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illustration of two merging black holes in the night sky above an L-shaped detector on earth.

Gravitational waves have revealed a wealth of information about distant black holes and neutron stars — but they can also provide large-scale insights into how our universe works. A new study explores how gravitational-wave detections may soon resolve the long-lived tension in measurements of our universe’s expansion.

An Expanding Problem

plot showing the different measurements made of H0 through the years. Local and global measurements are clearly not in agreement.

Some past measurements of H0 (click to enlarge). Black data points are local-universe distance-ladder measurements, which cluster around 73 km/s/Mpc; red data points are early-universe CMB measurements, which cluster around 67 km/s/Mpc. [Renerpho]

We know the universe is expanding, but we’re still not sure how quickly. The empirically derived value H0 — referred to as the Hubble constant or the Hubble-Lemaître constant — parametrizes the universe’s expansion rate. This controversial parameter, which describes how quickly galaxies are receding from us as a function of their distance from us, is traditionally measured in one of two ways:

  1. In the local universe, by determining the distances to and recession speeds of visible astronomical objects. This method relies on the distance ladder: the distances measured to far-off objects are built upon measured distances to nearer objects.
  2. On global scales, estimated by modeling measurements of the cosmic microwave background (CMB), relic radiation from the Big Bang.

The trouble? The values we come up with for H0 from these two methods are not consistent with one another! To resolve this tension, we need another way of measuring H0 that’s independent of these approaches. Enter: dark sirens.

The Call of Hidden Collisions

Dark sirens are the collisions of two black holes that, though they produce no light, can provide us with valuable distance information. When black holes merge, their gravitational-wave signal encodes a distance luminosity. By combining this piece of information with the physical distance to the merging black holes — identifiable if we can precisely pinpoint the host galaxy of the collision — we can get an independent measure of H0.

map showing the localization of GW170817 on the sky

This map shows the localization of the gravitational-wave, gamma-ray, and optical signals of the neutron-star merger detected on 17 August 2017. Upgrades to LIGO and Virgo should improve gravitational-wave localization, making it possible to identify the host galaxy of a merger even without electromagnetic counterparts. [Abbott et al. 2017]

The catch? Right now, our gravitational-wave technology isn’t quite good enough to identify a precise value of H0. This problem is rooted in two issues: the large uncertainty on the measured distance luminosity in the gravitational-wave signal, and the difficulty in accurately identifying the host galaxy of a black hole merger, which produces no electromagnetic counterpart.

But there’s hope! Future advancements in technology at gravitational-wave detectors may soon bring these precise measurements into reach, according to the calculations of a team of scientists led by Ssohrab Borhanian (Pennsylvania State University).

A Precise Future

Borhanian and collaborators explore a series of models for future detections of gravitational-wave events using current and upcoming detectors with increasingly advanced technology.

plot of delta(H0)/H0 for four different networks.

Estimated distribution of fractional errors in the measurement of H0 after 2 years of observing time for different networks of detectors. The left cluster (HLV+) represents 2G+ technology on a network consisting of only LIGO-Livingston, LIGO-Hanford, and Virgo detectors; the right cluster (ECC) represents the 3G technology of a future detector network. The different colors represent the authors’ different population models. [Adapted from Borhanian et al. 2020]

Upgrades to the Laser Interferometer Gravitational-wave Observatory (LIGO) and the European detector Virgo are currently underway. The authors show that this advancement to next-generation (known as 2G+) technology could allow these detectors to uniquely identify the host galaxies of binary black hole mergers, without the need for an electromagnetic counterpart to the merger.

Borhanian and collaborators estimate that with 2G+ technology, we’ll be able to measure H0 to a precision of 2% within 5 years — which is sufficient to resolve the Hubble tension. And if you want something to dream about, consider this: third-generation detector technology (which will include the proposed Einstein Telescope and Cosmic Explorer) will be able to measure H0 to within less than a percent. The call of dark sirens is leading us to a beautifully precise future!

Citation

“Dark Sirens to Resolve the Hubble–Lemaître Tension,” Ssohrab Borhanian et al 2020 ApJL 905 L28. doi:10.3847/2041-8213/abcaf5

A quasar sits on a sparse background of distant stars. The black hole is represented by a white circle at the center of a flat, pancake-like cloud of pink and blue dust and clouds. The black hole shoots out white jets and debris towards the upper-right and lower-left.

Some quasar host galaxies live in the early universe. This makes them especially interesting, since they had to have accumulated a lot of mass very quickly. Luckily for us, radio telescopes like ALMA can peer back in time and tell us more about these galaxies and their environments.

Finding Far-Off Quasars

ALMA

Antennas of the ALMA observatory under the Magellanic Clouds. [ESO/C. Malin]

Quasars are absurdly energetic objects. They are a version of the supermassive black holes at the centers of galaxies, and what makes them unique is the large amounts of energy they emit while actively accreting material. A significant portion of this energy is emitted as short-wavelength ultraviolet (UV) light, which is the key to studying quasars that live in the early universe.

The farther away an object is, the more its light becomes redshifted as it travels to us — that is, the wavelength at which light from the object was first emitted is shorter than the wavelength we observe when that light reaches us. So in the case of far-off quasars, their UV emission will be redshifted into radio wavelengths, where we can still observe it!

FIR (left) and [C II] (right) emission maps (distances shown in arcseconds) for two galaxies from this study. The redder regions indicate higher emission levels; bluer regions point to the absence of emission. [Adapted from Venemans et al. 2020]

In a recent study, a group of researchers led by Bram P. Venemans (Max-Planck Institute for Astronomy, Germany) used radio observations of distant quasar host galaxies to learn more about them, as well as conditions in the early universe.

Evidence from Emissions

All 27 galaxies in this study live at a redshift of roughly z = 6, or when the universe was just under a billion years old. Venemans and collaborators were especially interested in two types of emission from these galaxies: singly ionized carbon ([C II]) emission, which tracks the gas of the interstellar medium; and the general continuum brightness in the far-infrared (FIR), which is associated with dust. The spatial extent of the [C II] emission in particular is also sensitive to the motions of a galaxy and its surroundings.

The galaxies were observed by Atacama Large Millimeter/submillimeter Array (ALMA) in September 2019. The observations had a resolution of roughly a kiloparsec (or 19 trillion miles), which is pretty high definition for the early universe! This allowed Venemans and collaborators to examine the central regions of their galaxies. They were also able to probe the surrounding space for any companion galaxies.

Seeing Into the Center

Star formation rates versus distance from galaxy center. Each track represents a quasar host galaxy, with the color of the track corresponding to the FIR brightness of the galaxy. [Venemans et al. 2020]

It turned out that for the galaxies in this study, the central dust regions mapped closely onto the positions of central supermassive black holes. This may not sound like a profound observation, but it is observational evidence to support that these central black holes live at the hearts of dark matter halos, which are cosmological building blocks.

The [C II] emission revealed that about half of the quasar-hosting galaxies in this sample had companions. The FIR emission also allowed Venemans and collaborators to determine that in the central regions of their galaxies, star formation peaks at the center and then declines moving outward. The outer regions of these distant galaxies currently remain elusive, but as Venemans and collaborators noted, ALMA is quite capable of probing these galaxies further!

Citation:

“Kiloparsec-scale ALMA Imaging of [C II] and Dust Continuum Emission of 27 Quasar Host Galaxies at z ~ 6,” Bram P. Venemans et al 2020 ApJ 904 130. doi:10.3847/1538-4357/abc563

Composite image showing an explosive outflow that looks like a firework set against a backdrop of stars.

There’s still much we don’t know about the birth of massive stars — stars with more than 8 times the mass of the Sun. A recent study reveals details of a thousand-year-old explosion that might provide clues about the formation of these giants.

An Unexpected Explosion

Orion Nebula

The clouds of molecular gas in regions like the Orion nebula provide nurseries in which massive stars form and evolve. [ESO/G. Beccari]

Several decades ago, astronomers discovered something odd. In a region inside the Orion nebula where massive star formation is underway, scientists detected signs of an explosive outflow: dense molecular gas streaming outward from a central point at rapid speeds. Surprisingly, there was nothing at the center of this explosion.

This one-off discovery was intriguing. One could imagine a number of sudden, energy-liberating events that could occur in a massive star-forming environment — like the formation of a close massive stellar binary, or the merger of two young, massive protostars. And the discovery of several candidate runaway stars at the fringes of the explosion provided another hint to a dynamical origin.

Could this explosion help us understand the process of how massive stars form in their birth environments? Or was it just a fluke event? As years passed without astronomers finding evidence of another, similar outflow, these questions remained unanswered.

Map of SiO molecular gas shows streams of material moving outward from a central point.

This ALMA SiO map of the star-forming region G5.89 shows outflowing molecular gas surrounding an expanding, shell-like HII region (white contours). Two stars moving away from the origin are marked in magenta and cyan. [Adapted from Zapata et al. 2020]

Two of a Kind

Forty years later, we now have proof of another such explosive outflow in a massive star-forming environment. In a recent publication led by Luis Zapata (UNAM Radio Astronomy and Astrophysics Institute, Mexico), a team of scientists has used the Atacama Large Millimeter/submillimeter Array (ALMA) to confirm the presence of streamers of molecular gas flowing isotropically outward from a central point in the massive stellar birthplace G5.89, which lies roughly 10,000 light-years away from us.

Zapata and collaborators measured 34 molecular filaments in this explosive outflow, finding that the streamers are accelerating as they expand outward. This is consistent with behavior of the Orion explosion and shows that the density of the ejecta is substantially larger than the surrounding medium.

As with the Orion explosive outflow, the point of origin of the filaments contains no source. Previous studies, however, have identified several young, massive stars in the periphery of the G5.89 explosion that are speeding away from the point of origin at roughly the right speed to have been at the center 1,000 years previously at the time of explosion.

Learning about Stellar Birth

illustration of dust and gas swirling around a bright, newly forming star.

A protostar lies embedded in a disk of gas and dust in this visualization. The collision of two protostars could release enough energy to power an explosive molecular outflow — and produce a massive star. [NASA’s Goddard SFC]

What does all this tell us about the origins of massive stars? Explosive outflows like this — caused by dynamical interactions during the birth of massive stars — may be more common than we previously thought!

The authors estimate a rate for such outflows based on our limited observations, finding that there should be one every ~100 years. The fact that this is very close to the rate of supernovae further solidifies the connection of explosive molecular outflows to massive star formation.

Dedicated, high-sensitivity searches for more such outflows in nearby massive star-forming regions will certainly go a long way toward confirming this theory. In the meantime, the authors argue, we should consider revising high-mass star formation models to include dynamical interactions, as these stellar explosions may prove to be regular occurrences!

Bonus

The animation below shows a different view of the authors’ ALMA-observed streamers, traced by CO gas. Two axes give the position of observations, while the third axis and the colors show the radial velocity at each point in the streamers, showing how the ejecta are accelerating as they expand outward. The star marks the origin of the explosive outflow.

Citation

“Confirming the Explosive Outflow in G5.89 with ALMA,” Luis A. Zapata et al 2020 ApJL 902 L47. doi:10.3847/2041-8213/abbd3f

Left: Drawing of a disk representing the sun's surface, with several dark clusters of spots colored in. Right: image of the sun taken at 193 Å.

Astronomers have drawn detailed maps of dark spots on the Sun’s surface since Galileo’s time. Today, we have a host of modern spacecraft that make these observations for us, continuously charting the shifts in sunspot patterns and solar magnetic fields. Can computers help us to bridge between these historical and modern datasets?

A Long-Lived Record

photograph of a tall tower with a telescope dome at the top, surrounded by pine trees

Photograph of the 150-ft solar tower at Mt. Wilson Observatory, where daily sunspot drawings have been produced since 1912. [Susanna Kohler]

Every clear day since 1912, an observer at the Mt. Wilson Observatory near Los Angeles has hand-drawn a map of the dark spots on the face of the Sun — tracers of magnetic activity at and beneath the solar surface. This meticulous practice dates back to long ago: the first known sunspot drawings are from the year 1128 AD! Perhaps most famous among the astronomers who have undertaken this task is Galileo, whose early telescope allowed him to record detailed changes in sunspot geometry over a span of several months in 1612.

Historical sunspot records have provided valuable insight into the behavior of our nearest star. But today, we can also gather more sophisticated solar data. Space-based telescopes like the Solar Dynamics Observatory (SDO) monitor the Sun’s emission at a variety of wavelengths and produce magnetograms that reveal the magnetic field arrangements across the Sun’s surface. These modern observations allow us to explore the Sun’s magnetic flux and the light emitted from solar active regions — information that can tell us more about how the Sun’s activity evolves and how it impacts the Earth.

What if we could gain this same level of insight from historical daily sunspot drawings? Led by Harim Lee, a team of scientists from Kyung Hee University in the Republic of Korea has undertaken the challenge of translating sunspot drawings into something that more closely resembles modern satellite data.

photograph of a sunspot drawing covered in labels of regions

Photograph of a sunspot drawing produced at the Mt. Wilson Observatory. [Mt. Wilson Observatory]

Teaching a Computer to Translate Drawings

Lee and collaborators recognized that the 100+ years of daily sunspot drawings from Mt. Wilson Observatory have a significant benefit: there is overlap between these drawings and modern satellite data. The authors compiled a set of more than a thousand Mt. Wilson sunspot drawings from 2011 to 2015 that they then paired with the corresponding daily ultraviolet/extreme ultraviolet (UV/EUV) images and magnetograms captured with SDO.

The next step: train a computer to map between the datasets. Using a training set of 1,046 pairs of sunspot drawings and SDO images, Lee and collaborators developed a deep learning model that takes a sunspot drawing as input, and generates a magnetogram and a set of seven mock SDO images at different UV/EUV wavelengths as output.

eight-frame set of pairs of observations showing real vs. mock images of the sun.

Comparison between real SDO images (left image of each pair) and the model-generated ones (right image of each pair) for sunspot observations on 8 June, 2014. Click to enlarge. [Lee et al. 2021]

The authors then used the remaining 204 pairs of sunspot drawings and SDO observations to evaluate the success of their model, demonstrating that it accurately reproduces the bipolar structures of the magnetograms and the approximate geometry of active regions on the Sun.

Finally, Lee and collaborators apply their model to Galileo’s original sunspot drawings from 1612, generating mock SDO images and magnetograms for a time more than four centuries ago.

The authors note that this unique method of modernizing historical data is, of course, limited in what it can reproduce — but it does provide us with unusual insight into the long-term evolution of our Sun’s magnetic fields and radiation.

Citation

“Generation of Modern Satellite Data from Galileo Sunspot Drawings in 1612 by Deep Learning,” Harim Lee et al 2021 ApJ 907 118. doi:10.3847/1538-4357/abce5f

Illustration of magnetic field lines extending in a tail beyond the earth. the moon lies within the region shielded by the magnetic field.

Given plans for future manned missions to the Moon — and interest in the potential for longer-term lunar habitation — the presence of water on the Moon is of critical importance. Studies over the last few decades have revealed water lurking on our satellite in numerous forms. But how does it get there?

Water In, Water Out

Two maps, each showing a lunar pole, that indicate the locations of water measured by M3.

Overview of the lunar OH/H2 abundance in the polar regions of the Moon, as derived from M3 observations in January/February 2009. [Adapted from Wang et al. 2021]

Lunar water has been found locked in ice form in the cold, permanently shadowed craters at the Moon’s poles, and drifting in gas form in the very thin lunar atmosphere. In addition, we’ve discovered that water exists in trace amounts across the Moon’s surface, bound to lunar minerals.

But lunar water is more complicated than its mere presence or absence. The Moon is also thought to have a water cycle — water is continuously created on or delivered to the Moon’s surface, and then destroyed on or removed from it.

Understanding the driving processes in this cycle will enable us to best leverage the Moon’s resources and deepen our insight into the physics that influences airless rocky bodies throughout our solar system and beyond.

Identifying Processes

Based on laboratory experiments and lunar observations, here’s our understanding so far:

  1. Production
    We think the continuous production of lunar surface water may largely be driven by incoming protons — hydrogen nuclei — from the solar wind, which then bind with the oxygen in lunar minerals to form water. Other processes may also contribute, like production from additional sources of incoming protons, or episodic delivery of water via comets and asteroids.
  2. Removal
    Water on the Moon’s surface is primarily removed through continuous processes like photodissociation — the decomposition of water molecules by sunlight.

With the rich observations recently produced by missions like NASA’s Moon Mineralogy Mapper (M3) spectrometer on India’s Chandrayaan-1 orbiting probe, we’re currently in an excellent position to test this understanding.

In a new publication led by Huizi Wang (Shandong University and Chinese Academy of Sciences), a joint team of space physicists and planetary scientists presents an exploration of water production on the surface of the Moon.

Windy Production

Schematic showing the orbit of the moon around the earth and the portion of the lunar orbit where the Moon is shielded from the solar wind by the earth's magnetosphere

Schematic showing the Moon’s orbit around the Earth. The Moon spends 3–5 days each orbit passing through the Earth’s magnetosphere, where it is shielded from the solar wind. [Adapted from Wang et al. 2021]

As the Moon circles the Earth, it spends 3–5 days each month shielded from the solar wind by the Earth’s magnetosphere. If incoming protons from the solar wind are the primary driver of lunar water production, Wang and collaborators argue, then measurements of lunar water abundance should show a decrease during those 3–5 days, assuming water continues to be destroyed at the same rate via photodissociation.

Instead, the authors find that spectroscopy from M3 reveals no change in water abundances over the complete lunar orbit, despite observations showing the expected drop in incoming solar wind energy when the Moon passes through Earth’s magnetosphere.

Could another source contribute to production of water on the Moon, keeping abundances constant? Wang and collaborators demonstrate that when the Moon is shielded from the solar wind, incoming protons from the Earth’s wind — a weaker stream of charged particles from the Earth’s magnetosphere — could provide the protons needed to maintain observed water abundances on the Moon’s surface.

There are still many open questions, but the future holds more opportunities to refine our understanding. The Chinese Chang’e 5 lunar mission successfully measured lunar material and brought samples back to Earth late last year, and the planned Artemis missions to the Moon will soon provide further insight.

Citation

“Earth Wind as a Possible Exogenous Source of Lunar Surface Hydration,” H. Z. Wang et al 2021 ApJL 907 L32. doi:10.3847/2041-8213/abd559

GW190521 NR Simulation AEI Face On

Since beginning operation, gravitational-wave observatories have observed several mergers involving neutron stars and black holes. Both black holes and neutron stars are the result of supernovae, so is it possible for us to identify a pair of these objects pre-merger?

An artist’s impression of a black hole–neutron star binary. [Carl Knox, Arc Centre Of Excellence For Gravitational Wave Discovery (Ozgrav) At Swinburne University Of Technology]

Some Go Supernova First

The first black hole–black hole (BH–BH) merger was detected by the Laser Interferometer Gravitational-wave Observatory (LIGO) in 2015. Since then, LIGO and the Virgo interferometer have observed several BH–BH and neutron star–neutron star (NS–NS) mergers. Interestingly, the two observatories have also found candidates for BH–NS mergers. So how are the progenitors of these mergers formed?

One possibility is that black holes and neutron stars encounter each other in densely populated areas of space and just happen to pair off. Another possibility is that these pairs of dense objects start off as massive stars in a binary and evolve until they reach their pre-merger form.

Both scenarios involve supernovae, as the stars evolve to become neutron stars or black holes. But there’s an interesting consideration for the latter scenario, if one star becomes a black hole before the other finishes evolving: How would the black hole interact with the supernova caused by its companion?

In a recent study, a group of researchers led by He Gao (Beijing Normal University, China) tackle that question.

The light curves from two instances of a black hole interacting with material ejected from its companion’s supernova. In the upper panel, the energy from the interaction is larger than the energy associated solely with the supernova. In the lower panel, the energy from the interaction is comparable to the energy associated with the supernova. LBP is the brightness from black hole outflows, Ldisk is from the black hole’s accretion disk, and LNi comes from the radioactive decay of nickel associated with the supernova. Lmag is the total brightness from the system. [Gao et al. 2020]

Just Add Ejected Mass

Gao and collaborators first estimated how much mass and energy would be released by a massive star going supernova. They also put constraints on the velocity of the ejected mass, since it would play an important role in determining any interaction with the black hole.

If any material fell into the black hole’s sphere of influence, it would result in energy being released in multiple ways, like through jets and outflows. Gao and collaborators determined that these releases of energy could happen on timescales similar to the supernova. So what do you get when you look at the total energy released by the merger progenitor?

Energetically Interfering with Supernovae

If we plot the brightness of a supernova from start to finish, we get a light curve that peaks very quickly and then slowly tapers off. This curve can change based on the type of supernova involved, but broadly speaking, most supernovae have this characteristic shape in brightness–time space.

In the merger progenitor, energy released by ejected material interacting with the black hole would disrupt this characteristic supernova light curve. The extent of this disruption would depend on a variety of factors, but Gao and collaborators noted that at least a small fraction of these disrupted supernovae could be detected.

If we observed a number of these disrupted supernovae, we could compare the rate at which they occur to the rate of relevant mergers being detected by gravitational-wave observatories. The result could point us towards one of the two scenarios that produce merger progenitors. So, as with most things astronomy, more observations please!

Citation:

“Special Supernova Signature from BH–NS/BH Progenitor Systems,” He Gao et al 2020 ApJL 902 L37. doi:10.3847/2041-8213/abbef7

NOEMA observatory

The rate at which galaxies form stars is governed in part by how much star-making material — namely, cold molecular gas — is available. So how has the availability of molecular gas changed with time?

A map of the carbon monoxide in the galaxy NGC 253 based on observations taken by ALMA. Purple regions correspond to brighter CO emission while red regions correspond to fainter CO emission. [NSF/Erik Rosolowsky/University of Alberta]

Running Out of Fuel

Most galaxies aren’t forming new stars like they used to. In fact, star formation rates across the universe peaked at redshifts (z) of 1–2, or between 8 to 10 billion years ago. This time of frenzied star formation is still not fully understood, so it’s valuable to probe the availability and efficiency of star-formation fuel over the lifetime of the universe.

What fuels star formation? The typical answer is cold, dense molecular gas, which can be identified by associated emissions at particular wavelengths. Emissions from carbon monoxide (CO) are especially useful in this regard.

Previous searches for molecular gas using CO emissions have shown that galaxies at ~ 2 have more gas than galaxies local to us (at ~ 0). However, most of these high redshift galaxies were selected based on their appearance at other wavelengths, which could bias our understanding of the availability of molecular gas.

One of the newly identified CO sources as seen in PHIBSS2 (top) and the COSMOS survey (bottom). In the top panel, regions with higher signal to noise are in red. In the bottom panel, the red oval is a measure of the instrument resolution, and the white contours and red crosses correspond to detections. [Adapted from Lenkić et al. 2020]

To address this potential bias, a group of researchers led by Laura Lenkić (University of Maryland, College Park) attempted a search for CO-emitting galaxies in observations taken for the second Plateau de Bure High-z Blue Sequence Survey (PHIBSS2). The goal of this study was to determine how our knowledge of molecular gas would be impacted by serendipitously identified gas reservoirs.

Searching in the Dark

The PHIBSS2 observations leverage the Northern Extended Millimeter Array, a large array of radio dishes located on the Plateau de Bure in the French Alps. The total volume being searched was about 200,000 cubic megaparsecs, or 6 x 1063 cubic kilometers. The observations were made for a study similar to the one being conducted by Lenkić and collaborators, but the galaxies observed were selected based on their masses. The spatial extent of the observations was large, making them well suited for a search for other CO sources in each image.

To identify possible reservoirs of molecular gas, Lenkić and collaborators looked for three different emissions associated with CO in the PHIBSS2 data. Once they had found potential sources of CO emission, they then searched corresponding images taken by the Hubble Space Telescope to see if those sources had associated optical (shorter wavelength) emissions as well.

Comparing the targeted sources in PHIBSS2 (blue) with candidate sources color-coded based on their confidence levels, or R. The higher R is, the higher the confidence in the source. [Adapted from Lenkić et al. 2020]

Sources Spanning Across Time

Lenkić and collaborators ended up finding 67 candidate sources of CO emission within z ~ 0.6–3.6, when the universe was between 2 and 8 billion years old. Over half of the candidates have at least one optical detection in the Hubble data. These sources appear similar to other sources of CO emission that were found serendipitously, and they also closely trace the original PHIBSS2 targets.

This new, serendipitous sample will help us to better understand how star-formation fuel is distributed throughout galaxies in the distant universe, and it can be expanded with additional observations that cover a large area of the sky. Lenkić and collaborators note that these kinds of searches could also be done with older observations that weren’t taken for the express purpose of such a search. That would be a challenge, but certainly doable, as demonstrated by this work!

Citation

“Plateau de Bure High-z Blue Sequence Survey 2 (PHIBSS2): Search for Secondary Sources, CO Luminosity Functions in the Field, and the Evolution of Molecular Gas Density through Cosmic Time,” Laura Lenkić et al 2020 AJ 159 190. doi:10.3847/1538-3881/ab7458

magnetar outburst

Recent evidence points to highly magnetized neutron stars as the culprits that produce fast radio bursts — brief and energetic flashes of radio emission that we’ve spotted coming from distant galaxies. But do galaxy demographics support this picture? 

fast radio burst

Artist’s impression of observatories finding and localizing a fast radio burst offset from its host galaxy’s center. [CSIRO/Andrew Howells]

An Origin Mystery

In the past decade, we’ve found around a hundred unexplained, millisecond bursts of radio light that (mostly) originate from far beyond our galaxy. We’ve developed dozens of possible explanations for what might cause these fast radio bursts (FRBs) — like the mergers of compact objects, or phenomena associated with evolved or evolving stars, or even the weird physics of cosmic strings. Still, these all remain unverified theories.

When we successfully identified the host galaxy for an FRB for the first time in 2017, we hoped that this might finally reveal the cause of these explosions. Instead, the mystery of FRBs has only deepened: the ten FRBs that have well-known localizations are hosted by galaxies with surprisingly different properties.

In September 2020, a new clue was announced: a strongly magnetized neutron star — a magnetar — in our own galaxy had been observed to emit a radio burst similar to an FRB. Was this the evidence we’d been waiting for, finally proving that magnetars are the source of FRBs?

A team of scientists led by Mohammadtaher Safarzadeh (UC Santa Cruz; Center for Astrophysics | Harvard & Smithsonian) suggests that there’s a simple way to test this scenario: by comparing the demographics of magnetar-hosting and FRB-hosting galaxies.

Exploring Demographics

Three plots showing the CDFs for log stellar mass, log SFR, and offset distribution.

Top: comparison of the cumulative distribution function of FRB host galaxies (black line) to the expected global distribution of galaxies (colored lines) for total stellar mass of galaxies. Middle: same comparison, but for galaxy star formation rate. Bottom: Offset distribution of FRBs (black line) to expected distribution of magnetars in galaxies (red line). [Adapted from Safarzadeh et al. 2020]

Suppose, Safarzadeh and collaborators say, that magnetars are the progenitors of FRBs. Since magnetars are the remnants left behind soon after massive stars collapse, these objects ought to reside in or near the places where lots of stars are being born — regions of high star formation in our universe.

With this in mind, Safarzadeh and collaborators first explore the distributions of stellar mass and star formation rates for the ten localized FRB host galaxies, to see whether FRBs are preferentially hosted in galaxies that are likely to contain magnetars. As an additional check, the authors then examine the offset of the FRBs from the centers of their host galaxies, to test whether FRB locations track the star formation rate profile within the galaxies.

Magnetars or Not?

The result? The authors find that there’s a clear inconsistency between the star formation rates of expected magnetar hosts and the star formation rates for observed FRB hosts — strongly indicating that not all FRBs are caused by magnetars. On the other hand, the offsets of FRBs from their galaxy centers are not inconsistent with the predicted locations of magnetar birth sites.

So are FRBs caused by magnetars or not? The results are still inconclusive, but we’re just getting started — our sample of FRBs is growing rapidly, and we’re soon likely to have a much larger collection of localized FRBs with which we can better explore the properties of their hosts. Keep an eye out for more developments on the FRB front!

Citation

“Confronting the Magnetar Interpretation of Fast Radio Bursts through Their Host Galaxy Demographics,” Mohammadtaher Safarzadeh et al 2020 ApJL 905 L30. doi:10.3847/2041-8213/abd03e

photograph of a rocky, icy moon

Among Jupiter’s Galilean moons, icy Europa or volcanic Io often take the spotlight — but their sibling moon Ganymede has plenty of secrets to share. Powerful new millimeter observations have now provided insight into this complex satellite’s surface.

A World Apart

photograph showing rough, cratered, dark terrain crosscut by grooved, bright terrain.

A sharp boundary divides the ancient dark terrain of Nicholson Regio on Ganymede from the younger, finely grooved bright terrain of Harpagia Sulcus. [NASA]

The frozen, alien landscape of Ganymede contains a little of everything. Shadowy regions of ancient, battered dark terrain are cross-cut by newer patches of ice-rich, grooved bright terrain. Ganymede’s diverse surface features bridge the stark divide between its sibling Galilean moons, evoking both Callisto’s barren, rocky surface, and Europa’s bizarrely cracked and faulted icy landscape.

Ganymede’s complexity deepens when you look beyond its surface. Beneath its outer shell of rock and ice lurks a vast ocean that may contain more water than all of Earth’s oceans combined. What’s more, this planet-sized body (Ganymede is 26% larger than Mercury by volume!) is the only solar-system moon to produce its own, intrinsic magnetic field — which means it hosts a magnetosphere that interacts with the larger Jovian magnetosphere.

size comparison showing three bodies: Ganymede, the Earth, and the Moon.

Size comparison of the Earth, the Moon (top left), and Ganymede (bottom left). [Earth: NASA; Moon: Gregory H. Revera; Ganymede: NASA/JPL/DLR]

Digging Under the Surface

This complicated satellite’s properties means that there are many different processes — originating from both its interior and its exterior — that can modify its surface. To better understand what’s happening across Ganymede’s dramatic landscape, a recent study has now leveraged the high resolution of the Atacama Large Millimeter/submillimeter Array (ALMA) to explore the top layer of this moon’s rocky, icy surface.

Scientist Katherine de Kleer (California Institute of Technology) and collaborators observed Ganymede at several different millimeter wavelengths with ALMA and then compared these data to a thermal model, examining the thermal emission of the moon from its surface down to a depth of roughly 50 cm.

From these results, the team built global temperature maps of Ganymede and explored the vertical profile of the moon’s near-surface material to identify the physical and chemical processes at play in this region.

Taking Ganymede’s Temperature

De Kleer and collaborators found that Ganymede’s material becomes rapidly less porous and more densely packed below the surface: its porosity drops from 85% at the surface to just 10% at depth. This measurement tells us how rapidly the moon’s material responds to changes in heating (for instance, daytime illumination by the Sun): the more porous surface material loses and gains heat more quickly, whereas the deeper material responds slowly.

two plots showing places where temperature deviates from prediction for Ganymede's surface.

These maps of temperature residuals, formed by subtracting the best-fit global models, show regions where Ganymede’s surface temperature deviates from prediction. The bottom map contains the same data as the top, but is overplotted on an albedo map of Ganymede’s surface. [de Kleer et al. 2021]

From their global temperature maps, the authors identified the regions of Ganymede’s surface that deviate from best-fit models — like several bright craters that are substantially colder than predicted. Deviations like this point to variations in the local composition, porosity, and grain properties of the moon’s surface material.

De Kleer and collaborators also noted larger-scale deviations in temperature — in particular, excess heat measured at the equator and cooler temperatures than predicted at middle latitudes. These differences suggest that Ganymede’s surface is predominantly influenced by external processes, like bombardment by micrometeorites and plasma on its orbit around Jupiter.

More detailed studies of Ganymede are likely in the future, and ALMA observations of Europa and Callisto are currently being analyzed — so we can expect further insight into the surfaces of these complex, icy bodies soon.

Citation

“Ganymede’s Surface Properties from Millimeter and Infrared Thermal Emission,” Katherine de Kleer et al 2021 Planet. Sci. J. 2 5. doi:10.3847/PSJ/abcbf4

Active Galactic Nucleus

Supermassive black holes influence many aspects of our universe’s formation and evolution — yet there’s still a lot we don’t know about them! A new census of these lurking sources is helping us to answer questions. 

Hidden in Dust

epoch of reionization

In the schematic timeline of the universe, the epoch of reionization is when the first galaxies and quasars began to form and evolve. Click to enlarge. [NASA]

How many actively accreting supermassive black holes — known as active galactic nuclei, or AGN — lie scattered throughout our universe? How do these black holes grow alongside their galactic hosts? How did the powerful radiation of these AGN contribute to the reionization that shaped our universe into its current composition of low-density, ionized hydrogen?

To answer all these questions,we first need to form a complete census of the AGN in our universe. This prospect is challenging, however: though AGN radiate brightly across the electromagnetic spectrum, many of these mysterious sources lie obscured within dense shrouds of dust that prevent the majority of their radiation from escaping.

High Energy to the Rescue

Fortunately, however, extremely energetic X-ray radiation can escape even heavily obscured AGN. By compiling the observations from multiple space-based X-ray observatories — like NuSTAR, the Neil Gehrels Swift Observatory, and Chandra — a team of scientists has recently built a largely unbiased survey of the AGN throughout our universe, accounting for both unobscured sources and the many sources that are hidden by dust.

plot showing the contribution of reionizing photons from galaxies and AGN, measured vs. redshift.

Ionizing photon densities for AGN (black lines) and galaxies (orange lines) for several different models. The authors’ work suggests that galaxies provide a substantially larger contribution toward reionization than AGN do, at redshifts above z = 6. [Adapted from Ananna et al. 2020]

In a new study led by Tonima Ananna (Dartmouth College and Yale University), this team is now using their census of AGN to better understand the physics of supermassive black hole growth and the impact of these beasts on our universe’s evolution.

Reionizing Our Universe

Ananna and collaborators estimate the total amount of ionizing radiation that’s emitted from all AGN in our universe as a function of redshift, applying observational constraints from both the light that we can see and estimates of the light we can’t see based on the inferred obscured AGN population.

The authors find that the total contribution of ionizing photons that escape from all AGNs is fairly small. The AGN contribution to the reionization of our universe — a process that occurred between a few hundred million and ~1 billion years after the Big Bang — is less than a quarter of the total ionizing photon density at redshifts larger than z > 6. This suggests that first-generation stars and galaxies contributed the vast majority of the radiation that drove reionization.

probability distribution plot for black hole spin shows a peak at large values.

Authors’ probability distribution for the measurement of average black-hole spin among AGN, using several different models. High spins are significantly favored. [Adapted from Ananna et al. 2020]

Dizzy Black Holes

What can we learn about the black holes themselves? Ananna and collaborators use their census to compare the total light emitted from AGNs to the amount of mass they’ve accreted over time. This measure of accretion efficiency can then tell us how fast the supermassive black holes are likely spinning.

Ananna and collaborators find a high likely accretion efficiency — which indicates that, on average, growing supermassive black holes are spinning quite rapidly. If confirmed, this may mean that supermassive black hole growth is dominated by accretion of material (which produces fast-spinning black holes) rather than by mergers (which produce a low average spin since the black holes become randomly oriented).

We still have much to learn about supermassive black holes and their influence on the universe, but this recent study provides a clear step in the right direction.

Citation

“Accretion History of AGNs. III. Radiative Efficiency and AGN Contribution to Reionization,” Tonima Tasnim Ananna et al 2020 ApJ 903 85. doi:10.3847/1538-4357/abb815

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