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Recipes for the determination of SFRs of and within galaxies have enabled many advances in understanding the properties and physics of stellar and galaxy populations. However, like all recipes, they have significant limitations, and they are usually only applicable within the luminosity and physical range where they have been calibrated. Outside this range, they can under/overestimatethe true SFR up to factors of several. Recipes are based on the assumption of a constant SFR over some period of time. For practical reasons, the `mass of newly formed stars' is typically extrapolated from the sum of the mass of massive stars, and the `period of time' is the lifetime of those massive stars. These choices are dictated by purely observational constraints and the cumulative light from the massive stars is used for the purpose of measuring SFRs. Analysis of large samples of star-forming regions within galaxies can average out variations in physical properties, enabling the calibration of `local' SFR indicators. In this chapter single-band SFR indicators in the mid- and far-infrared arepresented and discussed as a function of region size. The need to account for both dust attenuated and unattenuated star formation has led to the formulation of SFR indicators that combine an optical or UV tracer with an infrared or radio tracer, both for galaxies and star–forming regions. We discuss these calibrations and the main limitations of these recipes when they are applied within galaxies.
Addressing the question of the formation and the evolution of galaxies in a cosmological context implies that we must understand their emission over the broadest electromagnetic spectrum. Using multi-wavelength data consistently enables to measure reliable physical parameters like star-formation rates and stellar masses.However, the drawback of this approach is that we do need more information in terms of data. We also need to handle them by using powerful computers and smart codes that are able to run ina reasonable amount of time and deal with a wealth of data and a huge number of models. A statistical approach is also mandatory to estimate the reliability of the results. In this chapter I will describe the different components and physical processesthat leave their imprints in the distribution of energy of galaxiesandhow physicalparameters related to their star formation history can be extracted from the fit of their spectral energy distribution. I willpresent physically-motivated codes which assume an energy balance between dust stellar absorption and re-emission
Observations of the high-energy (X-ray, γ-ray) emission for galaxies opens a new window to study star-forming activity through the detection of the remnants of massive stars. In this chapter we discuss the use of X-ray binaries, supernovae and supernova remnants,γ-ray emission, and γ-ray burstsas star-formation rate indicators. We give an introduction to the different types of X-ray binaries, recent efforts to model their population, and wepresent our current understanding of the scalling relations between populations of X-ray binaries, or their integrated X-ray emission, and the star-formation rate or stellar mass of their host galaxies. Special attention is given on the dependence of these scaling relations and the formation efficiency of X-ray binaries on the age and metallicity of the stellar populations.We also discuss the use of supernovae,supernova remnants, and γ-ray emission (γ-ray bursts and total γ-ray emission) as probes of star-forming activity, recent results and the limitations of these methods. Finally we discuss how gravitational wave sources can be used in order to probe the star-formation history of the Universe.
Stars play such a fundamental role in the evolution of galaxies, some of the key-questions in the field of galaxy evolution and cosmology are related to the history of their formation in galaxies. How do star formation and its history depend on the environment or on the mass of galaxies? When do stars form globally in the history of the universe ? When and how does starlight contribute to the re-ionization phase in the early universe?The goal of this book is to provide the reader an overall presentation of the theoretical and observational backgrounds about the definition and measurement of Star-Formation Rates in galaxies
The measured star-formation rates (SFRs) of galaxies comprise an important constraint on galaxy evolution and also on their cosmological boundary conditions. Any available tracer of the SFR depends on the shape of the mass-distribution of formed stars, i.e. on the stellar initial mass function(IMF). The luminous massive stars dominate the observed photon flux while the dim low-mass stars dominate the mass in the freshly formed population. Errors in the number ratio of the massive to low-mass stars lead to errors in SFR measurements and thus to errors concerning the gas-accretion ratesand the gas-consumption time-scales of galaxies. The stellar IMF has traditionally been interpreted to be a scale-invariant probability density distribution function (PDF), but it may instead be an optimal distribution function. In the PDF interpretation, the stellar IMF observed on the stales of individual star clusters is equal to the galaxy-wide IMF (gwIMF) which, by implication, would be invariant. In this chapter we discuss the fundamental properties of the IMF and of the gwIMF, the nature of both and their systematic variability as indicated by measurements and theoretical expectations, and we discuss the implications for the SFRs of galaxies.
We can trace star formation through a broad variety of observations: photospheric emission from massive stars in the ultraviolet, dust emission in the infrared from grains heated and excited by energetic photons, hydrogen and metal recombination lines from the optical to the infrared, and even free-free continuum and synchrotron emission in the radio domain. The first and foremost constraint for astronomers in estimating SFRs is the ability to obtain adequate observations. For instance, distant galaxies may have emission lines shifted beyond the near-infrared, making them inaccessible from the ground, or the object may be too faint for its free-free emission to be detected. The nature of the observed galaxy and the available instruments therefore strongly guide how we can measure star formation. In the context of this chapter we concentrate on detailing how we can use any observation in star formation tracing bands to measure the SFR as reliably as possible. We will start with theoretical considerations to understand the impact if the assumptions behind each SFR estimator and then discuss the observational constraints.
Dust impacts observations of stars and gas in galaxies by absorbing and scattering photons. Correctly accounting for the effects of dust allows for more accurate studies of a galaxy's stars and gas while also enabling the study of the dust grains themselves.The impact of dust on measurements of individual stars in a galaxy can be straightforwardly modeled as extinguishing the stellar light. Dust extinction towards a star is defined as the combined effect of absorption of photons and scattering of photons out of the line-of-sight towards the star. For integrated measurements of regions of galaxies or whole galaxies that contain multiple stars intermixed with dust, the effects of dust are termed attenuation and are harder to model. Integrated measurements include stars extinguished with different amounts of dust and scattering of photons into the measurement aperture. The infrared dust emission powered by the absorbed photons provides a vital measurement of the amount of energy absorbed by dust. This infrared measurement is not possible for individual stars butprovides an important constraint in modeling the effects of dust on integrated measurements. The aim of this chapter is to provide the details of dust extinction, attenuation, and emission and recommendations for how to model the effects ofdust on observations.
Active Galactic Nuclei (AGN) are thought to play major role in the evolution of galaxies, impacting both star formation and gas accretion onto galaxies.Clearly there is a need to determine the star-formation rates(SFRs) in AGN host galaxies in order to understand and disentangle the growth of SMBH and their hosts. At the same time, contribution of their non-stellar emission in the measured emission from a galaxy impacts all SFR tracers. In this chapter we present the different types of AGN and the main mechanisms responsible for their emission in different wavebands. We discuss the methods used to identify whether a galaxy hosts an AGN and the available techniques to determine the fractional contribution of the AGN to various SFR tracers.
In many ways the study of resolved stellar populations is the bestmethod for exploring properties of stellar populations. However, the method requires measurements to be obtained for individual stars, and this rapidly becomes challenging as the distance to extragalactic systems increases. The depths of resolved stellar samples in galaxies are primarily limited by the levels of stellarfluxes and effects of crowding. Currently most resolved stellar population studies are constrained to galaxies within a distance of about 20 Mpc. Fortunately, the short-lived massive stars, whose numbers trace SFRs, are luminous and thus among the most readily observed, especially when they are not obscured by interstellar dust. The number of stars above a fiducial luminosity in a set of spectroscopic band-passesare counted and corrected for incomplete sampling. The distribution of these stars is then compared to expectations of stellar population models to derive estimates for the observed mass in the form of stars detected in the data. Further modeling provides an interpretation in terms of stellar masses within age bins. In this chapter we provide a brief overview of the history and some of the techniques used to derive star-formation rates (SFRs) and the associated star-formation histories of galaxies through observations
We use the SPace Infrared telescope for Cosmology and Astrophysics (SPICA) project as a template to demonstrate how deep spectrophotometric surveys covering large cosmological volumes over extended fields (1–$15\, \rm{deg^2}$) with a mid-IR imaging spectrometer (17–$36\, \rm{\rm{\upmu m}}$) in conjunction with deep $70\, \rm{\rm{\upmu m}}$ photometry with a far-IR camera, at wavelengths which are not affected by dust extinction can answer the most crucial questions in current galaxy evolution studies. A SPICA-like mission will be able for the first time to provide an unobscured three-dimensional (3D, i.e. x, y, and redshift z) view of galaxy evolution back to an age of the universe of less than $\sim$ 2 Gyrs, in the mid-IR rest frame. This survey strategy will produce a full census of the Star Formation Rate (SFR) in the universe, using polycyclic aromatic hydrocarbons (PAH) bands and fine-structure ionic lines, reaching the characteristic knee of the galaxy luminosity function, where the bulk of the population is distributed, at any redshift up to $z \sim 3.5$. Deep follow-up pointed spectroscopic observations with grating spectrometers onboard the satellite, across the full IR spectral range (17–$210\, \rm{\rm{\upmu m}}$), would simultaneously measure Black Hole Accretion Rate (BHAR), from high-ionisation fine-structure lines, and SFR, from PAH and low- to mid-ionisation lines in thousands of galaxies from solar to low metallicities, down to the knee of their luminosity functions. The analysis of the resulting atlas of IR spectra will reveal the physical processes at play in evolving galaxies across cosmic time, especially its heavily dust-embedded phase during the activity peak at the cosmic noon ($z \sim 1$–3), through IR emission lines and features that are insensitive to the dust obscuration.
Faraday complexity describes whether a spectropolarimetric observation has simple or complex magnetic structure. Quickly determining the Faraday complexity of a spectropolarimetric observation is important for processing large, polarised radio surveys. Finding simple sources lets us build rotation measure grids, and finding complex sources lets us follow these sources up with slower analysis techniques or further observations. We introduce five features that can be used to train simple, interpretable machine learning classifiers for estimating Faraday complexity. We train logistic regression and extreme gradient boosted tree classifiers on simulated polarised spectra using our features, analyse their behaviour, and demonstrate our features are effective for both simulated and real data. This is the first application of machine learning methods to real spectropolarimetry data. With 95% accuracy on simulated ASKAP data and 90% accuracy on simulated ATCA data, our method performs comparably to state-of-the-art convolutional neural networks while being simpler and easier to interpret. Logistic regression trained with our features behaves sensibly on real data and its outputs are useful for sorting polarised sources by apparent Faraday complexity.
We present the first Faraday rotation measure (RM) grid study of an individual low-mass cluster—the Fornax cluster—which is presently undergoing a series of mergers. Exploiting commissioning data for the POlarisation Sky Survey of the Universe’s Magnetism (POSSUM) covering a ${\sim}34$ square degree sky area using the Australian Square Kilometre Array Pathfinder (ASKAP), we achieve an RM grid density of ${\sim}25$ RMs per square degree from a 280-MHz band centred at 887 MHz, which is similar to expectations for forthcoming GHz-frequency ${\sim}3\pi$-steradian sky surveys. These data allow us to probe the extended magnetoionic structure of the cluster and its surroundings in unprecedented detail. We find that the scatter in the Faraday RM of confirmed background sources is increased by $16.8\pm2.4$ rad m−2 within 1$^\circ$ (360 kpc) projected distance to the cluster centre, which is 2–4 times larger than the spatial extent of the presently detectable X-ray-emitting intracluster medium (ICM). The mass of the Faraday-active plasma is larger than that of the X-ray-emitting ICM and exists in a density regime that broadly matches expectations for moderately dense components of the Warm-Hot Intergalactic Medium. We argue that forthcoming RM grids from both targeted and survey observations may be a singular probe of cosmic plasma in this regime. The morphology of the global Faraday depth enhancement is not uniform and isotropic but rather exhibits the classic morphology of an astrophysical bow shock on the southwest side of the main Fornax cluster, and an extended, swept-back wake on the northeastern side. Our favoured explanation for these phenomena is an ongoing merger between the main cluster and a subcluster to the southwest. The shock’s Mach angle and stand-off distance lead to a self-consistent transonic merger speed with Mach 1.06. The region hosting the Faraday depth enhancement also appears to show a decrement in both total and polarised radio emission compared to the broader field. We evaluate cosmic variance and free-free absorption by a pervasive cold dense gas surrounding NGC 1399 as possible causes but find both explanations unsatisfactory, warranting further observations. Generally, our study illustrates the scientific returns that can be expected from all-sky grids of discrete sources generated by forthcoming all-sky radio surveys.
We present 63 new multi-site radial velocity (RV) measurements of the K1III giant HD 76920, which was recently reported to host the most eccentric planet known to orbit an evolved star. We focused our observational efforts on the time around the predicted periastron passage and achieved near-continuous phase coverage of the corresponding RV peak. By combining our RV measurements from four different instruments with previously published ones, we confirm the highly eccentric nature of the system and find an even higher eccentricity of $e=0.8782 \pm 0.0025$, an orbital period of $415.891^{+0.043}_{-0.039}\,\textrm{d}$, and a minimum mass of $3.13^{+0.41}_{-0.43}\,\textrm{M}_{\textrm{J}}$ for the planet. The uncertainties in the orbital elements are greatly reduced, especially for the period and eccentricity. We also performed a detailed spectroscopic analysis to derive atmospheric stellar parameters, and thus the fundamental stellar parameters ($M_*, R_*, L_*$), taking into account the parallax from Gaia DR2, and independently determined the stellar mass and radius using asteroseismology. Intriguingly, at periastron, the planet comes to within 2.4 stellar radii of its host star’s surface. However, we find that the planet is not currently experiencing any significant orbital decay and will not be engulfed by the stellar envelope for at least another 50–80 Myr. Finally, while we calculate a relatively high transit probability of 16%, we did not detect a transit in the TESS photometry.
A number of solar filaments/prominences demonstrate failed eruptions, when a filament at first suddenly starts to ascend and then decelerates and stops at some greater height in the corona. The mechanism of the termination of eruptions is not clear yet. One of the confining forces able to stop the eruption is the gravity force. Using a simple model of a partial current-carrying torus loop anchored to the photosphere and photospheric magnetic field measurements as the boundary condition for the potential magnetic field extrapolation into the corona, we estimated masses of 15 eruptive filaments. The values of the filament mass show rather wide distribution in the range of $4\times10^{15}$–$270\times10^{16}$ g. Masses of the most of filaments, laying in the middle of the range, are in accordance with estimations made earlier on the basis of spectroscopic and white-light observations.
We present the results of a search for additional exoplanets in all multiplanetary systems discovered to date, employing a logarithmic spacing between planets in our Solar System known as the Titius–Bode (TB) relation. We use the Markov Chain Monte Carlo method and separately analyse 229 multiplanetary systems that house at least three or more confirmed planets. We find that the planets in $\sim 53\%$ of these systems adhere to a logarithmic spacing relation remarkably better than the Solar System planets. Using the TB relation, we predict the presence of 426 additional exoplanets in 229 multiplanetary systems, of which 197 candidates are discovered by interpolation and 229 by extrapolation. Altogether, 47 predicted planets are located within the habitable zone of their host stars, and 5 of the 47 planets have a maximum mass limit of 0.1–2 ${\rm M}_{\oplus}$ and a maximum radius lower than 1.25 ${\rm R}_{\oplus}$. Our results and prediction of additional planets agree with previous studies’ predictions; however, we improve the uncertainties in the orbital period measurement for the predicted planets significantly.
Fireballs are infrequently recorded by seismic sensors on the ground. If recorded, they are usually reported as one-off events. This study is the first seismic bulk analysis of the largest single fireball data set, observed by the Desert Fireball Network (DFN) in Australia in the period 2014–2019. The DFN typically observes fireballs from cm-m scale impactors. We identified 25 fireballs in seismic time series data recorded by the Australian National Seismograph Network (ANSN). This corresponds to 1.8% of surveyed fireballs, at the kinetic energy range of $10^6$–$10^{10}$ J. The peaks observed in the seismic time series data were consistent with calculated arrival times of the direct airwave or ground-coupled Rayleigh wave caused by shock waves by the fireball in the atmosphere (either due to fragmentation or the passage of the Mach cone). Our work suggests that identification of fireball events in the seismic time series data depends on both physical properties of a fireball (such as fireball energy and entry angle in the atmosphere) and the sensitivity of a seismic instrument. This work suggests that fireballs are likely detectable within 200 km direct air distance between a fireball and seismic station, for sensors used in the ANSN. If each DFN observatory had been accompanied by a seismic sensor of similar sensitivity, 50% of surveyed fireballs could have been detected. These statistics justify the future consideration of expanding the DFN camera network into the seismic domain.
We introduce pinta, a pipeline for reducing the upgraded Giant Metre-wave Radio Telescope (uGMRT) raw pulsar timing data, developed for the Indian Pulsar Timing Array experiment. We provide a detailed description of the workflow and usage of pinta, as well as its computational performance and RFI mitigation characteristics. We also discuss a novel and independent determination of the relative time offsets between the different back-end modes of uGMRT and the interpretation of the uGMRT observation frequency settings and their agreement with results obtained from engineering tests. Further, we demonstrate the capability of pinta to generate data products which can produce high-precision TOAs using PSR J1909$-$3744 as an example. These results are crucial for performing precision pulsar timing with the uGMRT.