Search

Recent observations with JWST and ALMA have unveiled galaxies with regular discs at significantly higher redshifts than previously expected. This appears to be in contrast with constraints on the stellar populations of the Milky Way, suggesting that the bulk of the Galactic thin disc formed after $z=1$, and raises questions about the history, evolution, and survivability of primordial discs. Here, we use GigaEris, a state-of-the-art $N$-body, hydrodynamical, cosmological ``zoom-in'' simulation with a billion particles within the virial radius, to delve into the formation of the early kinematically cold discs (KCDs), defined by their ratio between the mean rotational velocity and the radial velocity dispersion, of a Milky Way-sized galaxy at redshifts $z\gtrsim 4$. Our analysis reveals a primarily inward migration pattern for disc stars formed at $z \gtrsim 6$, turning into a mix of inward and outward migration at later times. Stars migrating outwards undergo minimal kinematic heating, and might be identified as part of the thin disc forming at much later epochs. We find that approximately 76 per cent of all stars formed in the KCD at $z \sim 7$ become part of a pseudo-bulge by $z = 4.4$. This proportion decreases to below 10 per cent for KCD stars formed at $z \lesssim 5$. The inward migration of stars born in our KCDs at $z \gtrsim 4$ deviates from the expected inside-out formation scenario of thin discs at lower redshifts. Our results suggest a novel ``two-phase'' disc formation process, whereby the early disc transforms primarily into the pseudo-bulge within less than a billion years, whereas the present-day disc forms subsequently from higher-angular momentum material accreted at later times., Comment: 9 pages, 7 figures, submitted to MNRAS

In this work, we address the following question: ``can we use the current cosmological simulations to identify intermediate-mass black holes (IMBHs) and quantify a putative population of wandering IMBHs?''. We compare wandering-IMBH counts in different simulations with different sub-grid methods and post-processing recipes, the ultimate goal being to aid future wandering-IMBH detection efforts. In particular, we examine simulations in which IMBHs are identified as BH seeds forming at high redshift and those in which they are identified using star clusters as proxies, which implicitly appeals to a stellar dynamical formation channel. In addition, we employ the extremely high-resolution cosmological hydrodynamical ``zoom-in'' simulation GigaEris with the star cluster proxies method to identify IMBHs. We find consistent counts of wandering high-redshift IMBHs across most of the different cosmological simulations employed so far in the literature, despite the different identification approaches, resulting in 5 to 18 wandering IMBHs per Milky Way-sized galaxy at $z \geq 3$. Nevertheless, we argue this is only coincidental, as a significant discrepancy arises when examining the formation sites and the mass ranges of the wandering IMBHs. Furthermore, we cannot determine how many of the IMBHs identified at high redshift in GigaEris will be wandering IMBHs at $z = 0$ as opposed to how many will accrete to the central supermassive BH, promoting its growth. All of this casts doubts on the ability of current cosmological simulations to inform observational searches for wandering IMBHs., Comment: Submitted to MNRAS, 10 pages & 5 Figures

Nuclear star clusters (NSCs) are massive star clusters found in the innermost region of most galaxies. While recent studies suggest that low-mass NSCs in dwarf galaxies form largely out of the merger of globular clusters and NSCs in massive galaxies accumulate mass primarily through central star formation, the formation channel of the Milky Way's NSC is still uncertain. In this work, we use GigaEris, a high resolution N-body, hydrodynamical, cosmological ``zoom-in'' simulation, to investigate a possible formation path of the NSC in the progenitor of a Milky Way-sized galaxy, as well as its relation to the assembly and evolution of the galactic nuclear region. We study the possibility that bound, young, gas-rich, stellar clusters within a radius of 1.5 kpc of the main galaxy's centre at z>4 are the predecessors of the old, metal-poor stellar population of the Milky Way's NSC. We identify 47 systems which satisfy our criteria, with a total stellar mass of $10^{7.5}$ M$_{\odot}$. We demonstrate that both stellar cluster accretion and in-situ star formation will contribute to the formation of the NSC, providing evidence for a hybrid formation scenario for the first time in an N-body, hydrodynamical, cosmological ``zoom-in'' simulation. Additionally, we find that the gas required for in-situ star formation can originate from two pathways: gas-rich stellar clusters and gas influx driven by large-scale non-axisymmetric structures within the galaxy. This is partly supported by the presence of a stellar ring, resulting from gas dynamics, with properties similar to those of the Milky Way's nuclear stellar disc., Comment: 13 pages, 10 figures, Accepted by MNRAS

The formation history of globular clusters (GCs) at redshift $z > 4$ remains an unsolved problem. In this work, we use the cosmological, $N$-body hydrodynamical ``zoom-in'' simulation GigaEris to study the properties and formation of proto-GC candidates in the region surrounding the progenitor of a Milky Way-sized galaxy. The simulation employs a modern implementation of smoothed-particle hydrodynamics, including metal-line cooling and metal and thermal diffusion and allows to resolve systems at the scale of star clusters. We define proto-GC candidate systems as gravitationally bound stellar systems with baryonic mass fraction $F_{\rm b} \geq 0.75$ and stellar velocity dispersion $\sigma_{\star} < 20$ km s$^{-1}$. At $z=4.4$ we identify 9 systems which satisfy our criteria, all of which form between 10 kpc to 30 kpc from the centre of the main host. Their baryonic masses are in the range $10^5$- $10^7$ M$_{\odot}$. By the end of the simulation, they still have a relatively low stellar mass ($M_{\star} \sim 10^4$--$10^5$ M$_{\odot}$) and a metallicity ($-1.8 \lesssim {\rm [Fe/H]} \lesssim -0.8$) similar to the blue Galactic GCs. All of the identified systems except one appear to be associated with gas filaments accreting onto the main galaxy in the circum-galactic region, and formed at $z=5-4$. The exception is the oldest object, which appears to be a stripped compact dwarf galaxy that has interacted with the main halo between $z = 5.8$ and $z=5.2$ and has lost its entire dark matter content due to tidal mass loss., Comment: 11 pages, 8 figures, accepted for publication in MNRAS

High redshift disc galaxies are more gas rich, clumpier, and more turbulent than local Universe galaxies. This early era of galaxy formation imprints the distribution and kinematics of the stars that we observe today, but it is not yet well established how. In this work, we use simulations of isolated Milky Way-mass disc galaxies to study how kinematic properties of stars change when varying the gas fraction. This allows us to quantify the roles played by internal processes, e.g. gas turbulence and gravitational scattering off massive gas clumps, in establishing the observed stellar velocity dispersions and orbital eccentricities. We find that models with gas fractions $>20$ per cent feature a turbulent and clumpy interstellar medium (ISM), leading to zero-age stellar velocity dispersions $\sim 20-30~{\rm km\, s}^{-1}$ and high mean orbital eccentricities. Low eccentricities cannot arise from these physical conditions. For gas fractions below $20$ per cent, the ISM becomes less turbulent, with stellar velocity dispersions $<10~{\rm km\, s}^{-1}$, and nearly circular orbits for young stars. The turbulence present in gas-rich high redshift galaxies hence acts as a `barrier' against the formation of thin discs. We compare our findings to the Milky Way's age-velocity dispersion relation and argue that velocity dispersions imprinted already at star formation by the ISM contribute significantly at all times. Finally, we show that observed orbital eccentricities in the Milky Way's thick and thin discs can be explained entirely as imprints by the star-forming ISM, rather than by mergers or secular processes., Comment: 8 pages, 5 figures, MNRAS submitted

Air pollution is a major risk factor for global health, with both ambient and household air pollution contributing substantial components of the overall global disease burden. One of the key drivers of adverse health effects is fine particulate matter ambient pollution (PM$_{2.5}$) to which an estimated 3 million deaths can be attributed annually. The primary source of information for estimating exposures has been measurements from ground monitoring networks but, although coverage is increasing, there remain regions in which monitoring is limited. Ground monitoring data therefore needs to be supplemented with information from other sources, such as satellite retrievals of aerosol optical depth and chemical transport models. A hierarchical modelling approach for integrating data from multiple sources is proposed allowing spatially-varying relationships between ground measurements and other factors that estimate air quality. Set within a Bayesian framework, the resulting Data Integration Model for Air Quality (DIMAQ) is used to estimate exposures, together with associated measures of uncertainty, on a high resolution grid covering the entire world. Bayesian analysis on this scale can be computationally challenging and here approximate Bayesian inference is performed using Integrated Nested Laplace Approximations. Model selection and assessment is performed by cross-validation with the final model offering substantial increases in predictive accuracy, particularly in regions where there is sparse ground monitoring, when compared to current approaches: root mean square error (RMSE) reduced from 17.1 to 10.7, and population weighted RMSE from 23.1 to 12.1 $\mu$gm$^{-3}$. Based on summaries of the posterior distributions for each grid cell, it is estimated that 92% of the world's population reside in areas exceeding the World Health Organization's Air Quality Guidelines., Comment: 23 pages, 9 figures, 2 tables

The size of silicon transistors used in microelectronic devices is shrinking to the level where quantum effects become important. While this presents a significant challenge for the further scaling of microprocessors, it provides the potential for radical innovations in the form of spin-based quantum computers and spintronic devices. An electron spin in Si can represent a well-isolated quantum bit with long coherence times because of the weak spin-orbit coupling and the possibility to eliminate nuclear spins from the bulk crystal. However, the control of single electrons in Si has proved challenging, and has so far hindered the observation and manipulation of a single spin. Here we report the first demonstration of single-shot, time-resolved readout of an electron spin in Si. This has been performed in a device consisting of implanted phosphorus donors coupled to a metal-oxide-semiconductor single-electron transistor - compatible with current microelectronic technology. We observed a spin lifetime approaching 1 second at magnetic fields below 2 T, and achieved spin readout fidelity better than 90%. High-fidelity single-shot spin readout in Si opens the path to the development of a new generation of quantum computing and spintronic devices, built using the most important material in the semiconductor industry., Comment: 5 pages, 4 figures

We present a systematic study of quasi-one-dimensional density of states (DOS) in electron accumulation layers near a Si-SiO2 interface. In the experiments we have employed two conceptually different objects to probe DOS, namely, a phosphorus donor and a quantum dot, both operating in the single-electron tunneling regime. We demonstrate how the peaks in DOS can be moved in the transport window independently of the other device properties, and in agreement with the theoretical analysis. This method introduces a fast and convenient way of identifying excited states in these emerging nanostructures., Comment: 4 pages, 4 figures

We have developed nano-scale double-gated field-effect-transistors for the study of electron states and transport properties of single deliberately-implanted phosphorus donors. The devices provide a high-level of control of key parameters required for potential applications in nanoelectronics. For the donors, we resolve transitions corresponding to two charge states successively occupied by spin down and spin up electrons. The charging energies and the Lande g-factors are consistent with expectations for donors in gated nanostructures., Comment: 6 pages, 3 figures, journal

Triple donor devices have the potential to exhibit adiabatic tunneling via the CTAP (Coherent Tunneling Adiabatic Passage) protocol which is a candidate transport mechanism for scalable quantum computing. We examine theoretically the statistics of dopant placement using counted ion implantation by employing an analytical treatment of CTAP transport properties under hydrogenic assumptions. We determine theoretical device yields for proof of concept devices for different implant energies. In particular, we determine a significant theoretical device yield (~80%) for 14keV phosphorus in silicon with nominal 20nm spacing., Comment: 10 pages, 3 figures

Exposure to outdoor fine particulate matter (PM2.5) is a leading risk factor for mortality. We develop global estimates of annual PM2.5 concentrations and trends for 1998–2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM2.5 concentrations using geophysical relationships between surface PM2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM2.5 estimates are highly consistent with globally distributed ground monitors (R2 = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM2.5 estimates to predict and account for the residual bias with PM2.5 monitors, yielding even higher cross validated agreement (R2 = 0.90–0.92; slope = 0.90–0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (−0.28 ± 0.03 μg/m3/yr), Europe (−0.15 ± 0.03 μg/m3/yr), India (1.13 ± 0.15 μg/m3/yr), and globally (0.04 ± 0.02 μg/m3/yr). The positive trend (2.44 ± 0.44 μg/m3/yr) for India over 2005–2013 and the negative trend (−3.37 ± 0.38 μg/m3/yr) for China over 2011–2018 are remarkable, with implications for the health of billions of people.

Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1 km2(exp) resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12 km2(exp) horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5∕AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5∕AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5∕AOD lead to an error of 11 µg m−3(exp) in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 µg m−3(exp). Using multi-platform ground, airborne, and radiosonde measurements, we show that uncertainties of modeled PM2.5∕AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998−2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

Exposure to airborne particles can cause acute or chronic respiratory disease and can exacerbate heart disease, some cancers, and other conditions in susceptible populations. Ground stations that monitor fine particulate matter in the air (smaller than 2.5 microns, called PM2.5) are positioned primarily to observe severe pollution events in areas of high population density; coverage is very limited, even in developed countries, and is not well designed to capture long-term, lower-level exposure that is increasingly linked to chronic health effects. In many parts of the developing world, air quality observation is absent entirely. Instruments aboard NASA Earth Observing System satellites, such as the MODerate resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR), monitor aerosols from space, providing once daily and about once-weekly coverage, respectively. However, these data are only rarely used for health applications, in part because the can retrieve the amount of aerosols only summed over the entire atmospheric column, rather than focusing just on the near-surface component, in the airspace humans actually breathe. In addition, air quality monitoring often includes detailed analysis of particle chemical composition, impossible from space. In this paper, near-surface aerosol concentrations are derived globally from the total-column aerosol amounts retrieved by MODIS and MISR. Here a computer aerosol simulation is used to determine how much of the satellite-retrieved total column aerosol amount is near the surface. The five-year average (2001-2006) global near-surface aerosol concentration shows that World Health Organization Air Quality standards are exceeded over parts of central and eastern Asia for nearly half the year.