Search

The low-frequency component of the upcoming Square Kilometre Array Observatory (SKA-Low) will be sensitive enough to construct 3D tomographic images of the 21-cm signal distribution during reionization. However, foreground contamination poses challenges for detecting this signal, and image recovery will heavily rely on effective mitigation methods. We introduce \texttt{SERENEt}, a deep-learning framework designed to recover the 21-cm signal from SKA-Low's foreground-contaminated observations, enabling the detection of ionized (HII) and neutral (HI) regions during reionization. \texttt{SERENEt} can recover the signal distribution with an average accuracy of 75 per cent at the early stages ($\overline{x}_\mathrm{HI}\simeq0.9$) and up to 90 per cent at the late stages of reionization ($\overline{x}_\mathrm{HI}\simeq0.1$). Conversely, HI region detection starts at 92 per cent accuracy, decreasing to 73 per cent as reionization progresses. Beyond improving image recovery, \texttt{SERENEt} provides cylindrical power spectra with an average accuracy exceeding 93 per cent throughout the reionization period. We tested \texttt{SERENEt} on a 10-degree field-of-view simulation, consistently achieving better and more stable results when prior maps were provided. Notably, including prior information about HII region locations improved 21-cm signal recovery by approximately 10 per cent. This capability was demonstrated by supplying \texttt{SERENEt} with ionizing source distribution measurements, showing that high-redshift galaxy surveys of similar observation fields can optimize foreground mitigation and enhance 21-cm image construction., Comment: 16 pages, 14 figures, 1 table

A key problem in agent-based simulation is that integrating qualitative insights from multiple discipline experts is extremely hard. In most simulations, agent capabilities and corresponding behaviour needs to be programmed into the agent. We report on the architecture of a tool that disconnects the programmed functions of the agent, from the acquisition of capability and displayed behaviour. This allows multiple different domain experts to represent qualitative insights, without the need for code to be changed. It also allows a continuous integration (or even change) of qualitative behaviour processes, as more insights are gained. The consequent behaviour observed in the model is both, more faithful to the expert's insight as well as able to be contrasted against other models representing other insights., Comment: 14 pages, 6 figures, accepted at the 19th Social Simulation Conference 2024

This paper demonstrates a disconnected ABM architecture that enables domain experts, and non-programmers to add qualitative insights into the ABM model without the intervention of the programmer. This role separation within the architecture allows policy-makers to systematically experiment with multiple policy interventions, different starting conditions, and visualizations to interrogate their ABM, Comment: 6 pages, including references, 4 figures. Accepted for the demo track at EUMAS 2024

We theoretically study an artificial neuron circuit containing a quantum memristor in the presence of relaxation and dephasing. The charge transport in the quantum element is realized via tunneling of a charge through a quantum particle which shuttles between two terminals -- a functionality reminiscent of classical diffusive memristors. We demonstrate that this physical principle enables hysteretic behavior of the current-voltage characteristics of the quantum device. In addition, being used in artificial neural circuit, the quantum switcher is able to generate self-sustained current oscillations. Our analysis reveals that these self-oscillations are triggered only in quantum regime with a moderate rate of relaxation, and cannot exist either in a purely coherent regime or at a very high decoherence. We investigate the hysteresis and instability leading to the onset of current self-oscillations and analyze their properties depending on the circuit parameters. Our results provide a generic approach to the use of quantum regimes for controlling hysteresis and generating self-oscillations., Comment: 14 pages, 7 figures, 6 appendices

For the first time, we demonstrate the application of an inverse Compton scattering X-ray Source, driven by a laser-plasma accelerator, to image an additively manufactured component. X-rays with a mean energy of 380 keV were produced and used to image an additively manufactured part made of an Inconel (Nickel 718) alloy. Because inverse Compton scattering driven by laser-plasma acceleration produces high-energy X-rays while maintaining a focal spot size on the order of a micron, the source can provide several benefits over conventional X-ray production methods, particularly when imaging superalloy parts, with the potential to revolutionise what can be inspected.

Globally, artificial intelligence (AI) implementation is growing, holding the capability to fundamentally alter organisational processes and decision making. Simultaneously, this brings a multitude of emergent risks to organisations, exposing vulnerabilities in their extant risk management frameworks. This necessitates a greater understanding of how organisations can position themselves in response. This issue is particularly pertinent within the financial sector with relatively mature AI applications matched with severe societal repercussions of potential risk events. Despite this, academic risk management literature is trailing behind the speed of AI implementation. Adopting a management perspective, this study aims to contribute to the understanding of AI risk management in organisations through an exploratory empirical investigation into these practices. In-depth insights are gained through interviews with nine practitioners from different organisations within the UK financial sector. Through examining areas of organisational convergence and divergence, the findings of this study unearth levels of risk management framework readiness and prevailing approaches to risk management at both a processual and organisational level. Whilst enhancing the developing literature concerning AI risk management within organisations, the study simultaneously offers a practical contribution, providing key areas of guidance for practitioners in the operational development of AI risk management frameworks.

Tidal flow of seawater across the Earth's magnetic field induces electric currents and magnetic fields within the ocean and solid Earth. The amplitude and phase of the induced fields depends on electrical properties of both the seawater and the solid Earth, thus can be used as a proxy to study seabed properties or potentially for monitoring long-term trends in the global ocean climatology. This paper presents new global oceanic tidal magnetic field models and their uncertainties for four tidal constituents, including $M_2, N_2, O_1$ and for the first time $Q_1$. Models are obtained through a robust least-squares analysis of magnetic field observations from the \textit{Swarm} and CHAMP satellites using a specially designed data selection scheme. We compare the retrieved magnetic signals with several alternative models reported in the literature. Additionally, we validate them using a series of high-resolution global 3-D electromagnetic simulations and place constraints on the conductivity of sub-oceanic mantle for all tidal constituents, revealing an excellent agreement between all tidal constituents and the oceanic upper mantle structure., Comment: Accepted

We study surface acoustic waves (SAWs) in yttrium iron garnet (YIG)/zinc oxide (ZnO) heterostructures, comparing the results of a computationally lightweight analytical model with time-resolved micro-focused Brillouin light scattering data. Interdigital transducers (IDTs), with operational frequencies in the gigahertz regime, were fabricated on 50 and 100nm thin films of YIG prior to sputter deposition of 830nm and 890nm films of piezoelectric ZnO. We find good agreement between our analytical model and micro-focused Brillouin light scattering data of the IDT frequency response and SAW group velocity, with clear differentiation between the Rayleigh and Sezawa-like modes. This work paves the way for the study of SAW-spin wave (SW) interactions in low SW damping YIG, with the possibility of a method for future energy-efficient SW excitation., Comment: 9 pages, 5 figures. SM 11 pages, 7 figures. Submitted to Physical Review B

Satellite observations of the geomagnetic field contain signals generated in Earth's interior by electrical currents in the core and by magnetized rocks in the lithosphere. At short wavelengths the lithospheric signal dominates, obscuring the signal from the core. Here we present details of a method to co-estimate separate models for the core and lithospheric fields, which are allowed to overlap in spherical harmonic degree, that makes use of prior information to aid the separation. Using a maximum entropy method we estimate probabilistic models for the time-dependent core field and the static lithospheric field that satisfy constraints provided by satellite observations while being consistent with prior knowledge of the spatial covariance and expected magnitude of each field at its source surface., Comment: Accepted version of manuscript

We jointly invert for magnetic and velocity fields at the core surface over the period 1997-2017, directly using ground-based observatory time series and measurements from the CHAMP and Swarm satellites. Satellite data are reduced to the form of virtual observatory time series distributed on a regular grid in space. Such a sequential storage helps incorporate voluminous modern magnetic data into a stochastic Kalman filter, whereby spatial constraints are incorporated based on a norm derived from statistics of a numerical geodynamo model. Our algorithm produces consistent solutions both in terms of the misfit to the data and the estimated posterior model uncertainties. We retrieve core flow features previously documented from the analysis of spherical harmonic field models, such as the eccentric anti-cyclonic gyre. We find enhanced diffusion patterns under both Indonesia and Africa. In contrast to a steady flow that is strong under the Atlantic hemisphere but very weak below the Pacific, interannual motions appear evenly distributed over the two hemispheres. Recovered interannual to decadal flow changes are predominantly symmetrical with respect to the equator outside the tangent cylinder. In contrast, under the Northern Pacific we find an intensification of a high latitude jet, but see no evidence for a corresponding feature in the Southern hemisphere. The largest flow accelerations that we isolate over the studied era are associated with meanders, attached to the equatorward meridional branch of the planetary gyre in the Eastern hemisphere, that is l, Comment: Geophysical Journal International publication; Earth core; Data assimilation; Core flows inversion; 19 pages; 14 figures

We present investigations of rapidly-rotating convection in a thick spherical shell geometry relevant to planetary cores, comparing results from Quasi-Geostrophic, 3D and hybrid QG-3D models. The 170 reported calculations span Ekman numbers, $Ek$, between $10^{-4}$ and $10^{-10}$, Rayleigh numbers, $Ra$, between $2$ and $150$ times supercritical, and Prandtl numbers, $Pr$, between $10$ and $10^{-2}$. In general, we find convection is dominated by zonal jets at mid-depths in the shell, with thermal Rossby waves prominent close to the outer boundary when the driving is weaker. For the specific geometry studied here the hybrid method is best suited for studying convection at modest forcing, $Ra \leq 10 \, Ra_c$ when $Pr=1$, and departs from the 3D model results at higher $Ra$, displaying systematically lower heat transport. We find that the lack of equatorially anti-symmetric and $z$-correlations between temperature and velocity in the buoyancy force contributes to the weaker flows in the hybrid formulation. On the other hand, the QG models yield broadly similar results to the 3D models, for the specific range of parameters explored here. We cannot point to major disagreements between these two datasets at $Pr \geq 0.1$, although the QG model is effectively more strongly driven than the hybrid case. When $Pr$ is decreased, the range of agreement between the Hybrid and 3D models expands, indicating the hybrid method may be better suited to study convection in the regime $Pr \ll 1$. Previously proposed scaling laws for rapidly-rotating convection are retrieved: our simulations are overall well described by a triple balance between Coriolis, inertia and Archimedean forces with the length-scale of the convection following the diffusion-free Rhines-scaling., Comment: Geophysical Journal International publication; Earth core; Thermal convection; Quasi-geostrophic flows; 29 pages; 15 figures

We present dynamos computed using a hybrid QG-3D numerical scheme in a thick spherical shell geometry. Our model is based on a quasi-geostrophic convection code extended with a 3D treatment of heat transport and magnetic induction. We find a collection of self-sustained, multipolar, weak field dynamos with magnetic energy one or two orders of magnitude lower than the kinetic energy. The poloidal magnetic energy is weak and, by construction, there is a lack of equatorially anti-symmetric components in the Buoyancy and Lorentz forces. This leads to configurations where the velocity field is only weakly impacted by the magnetic field, similar to dynamos found in 3D simulations where zonal flows and the $\Omega$-effect dominate. The time-dependence of these dynamos is characterised by quasi-periodic oscillations that we attribute to dynamo waves. The QG-3D dynamos found so far are not Earth-like. The inability of our setup to produce strong, dipole-dominated, magnetic fields likely points to a missing ingredient in our QG flows, and a related lack of helicity and $\alpha$-effect. The models presented here may be more relevant for studying stellar dynamos where zonal flows are known to dominate. This study was carried out at modest control parameters, however moving to lower Ekman numbers, when smaller values of both the magnetic and hydrodynamic Prandtl numbers can be of interest, our approach will be able to gain in efficiency by using relatively coarse grids for the 3D magnetic and temperature fields and a finer grid for the QG velocity field., Comment: Geophysical Journal International publication; Earth core magnetic field; Dynamo modelling; Quasi-geostrophic flows; 18 pages; 9 figures

We consider some integral-geometric quantities that have recently arisen in harmonic analysis and elsewhere, derive some sharp geometric inequalities relating them, and place them in a wider context.

Estimating high resolution models of the Earth's core magnetic field and its time variation in the polar regions requires that one can adequately account for magnetic signals produced by polar ionospheric currents, which vary on a wide range of time and length scales. Limitations of existing ionospheric field models in the challenging polar regions can adversely affect core field models, which in turn has important implications for studies of the core flow dynamics in those regions. Here we implement a new approach to co-estimate a climatological model of the ionospheric field together with a model of the internal and magnetospheric fields within the CHAOS geomagnetic field modelling framework. The parametrization of the ionospheric field exploits non-orthogonal magnetic coordinates and scales linearly with external driving parameters related to the solar wind and the interplanetary magnetic field. Using this approach we derive a new geomagnetic field model from measurements of the magnetic field collected by low Earth orbit satellites, which in addition to the internal field provides estimates of the typical current system in the polar ionosphere. We find that the time derivative of the estimated internal field is less contaminated by the polar currents, which is mostly visible in the zonal and near-zonal terms at high spherical harmonic degrees. Distinctive patches of strong secular variation at the core-mantle boundary, which have important implications for core dynamics, persist. Relaxing the temporal regularisation reveals annual oscillations, which could indicate remaining ionospheric field or related induced signals in the internal field model. Using principal component analysis we find that the annual oscillations mostly affect the zonal low-degree spherical harmonics of the internal field., Comment: 26 pages, 15 figures, 3 tables

In this paper we propose a novel method for zero-shot, cross-domain image retrieval in which we make two key contributions. The first is a test-time re-ranking procedure that enables query-gallery pairs, without meaningful shared visual features, to be matched by incorporating gallery-gallery ranks into an iterative re-ranking process. The second is the use of cross-attention at training time and knowledge distillation to encourage cross-attention-like features to be extracted at test time from a single image. When combined with the Vision Transformer architecture and zero-shot retrieval losses, our approach yields state-of-the-art results on the Sketchy and TU-Berlin sketch-based image retrieval benchmarks. However, unlike many previous methods, none of the components in our approach are engineered specifically towards the sketch-based image retrieval task - it can be generally applied to any cross-domain, zero-shot retrieval task. We therefore also show results on zero-shot cartoon-to-photo retrieval using the Office-Home dataset.

Radio interferometry calibration and Radio Frequency Interference (RFI) removal are usually done separately. Here we show that jointly modelling the antenna gains and RFI has significant benefits when the RFI follows precise trajectories, such as for satellites. One surprising benefit is improved calibration solutions, by leveraging the RFI signal itself. We present tabascal (TrAjectory BAsed RFI Subtraction and CALibration), a new algorithm that jointly models the RFI and calibration parameters in visibilities. We test tabascal on simulated MeerKAT calibration observations contaminated by satellite-based RFI. We obtain gain estimates that are both unbiased and up to an order of magnitude better constrained compared to uncontaminated data. When combined with an ad hoc RFI subtraction scheme, tabascal solutions can be further applied to an adjacent target observation: 5 minutes of calibration data results in an image with about a third the noise achieved when using flagging alone. The recovered flux distribution of RFI subtracted data was on par with uncontaminated data. In contrast, RFI flagging alone resulted in a higher detection threshold and consistent underestimation of source fluxes. For a mean RFI amplitude of 17 Jy, using RFI subtraction leads to less than 1% loss of data compared to 75% data loss from an ideal $3\sigma$ flagging algorithm, a very significant increase in data available for science analysis. Although we have examined the case of satellite RFI, tabascal should work for any RFI moving on parameterizable trajectories, relative to the phase centre, such as planes and/or objects fixed to the ground., Comment: 21 pages, 17 figures, 4 tables

Video game testing requires game-specific knowledge as well as common sense reasoning about the events in the game. While AI-driven agents can satisfy the first requirement, it is not yet possible to meet the second requirement automatically. Therefore, video game testing often still relies on manual testing, and human testers are required to play the game thoroughly to detect bugs. As a result, it is challenging to fully automate game testing. In this study, we explore the possibility of leveraging the zero-shot capabilities of large language models for video game bug detection. By formulating the bug detection problem as a question-answering task, we show that large language models can identify which event is buggy in a sequence of textual descriptions of events from a game. To this end, we introduce the GameBugDescriptions benchmark dataset, which consists of 167 buggy gameplay videos and a total of 334 question-answer pairs across 8 games. We extensively evaluate the performance of six models across the OPT and InstructGPT large language model families on our benchmark dataset. Our results show promising results for employing language models to detect video game bugs. With the proper prompting technique, we could achieve an accuracy of 70.66%, and on some video games, up to 78.94%. Our code, evaluation data and the benchmark can be found on https://asgaardlab.github.io/LLMxBugs