.	As with the other source in this study, PKS 1345+12 shows a young stellar population \citep{tad05}, a FIR excess (ULIRG) and near-UV emission \citep[][Labiano et al., in prep]{evans99}, indicating the presence of considerable star formation.
Using optical spectroscopy. ITTAL03 lave observed 3. distinct unclear kineniatical componcuts in PERS 1315\|12. the narrowest of which (PWIIMz310kans1) is interpreted as the systemic velocity.	Using optical spectroscopy, HTM03 have observed 3 distinct nuclear kinematical components in PKS 1345+12, the narrowest of which $\approx340{\rm~km~s^{-1}}$ ) is interpreted as the systemic velocity.
The two other compoucuts. designated “intermediate” and “broad”. show FATAL of ~1250kins and ~L950kins\| respectively. with corresponding bluc-shifts of ~lOOlas+ and L980last with respect to the rest frame.	The two other components, designated “intermediate” and “broad”, show FWHM of $\sim1250{\rm~km~s^{-1}}$ and $\sim1950{\rm~km~s^{-1}}$ respectively, with corresponding blue-shifts of $\sim400{\rm~km~s^{-1}}$ and $\sim1980{\rm~km~s^{-1}}$ with respect to the rest frame.
Due to the reddening observed in cach component. it is proposed that the broad component originates from the imnoer most reeions closest to the obscured quasar. whilst the narrow component represents a quiesceut halo.	Due to the reddening observed in each component, it is proposed that the broad component originates from the inner most regions closest to the obscured quasar, whilst the narrow component represents a quiescent halo.
Iu Figure 3. we preseut the new ACS data for PIS 1315\|12.	In Figure \ref{fig:1345acs} we present the new ACS data for PKS 1345+12.
Iu both the Πα and [OTH] line aud coutiuuun nuages we find the two separate nuclei clearly visible within an extended diffuse euvelope.	In both the $\alpha$ and [OIII] line and continuum images we find the two separate nuclei clearly visible within an extended diffuse envelope.
The 270 (~5 kpc) separation of the two nuclei measured here is ~(71 ercater than the separation reported by Weckmanetal.(19056) aud Cülinore&Shaw(1986).	The $2\farcs0$ $\sim5$ kpc) separation of the two nuclei measured here is $\sim0\farcs1$ greater than the separation reported by \citet{heck86} and \citet{gands86}.
. The continuuni subtracted emission line dmages (Figures 2cc aud £f) show hat an insignificant amount of line cussion ομαλάτος roni the easteru component when compared to the western uucleus.	The continuum subtracted emission line images (Figures \ref{fig:1345acs}c c and f) show that an insignificant amount of line emission emanates from the eastern component when compared to the western nucleus.
To the northwest of this western micleus there is an extended cussion line filament (6.8.. Figures Saa. ο, d and f).	To the north-west of this western nucleus there is an extended emission line filament (e.g., Figures \ref{fig:1345acs}a a, c, d and f).
haniediately north-east of the nai nuclear structure there is a separate island of ΟΠΠ enission (see Figure 300) and a “mushroom Like norpholoey to the Ta coutiuuua (see Figure 3bb): this is clear evidence of a dust lane running approximatcly south-cast to uorth-west.	Immediately north-east of the main nuclear structure there is a separate island of [OIII] emission (see Figure \ref{fig:1345acs}e e) and a “mushroom” like morphology to the $\alpha$ continuum (see Figure \ref{fig:1345acs}b b); this is clear evidence of a dust lane running approximately south-east to north-west.
On the larger scale we can again compare this data to the findings of Heckmanotal.(1986).	On the larger scale we can again compare this data to the findings of \citet{heck86}.
. Figure 1. highlights the distorted morphology and lints at some of the south-west curved tail exteusions mentioned by TWeckmanetal.(1986).	Figure \ref{fig:1345ls} highlights the distorted morphology and hints at some of the south-west curved tail extensions mentioned by \citet{heck86}.
.. We also see that the halo of PISS 1315112 coutams similar point like sources (to the south of the eastern nucleus) to the foreground stars or possible star cluster seen around PISS 1519-79.	We also see that the halo of PKS 1345+12 contains similar point like sources (to the south of the eastern nucleus) to the foreground stars or possible star cluster seen around PKS 1549-79.
Further study has shown these sources to be super star cluster with voung stellar populations (RodriguezZaurinetal.2006).	Further study has shown these sources to be super star cluster with young stellar populations \citep{rod06}.
. Iu this section we closely examune the iuner structures of the observed nuclei aud determine the most likely position of the ACN in the ACS emission line images (and therefore the likely position of the radio cores).	In this section we closely examine the inner structures of the observed nuclei and determine the most likely position of the AGN in the ACS emission line images (and therefore the likely position of the radio cores).
Di-couical structures will sugecst that the outflows are wind driven. whereas structures similar to the radio morphologies will suggest that the outflows are driven by the radio jets.	Bi-conical structures will suggest that the outflows are wind driven, whereas structures similar to the radio morphologies will suggest that the outflows are driven by the radio jets.
However. first we cxamine the relative astromietrv in the ACS data in order to estimate the "uncertainties in derived positions.	However, first we examine the relative astrometry in the ACS data in order to estimate the uncertainties in derived positions.
There are two clemenuts that could contribute to differeuces hetween the spatial offsets of objects measured ou the WECT aud URC frames: the errors iu measuring the positious themselves. i.e. true positions as related to iieasured positions. aud he residual errors in the correction of the spatial distortiou by the pipeline reduction.	There are two elements that could contribute to differences between the spatial offsets of objects measured on the WFC1 and HRC frames: the errors in measuring the positions themselves, i.e., true positions as related to measured positions, and the residual errors in the correction of the spatial distortion by the pipeline reduction.
By quautifviug these errors we cau estimate the astrometric uncertainties present 1 ithe ACS images.	By quantifying these errors we can estimate the astrometric uncertainties present in the ACS images.
in probing these scales in order to understand them on their own terms. describing substructure and. the cuspiness of halos: cosmic flexion is also complementary to cosmic shear. probing small scales in an isolated. fashion. whereas cosmic shear has a broad window function for power.	in probing these scales in order to understand them on their own terms, describing substructure and the cuspiness of halos; cosmic flexion is also complementary to cosmic shear, probing small scales in an isolated fashion, whereas cosmic shear has a broad window function for power.
The cosmic Hexion signal will be a useful means of testing theories of stable clustering or stable merging (ef.	The cosmic flexion signal will be a useful means of testing theories of stable clustering or stable merging (c.f.
Smith et al 2003).	Smith et al 2003).
lt should be noted that in this analysis we have neglected the power that might exist from intrinsic. physical llexion correlations between galaxies.	It should be noted that in this analysis we have neglected the power that might exist from intrinsic, physical flexion correlations between galaxies.
The analogous intrinsic cllipticity correlation between galaxies has been shown (e.g. Llevmans et al 2004) to be small: however. further work will be necessary to measure the level of contamination of cosmic Llexion due to intrinsic. [lexion alignments.	The analogous intrinsic ellipticity correlation between galaxies has been shown (e.g. Heymans et al 2004) to be small; however, further work will be necessary to measure the level of contamination of cosmic flexion due to intrinsic flexion alignments.
In addition to the Hexion power spectrum. we are also able to calculate the convergence-Hexion. cross power spectrum. which can easily be related to the shear-Dexion cross power spectrum.	In addition to the flexion power spectrum, we are also able to calculate the convergence-flexion cross power spectrum, which can easily be related to the shear-flexion cross power spectrum.
We note that to do this we can again use Limber's equation (79)). but this time using £5 from the outset rather than 2s).	We note that to do this we can again use Limber's equation \ref{eq:limber}) ), but this time using $P_\delta$ from the outset rather than $P_{\delta'}$.
In this case. from our final power spectrum: for Uexion (equation 84)) we see that the relevant choice of q for llexion in Limber’s equation is 1n αστοι. [rom equationi (74)). we see that the choice of q suitable for convergence is llence the cross-power spectrum between convergence and Hexion can be written as ‘This is shown in Figure Ll. together with the associated convergence-I[exion. cross-correlation function in Figure 12 with appropriate errors for a 100. square degree survey.	In this case, from our final power spectrum for flexion (equation \ref{eqn:pf}) ) we see that the relevant choice of $q$ for flexion in Limber's equation is In addition, from equation \ref{eqn:kappa}) ), we see that the choice of $q$ suitable for convergence is Hence the cross-power spectrum between convergence and flexion can be written as This is shown in Figure 11, together with the associated convergence-flexion cross-correlation function in Figure 12 with appropriate errors for a 100 square degree survey.
We see that this quantity has a measurement limit on an intermediate scale to shear and flexion limits ( 2’).	We see that this quantity has a measurement limit on an intermediate scale to shear and flexion limits $\simeq 2'$ ).
Ht is a valuable quantity to measure. as it gives a stronger signal-to-noise than cosmic flexion. anc olfers a stringent check on svstematic errors between the shear or convergence and llexion signals.	It is a valuable quantity to measure, as it gives a stronger signal-to-noise than cosmic flexion, and offers a stringent check on systematic errors between the shear or convergence and flexion signals.
In this paper. we have cxamined how Uexion can be applied	In this paper, we have examined how flexion can be applied
how systems with negative heat capacity evolve (Lyudeu-Bell1999).	how systems with negative heat capacity evolve \citep{l99}.
. However the theory does uot describe accurately real clusters. at least those of modest population on which we lave focused.	However the theory does not describe accurately real clusters, at least those of modest population on which we have focused.
The two main [actors ehanging the pleture are binary beating aud stellar evolution.	The two main factors changing the picture are binary heating and stellar evolution.
Both processes are. of course. well understood. but their combined effect lias uot been appreciatect.	Both processes are, of course, well understood, but their combined effect has not been appreciated.
All clusters are born with a largeDm fraction of binaries. but these do not provide the largestDm effect.	All clusters are born with a large fraction of binaries, but these do not provide the largest effect.
It is the systems most massive stars coupling together that generate most of the heating through three-body interactions.	It is the system's most massive stars coupling together that generate most of the heating through three-body interactions.
This heating easily reverses inciplent core contraction. so that the central cleusity climbs only. slightly before the uew phase of global expansion begius.	This heating easily reverses incipient core contraction, so that the central density climbs only slightly before the new phase of global expansion begins.
This phase resembles. at least qualitatively. the post-collapse evolution described by Hénou(1972).	This phase resembles, at least qualitatively, the post-collapse evolution described by \citet{h72}.
. However. the reversal [rom coutraction occurs at wach lower density thai iu earlier accounts.	However, the reversal from contraction occurs at much lower density than in earlier accounts.

Since in starburst environments the aand eemission lines are expected to be driven mainly by ionization (e.g.,?),, the lower ratios found along the southwest axis are likely due to a eemission enhanced by the starburst ring.

Since in starburst environments the and emission lines are expected to be driven mainly by photo-ionization \citep[e.g.,][]{ho07}, the lower ratios found along the northeast-southwest axis are likely due to a emission enhanced by the starburst ring.

Although, these low ratios are also consistent with a ratio II] €O.1 found in shocks (?) where the low ionization line ccan also be enhanced (2).

Although, these low ratios are also consistent with a ratio $\leq$ 0.1 found in shocks \citep{binette85} where the low ionization line can also be enhanced \citep{voit92}.

. On the other hand, the highest rratios found above and below the starburst ring are larger than those typically found in shocks.

On the other hand, the highest ratios found above and below the starburst ring are larger than those typically found in shocks.

These higher ratios could actually be tracing an additional contribution to the [NellI] emission by a conically shaped narrow line region (NLR).

These higher ratios could actually be tracing an additional contribution to the [NeIII] emission by a conically shaped narrow line region (NLR).

Previously, no evidence was found for the existence of such a NLR, given the absence of emission in the central 800pcx800pc (?)..

Previously, no evidence was found for the existence of such a NLR, given the absence of emission in the central $\times$ 800pc \citep{moorwood96a}.

Instead the conical cavity traced by optical and near-infrared line and continuum tracers (??) was associated with a starburst super wind.

Instead the conical cavity traced by optical and near-infrared line and continuum tracers \citep{moorwood96a, marconi00} was associated with a starburst super wind.

However, given the high extinction implied by our observations, optical eemission can be easily attenuated; mid-infrared eemission less so.

However, given the high extinction implied by our observations, optical emission can be easily attenuated; mid-infrared emission less so.

A hypothetical conical NLR would be

Since in microlensing experiments the event durations are found by photometric fitüng and since the optical depth is proportional to the sum of the fit /zs. when making corrections [or blending it is important to properly relate the lens-light lraction of each event to the underlying event duration.

Since in microlensing experiments the event durations are found by photometric fitting and since the optical depth is proportional to the sum of the fit $\te$ 's, when making corrections for blending it is important to properly relate the lens-light fraction of each event to the underlying event duration.

and ((1997) (WP) studied the degeneracy of blend fits and concluded that in many cases blended and unblended lightcurves cannot be distinguished by photometric fitüng.

and (1997) (WP) studied the degeneracy of blend fits and concluded that in many cases blended and unblended lightcurves cannot be distinguished by photometric fitting.

They described areas of parameter space where blend fits would be useful and areas where they would not.

While we think that WP did an accurate and very useful caleulation, and we agree with their conclusion that blend fits are usually not very useful, we wanted to repeat their analysis for several reasons.

While we think that WP did an accurate and very useful calculation, and we agree with their conclusion that blend fits are usually not very useful, we wanted to repeat their analysis for several reasons.

First, WP did not include the baseline magnitude in their fits. reasoning that since many measurements are taken before and aller the event, the error in baseline magnitude was not significant.

First, WP did not include the baseline magnitude in their fits, reasoning that since many measurements are taken before and after the event, the error in baseline magnitude was not significant.

In fact, we find that error in the baseline magnitude is one of the most severe problems in blend fits.

We find that errors even at the few percent level can drasucally alter the parameter values extracted [rom the fit.

We find that errors even at the few percent level can drastically alter the parameter values extracted from the fit.

Second, WP considered only evenly spaced observations and we wanted to consider whether different [ollow-up strategies could improve the ability to extract the parameters.

Second, WP considered only evenly spaced observations and we wanted to consider whether different follow-up strategies could improve the ability to extract the parameters.

In our studies, we find the error in fit parameters three ways.

First we create artificial lightcurves using the theoretical formula and add Gaussian random noise to each measurement.

We perform blended and unblended fits on these lghtcurves using Minuit (CERN Lib.

We perform blended and unblended fits on these lightcurves using Minuit (CERN Lib.

2003).

Second we calculate the error matrix by inverting the Hessian matrix as discussed in Gould (2003).

Finally to understand the e[Iect of the non-Gaussianity of the errors in real microlensing experiments we create. artificial lensing lighteurves by adding microlensing signal into actual non-microlensing lightcurves obtained by the MACHO collaboration, and then fit these.

Finally to understand the effect of the non-Gaussianity of the errors in real microlensing experiments we create artificial lensing lightcurves by adding microlensing signal into actual non-microlensing lightcurves obtained by the MACHO collaboration, and then fit these.

Since the method of calculating the error matrix is closest to what WP did, we first give these results.

Briefly, we calculate the Hessian matrix (the matrix of second derivatives of the light curve residuals with respect to each parameter) then invert it.

The square root of the diagonal elements of the resulting matrix are then the one sigma errorbars of the parameters.

This accounts for correlations in the parameters, but not any nonlineariues.

This accounts for correlations in the parameters, but not any nonlinearities.

WP used a very similar method, but used it to calculate the ο of the error bars.

WP used a very similar method, but used it to calculate the $\Delta \chi^2$ instead of the error bars.

In figure 3. we show that our method brackets WP's.

In figure \ref{fig:wp} we show that our method brackets WP's.

We show limits calculated as both the one sigma lower limit on. { for an unblended hghtcurve and the value of fy that gives fj,ση= 1.

We show limits calculated as both the one sigma lower limit on $f_{ll}$ for an unblended lightcurve and the value of $f_{ll}$ that gives $f_{ll}+\sigma_{f_{ll}} = 1$

In the case of narrow line or edge features. in different combinations of spectral order. data reduction method aud binning size. we identify possible structure in residuals al 26.5. 21.6. 34.4. 32.4. and 35.9 (emission like features). and at 28.2. 39.1. and 86.5 (absorption like features). that might be tempting to attribute to the source.

In the case of narrow line or edge features, in different combinations of spectral order, data reduction method and binning size, we identify possible structure in residuals at 26.5, 27.6, 34.4, 32.4, and 35.9 (emission like features), and at 28.2, 39.1, and 86.5 (absorption like features), that might be tempting to attribute to the source.

ILowever. we cannot exclude the possibility that anv are chance fluctuations at the level.

However, we cannot exclude the possibility that any are chance fluctuations at the level.

The issue is complicated by possible calibration uncertainties on smaller scales. believed to be at a level of about oor less. that should be largely smoothed out by dither.

The issue is complicated by possible calibration uncertainties on smaller scales, believed to be at a level of about or less, that should be largely smoothed out by dither.

We have also used a 60ks observation (ObsID 331) of2155-304. currently thought to be a featureless continuum in the speclral range we are concerned wilh here (Marshall οἱ al..

We have also used a 60ks observation (ObsID 331) of, currently thought to be a featureless continuum in the spectral range we are concerned with here (Marshall et al.,

in preparation). as a flat field source lo aid in feature identification.

in preparation), as a flat field source to aid in feature identification.

This spectrum comprises about eight limes (he number of first order counts of the combined ddata.

This spectrum comprises about eight times the number of first order counts of the combined data.

Moreover. we have imposed a constraint that features must appear in both positive and negative orders in the sspectrum.

Moreover, we have imposed a constraint that features must appear in both positive and negative orders in the spectrum.

We examined deviations [rom the model on scales up to 3 aad find only the expected normal distribution of residuals after allowing [for smooth departures resulting [rom calibration.

We examined deviations from the model on scales up to 3 and find only the expected normal distribution of residuals after allowing for smooth departures resulting from calibration.

The Ixolmogorov-5Smürnov. test applied to deviations on different scales also revealed no evidence for significant features (hese scales.

The Kolmogorov-Smirnov test applied to deviations on different scales also revealed no evidence for significant features these scales.

In summary. all significant deviations in the residuals (hat have been found can reasonably be explained bv instrumental effects.

In summary, all significant deviations in the residuals that have been found can reasonably be explained by instrumental effects.

Equivalent width upper limits were derived by applying counting statistics to a convolution of the spectrum with a triangular kernel (Figure 2)).

Equivalent width upper limits were derived by applying counting statistics to a convolution of the spectrum with a triangular kernel (Figure \ref{f:ew}) ).

The distance of 62 pe derived by Walter (2001) seems at odds with the neutral HE column density. Vj). of LO?" ? derived [rom the Chandra spectra: measured Vy, values for objects al this distance based on different techniques are typically in the range 107-10?) 7 FFruscione οἱ 1994).

The distance of 62 pc derived by Walter (2001) seems at odds with the neutral H column density, $N_H$ , of $10^{20}$ $^{-2}$ derived from the Chandra spectra: measured $N_H$ values for objects at this distance based on different techniques are typically in the range $10^{18}$ $10^{19}$ $^{-2}$ Fruscione et 1994).

Walter (2001) indeed remarked on (his. citing reddening values Epv olf up to 0.1 derived by Ixnude Hog (1998) in support of the distance.

Walter (2001) indeed remarked on this, citing reddening values $E_{B-V}$ of up to 0.1 derived by Knude g (1998) in support of the distance.

However. these redclening values show considerable scatter at low reddening and are based only on a relalively coarse attribution of spectral twpe to the stars considered.

However, these reddening values show considerable scatter at low reddening and are based only on a relatively coarse attribution of spectral type to the stars considered.

We have estimated Ny, and the mean local neutral hvdrogen number density. 2,;. in the line-of-sight. toward aas a [unetion of distance by spatial interpolation in (he measurements compiled by Fruscione et ((1994) ancl Diplas Savage(1994) using a technique developed by P. Jelinsky

We have estimated $N_H$ and the mean local neutral hydrogen number density, $n_H$, in the line-of-sight toward as a function of distance by spatial interpolation in the measurements compiled by Fruscione et (1994) and Diplas Savage(1994) using a technique developed by P. Jelinsky

Ou the large scale (Figure 2)) we can see extremely faint. diffuse ciuission that exteuds for ~675 (20 kpc} in the east-west direction.

On the large scale (Figure \ref{fig:1549ls}) ) we can see extremely faint, diffuse emission that extends for $\sim6\farcs5$ (20 kpc) in the east-west direction.

The north-south exteusion. as noted bv Prestage&Peacock(1983).. cam be seen.

The north-south extension, as noted by \citet{pandp83}, can be seen.

This Figure shares simul features to the deep Very Large Telescope Comm rk image of IT06 (their Figure 1).

This Figure shares similar features to the deep Very Large Telescope Gunn $r$ image of H06 (their Figure 1).

The authors note that the north-south extended features appear to contain knots of enuüssiou.

The authors note that the north-south extended features appear to contain knots of emission.

Πας we cau see poiut-like sources im similar positious to these knots. which could be foreground stars but may also be super star clusters associated with the tidal tails of PISSIS19-το,

Here we can see point-like sources in similar positions to these knots, which could be foreground stars but may also be super star clusters associated with the tidal tails of PKS1549-79.

The radio15 source PISS 1315112 las also hac wach previous work carried out on it.

The radio source PKS 1345+12 has also had much previous work carried out on it.

Again. a brief outline of its main properties will be given before the new data are presented.

Again, a brief outline of its main properties will be given before the new data are presented.

Readers iuterested iu a more thorough review are directed toward ITALO3.

Readers interested in a more thorough review are directed toward HTM03.

PISS 1315)12 (1€ 12.50) is one of the closest GPS sources.

PKS 1345+12 (4C 12.50) is one of the closest GPS sources.

This allows the compact double jet and core structure. noted frou, VLBI (δα) and VLBA (Gein) radio observatious. to preseut proportions of ~0715.

This allows the compact double jet and core structure, noted from VLBI (2cm) and VLBA (6cm) radio observations, to present proportions of $\sim0\farcs15$.

The more pronünent S-shaped jet componcut extends to the south-cast before beudiug aud expanding into a diffuse lobe.

The more prominent S-shaped jet component extends to the south-east before bending and expanding into a diffuse lobe.

Protruding to the north-west of the core (the core being identified from the relative fatness of the radio spectimm) weak radio cussion is detected.

Protruding to the north-west of the core (the core being identified from the relative flatness of the radio spectrum) weak radio emission is detected.

On larger scales. diffuse radio cussion is detected exteudiue 35700 (NU kpe) to the north. aud 25700 (~55 kpc) to the south (Stanghellinietal.2005).

On larger scales, diffuse radio emission is detected extending 0 $\sim$ 80 kpc) to the north, and 0 $\sim$ 55 kpc) to the south \citep{stang05}.

. Optically. PISS 1315|12 shows a couples morphology characterized by two nuclei; the western most of which. identified as a 17.5(V) magnitude elliptical. possessing an extended curved tail.

Optically, PKS 1345+12 shows a complex morphology characterized by two nuclei, the western most of which, identified as a 17.5(V) magnitude elliptical, possessing an extended curved tail.

PreviousAST studies. which are unable to resolve structure down to the scale of the radio mmorphology. have shown the western nucleus to be associated with the radio source (Axonetal.2000).

Previous studies, which are unable to resolve structure down to the scale of the radio morphology, have shown the western nucleus to be associated with the radio source \citep{axon00}.

. From the ACS data presented here we find optical radio offsets (Table 2)) similar to those fouud by Axonetal. (2000).. which coufizius the western nucleus as the host of the radio source.

From the ACS data presented here we find optical – radio offsets (Table \ref{tab:astro}) ) similar to those found by \citet{axon00}, which confirms the western nucleus as the host of the radio source.

The double nuuceus and distorted appearance of PISS 1315|12 shows tha tagnereer event Is taking place.

The double nucleus and distorted appearance of PKS 1345+12 shows that a merger event is taking place.

As with the other source in this study; PISS 1315|12 shows a voung stellar populaion (Tadluuteretal. 2005).. a FIR excess (ULIRG) and near-UV cussion (Evansctal.1999.Labianoetal..inprep).. mdicatiug the presence of considerable star formation.

As with the other source in this study, PKS 1345+12 shows a young stellar population \citep{tad05}, a FIR excess (ULIRG) and near-UV emission \citep[][Labiano et al., in prep]{evans99}, indicating the presence of considerable star formation.

Using optical spectroscopy. ITTAL03 lave observed 3. distinct unclear kineniatical componcuts in PERS 1315|12. the narrowest of which (PWIIMz310kans1) is interpreted as the systemic velocity.

Using optical spectroscopy, HTM03 have observed 3 distinct nuclear kinematical components in PKS 1345+12, the narrowest of which $\approx340{\rm~km~s^{-1}}$ ) is interpreted as the systemic velocity.

The two other compoucuts. designated “intermediate” and “broad”. show FATAL of ~1250kins and ~L950kins| respectively. with corresponding bluc-shifts of ~lOOlas+ and L980last with respect to the rest frame.

The two other components, designated “intermediate” and “broad”, show FWHM of $\sim1250{\rm~km~s^{-1}}$ and $\sim1950{\rm~km~s^{-1}}$ respectively, with corresponding blue-shifts of $\sim400{\rm~km~s^{-1}}$ and $\sim1980{\rm~km~s^{-1}}$ with respect to the rest frame.

Due to the reddening observed in cach component. it is proposed that the broad component originates from the imnoer most reeions closest to the obscured quasar. whilst the narrow component represents a quiesceut halo.

Due to the reddening observed in each component, it is proposed that the broad component originates from the inner most regions closest to the obscured quasar, whilst the narrow component represents a quiescent halo.

Iu Figure 3. we preseut the new ACS data for PIS 1315|12.

In Figure \ref{fig:1345acs} we present the new ACS data for PKS 1345+12.

Iu both the Πα and [OTH] line aud coutiuuun nuages we find the two separate nuclei clearly visible within an extended diffuse euvelope.

In both the $\alpha$ and [OIII] line and continuum images we find the two separate nuclei clearly visible within an extended diffuse envelope.

The 270 (~5 kpc) separation of the two nuclei measured here is ~(71 ercater than the separation reported by Weckmanetal.(19056) aud Cülinore&Shaw(1986).

The $2\farcs0$ $\sim5$ kpc) separation of the two nuclei measured here is $\sim0\farcs1$ greater than the separation reported by \citet{heck86} and \citet{gands86}.

. The continuuni subtracted emission line dmages (Figures 2cc aud £f) show hat an insignificant amount of line cussion ομαλάτος roni the easteru component when compared to the western uucleus.

The continuum subtracted emission line images (Figures \ref{fig:1345acs}c c and f) show that an insignificant amount of line emission emanates from the eastern component when compared to the western nucleus.

To the northwest of this western micleus there is an extended cussion line filament (6.8.. Figures Saa. ο, d and f).

To the north-west of this western nucleus there is an extended emission line filament (e.g., Figures \ref{fig:1345acs}a a, c, d and f).

haniediately north-east of the nai nuclear structure there is a separate island of ΟΠΠ enission (see Figure 300) and a “mushroom Like norpholoey to the Ta coutiuuua (see Figure 3bb): this is clear evidence of a dust lane running approximatcly south-cast to uorth-west.

Immediately north-east of the main nuclear structure there is a separate island of [OIII] emission (see Figure \ref{fig:1345acs}e e) and a “mushroom” like morphology to the $\alpha$ continuum (see Figure \ref{fig:1345acs}b b); this is clear evidence of a dust lane running approximately south-east to north-west.

On the larger scale we can again compare this data to the findings of Heckmanotal.(1986).

On the larger scale we can again compare this data to the findings of \citet{heck86}.

. Figure 1. highlights the distorted morphology and lints at some of the south-west curved tail exteusions mentioned by TWeckmanetal.(1986).

Figure \ref{fig:1345ls} highlights the distorted morphology and hints at some of the south-west curved tail extensions mentioned by \citet{heck86}.

.. We also see that the halo of PISS 1315112 coutams similar point like sources (to the south of the eastern nucleus) to the foreground stars or possible star cluster seen around PISS 1519-79.

We also see that the halo of PKS 1345+12 contains similar point like sources (to the south of the eastern nucleus) to the foreground stars or possible star cluster seen around PKS 1549-79.

Further study has shown these sources to be super star cluster with voung stellar populations (RodriguezZaurinetal.2006).

Further study has shown these sources to be super star cluster with young stellar populations \citep{rod06}.

. Iu this section we closely examune the iuner structures of the observed nuclei aud determine the most likely position of the ACN in the ACS emission line images (and therefore the likely position of the radio cores).

In this section we closely examine the inner structures of the observed nuclei and determine the most likely position of the AGN in the ACS emission line images (and therefore the likely position of the radio cores).

Di-couical structures will sugecst that the outflows are wind driven. whereas structures similar to the radio morphologies will suggest that the outflows are driven by the radio jets.

Bi-conical structures will suggest that the outflows are wind driven, whereas structures similar to the radio morphologies will suggest that the outflows are driven by the radio jets.

However. first we cxamine the relative astromietrv in the ACS data in order to estimate the "uncertainties in derived positions.

However, first we examine the relative astrometry in the ACS data in order to estimate the uncertainties in derived positions.

There are two clemenuts that could contribute to differeuces hetween the spatial offsets of objects measured ou the WECT aud URC frames: the errors iu measuring the positious themselves. i.e. true positions as related to iieasured positions. aud he residual errors in the correction of the spatial distortiou by the pipeline reduction.

There are two elements that could contribute to differences between the spatial offsets of objects measured on the WFC1 and HRC frames: the errors in measuring the positions themselves, i.e., true positions as related to measured positions, and the residual errors in the correction of the spatial distortion by the pipeline reduction.

By quautifviug these errors we cau estimate the astrometric uncertainties present 1 ithe ACS images.

By quantifying these errors we can estimate the astrometric uncertainties present in the ACS images.

in probing these scales in order to understand them on their own terms. describing substructure and. the cuspiness of halos: cosmic flexion is also complementary to cosmic shear. probing small scales in an isolated. fashion. whereas cosmic shear has a broad window function for power.

in probing these scales in order to understand them on their own terms, describing substructure and the cuspiness of halos; cosmic flexion is also complementary to cosmic shear, probing small scales in an isolated fashion, whereas cosmic shear has a broad window function for power.

The cosmic Hexion signal will be a useful means of testing theories of stable clustering or stable merging (ef.

The cosmic flexion signal will be a useful means of testing theories of stable clustering or stable merging (c.f.

Smith et al 2003).

lt should be noted that in this analysis we have neglected the power that might exist from intrinsic. physical llexion correlations between galaxies.

It should be noted that in this analysis we have neglected the power that might exist from intrinsic, physical flexion correlations between galaxies.

The analogous intrinsic cllipticity correlation between galaxies has been shown (e.g. Llevmans et al 2004) to be small: however. further work will be necessary to measure the level of contamination of cosmic Llexion due to intrinsic. [lexion alignments.

The analogous intrinsic ellipticity correlation between galaxies has been shown (e.g. Heymans et al 2004) to be small; however, further work will be necessary to measure the level of contamination of cosmic flexion due to intrinsic flexion alignments.

In addition to the Hexion power spectrum. we are also able to calculate the convergence-Hexion. cross power spectrum. which can easily be related to the shear-Dexion cross power spectrum.

In addition to the flexion power spectrum, we are also able to calculate the convergence-flexion cross power spectrum, which can easily be related to the shear-flexion cross power spectrum.

We note that to do this we can again use Limber's equation (79)). but this time using £5 from the outset rather than 2s).

We note that to do this we can again use Limber's equation \ref{eq:limber}) ), but this time using $P_\delta$ from the outset rather than $P_{\delta'}$.

In this case. from our final power spectrum: for Uexion (equation 84)) we see that the relevant choice of q for llexion in Limber’s equation is 1n αστοι. [rom equationi (74)). we see that the choice of q suitable for convergence is llence the cross-power spectrum between convergence and Hexion can be written as ‘This is shown in Figure Ll. together with the associated convergence-I[exion. cross-correlation function in Figure 12 with appropriate errors for a 100. square degree survey.

In this case, from our final power spectrum for flexion (equation \ref{eqn:pf}) ) we see that the relevant choice of $q$ for flexion in Limber's equation is In addition, from equation \ref{eqn:kappa}) ), we see that the choice of $q$ suitable for convergence is Hence the cross-power spectrum between convergence and flexion can be written as This is shown in Figure 11, together with the associated convergence-flexion cross-correlation function in Figure 12 with appropriate errors for a 100 square degree survey.

We see that this quantity has a measurement limit on an intermediate scale to shear and flexion limits ( 2’).

We see that this quantity has a measurement limit on an intermediate scale to shear and flexion limits $\simeq 2'$ ).

Ht is a valuable quantity to measure. as it gives a stronger signal-to-noise than cosmic flexion. anc olfers a stringent check on svstematic errors between the shear or convergence and llexion signals.

It is a valuable quantity to measure, as it gives a stronger signal-to-noise than cosmic flexion, and offers a stringent check on systematic errors between the shear or convergence and flexion signals.

In this paper. we have cxamined how Uexion can be applied

In this paper, we have examined how flexion can be applied

how systems with negative heat capacity evolve (Lyudeu-Bell1999).

how systems with negative heat capacity evolve \citep{l99}.

. However the theory does uot describe accurately real clusters. at least those of modest population on which we lave focused.

However the theory does not describe accurately real clusters, at least those of modest population on which we have focused.

The two main [actors ehanging the pleture are binary beating aud stellar evolution.

The two main factors changing the picture are binary heating and stellar evolution.

Both processes are. of course. well understood. but their combined effect lias uot been appreciatect.

Both processes are, of course, well understood, but their combined effect has not been appreciated.

All clusters are born with a largeDm fraction of binaries. but these do not provide the largestDm effect.

All clusters are born with a large fraction of binaries, but these do not provide the largest effect.

It is the systems most massive stars coupling together that generate most of the heating through three-body interactions.

It is the system's most massive stars coupling together that generate most of the heating through three-body interactions.

This heating easily reverses inciplent core contraction. so that the central cleusity climbs only. slightly before the uew phase of global expansion begius.

This heating easily reverses incipient core contraction, so that the central density climbs only slightly before the new phase of global expansion begins.

This phase resembles. at least qualitatively. the post-collapse evolution described by Hénou(1972).

This phase resembles, at least qualitatively, the post-collapse evolution described by \citet{h72}.

. However. the reversal [rom coutraction occurs at wach lower density thai iu earlier accounts.

However, the reversal from contraction occurs at much lower density than in earlier accounts.