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the Strómmegren e filter.
the Strömmgren $v$ filter.
In this filter. the aniitudes o£ 67 "Tau are higher by about reative those in the y filter.
In this filter, the amplitudes of $\theta^2$ Tau are higher by about relative those in the $y$ filter.
In power spectra. the location o “the peaks in frequency. are not alfected by mixing data wihc illerent anjitudes.
In power spectra, the location of the peaks in frequency are not affected by mixing data with different amplitudes.
Consequently. for the power spectra we have used the data from all filters.
Consequently, for the power spectra we have used the data from all filters.
The slight phase shift up to 10 in the light curves of & Scuti stars between the ciferent fillers was ignored.o since numerical simulations show that [or 0 Scuti stars the power spectra are not allected »v such small shifts.
The slight phase shift up to $\degr$ in the light curves of $\delta$ Scuti stars between the different filters was ignored, since numerical simulations show that for $\delta$ Scuti stars the power spectra are not affected by such small shifts.
Llowever. for prewhitening. the data from the two filters had to be treated separately.
However, for prewhitening, the data from the two filters had to be treated separately.
The multiperiodic fitting of sinusoids to the data relies on the minimization. of the residuals between the fit and the observations ancl requires correct amplitudes.
The multiperiodic fitting of sinusoids to the data relies on the minimization of the residuals between the fit and the observations and requires correct amplitudes.
This problemi was solved by computing separate solutions for the two colors. which could then be prewhitened.
This problem was solved by computing separate solutions for the two colors, which could then be prewhitened.
One of the most important questions in the examination of multiperiodicity. concerns the decision as to which of the detected. peaks in the power spectrum can be regarded as variability intrinsic to the star.
One of the most important questions in the examination of multiperiodicity concerns the decision as to which of the detected peaks in the power spectrum can be regarded as variability intrinsic to the star.
Due to the presence of nonrandom errors in photometric observations and. because of observing gaps. the predictions of standard: statistical false-alarm tests give answers which are considered by us to be overly optimistic.
Due to the presence of nonrandom errors in photometric observations and because of observing gaps, the predictions of standard statistical false-alarm tests give answers which are considered by us to be overly optimistic.
In a previous paper (Dreger οἱ al.
In a previous paper (Breger et al.
1993) we have argued that a ratio of amplitude signal/noise = 4.0 provides a useful criterion for judging the reality of a peak.
1993) we have argued that a ratio of amplitude signal/noise = 4.0 provides a useful criterion for judging the reality of a peak.
This corresponds to a power signal/noise ratio of
This corresponds to a power signal/noise ratio of
llorowitz (1997).
Horowitz (1997).
Therefore. (he ion-ion correlation elfect on the neutrino-nucleus scattering in supernova cores will be more important than has hitherto been recognized.
Therefore, the ion-ion correlation effect on the neutrino-nucleus scattering in supernova cores will be more important than has hitherto been recognized.
However. the consequence of the modification in (he ion-ion correlation elfect may not be so great as {ο drastically change the whole scenario of the supernova explosion. since the phase space for these low energy neutrinos is relatively small.
However, the consequence of the modification in the ion-ion correlation effect may not be so great as to drastically change the whole scenario of the supernova explosion, since the phase space for these low energy neutrinos is relatively small.
In (his section we present an accurate analvGec lilting formula for «5>(D.e) in orcer to facilitate the application of the numerical results obtained in the present paper.
In this section we present an accurate analytic fitting formula for $<S>(\Gamma,\epsilon)$ in order to facilitate the application of the numerical results obtained in the present paper.
We have carried out the numerical calculations of <5>(I.e) for 1<P€160. 0.01ce€10.0.
We have carried out the numerical calculations of $<S>(\Gamma,\epsilon)$ for $1 \leq \Gamma \leq 160$, $0.01 \leq \epsilon \leq 10.0$.
We express (he analvtic fitting formula for this range bv The ratio of the present fitting fornia value to our numerical result κοpj,/<5> is shown in Figure 4.
We express the analytic fitting formula for this range by The ratio of the present fitting formula value to our numerical result $<S>_{fit}/<S>$ is shown in Figure 4.
It is readily seen that the accuracy of the fitting is better than for all (he parameter range considered.
It is readily seen that the accuracy of the fitting is better than for all the parameter range considered.
We have caleulated the ion-ion correlation effect on the neutrimo-nucleus scattering in supernova cores bv using (he liquid structure factor of the classical one-component plasma obtained bv the improved hyvpernetted-chain scheme.
We have calculated the ion-ion correlation effect on the neutrino-nucleus scattering in supernova cores by using the liquid structure factor of the classical one-component plasma obtained by the improved hypernetted-chain scheme.
We have found. a cdiaamatic reduction
We have found a dramatic reduction
the Jeans scale at the time of observation.
the Jeans scale at the time of observation.
Modeling the filtering as a Gaussian and assuming 2«10 K gas (222222) gives v=0.13/7! Mpe at z2 and o20.1247! Mpe at ==3.
Modeling the filtering as a Gaussian and assuming $2\times 10^4\,$ K gas \citep{RicGneShu00,Sch00,McD01,ZalHuiTeg01,The02,Lid09} gives $\sigma=0.14\,h^{-1}$ Mpc at $z=2$ and $\sigma=0.12\,h^{-1}$ Mpc at $z=3$.
Given the uncertainties. and the approximate treatment of this physics. we shall assume o=100/77! kpe in what follows.
Given the uncertainties, and the approximate treatment of this physics, we shall assume $\sigma=100\,h^{-1}$ kpc in what follows.
For numerical reasons we used a spline kernel (?) rather than a Gaussian.
For numerical reasons we used a spline kernel \citep{Deh01} rather than a Gaussian.
The spline kernel approximates a Gaussian well in the core. but vanishes identically beyond a range. R.
The spline kernel approximates a Gaussian well in the core, but vanishes identically beyond a range, $R$.
A good match is found when R=3.250. so we adopt R20.3254! Mpe (o~100/7'kpe) which is larger than our mesh scale and mean inter-particle spacing.
A good match is found when $R=3.25\,\sigma$, so we adopt $R=0.325\,h^{-1}$ Mpc $\sigma\simeq 100\,h^{-1}$ kpc) which is larger than our mesh scale and mean inter-particle spacing.
We have checked that increasing the resolution does not appreciably change the spectra when the density field is smoothed on these scales. indicating that we are numerically converged.
We have checked that increasing the resolution does not appreciably change the spectra when the density field is smoothed on these scales, indicating that we are numerically converged.
For each of 22.500 randomly placed lines-of-sight per box the fluctuating Gunn-Peterson approximation (FGPA: ???)) was used to generate skewers of optical depth with 4.000 pixels each.
For each of $22,500$ randomly placed lines-of-sight per box the fluctuating Gunn-Peterson approximation (FGPA; \citealt{CWKH98,GneHui98,Mei09}) ) was used to generate skewers of optical depth with $4,000$ pixels each.
We assumed a temperature at mean density of 2.10 K (22) and equations of state running from ~=0.5 to 5=1.5.
We assumed a temperature at mean density of $2\times 10^4$ K \citep{McD01,The02} and equations of state running from $\gamma=0.5$ to $\gamma=1.5$.
Different choices for the slope. even the inverted equation of state (< 1). quantitatively but not qualitatively change our conclusions.
Different choices for the slope, even the inverted equation of state $\gamma<1$ ), quantitatively but not qualitatively change our conclusions.
The optical depth included thermal broadening (assumed Gaussian) and skewers are generated both with and without peculiar velocities for the σας.
The optical depth included thermal broadening (assumed Gaussian) and skewers are generated both with and without peculiar velocities for the gas.
The optical depth was scaled so that the mean transmitted flux F=(exp(-—7)) approximately matched that of the data compiled in ?:: valid for 1.2«z4.
The optical depth was scaled so that the mean transmitted flux $\bar{F}=\left\langle\exp(-\tau)\right\rangle$ approximately matched that of the data compiled in \citet{MeiWhi04}: valid for $1.2<z<4$.
We impose this mean flux condition over the entire volume.
We impose this mean flux condition over the entire volume.
As described later. we also generate skewers in which F changes across the volume to understand the effect of incomplete modeling of the mean flux evolution.
As described later, we also generate skewers in which $\bar{F}$ changes across the volume to understand the effect of incomplete modeling of the mean flux evolution.
Another way to set F 1s via the amplitude of the flux power spectrum.
Another way to set $\bar{F}$ is via the amplitude of the flux power spectrum.
Conveniently. these two methods agreed quite well.
Conveniently, these two methods agreed quite well.
For completeness. we also generate the skewers with dark-matter over-density only. so we can compare the flux statistics to those of the underlying mass.
For completeness, we also generate the skewers with dark-matter over-density only, so we can compare the flux statistics to those of the underlying mass.
We work throughout with relative fluctuations in the flux. op=ΕΕ—l1. so our fundamental data set is ÓOpCQU on 22.500 skewers of 4.000 pixels each per box.
We work throughout with relative fluctuations in the flux, $\delta_F = F(\hat{x})/\bar{F} -1$, so our fundamental data set is $\delta_F(\vec{x})$ on $22,500$ skewers of $4,000$ pixels each per box.
Our 9 simulations have V~3.8Ur!Gpey and cover approximately 1.000 sq.deg..
Our 9 simulations have $V\simeq 3.8\,(h^{-1}{\rm Gpc})^3$ and cover approximately $1,000$ sq.deg.,
or of the coverage planned for BOSS.
or of the coverage planned for BOSS.
On the other hand the line-of-sight areal density (~200 per sq.deg.
On the other hand the line-of-sight areal density $\sim 200$ per sq.deg.
at z2 2.5) is much larger than anticipated from BOSS.
at $z=2.5$ ) is much larger than anticipated from BOSS.
This allows us to study the impact of quasar number density on forest studies for future missions.
This allows us to study the impact of quasar number density on forest studies for future missions.
Of course any observational program will likely analyze the data in small shells of over which the evolution of e.g. the mean flux. is small.
Of course any observational program will likely analyze the data in small shells of over which the evolution of e.g. the mean flux, is small.
A surveysuch as BOSS should also be able to detect the evolution in H(z) across the redshift range 2«z«3 by the shift in the acoustic feature in velocity space.
A surveysuch as BOSS should also be able to detect the evolution in $H(z)$ across the redshift range $2<z<3$ by the shift in the acoustic feature in velocity space.
At the fiducial redshift of our box. z—2.5. the Ly-a feature is redshifted to approximately 4.000À.. and the box has a velocity "length" of 73.000 knys. Each of our mock spectra thus encompasses the full Ly- to Ly-./ region for QSOs atz-2.5 (Table 1)).
At the fiducial redshift of our box, $z\sim 2.5$, the $\alpha$ feature is redshifted to approximately $4,000\,$, and the box has a velocity “length” of $73,000\,$ km/s. Each of our mock spectra thus encompasses the full $\alpha$ to $\beta$ region for QSOs at $z\sim 2.5$ (Table \ref{tab:conversion}) ).
For z2-3 a comoving /r! Mpe is approximately equal to ((Table 1)) so with 4.000. pixels per spectrum. each simulation pixel is 0.277! Mpe wide.
For $z\simeq 2-3$ a comoving $h^{-1}$ Mpc is approximately equal to (Table \ref{tab:conversion}) ), so with $4,000$ pixels per spectrum, each simulation pixel is $0.2\,h^{-1}$ Mpc wide.
For comparison each SDSS-III pixel is about 75 kni/s (or just under 1/7! Mpc). so our spectra are comparably well resolved.
For comparison each SDSS-III pixel is about $75\,$ km/s (or just under $1\,h^{-1}$ Mpc), so our spectra are comparably well resolved.
We normalize the optical depths so that the mean transmitted flux matches observations.
We normalize the optical depths so that the mean transmitted flux matches observations.
ΑΠ. additional constraint then comes from comparing the flux variance of the simulations and observations.
An additional constraint then comes from comparing the flux variance of the simulations and observations.
For ~=0.5—1.5 we find o;=0.1. which is very comparable to the measurements reported in ?..
For $\gamma=0.5-1.5$ we find $\sigma_F^2=0.1$, which is very comparable to the measurements reported in \citet{McD00}.
Figure 2 shows the flux PDF in the simulations compared to that measured from high resolution spectra at <x2.4 in ?.
Figure \ref{fig:Fpdf} shows the flux PDF in the simulations compared to that measured from high resolution spectra at $z\simeq 2.4$ in \citet{Kim07}.
We see that the distribution of high and low absorption regions is approximately correct. indicating that the spectra could be useful for testing analysis pipelines and investigating the impact of systematic errors.
We see that the distribution of high and low absorption regions is approximately correct, indicating that the spectra could be useful for testing analysis pipelines and investigating the impact of systematic errors.
While the discrepancies are larger than the quoted observational error bars. we note that our modeling could be improved and the flux PDF is notoriously difficult to measure observationally (especially in regions of low absorption).
While the discrepancies are larger than the quoted observational error bars, we note that our modeling could be improved and the flux PDF is notoriously difficult to measure observationally (especially in regions of low absorption).
We have not attempted a more detailed comparison since the level of agreement will be sufficient for our purposes.
We have not attempted a more detailed comparison since the level of agreement will be sufficient for our purposes.
The line-of-sight power spectrum of the flux at z~2.4. compared to the measurements of ?.. ? and ?.. is shown in Figure 3..
The line-of-sight power spectrum of the flux at $z\simeq 2.4$, compared to the measurements of \citet{Croft02}, \citet{Kim04} and \citet{McD06}, is shown in Figure \ref{fig:SmallPk}.
There is some tension between the flux PDF and the power spectrum in the preferred value of F: the flux PDF ts better fit if we slightly raise F. increasing the number of lines of sight with little or no absorption and decreasing the number with little or no transmission.
There is some tension between the flux PDF and the power spectrum in the preferred value of $\bar{F}$: the flux PDF is better fit if we slightly raise $\bar{F}$, increasing the number of lines of sight with little or no absorption and decreasing the number with little or no transmission.
The flux power spectrum is better fit if we lower F. raising the amplitude of P(A).
The flux power spectrum is better fit if we lower $\bar{F}$, raising the amplitude of $P_F(k)$.
For F~0.8 the overall the level of agreement is good in both statistics. indicating that the relative amounts of power on different scales are approximately as observed in the real Universe.
For $\bar{F}\simeq 0.8$ the overall the level of agreement is good in both statistics, indicating that the relative amounts of power on different scales are approximately as observed in the real Universe.
We have chosen to match to the later. SDSS-based measurements of ?— rather than the slightly higher results of ??..
We have chosen to match to the later, SDSS-based measurements of \citet{McD06} rather than the slightly higher results of \citet{Croft02,Kim04}.
Our spectra thus contain approximately the right distribution of fluxes and approximately the right amount of small-scale structure. which acts as a source of "noise" in the measurement of the acoustic scale.
Our spectra thus contain approximately the right distribution of fluxes and approximately the right amount of small-scale structure, which acts as a source of “noise” in the measurement of the acoustic scale.
In what follows we will work with 6). ignoring real- issues such às continuum fitting or subtraction. damped systems and metal lines.
In what follows we will work with $\delta_F$ , ignoring real-world issues such as continuum fitting or subtraction, damped systems and metal lines.
We expect the damping wings and metal lines to be uncorrelated with the signal of interest. and so not produce a feature at the acoustic scale.
We expect the damping wings and metal lines to be uncorrelated with the signal of interest, and so not produce a feature at the acoustic scale.
? reports the discovery of an ultraviolet companion to the ULL giant 4 Draconis.
\scite{Reimers85} reports the discovery of an ultraviolet companion to the III giant 4 Draconis.
International Ultraviolet Explorer (IUIS) observations show its spectrum is similar to that of high-accretion-rate cataclysmic variables. with a slowly decreasing continuum in the range which then rises steeply to shorter wavelengths.
International Ultraviolet Explorer (IUE) observations show its spectrum is similar to that of high-accretion-rate cataclysmic variables, with a slowly decreasing continuum in the range which then rises steeply to shorter wavelengths.
There are strong and broad. high-excitation. emission lines (also tvpical of cataclysmic variables) ancl some narrow Iow-excitation emission lines which Reimers attributes to the ionisecl wind of the giant.
There are strong and broad high-excitation emission lines (also typical of cataclysmic variables) and some narrow low-excitation emission lines which Reimers attributes to the ionised wind of the giant.
Alore detailed. ultraviolet ancl optical-racial-velocity measurementsare presented. by 2..
More detailed ultraviolet and optical-radial-velocity measurementsare presented by \scite{Reimers88}.
They. determined. the orbit of the giant. and claimed that the ultraviolet. Lux is modulated at a period of 4hh. Based largely on this period. rey conclude that the ultraviolet companion is most likely an AM Ller-type cataclysmic variable.
They determined the orbit of the giant and claimed that the ultraviolet flux is modulated at a period of h. Based largely on this period, they conclude that the ultraviolet companion is most likely an AM Her-type cataclysmic variable.
7 point out that the orbit of the wide pair in 4 Draconis μμξ τὸο) severely. limits the size of the progenitor of a cataclysmic variable ancl places unique constraints on its evolution.
\scite{Eggleton89} point out that the orbit of the wide pair in 4 Draconis $\rm P_{orb}$ d) severely limits the size of the progenitor of a cataclysmic variable and places unique constraints on its evolution.
Without constraints on even the inclinations of the two binary orbits they argue that any. cataclysmic variable must. have evolved. from a progenitor with initial Dos z100dd. However Eeeleton ct also point out that the identification as an AAL Her systeni is uncertain. and that an isolated white dwarf may explain the observations equally well.
Without constraints on even the inclinations of the two binary orbits they argue that any cataclysmic variable must have evolved from a progenitor with initial $\rm P_{\sc orb}\leq$ d. However Eggleton et also point out that the identification as an AM Her system is uncertain, and that an isolated white dwarf may explain the observations equally well.
In. this picture the white να would he accreting from the wind of the giant and the four hour period would be its spin period.
In this picture the white dwarf would be accreting from the wind of the giant and the four hour period would be its spin period.
"This requires a magnetic field on the white cwarf sullicient to funnel the accretion Low onto its poles.
This requires a magnetic field on the white dwarf sufficient to funnel the accretion flow onto its poles.
In this paper we present the first X-ray observations of 4 Draconis. and discuss the nature of the svstem.
In this paper we present the first X-ray observations of 4 Draconis, and discuss the nature of the system.
4 Draconis was observed four times with ROSAT (?): once during the ROSAT all-skv. survey (RASS) with the position sensitive. proportional counter (PSPC. 2)): twice during the pointed. phase of the mission with the PSPC. once as the target and once serendipitously: and once with the high-resolution imager (LIU. 23).
4 Draconis was observed four times with ROSAT \cite{Trumper83}: once during the ROSAT all-sky survey (RASS) with the position sensitive proportional counter (PSPC, \ncite{Pfeffermann87}) ); twice during the pointed phase of the mission with the PSPC, once as the target and once serendipitously; and once with the high-resolution imager (HRI, \ncite{Zombeck95}) ).
A log of the pointed observations is presented in reftab-log..
A log of the pointed observations is presented in \\ref{tab-log}. .
4 Draconis was detected in all four observations
4 Draconis was detected in all four observations
and the direction of motion with respect to the observer).
and the direction of motion with respect to the observer).
If indeed the Doppler factor is the dominant parameter among GRBs. a relation between spectra lagsvariability axd luminosity Is expected.
If indeed the Doppler factor is the dominant parameter among GRBs, a relation between spectral lags/variability and luminosity is expected.
Crucial to our understanding of what causes the GRD is the question of whether CRB cugines are ln sonie sense “standard candles”.
Crucial to our understanding of what causes the GRB is the question of whether GRB engines are in some sense “standard candles”.
Oservationally it is found that the isotropic equivalent euergies of CRBs rause Yolu about 5 « 1075 to l.l « yi cres (Bloomctal.2001).
Observationally it is found that the isotropic equivalent energies of GRBs range from about 5 $\times$ $^{51}$ to 1.4 $\times$ $^{54}$ ergs \citep{bfs01}.
. Tlowever. transitious have οσοι observed at optical aud radio wavelengths whichcan be interpreted being due to collimated (jetted) outflow (Uarrisouetal. 1999).
However, transitions have been observed at optical and radio wavelengths which can be interpreted as being due to collimated (jetted) outflow \citep{hbf+99}.
. When correcting the observed energies for he gecomoetrv of the outflow. GRB enereles appear iurowly clustered around 5xLae? eres (Frail et al.
When correcting the observed $\gamma$ -ray energies for the geometry of the outflow, GRB energies appear narrowly clustered around $5 \times 10^{50}$ ergs (Frail et al.
2001: see also Panaiteseu and Iun 2001..
2001; see also Panaitescu and Kumar \nocite{fksd01,pk01}.
Frailetal.(2001) inter the jet opening angle from the observed jet-break time id find that there is a wide range iu opening ieles.
\citet{fksd01} infer the jet opening angle from the observed jet-break time and find that there is a wide range in opening angles.
The reason for why this range in angles exists is currently not understood.
The reason for why this range in angles exists is currently not understood.
The idea that CRD cuereics nay. be narrowly clustered was also put forward by Saluouson(2000. 2001).
The idea that GRB energies may be narrowly clustered was also put forward by \citet{jay00,jay01}.
. However. Saliuouson(2001) proposed that there exists not a range iu oponiug angles. but that all bursts derive frou a single-burst-jet morphology aud that the variation iu viewing angle of the jet vields the observed variation amone GRBs.
However, \citet{jay01} proposed that there exists not a range in opening angles, but that all bursts derive from a single-burst-jet morphology and that the variation in viewing angle of the jet yields the observed variation among GRBs.
Iu this oper is presented a tight correlation between je-break tues. rj. aud pulse lags.
In this paper is presented a tight correlation between jet-break times, $\tau_j$, and pulse lags, $\Delta t$.
Since huninosity aud pulse lags have Όσοι shown to be correlated. this also represeuts a relation between huninosity and jet-break times.
Since luminosity and pulse lags have been shown to be correlated, this also represents a relation between luminosity and jet-break times.
As time scales and peak hnuuiuositv are strong functions of the Doppler factor of he outflow. this relation sugeests the jet-break time to also be a stroug function. of the Doppler factor.
As time scales and peak luminosity are strong functions of the Doppler factor of the outflow, this relation suggests the jet-break time to also be a strong function of the Doppler factor.
We discuss the iuplications of this result on oir understanding of the morphology of the explosion.
We discuss the implications of this result on our understanding of the morphology of the explosion.
The relativistic blast-wave model has become the "standard model for the interpretation of CRBs aud their afterglows (sce Piran for a review).
The relativistic blast-wave model has become the `standard' model for the interpretation of GRBs and their afterglows (see Piran \nocite{pira00} for a review).
It invokes the release of a large amount of cnereyv. resulting iu au ultra-rvelativistic outflow.
It invokes the release of a large amount of energy, resulting in an ultra-relativistic outflow.
Tn this model the GRB is produced iu internal shocks.
In this model the GRB is produced in internal shocks.
During or after the GRB cnussion phase a strong shock is formed when these (anergec) shells run iuto the surrounding medium.
During or after the GRB emission phase a strong shock is formed when these (merged) shells run into the surrounding medium.
As the (forward) shock is weighed cowji by increasing amounts of swept-up material it produces a slowly facing ‘afterglow at radio to X-ray waveleneths.
As the (forward) shock is weighed down by increasing amounts of swept-up material it produces a slowly fading `afterglow' at radio to X-ray wavelengths.
Observations of the GRD aud tje afterglow at eanunia- and X-ray wavelengths (Cablinetal.1999) sugecst that indeed in SOL cases the afterelow commences during or srortly after the CRB.
Observations of the GRB and the afterglow at gamma- and X-ray wavelengths \citep{gvk+99} suggest that indeed in some cases the afterglow commences during or shortly after the GRB.
It the GRB is due to internal shocks aud the afterglow is due to the external forward shock then little connection between the twx| phenomena is to be expeced.
If the GRB is due to internal shocks and the afterglow is due to the external forward shock then little connection between the two phenomena is to be expected.