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

Au example of a (sin/),, distribution that includes the effects of observational uucertainties is shown in Fig. 6..

An example of a $(\sin i)_{m}$ distribution that includes the effects of observational uncertainties is shown in Fig. \ref{modeledsini}.

Iu order to incorporate the effects of the esin; cutoff adopted iu 512 iuto our model it is unecessary to assunie sole prescription— for the distribution of the true equatorial velocities. c4.

In order to incorporate the effects of the $v \sin i$ cutoff adopted in $\S$ \ref{sampleselection} into our model it is necessary to assume some prescription for the distribution of the true equatorial velocities, $v_{true}$.

Once such a prescription has been assumed. modeled esiu; values can be calculated. allowing the model sample to be restricted in the same manner as the observational sample.

Once such a prescription has been assumed, modeled $v \sin i$ values can be calculated, allowing the model sample to be restricted in the same manner as the observational sample.

Wo tested ai variety of C42 distributions hy colubining randomly sampled ¢ values with random axial orientatious and comparing the resultant set of modeled ομαι values with the observed esin; values.

We tested a variety of $v_{true}$ distributions by combining randomly sampled $v$ values with random axial orientations and comparing the resultant set of modeled $v \sin i$ values with the observed $v \sin i$ values.

The mput ey. distribution was adjusted until the saluplecd population produced a satistactory match witli the observed cesiní values. as dudicated by a two-sided) EKohuogorov-Siuirnov (INS) test.

The input $v_{true}$ distribution was adjusted until the sampled population produced a satisfactory match with the observed $v \sin i$ values, as indicated by a two-sided Kolmogorov-Smirnov (KS) test.

We find that modeling the c44, distribution as an exponentially decaving function with a constaut offset (PCCie}xCoUemC loads to a good match with the observed esin/ distribution.

We find that modeling the $v_{true}$ distribution as an exponentially decaying function with a constant offset $P(v_{true}) \propto e^{-\alpha \cdotp v_{true}} + C$ ) leads to a good match with the observed $v \sin i$ distribution.

Our best matching 0i, model has a=0.09 and C=0.001.

Our best matching $v_{true}$ model has $\alpha = 0.09$ and $C = 0.004$.

A IS test comparing the resultant modeled esin distribution with the observed distribution vields. ou average. a probability of ~95% that our moceled ¢sin/ distribution comes from the same uuderlving distribution as the observed esiun/s. A flat distribution of ci. ou the other haud. can be rejected with a probability greater than 99.9994.

A KS test comparing the resultant modeled $v \sin i$ distribution with the observed distribution yields, on average, a probability of $\sim 95 \%$ that our modeled $v \sin i$ distribution comes from the same underlying distribution as the observed $v \sin i$ 's. A flat distribution of $v_{true}$, on the other hand, can be rejected with a probability greater than $99.999 \%$.

See Fig.

7. for a coniparison of the assumed ρω distributious.

\ref{vtrue_distribs} for a comparison of the assumed $v_{true}$ distributions.

This result is in agreement with that found by Jeffries(2007).

This result is in agreement with that found by \citet{Jeffries}.

. Some uukuown fraction. B. of the stars ποιά iu our catalog are unresolved binary systenis.

Some unknown fraction, $B$, of the stars included in our catalog are unresolved binary systems.

For such σοςsystems. the value of L that we calculate will characterize the total svstemi huuinositv. not the huuinositv of a single star.

For such systems, the value of $L$ that we calculate will characterize the total system luminosity, not the luminosity of a single star.

That is. wuresolved biuaries result iu overestimates of the huninosity of the primary star.

That is, unresolved binaries result in overestimates of the luminosity of the primary star.

Since the value of siui depends inversely on VL. the preseuce of unresolved binaries da our observational suuple will cause sin; to be systematically underestimated. or conversely. for the value of (sin/),, to be systematically overestimated.

Since the value of $\sin i$ depends inversely on $\sqrt{ L }$ , the presence of unresolved binaries in our observational sample will cause $\sin i$ to be systematically underestimated, or conversely, for the value of $(\sin i)_{m}$ to be systematically overestimated.

To correct (sin/),, to account for uuresolved binaries. we asstune that the masses aud Inninosities of both the

To correct $(\sin i)_{m}$ to account for unresolved binaries, we assume that the masses and luminosities of both the

results suggest that the teclinology for astrometric detection of nearby Earths is at laud.

results suggest that the technology for astrometric detection of nearby Earths is at hand.

The research described in this paper was carried out at the Jet Propulsion Laboratory. California Tustitute of Technology. uuder a contract with the National Aeronautics and Space Aciiuistration.

The research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

Goverment sponsorship acknowledged.

Government sponsorship acknowledged.

at z=0, where baryons = stars + HI gas.

at $z=0$, where baryons = stars + HI gas.

The baryons distribution is normalised to have a peak at the same hight as the bulge gas.

The median (mean) values for the BG, stars formed from BG, and z=0 baryons are 35.7 (43.9), 92 (205) and 164 (305) kms~! kpc respectively.

The median (mean) values for the BG, stars formed from BG, and $z=0$ baryons are 35.7 (43.9), 92 (205) and 164 (305) $^{-1}$ kpc respectively.

The shape of the distribution of stars formed from BG (blue line) closely resembles the z—0 baryon distribution, while the BG (red line) has universally low angular momentum.

The shape of the distribution of stars formed from BG (blue line) closely resembles the $z=0$ baryon distribution, while the BG (red line) has universally low angular momentum.

The angular momentum of the bulge gas has been dramaticallyredistributed during the process of being blown out of the central region and cooling back to the disc via the galactic fountain.

The angular momentum of the bulge gas has been dramatically during the process of being blown out of the central region and cooling back to the disc via the galactic fountain.

Rather than form bulge stars, the re-accreted gas now primarily forms disc stars.

In Fig. 10,

In Fig. \ref{trendstime},

we trace the history of the of the bulge gas which forms stars, and refer to this as "star forming bulge gas" (BGs).

we trace the history of the of the bulge gas which forms stars, and refer to this as “star forming bulge gas" (BGs).

Redshifts are shown on the upper x-axis.

In the top panel, the log of the Maximum Temperature that BGs reaches subsequent to the time that it was identified (ie. after they were measured as being in the inner 2 kpc with T «30,000K) is plotted against the age of the stars which form from BGs.

In the top panel, the log of the Maximum Temperature that BGs reaches subsequent to the time that it was identified (i.e. after they were measured as being in the inner 2 kpc with T $<30,000$ K) is plotted against the age of the stars which form from BGs.

In the middle panel, the maximum distance that BGs reaches from the centre of the galaxy subsequent to the time that they were identified, is plotted against the age of BGs stars.

In the bottom panel, the mean angular momentum of BGs stars is plotted against their age.

of the BG forms stars in the bulge region shortly after the time that it is first identified, before it is blown out of the central region, and consequently forms these stars with the low angular momentum it had when identifed (Fig 9)).

of the BG forms stars in the bulge region shortly after the time that it is first identified, before it is blown out of the central region, and consequently forms these stars with the low angular momentum it had when identifed (Fig \ref{jzhist}) ).

Supernova feedback heats gas which has low angular momentum and removes it from the inner central region of the galaxy, with the hottest gas traveling the furthest from the centre.

Supernova feedback heats gas which has low angular momentum and removes it from the inner central region of the galaxy, with the hottest gas travelling the furthest from the centre.

The ejected gas mixes with the corona gas, as well as later accreting gas, and returns to the disk with a significantly altered angular momentum distribution.

In particular, gas that is re-accreted from the galactic fountain at later times has a significanlty less negative and low angular momentum baryons, a far greater amount of high angular momentum material, a higher median angular momentum, and forms stars in the disc rather than bulge.

In Paper I and in this study, we have shown that in our simulations, there are two ways in which galaxies can alter the angular momentum distribution of their baryons:ejection in large scale outflows and of low angular momentum material in galactic fountains.

In Paper I and in this study, we have shown that in our simulations, there are two ways in which galaxies can alter the angular momentum distribution of their baryons: in large scale outflows and of low angular momentum material in galactic fountains.

Ejection was shown to be a crucial process in simulated dwarf galaxies, and this meshes well with the low baryonic mass fractions, while redistribution was shown to be a crucial process in the more massive simulated galaxy considered in this study.

Both processes occur at both mass scales in our simulations.

Lower than universal baryon fractions indicating thatejection may play a central role at all galaxy mass scales.

Lower than universal baryon fractions indicating that may play a central role at all galaxy mass scales.

We caution that the relative significance ofejection toredistribution is probably not precisely reproduced in current simulations.

We caution that the relative significance of to is probably not precisely reproduced in current simulations.

This is due to the uncertainty involving the inclusion of feedback and the manner in which it couples to the ISM, a problem which is inherent to all galaxy formation models.

In a semi-analytic study which assumes the ejection of low angular momentum gas, ? found that it

In a semi-analytic study which assumes the ejection of low angular momentum gas, \cite{dutton09} found that it

was averaged over five partially overlapping. 3-G month intervals between. 1999 and 2002.

was averaged over five partially overlapping, 3-6 month intervals between 1999 and 2002.

As illustrated in Fig.

2a. the DM of PSR JO538+2817 shows an approximately monotonic increase al arate of «0.008 pe em!/vr.

2a, the DM of PSR J0538+2817 shows an approximately monotonic increase at a rate of $\sim$ 0.008 pc $^{-3}$ /yr.

Second. with the DM variations fixed. the remaining parameters were determined from a least-squares lit of (he model to the TOA measurements.

Second, with the DM variations fixed, the remaining parameters were determined from a least-squares fit of the model to the TOA measurements.

Slow TOA variations caused by the timing noise were fitted out by including a second time derivative of the pulsars spin period in the model.

Slow TOA variations caused by the timing noise were fitted out by including a second time derivative of the pulsar's spin period in the model.

Because of a relatively short. 2.5-vr span of the data used in this analvsis. we found it unnecessary to model the timing noise by means of more precise methods (e.g. ILobbs. Lyne Kramer 2003).

Because of a relatively short, 2.5-yr span of the data used in this analysis, we found it unnecessary to model the timing noise by means of more precise methods (e.g. Hobbs, Lyne Kramer 2003).

The resulting best-fit TOA residuals are shown in Fig.

2b and the final model parameters are listed in Table 2.

The fit is characterized by an rms residual of 169 prs (111 pes for daily-averaged TOAs).

The fit is characterized by an rms residual of 169 $\mu$ s (111 $\mu$ s for daily-averaged TOAs).

Other pulsar parameters derived [rom (he timing model are given in Table 4.

Other pulsar parameters derived from the timing model are given in Table 4.

Approximate timing models for 12 ont of the 10 vordinary”. slow pulsars discussed here have been published by Foster et al. (

Approximate timing models for 12 out of the 16 “ordinary”, slow pulsars discussed here have been published by Foster et al. (

1995) along with the list of unconfirmed pulsar candidates.

Our timing observations initiated after the Arecibo upgrade have resulted in sienilicant improvements of these models and in establishing (he models for two more confirmed pulsars from (he original list. PSR J2151+2315 aud PSR. J2155+2813.

Our timing observations initiated after the Arecibo upgrade have resulted in significant improvements of these models and in establishing the models for two more confirmed pulsars from the original list, PSR J2151+2315 and PSR J2155+2813.

In addition. sullicient data have been gathered for (wo more recently discovered pulsars. PSR. J13134-1822 and PSR. JL908+2351. to determine their timing behavior for the first time.

In addition, sufficient data have been gathered for two more recently discovered pulsars, PSR J1813+1822 and PSR J1908+2351, to determine their timing behavior for the first time.

All the post-upgrade timing observations of the 16 pulsars were conducted at 430 MIIz between late 1993 and mid-2001.

All the post-upgrade timing observations of the 16 pulsars were conducted at 430 MHz between late 1998 and mid-2001.

For pulsars observed before 1995. the new TOAs were phased with the old ones across the 3-vr Arecibo upgrade gap in the model fitting process.

For pulsars observed before 1995, the new TOAs were phased with the old ones across the 3-yr Arecibo upgrade gap in the model fitting process.

For the four newer objects mentioned above. the TOA modeling was based on the data collected over à 2.5-vr post-uperade period.

For the four newer objects mentioned above, the TOA modeling was based on the data collected over a 2.5-yr post-upgrade period.

The least-squares fits of the timing models included the standard spin and astrometric parameters of the pulsars.

Because no second frequency data were available for these objects. their dispersion measures were determined by splitting the 8 MIIz bandpass of the PSPM into two bands. 4 MIEZ apart. caleulating the TOAs for the two center frequencies and fitting lor DM using the 6wo-Irequenev TOA sets.

Because no second frequency data were available for these objects, their dispersion measures were determined by splitting the 8 MHz bandpass of the PSPM into two bands, 4 MHz apart, calculating the TOAs for the two center frequencies and fitting for DM using the two-frequency TOA sets.

The best-fit timing; ancl derived parameters for all (he 16 pulsars are listed in Tables 3 and 4. respectively.

The best-fit timing and derived parameters for all the 16 pulsars are listed in Tables 3 and 4, respectively.

Typically. the models fitted have rms residuals in the 0.5 - 1.5 ms range for a 180 s integration time per TOA measurement. depending on the pulse strength and width.

Typically, the models fitted have rms residuals in the 0.5 - 1.5 ms range for a 180 s integration time per TOA measurement, depending on the pulse strength and width.

The average pulse profiles of 12 pulsars discovered before 1995 have been published by Foster et al. (

1995).

The profiles of the four newer pulsars discussed above are shown in Fig.

3.

Also shown are the two proliles of PSR. J17464-2540 which was found to undergo clearly

Also shown are the two profiles of PSR J1746+2540 which was found to undergo clearly

2001: Petrosian 2001: Kuo. Hwang. Ip 2003).

2001; Petrosian 2001; Kuo, Hwang, Ip 2003).

The present value of the ΗΝ flix is slightly lower (han (hat reported in Fusco-Femiüano (1999) favoring a central magnetic field strength of 12 iQ in thefreo-phase model of Brunetti (2001). more consistent with the Dj values.

The present value of the HXR flux is slightly lower than that reported in Fusco-Femiano (1999) favoring a central magnetic field strength of 1–2 $\mu$ G in the model of Brunetti (2001), more consistent with the $B_{FR}$ values.

The alternative between primary and secondary electrons as responsible for non-thermal phenomena in clusters of galaxies is discussed in many papers.

Primary electrons may be injected in the ICM of the Coma cluster by some processes (starbursts. AGNs. shocks. turbulence) during a first phase ancl re-accelerated during a second phase (Brunetti 2001).

Primary electrons may be injected in the ICM of the Coma cluster by some processes (starbursts, AGNs, shocks, turbulence) during a first phase and re-accelerated during a second phase (Brunetti 2001).

secondary electrons may be due to decay of charged pions generated in cosmic rav collisions within the ICM (Dennison 1980: Blasi Colafrancesco 1999: Dolag EnBlin 2000: Miniati 2001: Miniati 2003).

Secondary electrons may be due to decay of charged pions generated in cosmic ray collisions within the ICM (Dennison 1980; Blasi Colafrancesco 1999; Dolag $\ss$ lin 2000; Miniati 2001; Miniati 2003).

Radio ancl LIAR spectral properties of Coma provide observational constraints able to discriminate between (hese two different populations of electrons (Brunetti 2002).

Radio and HXR spectral properties of Coma provide observational constraints able to discriminate between these two different populations of electrons (Brunetti 2002).

In particular. the derived. volume-averaged intracluster magnetic field of ~0.254C implies relativistic electrons at energies >~10! to explain the observed diffuse svnchrotron emission.

In particular, the derived volume-averaged intracluster magnetic field of $\sim 0.2\mu G$ implies relativistic electrons at energies $\gamma\sim 10^4$ to explain the observed diffuse synchrotron emission.

At these energies IC losses may determine a cutoff in the spectrum of the accelerated electrons as supported by the radio spectral cutoff observed in Coma (Deiss 1997).

The cutoff in the electron spectrum may be naturally accounted for in the context of models. while it is not expected if the radio emission is due to a continuous production of secondary. electrons.

The cutoff in the electron spectrum may be naturally accounted for in the context of re-acceleration models, while it is not expected if the radio emission is due to a continuous production of secondary electrons.

More recently. a radio spectral cutoff. has been found also in the ease of A754 by relating the VLA observation at 1.4 Gllz (Baechi 2003) to the observations of Nassim (2001) at lower frequencies.

More recently, a radio spectral cutoff has been found also in the case of A754 by relating the VLA observation at 1.4 GHz (Bacchi 2003) to the observations of Kassim (2001) at lower frequencies.

This cluster also shows INR radiation detected at a confidence level slightly above 36 by (Fusco-Femiano 2003) and the derived. value of the magnetic field is of the same order of that. determined in Coma.

This cluster also shows HXR radiation detected at a confidence level slightly above $\sigma$ by (Fusco-Femiano 2003) and the derived value of the magnetic field is of the same order of that determined in Coma.

The PDS detection should be confirmed by a deeper observation with imaging instruments for the presence of the radio galaxy 26W20 located ab a distance of ~27' from the pointing.

The PDS detection should be confirmed by a deeper observation with imaging instruments for the presence of the radio galaxy 26W20 located at a distance of $\sim 27'$ from the pointing.

IBIS on-board with its spatial resolution of ~12’ has the possibility to eliminate this ambiguity and (ο detect the excess al a higher confidence level with respect to that obtained byBeppoS.

IBIS on-board with its spatial resolution of $\sim 12'$ has the possibility to eliminate this ambiguity and to detect the excess at a higher confidence level with respect to that obtained by.

lX. We wish to thank F. Frontera for stimulating discussions and the referee for the useful sugeestions.

We wish to thank F. Frontera for stimulating discussions and the referee for the useful suggestions.

This research has made use of the SINIBAD database. operated αἱ CDS. Strasbourg. France. and of data retrieved. [rom the ASI Scientific Data Center operated al the ESA establishment of ESRIN. Frascati. Παν,

This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France, and of data retrieved from the ASI Scientific Data Center operated at the ESA establishment of ESRIN, Frascati, Italy.

As the counterparts to the fainter, redder sources in the LMC, we look into the properties of the galactic less luminous (although they are among the brightest sample in our data set) red giants.

We extract M-type giants, carbon stars, and type stars that satisfy (S9W— L18W) > 0.4 and Mj —6.

We extract M-type giants, carbon stars, and S-type stars that satisfy $S9W-L18W$ ) $>$ 0.4 and $M_{\textrm{L18W}} < -6$ .

There are 4 S-type stars, 7 Carbon stars, and 38 1gwM- giants that match the criteria.

There are 4 S-type stars, 7 Carbon stars, and 38 M-type giants that match the criteria.

Then, we checked their pulsation properties (variability type and pulsation period), and also searched for their ISO/SWS spectra.

The results are summarized in Table 8..

The results are summarized in Table \ref{faintgiant}.

We found that all but one (HIP 56551) stars are known variable stars.

Most of them show irregular or semi-regular type light variations.

Judging from their relatively long pulsation periods, it is likely that they are on the asymptotic red giant branch (AGB), because faint variables with luminosities at around or below the tip of the first red giant branch (RGB) have shorter periods of about 30 days (e.g., Ita et al. 2004)).

Judging from their relatively long pulsation periods, it is likely that they are on the asymptotic red giant branch (AGB), because faint variables with luminosities at around or below the tip of the first red giant branch (RGB) have shorter periods of about 30 days (e.g., Ita et al. \cite{ita2004}) ).

Among the 49 samples listed in Table 8,, the ISO/SWS spectra (Sloan et al. 2003a))

Among the 49 samples listed in Table \ref{faintgiant}, the ISO/SWS spectra (Sloan et al. \cite{sloan2003a}) )

are available for 7 stars.

These spectra are shown in Figure 10 with their names and classification indices defined in Kraemer et al. (2002)).

These spectra are shown in Figure \ref{isosws} with their names and classification indices defined in Kraemer et al. \cite{kraemer2002}) ).

According to their classification, group 2 includes sources with SEDs dominated by the stellar photosphere but also influenced by dust emission.

The SE and CE subgroups correspond to the oxgen-rich dust emission and carbon-rich dust emission, respectively.

The M subgroup denotes miscellaneous.

It is clear that all of the stars are surrounded by optically-thin circumstellar dust shells.

Silicate dust features are seen in almost all M-type giants and S-type stars.