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S. Gibson

Publications and source records attributed to S. Gibson.

12 recordsLinked to original sources
arXiv2023

Ground-based Synoptic Studies of the Sun

Ground-based synoptic solar observations provide critical contextual data used to model the large-scale state of the heliosphere. The next decade will see a combination of ground-based telescopes and space missions that will study our Sun's atmosphere microscopic processes with unprecedented detail. This white paper describes contextual observations from a ground-based network needed to fully exploit this new knowledge of the underlying physics that leads to the magnetic linkages between the heliosphere and the Sun. This combination of a better understanding of small-scale processes and the appropriate global context will enable a physics-based approach to Space Weather comparable to Terrestrial Weather forecasting.

astro-ph.IM↗
arXiv2021

Joint machine learning analysis of muon spectroscopy data from different materials

Machine learning (ML) methods have proved to be a very successful tool in physical sciences, especially when applied to experimental data analysis. Artificial intelligence is particularly good at recognizing patterns in high dimensional data, where it usually outperforms humans. Here we applied a simple ML tool called principal component analysis (PCA) to study data from muon spectroscopy. The measured quantity from this experiment is an asymmetry function, which holds the information about the average intrinsic magnetic field of the sample. A change in the asymmetry function might indicate a phase transition; however, these changes can be very subtle, and existing methods of analyzing the data require knowledge about the specific physics of the material. PCA is an unsupervised ML tool, which means that no assumption about the input data is required, yet we found that it still can be successfully applied to asymmetry curves, and the indications of phase transitions can be recovered. The method was applied to a range of magnetic materials with different underlying physics. We discovered that performing PCA on all those materials simultaneously can have a positive effect on the clarity of phase transition indicators and can also improve the detection of the most important variations of asymmetry functions. For this joint PCA we introduce a simple way to track the contributions from different materials for a more meaningful analysis.

cond-mat.mtrl-sci↗
arXiv2020

Machine Learning approach to muon spectroscopy analysis

In recent years, Artificial Intelligence techniques have proved to be very successful when applied to problems in physical sciences. Here we apply an unsupervised Machine Learning (ML) algorithm called Principal Component Analysis (PCA) as a tool to analyse the data from muon spectroscopy experiments. Specifically, we apply the ML technique to detect phase transitions in various materials. The measured quantity in muon spectroscopy is an asymmetry function, which may hold information about the distribution of the intrinsic magnetic field in combination with the dynamics of the sample. Sharp changes of shape of asymmetry functions - measured at different temperatures - might indicate a phase transition. Existing methods of processing the muon spectroscopy data are based on regression analysis, but choosing the right fitting function requires knowledge about the underlying physics of the probed material. Conversely, Principal Component Analysis focuses on small differences in the asymmetry curves and works without any prior assumptions about the studied samples. We discovered that the PCA method works well in detecting phase transitions in muon spectroscopy experiments and can serve as an alternative to current analysis, especially if the physics of the studied material are not entirely known. Additionally, we found out that our ML technique seems to work best with large numbers of measurements, regardless of whether the algorithm takes data only for a single material or whether the analysis is performed simultaneously for many materials with different physical properties.

cond-mat.mtrl-sci↗
arXiv2020

Major Scientific Challenges and Opportunities in Understanding Magnetic Reconnection and Related Explosive Phenomena in Solar and Heliospheric Plasmas

Magnetic reconnection underlies many explosive phenomena in the heliosphere and in laboratory plasmas. The new research capabilities in theory/simulations, observations, and laboratory experiments provide the opportunity to solve the grand scientific challenges summarized in this whitepaper. Success will require enhanced and sustained investments from relevant funding agencies, increased interagency/international partnerships, and close collaborations of the solar, heliospheric, and laboratory plasma communities. These investments will deliver transformative progress in understanding magnetic reconnection and related explosive phenomena including space weather events.

physics.space-ph↗
arXiv2020

The Science Case for the $4π$ Perspective: A Polar/Global View for Studying the Evolution & Propagation of the Solar Wind and Solar Transients

To make progress on the open questions on CME/CIR propagation, their interactions and the role and nature of the ambient solar wind, we need spatially resolved coverage of the inner heliosphere -- both in-situ and (critically) imaging -- at temporal scales matching the evolutionary timescales of these phenomena (tens of minutes to hours), and from multiple vantage points. The polar vantage is uniquely beneficial because of the wide coverage and unique perspective it provides. The ultimate goal is to achieve full $4π$ coverage of the solar surface and atmosphere by 2050.

astro-ph.SR↗
arXiv2020

The Laser-hybrid Accelerator for Radiobiological Applications

The `Laser-hybrid Accelerator for Radiobiological Applications', LhARA, is conceived as a novel, uniquely-flexible facility dedicated to the study of radiobiology. The technologies demonstrated in LhARA, which have wide application, will be developed to allow particle-beam therapy to be delivered in a completely new regime, combining a variety of ion species in a single treatment fraction and exploiting ultra-high dose rates. LhARA will be a hybrid accelerator system in which laser interactions drive the creation of a large flux of protons or light ions that are captured using a plasma (Gabor) lens and formed into a beam. The laser-driven source allows protons and ions to be captured at energies significantly above those that pertain in conventional facilities, thus evading the current space-charge limit on the instantaneous dose rate that can be delivered. The laser-hybrid approach, therefore, will allow the vast ``terra incognita'' of the radiobiology that determines the response of tissue to ionising radiation to be studied with protons and light ions using a wide variety of time structures, spectral distributions, and spatial configurations at instantaneous dose rates up to and significantly beyond the ultra-high dose-rate `FLASH' regime. It is proposed that LhARA be developed in two stages. In the first stage, a programme of in vitro radiobiology will be served with proton beams with energies between 10MeV and 15MeV. In stage two, the beam will be accelerated using a fixed-field accelerator (FFA). This will allow experiments to be carried out in vitro and in vivo with proton beam energies of up to 127MeV. In addition, ion beams with energies up to 33.4MeV per nucleon will be available for in vitro and in vivo experiments. This paper presents the conceptual design for LhARA and the R&D programme by which the LhARA consortium seeks to establish the facility.

physics.acc-ph↗
arXiv2020

Solar physics in the 2020s: DKIST, parker solar probe, and solar orbiter as a multi-messenger constellation

The National Science Foundation (NSF) Daniel K. Inouye Solar Telescope (DKIST) is about to start operations at the summit of Haleakala (Hawaii). DKIST will join the early science phases of the NASA and ESA Parker Solar Probe and Solar Orbiter encounter missions. By combining in-situ measurements of the near-sun plasma environment and detail remote observations of multiple layers of the Sun, the three observatories form an unprecedented multi-messenger constellation to study the magnetic connectivity inside the solar system. This white paper outlines the synergistic science that this multi-messenger suite enables.

astro-ph.SR↗
arXiv2016

Diagnostics of Coronal Magnetic Fields Through the Hanle Effect in UV and IR Lines

The plasma thermodynamics in the solar upper atmosphere, particularly in the corona, are dominated by the magnetic field, which controls the flow and dissipation of energy. The relative lack of knowledge of the coronal vector magnetic field is a major handicap for progress in coronal physics. This makes the development of measurement methods of coronal magnetic fields a high priority in solar physics. The Hanle effect in the UV and IR spectral lines is a largely unexplored diagnostic. We use magnetohydrodynamic (MHD) simulations to study the magnitude of the signal to be expected for typical coronal magnetic fields for selected spectral lines in the UV and IR wavelength ranges, namely the H I Ly-$α$ and the He I 10830 Å lines. We show that the selected lines are useful for reliable diagnosis of coronal magnetic fields. The results show that the combination of polarization measurements of spectral lines with different sensitivities to the Hanle effect may be most appropriate for deducing coronal magnetic properties from future observations.

astro-ph.SR↗
arXiv2013

Observations of Coronal Mass Ejections with the Coronal Multichannel Polarimeter

The Coronal Multichannel Polarimeter (CoMP) measures not only the polarization of coronal emission, but also the full radiance profiles of coronal emission lines. For the first time, CoMP observations provide high-cadence image sequences of the coronal line intensity, Doppler shift and line width simultaneously in a large field of view. By studying the Doppler shift and line width we may explore more of the physical processes of CME initiation and propagation. Here we identify a list of CMEs observed by CoMP and present the first results of these observations. Our preliminary analysis shows that CMEs are usually associated with greatly increased Doppler shift and enhanced line width. These new observations provide not only valuable information to constrain CME models and probe various processes during the initial propagation of CMEs in the low corona, but also offer a possible cost-effective and low-risk means of space weather monitoring.

astro-ph.SR↗
arXiv2012

Planar Pixel Sensors for the ATLAS Upgrade: Beam Tests results

Results of beam tests with planar silicon pixel sensors aimed towards the ATLAS Insertable B-Layer and High Luminosity LHC (HL-LHC) upgrades are presented. Measurements include spatial resolution, charge collection performance and charge sharing between neighbouring cells as a function of track incidence angle for different bulk materials. Measurements of n-in-n pixel sensors are presented as a function of fluence for different irradiations. Furthermore p-type silicon sensors from several vendors with slightly differing layouts were tested. All tested sensors were connected by bump-bonding to the ATLAS Pixel read-out chip. We show that both n-type and p-type tested planar sensors are able to collect significant charge even after integrated fluences expected at HL-LHC.

physics.ins-det↗
arXiv2009

How do Galaxies Accrete Gas and Form Stars?

Great strides have been made in the last two decades in determining how galaxies evolve from their initial dark matter seeds to the complex structures we observe at z=0. The role of mergers has been documented through both observations and simulations, numerous satellites that may represent these initial dark matter seeds have been discovered in the Local Group, high redshift galaxies have been revealed with monstrous star formation rates, and the gaseous cosmic web has been mapped through absorption line experiments. Despite these efforts, the dark matter simulations that include baryons are still unable to accurately reproduce galaxies. One of the major problems is our incomplete understanding of how a galaxy accretes its baryons and subsequently forms stars. Galaxy formation simulations have been unable to accurately represent the required gas physics on cosmological timescales, and observations have only just begun to detect the star formation fuel over a range of redshifts and environments. How galaxies obtain gas and subsequently form stars is a major unsolved, yet tractable problem in contemporary extragalactic astrophysics. In this paper we outline how progress can be made in this area in the next decade.

astro-ph.CO↗