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Existence of quasi-static negative capacitance (QSNC) was proposed from an interpretation of the widely accepted Landau model of ferroelectrics. However, many works showed not to support the QSNC theory, making it controversial. In this letter we show the Landau model when used together with transition-state-theory, can connect various models including first-principles, Landau, Preisach and nucleation limited switching while it does not predict the existence of QSNC.

Surface waves on Earth's magnetopause have a controlling effect upon global magnetospheric dynamics. Since spacecraft provide sparse in situ observation points, remote sensing these modes using ground-based instruments in the polar regions is desirable. However, many open conceptual questions on the expected signatures remain. Therefore, we provide predictions of key qualitative features expected in auroral, ionospheric, and ground magnetic observations through both magnetohydrodynamic theory and a global coupled magnetosphere-ionosphere simulation of a magnetopause surface eigenmode. These show monochromatic oscillatory field-aligned currents, due to both the surface mode and its non-resonant Alfv\'en coupling, are present throughout the magnetosphere. The currents peak in amplitude at the equatorward edge of the magnetopause boundary layer, not the open-closed boundary as previously thought. They also exhibit slow poleward phase motion rather than being purely evanescent. We suggest the upward field-aligned current perturbations may result in periodic auroral brightenings. In the ionosphere, convection vortices circulate the poleward moving field-aligned current structures. Finally, surface mode signals are predicted in the ground magnetic field, with ionospheric Hall currents rotating perturbations by approximately (but not exactly) 90{\deg} compared to the magnetosphere. Thus typical dayside magnetopause surface modes should be strongest in the East-West ground magnetic field component. Overall, all ground-based signatures of the magnetopause surface mode are predicted to have the same frequency across L-shells, amplitudes that maximise near the magnetopause's equatorward edge, and larger latitudinal scales than for field line resonance. Implications in terms of ionospheric Joule heating and geomagnetically induced currents are discussed.

Space weather and its impact on infrastructure presents a clear risk in the modern era, as evidenced by the adverse effects of geomagnetically induced currents (GICs) in power networks. To model GICs, ground-based geomagnetic field (B-field) measurements are critical and need to be available in the region of interest. A challenge globally lies in the sparse distribution of magnetometer arrays, which are seldom located near critical power network nodes. Interpolation of the geomagnetic field (B-field) is often needed, with the spherical elementary current system (SECS) approach developed for high-latitude regions favoured. We adapt this interpolation scheme to include low-cost variometers to interpolate dB/dt directly and increase interpolation accuracy. A further adaptation to the scheme is to physically represent the mid-latitude context where most power networks and pipelines lie. The driving current systems in these regions differ from their high-latitude counterparts. Using a physics-consistent mid-latitude version of SECS, we show why previous implementations in Southern Africa are incorrect but still result in useful interpolation. The scope of these adaptations not only has direct application to research in general, but also to utilities, where effective low-cost instrumentation can be used to improve GIC modelling accuracy., Comment: 10 pages, 8 figures, submitted to Advances in Space Research

As the superconducting qubit platform matures towards ever-larger scales in the race towards a practical quantum computer, limitations due to qubit inhomogeneity through lack of process control become apparent. To benefit from the advanced process control in industry-scale CMOS fabrication facilities, different processing methods will be required. In particular, the double-angle evaporation and lift-off techniques used for current, state-of-the art superconducting qubits are generally incompatible with modern day manufacturable processes. Here, we demonstrate a fully CMOS compatible qubit fabrication method, and show results from overlap Josephson junction devices with long coherence and relaxation times, on par with the state-of-the-art. We experimentally verify that Argon milling - the critical step during junction fabrication - and a subtractive etch process nevertheless result in qubits with average qubit energy relaxation times T1 reaching 70 $\mu$s, with maximum values exceeding 100 $\mu$s. Furthermore, we show that our results are still limited by surface losses and not, crucially, by junction losses. The presented fabrication process therefore heralds an important milestone towards a manufacturable 300 mm CMOS process for high-coherence superconducting qubits and has the potential to advance the scaling of superconducting device architectures., Comment: 13+6 pages, 3+6 figures, 0+2 tables

Using micromagnets to enable electron spin manipulation in silicon qubits has emerged as a very popular method, enabling single-qubit gate fidelities larger than 99:9%. However, these micromagnets also apply stray magnetic field gradients onto the qubits, making the spin states susceptible to electric field noise and limiting their coherence times. We describe here a magnet design that minimizes qubit dephasing, while allowing for fast qubit control and addressability. Specifically, we design and optimize magnet dimensions and position relative to the quantum dots, minimizing dephasing from magnetic field gradients. The micromagnet-induced dephasing rates with this design are up to 3-orders of magnitude lower than state-of-the-art implementations, allowing for long coherence times. This design is robust against fabrication errors, and can be combined with a wide variety of silicon qubit device geometries, thereby allowing exploration of coherence limiting factors and novel upscaling approaches., Comment: 5 pages, 4 figures

Larger arrays of electron spin qubits require radical improvements in fabrication and device uniformity. Here we demonstrate excellent qubit device uniformity and tunability from 300K down to mK temperatures. This is achieved, for the first time, by integrating an overlapping polycrystalline silicon-based gate stack in an 'all-Silicon' and lithographically flexible 300mm flow. Low-disorder Si/SiO$_2$ is proved by a 10K Hall mobility of $1.5 \cdot 10^4$ $cm^2$/Vs. Well-controlled sensors with low charge noise (3.6 $\mu$eV/$\sqrt{\mathrm{Hz}}$ at 1 Hz) are used for charge sensing down to the last electron. We demonstrate excellent and reproducible interdot coupling control over nearly 2 decades (2-100 GHz). We show spin manipulation and single-shot spin readout, extracting a valley splitting energy of around 150 $\mu$eV. These low-disorder, uniform qubit devices and 300mm fab integration pave the way for fast scale-up to large quantum processors., Comment: 2021 Symposium on VLSI Circuits. IEEE, 2021. Copyright 2021 by The Japan Society of Applied Physics. All rights reserved

The coherence of state-of-the-art superconducting qubit devices is predominantly limited by two-level-system defects, found primarily at amorphous interface layers. Reducing microwave loss from these interfaces by proper surface treatments is key to push the device performance forward. Here, we study niobium resonators after removing the native oxides with a hydrofluoric acid etch. We investigate the reappearance of microwave losses introduced by surface oxides that grow after exposure to the ambient environment. We find that losses in quantum devices are reduced by an order of magnitude, with internal Q-factors reaching up to 7 $\cdot$ 10$^6$ in the single photon regime, when devices are exposed to ambient conditions for 16 min. Furthermore, we observe that Nb2O5 is the only surface oxide that grows significantly within the first 200 hours, following the extended Cabrera-Mott growth model. In this time, microwave losses scale linearly with the Nb$_2$O$_5$ thickness, with an extracted loss tangent tan$\delta$ = 9.9 $\cdot$ 10$^{-3}$. Our findings are of particular interest for devices spanning from superconducting qubits, quantum-limited amplifiers, microwave kinetic inductance detectors to single photon detectors., Comment: 5+11 pages, 5+7 figures, 0+7 tables

As reliance on power networks has increased over the last century, the risk of damage from geomagnetically induced currents (GICs) has become a concern to utilities. The current state of the art in GIC modelling requires significant geophysical modelling and a theoretically derived network response, but has limited empirical validation. In this work, we introduce a probabilistic engineering step between the measured geomagnetic field and GICs, without needing data about the power system topology or the ground conductivity profiles. The resulting empirical ensembles are used to analyse the TVA network (south-eastern USA) in terms of peak and cumulative exposure to 5 moderate to intense geomagnetic storms. Multiple nodes are ranked according to susceptibility and the measured response of the total TVA network is further calibrated to existing extreme value models. The probabilistic engineering step presented can complement present approaches, being particularly useful for risk assessment of existing transformers and power systems., Comment: 6 pages, 7 figures, accepted for PMAPS 2020

Typical geomagnetically induced current (GIC) modelling assumes the induced quasi-DC current at a node in the transmission network is linearly related to the local geoelectric field by a pair of network parameters. Given a limited time-series of measured geomagnetic and GIC data, an empirical method is presented that results in a statistically significant generalised ensemble of parameter estimates with the error in the estimates identified. The method is showcased for different transmission networks and geomagnetic storms and, where prior modelling exists, shows improved GIC estimation. Furthermore, modelled networks can be locally characterised and probed without any further network knowledge. Insights include network parameter variation, effective network directionality and response. Merging the network parameters and geoelectric field estimation, a transfer function is derived which offers an alternative approach to assessing transformer exposure to GICs., Comment: 8 pages, 8 figures, accepted for PSCC 2020

Geomagnetically induced currents (GICs) in power systems are conventionally modelled as direct currents, based on their commonly described quasi-DC nature. For more representative power system dynamic response modelling, it is necessary to model GICs using low-frequency AC. After analysing spectra of geomagnetic field measurements and GICs in several power systems, preliminary results indicate that the GIC spectra depend on the magnitude and frequency spectrum of the geomagnetic disturbance, the earth conductivity and the electrical characteristics of the network. In this paper, analysis based on measured GIC power spectra suggests that the dominant frequencies to use in GIC modelling and simulation are typically below 50 mHz. The associated error introduced by only using these frequencies is also quantified. The results have implications for modelling the geoelectric fields inducing GICs, dynamic models of power system response and the need for GICs and their associated driving fields to be measured at intervals not exceeding 10 s., Comment: 6 pages, 6 figures, accepted for SAUPEC/RobMech/PRASA 2020

One of the best tools we have in geophysical modelling is the ability to interpolate the horizontal geomagnetic field at the surface of the Earth. This is especially useful in regions, such as southern Africa, where there is a sparse array of absolute magnetometers available for geomagnetic field measurements. In terms of geomagnetic field interpolation, the spherical elementary current systems (SECS) spatial interpolation scheme has shown to be very successful, and the planar approximation of this method adequate for modelling at mid-latitudes. The SECS interpolation scheme is physics based, making use of the Biot-Savart law and equivalent ionospheric currents to interpolate measured geomagnetic field data. As with most interpolation methods, more data points result in lower error. Therefore, we adapt the SECS method to work with variometers. These instruments measure variations in magnetic field and are more abundant in southern Africa. Merging the two resulting interpolated datasets, the initial absolute geomagnetic field interpolation can be significantly improved. This improved interpolation scheme is not only incredibly useful locally, where a sparse magnetometer array is a challenge, but can also be applied just as effectively in other cases across the globe where there are numerous magnetometers and variometers available., Comment: 6 pages, 5 figures, available online at: http://events.saip.org.za

It has long been known that large grounded conducting networks on the surface of Earth are affected by solar activity and geomagnetic storms. Power networks are such extensive grounded conductors and are susceptible to geomagnetically induced currents (GICs). GICs at any specific node in a power network are assumed to be linearly related to the horizontal vector components of an induced plane-wave geoelectric field by a pair of network parameters. These network parameters are not easily measured in the network, but may be estimated empirically. In this work, we present a new approach of using an ensemble of network parameters estimates. The ensembles include a huge number of parameter pair estimates calculated from simultaneously solving pairs of time instances of the governing GIC equation. Each individual estimate is not the true state of the system, but a possible state. Taking the ensemble as a whole though gives the most probable parameter estimate. The most probable parameter estimate for both network parameters, as defined by their respective ensembles, is used directly in the modelling of GICs. The ensembles themselves however allow for further analysis into the nature of GICs. An improvement is seen when comparing the out-of-sample performance of the ensemble estimates with previous GIC modelling in the South African power network during the Halloween Storm of 2003. For the first time, it is shown that errors in the GIC modelling chain are absorbed into the network parameter estimates. Using a range of estimates from the ensemble, a GIC prediction band is produced. This band corresponds to an error estimate for predicted GIC. Furthermore, it has been explicitly shown that estimated network parameters vary with GIC magnitude during an event. This behaviour is then used to refine the parameter estimation further and allow for real time dynamic network parameter estimation., Comment: 6 pages, 3 figures, available online at: http://events.saip.org.za