Searcharxiv⌕ Search

arXiv subjects

Thomas Williams

Publications and source records attributed to Thomas Williams.

31 records · Page 2Linked to original sources
arXiv2022

Automated detection of coronaL MAss ejecta origiNs for space weather AppliCations (ALMANAC)

Alerts of potentially hazardous coronal mass ejections (CME) are based on the detection of rapid changes in remote observations of the solar atmosphere. This paper presents a method that detects and estimates the central coordinates of CME eruptions in Extreme Ultraviolet (EUV) data, with the dual aim of providing an early alert, and giving an initial estimate of the CME direction of propagation to a CME geometrical model. In particular, we plan to link the ALMANAC method to the CME detection and characterisation module of the Space Weather Empirical Ensemble Package (SWEEP), which is a fully automated modular software package for operational space weather capability currently being developed for the UK Meteorological Office. In this work, ALMANAC is applied to observations by the Atmospheric Imaging Assembly (AIA) aboard the Solar Dynamics Observatory (SDO). As well as presenting the method, a proof of concept test is made on a limited set of data associated with twenty halo CMEs recorded by the Coordinated Data Analysis Workshop (CDAW) catalogue near the activity maximum of solar cycle 24. SDO/AIA data for each event is processed at 6 minute cadence to identify the on-disk location and time of each CME. The absolute mean deviance between the ALMANAC and CDAW source event coordinates are within 37.05 +- 29.71 minutes and 11.01 +- 10.39 degrees. These promising results give a solid foundation for future work, and will provide initial constraints to an automated CME alert and forecasting system.

astro-ph.SR↗
arXiv2022

Choice of spatial discretisation influences the progression of viral infection within multicellular tissues

There has been an increasing recognition of the utility of models of the spatial dynamics of viral spread within tissues. Multicellular models, where cells are represented as discrete regions of space coupled to a virus density surface, are a popular approach to capture these dynamics. Conventionally, such models are simulated by discretising the viral surface and depending on the rate of viral diffusion and other considerations, a finer or coarser discretisation may be used. The impact that this choice may have on the behaviour of the system has not been studied. Here we demonstrate that, if rates of viral diffusion are small, then the choice of spatial discretisation of the viral surface can have quantitative and even qualitative influence on model outputs. We investigate in detail the mechanisms driving these phenomena and discuss the constraints on the design and implementation of multicellular viral dynamics models for different parameter configurations.

q-bio.QM↗
arXiv2022

A solar-cycle study of coronal rotation: large variations, rapid changes, and implications for solar wind models

Information on the rotation rate of the corona, and its variation over latitude and solar cycle, is valuable for making global connections between the corona and the Sun, for global estimates of reconnection rates, and as a basic parameter for solar wind modelling. Here, we use a time series of tomographical maps gained from coronagraph observations between 2007 - 2020 to directly measure the longitudinal drift of high-density streamers over time. The method reveals abrupt changes in rotation rates, revealing a complex relationship between the coronal rotation and the underlying photosphere. The majority of rates are between -1.0 to +0.5$^\circ$/day relative to the standard Carrington rate of 14.18$^\circ$/day, although rates are measured as low as -2.2$^\circ$/day and as high as 1.6$^\circ$/day. Equatorial rotation rates during the 2008 solar minimum are slightly faster than the Carrington rate, with an abrupt switch to slow rotation in 2009, then a return to faster rates in 2017. Abrupt changes and large variations in rates are seen at all latitudes. Comparison with a magnetic model suggests that periods of equatorial fast rotation are associated with times when a large proportion of the magnetic footpoints of equatorial streamers are near the equator, and we interpret the abrupt changes in terms of the latitudinal distribution of the streamer photospheric footpoints. The coronal rotation rate is a key parameter for solar wind models, and variations of up to a degree per day or more can lead to large systematic errors over forecasting periods of longer than a few days. The approach described in this paper gives corrected values that can form a part of future forecasting efforts.

astro-ph.SR↗
arXiv2021

Star Cluster Classification in the PHANGS-HST Survey: Comparison between Human and Machine Learning Approaches

When completed, the PHANGS-HST project will provide a census of roughly 50,000 compact star clusters and associations, as well as human morphological classifications for roughly 20,000 of those objects. These large numbers motivated the development of a more objective and repeatable method to help perform source classifications. In this paper we consider the results for five PHANGS-HST galaxies (NGC 628, NGC 1433, NGC 1566, NGC 3351, NGC 3627) using classifications from two convolutional neural network architectures (RESNET and VGG) trained using deep transfer learning techniques. The results are compared to classifications performed by humans. The primary result is that the neural network classifications are comparable in quality to the human classifications with typical agreement around 70 to 80$\%$ for Class 1 clusters (symmetric, centrally concentrated) and 40 to 70$\%$ for Class 2 clusters (asymmetric, centrally concentrated). If Class 1 and 2 are considered together the agreement is 82 $\pm$ 3$\%$. Dependencies on magnitudes, crowding, and background surface brightness are examined. A detailed description of the criteria and methodology used for the human classifications is included along with an examination of systematic differences between PHANGS-HST and LEGUS. The distribution of data points in a colour-colour diagram is used as a 'figure of merit' to further test the relative performances of the different methods. The effects on science results (e.g., determinations of mass and age functions) of using different cluster classification methods are examined and found to be minimal.

astro-ph.GA↗
arXiv2021

The cross-sectional shape and height expansion of coronal loops: High-resolution Coronal Imager (Hi-C) analysis of AR 12712

Coronal loop observations have existed for many decades yet the precise shape of these fundamental coronal structures is still widely debated since the discovery that they appear to undergo negligible expansion between their footpoints and apex. In this work a selection of eight EUV loops and their twenty-two sub-element strands are studied from the second successful flight of NASA's High resolution Coronal Imager (Hi-C 2.1). Four of the loops correspond to open fan structures with the other four considered to be magnetically closed loops. Width analysis is performed on the loops and their sub-resolution strands using our method of fitting multiple Gaussian profiles to cross-sectional intensity slices. It is found that whilst the magnetically closed loops and their sub-element strands do not expand along their observable length, open fan structures may expand an additional 150% of their initial width. Following recent work, the Pearson correlation coefficient between peak intensity and loop/strand width are found to be predominantly positively correlated for the loops (~88%) and their sub-element strands (~80%). These results align with the hypothesis of Klimchuk & DeForest that loops and - for the first time - their sub-element strands have approximately circular cross-sectional profiles.

astro-ph.SR↗
arXiv2021

Multi-Stranded Coronal Loops: Quantifying Strand Number and Heating Frequency from Simulated Solar Dynamics Observatory (SDO) Atmospheric Imaging Assembly (AIA) Observations

Coronal loops form the basic building blocks of the magnetically closed solar corona yet much is still to be determined concerning their possible fine-scale structuring and the rate of heat deposition within them. Using an improved multi-stranded loop model to better approximate the numerically challenging transition region, this paper examines synthetic NASA Solar Dynamics Observatory's (SDO) Atmospheric Imaging Assembly (AIA) emission simulated in response to a series of prescribed spatially and temporally random, impulsive and localised heating events across numerous sub-loop elements with a strong weighting towards the base of the structure; the nanoflare heating scenario. The total number of strands and nanoflare repetition times are varied systematically in such a way that the total energy content remains approximately constant across all the cases analysed. Repeated time lag detection during an emission time series provides a good approximation for the nanoflare repetition time for low-frequency heating. Furthermore, using a combination of AIA 171/193 and 193/211 channel ratios in combination with spectroscopic determination of the standard deviation of the loop apex temperature over several hours alongside simulations from the outlined multi-stranded loop model, it is demonstrated that both the imposed heating rate and number of strands can be realised.

astro-ph.SR↗
arXiv2021

Resolving the Dust-to-Metals Ratio and CO-to-H$_2$ Conversion Factor in the Nearby Universe

We investigate the relationship between the dust-to-metals ratio (D/M) and the local interstellar medium environment at ~2 kpc resolution in five nearby galaxies: IC342, M31, M33, M101, and NGC628. A modified blackbody model with a broken power-law emissivity is used to model the dust emission from 100 to 500 um observed by Herschel. We utilize the metallicity gradient derived from auroral line measurements in HII regions whenever possible. Both archival and new CO rotational line and HI 21 cm maps are adopted to calculate gas surface density, including new wide field CO and HI maps for IC342 from IRAM and the VLA, respectively. We experiment with several prescriptions of CO-to-H$_2$ conversion factor, and compare the resulting D/M-metallicity and D/M-density correlations, both of which are expected to be non-negative from depletion studies. The D/M is sensitive to the choice of the conversion factor. The conversion factor prescriptions based on metallicity only yield too much molecular gas in the center of IC342 to obtain the expected correlations. Among the prescriptions tested, the one that yields the expected correlations depends on both metallicity and surface density. The 1-$σ$ range of the derived D/M spans 0.40-0.58. Compared to chemical evolution models, our measurements suggest that the dust growth time scale is much shorter than the dust destruction time scale. The measured D/M is consistent with D/M in galaxy-integrated studies derived from infrared dust emission. Meanwhile, the measured D/M is systematically higher than the D/M derived from absorption, which likely indicates a systematic offset between the two methods.

astro-ph.GA↗
arXiv2020

Evidence for and Analysis of Multiple Hidden Coronal Strands in Cross-Sectional Emission Profiles: Further Results from NASA's High-resolution Solar Coronal Imager

Previous work utilising NASA's High-resolution Coronal Imager (Hi-C 2.1) 17.2 nm observations revealed that, even at the increased spatial scales available in the data-set, there may be evidence for coronal structures that are still not fully resolved. In this follow-up study, cross-section slices of coronal strands are taken across the Hi-C 2.1 field-of-view. Following previous loop width studies, the background emission is removed to isolate the coronal strands. The resulting intensity variations are reproduced by simultaneously fitting multiple Gaussian profiles using a non-linear least-squares curve fitting method. In total, 183 Gaussian profiles are examined for possible structures that are hinted at in the data. The full width at half maximum (FWHM) is determined for each Gaussian, which are then collated and analysed. The most frequent structural widths are $\approx$450-575 km with 47% of the strand widths beneath NASA's Solar Dynamics Observatory Atmospheric Imaging Assembly (AIA) resolving scale (600-1000 km). Only 17% reside beneath an AIA pixel width (435 km) with just 6% of the strands at the Hi-C 2.1 resolving scale ($\approx$220-340 km). These results suggest that non-Gaussian shaped cross-sectional emission profiles observed by Hi-C 2.1 are the result of multiple strands along the integrated line-of-sight that can be resolved, rather than being the result of even finer sub-resolution elements.

astro-ph.SR↗
arXiv2020

Is the High-Resolution Coronal Imager Resolving Coronal Strands? Results from AR 12712

Following the success of the first mission, the High-Resolution Coronal Imager (Hi-C) was launched for a third time (Hi-C 2.1) on 29th May 2018 from the White Sands Missile Range, NM, USA. On this occasion, 329 seconds of 17.2 nm data of target active region AR 12712 was captured with a cadence of ~4s, and a plate scale of 0.129''/pixel. Using data captured by Hi-C 2.1 and co-aligned observations from SDO/AIA 17.1 nm we investigate the widths of 49 coronal strands. We search for evidence of substructure within the strands that is not detected by AIA, and further consider whether these strands are fully resolved by Hi-C 2.1. With the aid of Multi-Scale Gaussian Normalization (MGN), strands from a region of low-emission that can only be visualized against the contrast of the darker, underlying moss are studied. A comparison is made between these low-emission strands with those from regions of higher emission within the target active region. It is found that Hi-C 2.1 can resolve individual strands as small as ~202km, though more typical strands widths seen are ~513km. For coronal strands within the region of low-emission, the most likely width is significantly narrower than the high-emission strands at ~388km. This places the low-emission coronal strands beneath the resolving capabilities of SDO/AIA, highlighting the need of a permanent solar observatory with the resolving power of Hi-C.

astro-ph.SR↗
arXiv2019

Astro2020: Unleashing the Potential of Dust Emission as a Window onto Galaxy Evolution

We present the severe, systematic uncertainties currently facing our understanding of dust emission, which stymie our ability to truly exploit dust as a tool for studying galaxy evolution. We propose a program of study to tackle these uncertainties, describe the necessary facilities, and discuss the potential science gains that will result. This white paper was submitted to the US National Academies' Astro2020 Decadal Survey on Astronomy and Astrophysics.

astro-ph.GA↗
arXiv2018

JINGLE, a JCMT legacy survey of dust and gas for galaxy evolution studies: I. Survey overview and first results

JINGLE is a new JCMT legacy survey designed to systematically study the cold interstellar medium of galaxies in the local Universe. As part of the survey we perform 850um continuum measurements with SCUBA-2 for a representative sample of 193 Herschel-selected galaxies with M*>10^9Msun, as well as integrated CO(2-1) line fluxes with RxA3m for a subset of 90 of these galaxies. The sample is selected from fields covered by the Herschel-ATLAS survey that are also targeted by the MaNGA optical integral-field spectroscopic survey. The new JCMT observations combined with the multi-wavelength ancillary data will allow for the robust characterization of the properties of dust in the nearby Universe, and the benchmarking of scaling relations between dust, gas, and global galaxy properties. In this paper we give an overview of the survey objectives and details about the sample selection and JCMT observations, present a consistent 30 band UV-to-FIR photometric catalog with derived properties, and introduce the JINGLE Main Data Release (MDR). Science highlights include the non-linearity of the relation between 850um luminosity and CO line luminosity, and the serendipitous discovery of candidate z>6 galaxies.

astro-ph.GA↗
arXiv2018

Models for Capturing Temporal Smoothness in Evolving Networks for Learning Latent Representation of Nodes

In a dynamic network, the neighborhood of the vertices evolve across different temporal snapshots of the network. Accurate modeling of this temporal evolution can help solve complex tasks involving real-life social and interaction networks. However, existing models for learning latent representation are inadequate for obtaining the representation vectors of the vertices for different time-stamps of a dynamic network in a meaningful way. In this paper, we propose latent representation learning models for dynamic networks which overcome the above limitation by considering two different kinds of temporal smoothness: (i) retrofitted, and (ii) linear transformation. The retrofitted model tracks the representation vector of a vertex over time, facilitating vertex-based temporal analysis of a network. On the other hand, linear transformation based model provides a smooth transition operator which maps the representation vectors of all vertices from one temporal snapshot to the next (unobserved) snapshot-this facilitates prediction of the state of a network in a future time-stamp. We validate the performance of our proposed models by employing them for solving the temporal link prediction task. Experiments on 9 real-life networks from various domains validate that the proposed models are significantly better than the existing models for predicting the dynamics of an evolving network.

cs.SI↗