Flux Bias Research Articles

The Representation of Soil Moisture-Atmosphere Feedbacks across the Tibetan Plateau in CMIP6

Thermal processes on the Tibetan Plateau (TP) influence atmospheric conditions on regional and global scales. Given this, previous work has shown that soil moisture–driven surface flux variations feed back onto the atmosphere. Whilst soil moisture is a source of atmospheric predictability, no study has evaluated soil moisture–atmosphere coupling on the TP in general circulation models (GCMs). In this study, we use several analysis techniques to assess soil moisture-atmosphere coupling in CMIP6 simulations including: instantaneous coupling indices; analysis of flux and atmospheric behaviour during dry spells; and a quantification of the preference for convection over drier soils. Through these metrics we partition feedbacks into their atmospheric and terrestrial components.Consistent with previous global studies, we conclude substantial inter-model differences in the representation of soil moisture–atmosphere coupling, and that most models underestimate such feedbacks. Focusing on dry spell analysis, most models underestimate increased sensible heat during periods of rainfall deficiency. For example, the model-mean bias in anomalous sensible heat flux is 10 W m−2 (≈25%) smaller compared to observations. Deficient dry-spell sensible heat fluxes lead to a weaker atmospheric response. We also find that most GCMs fail to capture the negative feedback between soil moisture and deep convection. The poor simulation of feedbacks in CMIP6 experiments suggests that forecast models also struggle to exploit soil moisture–driven predictability. To improve the representation of land–atmosphere feedbacks requires developments in not only atmospheric modelling, but also surface processes, as we find weak relationships between rainfall biases and coupling indexes.

Ramifications of groundwater model in WRF/Noah‐MP coupled system: Effects on soil‐moisture and regional climate simulation

AbstractSoil moisture is a key variable that contributes for flux partitioning into sensible and latent heat components. There is a pressing need to study the impacts of shallow groundwater table dynamics on antecedent soil moisture and corresponding feedbacks to atmosphere. In this study, we evaluate WRF‐NoahMP simulated soil moisture using two experimental configurations: one with the default, free drainage approach (CTL) and with Miguez‐Macho groundwater scheme (GW). Results are presented for the study conducted over Ganga River basin, India between the years 2008 and 2014 for all the three seasons (pre‐monsoon, monsoon, post‐monsoon). It was observed that the GW model runs, improve soil moisture in topmost and bottom‐most layers. We discovered that the simulations improved temporal negative bias of seasonal accumulation during monsoon by around 91 mm. In addition, the average negative bias in latent heat flux improved by around 28 W/m2. Compared to CTL, GW was found to contribute additional atmospheric moisture content ranging between 3% and 5%. Comparison with in‐situ ground water showed that model overestimates the ground water table depth. This can be attributed to the ability of the model to only simulate natural occurring variabilities and lack of inclusion of anthropogenic factors such as ground water pumping in the model. The groundwater trend in Ganga is declining at alarming rate. In addition, if over exploitation of groundwater is not monitored properly, water and food scarcity is an imminent threat to the country's economy. To the best of authors knowledge, this is the first study of its kind to be implemented over Ganga basin, which evaluates the role of shallow ground water table on regional climate using coupled atmosphere‐land surface‐groundwater model. In summary, we highlight that the groundwater component along with WRF‐NoahMP coupled model improves soil moisture and precipitation representation over the Ganga basin.

Qubit energy tuner based on single flux quantum circuits

A device called the qubit energy tuner (QET), based on single flux quantum (SFQ) circuits, has been proposed for Z control of superconducting qubits. The QET is created by improving flux digital-to-analog converters (flux DACs). It can set the energy levels or frequencies of qubits, particularly flux-tunable transmons, and perform gate operations requiring Z control. The circuit structure of the QET is elucidated, consisting of an inductor loop and flux bias units for coarse or fine-tuning. The key feature of the QET is analyzed to understand how SFQ pulses change the inductor loop current, which provides external flux for qubits. Three simulations were performed to verify QET functionality. The first simulation verified the responses of the inductor loop current to SFQ pulses, showing a relative deviation of approximately 4.259% between the analytical solutions of the inductor loop current and the solutions from the WRSpice time-domain simulation. The second and third simulations, using QuTip, demonstrated how to perform a Z gate and an iSWAP gate using the QET, respectively, with corresponding fidelities of 99.99884% and 99.93906% for only one gate operation to specific initial states. These simulations indicate that the SFQ-based QET could act as an efficient component of SFQ-based quantum–classical interfaces for digital Z control of large-scale superconducting quantum computers.

Red Blood Cell Partitioning Using a Microfluidic Channel with Ladder Structure.

This study investigated the partitioning characteristics of red blood cells (RBCs) within capillaries, with a specific focus on ladder structures observed near the end of the capillaries. In vitro experiments were conducted using microfluidic channels with a ladder structure model comprising six bifurcating channels that exhibited an anti-parallel flow configuration. The effects of various factors, such as the parent channel width, distance between branches, and hematocrit, on RBC partitioning in bifurcating channels were evaluated. A decrease in the parent channel width resulted in an increase in the heterogeneity in the hematocrit distribution and a bias in the fractional RBC flux. Additionally, variations in the distance between branches affected the RBC distribution, with smaller distances resulting in greater heterogeneity. The bias of the RBC distribution in the microchannel cross section had a major effect on the RBC partitioning characteristics. The influence of hematocrit variations on the RBC distribution was also investigated, with lower hematocrit values leading to a more pronounced bias in the RBC distribution. Overall, this study provides valuable insights into RBC distribution characteristics in capillary networks, contributing to our understanding of the physiological mechanisms of RBC phase separation in the microcirculatory system. These findings have implications for predicting oxygen heterogeneity in tissues and could aid in the study of diseases associated with impaired microcirculation.

Small lateral air pressure gradients generated by a large chamber system have a strong effect onCO2transport in soil

AbstractGas transport in soils is usually assumed to be purely diffusive, although several studies have shown that non‐diffusive processes can significantly enhance soil gas transport. These processes include barometric air pressure changes, wind‐induced pressure pumping and static air pressure fields generated by wind interacting with obstacles. The associated pressure gradients in the soil can cause advective gas fluxes that are much larger than diffusive fluxes. However, the contributions of the respective transport processes are difficult to separate. We developed a large chamber system to simulate pressure fields and investigate their influence on soil gas transport. The chamber consists of four subspaces in which pressure is regulated by fans that blow air in or out of the chamber. With this setup, we conducted experiments with oscillating and static pressure fields. CO2concentrations were measured along two soil profiles beneath the chamber. We found a significant relationship between static lateral pressure gradients and the change in the CO2profiles (R2 = 0.53;p‐value <2e‐16). Even small pressure gradients between −1 and 1 Pa relative to ambient pressure resulted in an increase or decrease in CO2concentrations of 8% on average in the upper soil, indicating advective flow of air in the pore space. Positive pressure gradients resulted in decreasing, negative pressure gradients in increasing CO2concentrations. The concentration changes were probably caused by an advective flow field in the soil beneath the chamber generated by the pressure gradients. No effect of oscillating pressure fields was observed in this study. The results indicate that static lateral pressure gradients have a substantial impact on soil gas transport and therefore are an important driver of gas exchange between soil and atmosphere. Lateral pressure gradients in a comparable range can be induced under windy conditions when wind interacts with terrain features. They can also be caused by chambers used for flux measurements at high wind speed or by fans used for head‐space mixing within the chambers, which yields biased flux estimates.

Fusion of MISR Stereo Cloud Heights and Terra‐MODIS Thermal Infrared Radiances to Estimate Two‐Layered Cloud Properties

AbstractOur longest, stable record of cloud‐top pressure (CTP) and cloud‐top height (CTH) are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi‐Angle Imaging Spectroradiometer (MISR) on Terra. Because of single cloud‐layer assumptions in their standard algorithms, they provide only single CTP/CTH retrievals in multi‐layered situations. In the predominant multi‐layered regime of thin cirrus over low clouds, MODIS significantly overestimates cirrus CTP and emissivity, while MISR accurately retrieves low‐cloud CTH. Utilizing these complementary capabilities, we develop a retrieval algorithm for accurately determining both‐layer CTP and cirrus emissivity for such 2‐layered clouds, by applying the MISR low‐cloud CTH as a boundary condition to a modified MODIS CO2‐slicing retrieval. We evaluate our 2‐layered retrievals against collocated Cloud‐Aerosol Transport System (CATS) lidar observations. Relative to CATS, the mean bias of the upper cloud CTP and emissivity are reduced by ∼90% and ∼75% respectively in the new technique, compared to standard MODIS products. We develop an error model for the 2‐layered retrieval accounting for systematic and random errors. We find up to 87% of all residuals lie within modeled 95% confidence intervals, indicating a near‐closure of error budget. This reduction in error leads to a reduction in modeled atmospheric longwave radiative flux biases ranging between 5 and 40 W m−2, depending on the position and optical properties of the layers. Given this large radiative impact, we recommend that the pixel‐level 2‐layered MODIS + MISR fusion algorithm be applied over the entire MISR swath for the 22‐year Terra record, leading to a first‐of‐its‐kind 2‐layered cloud climatology from Terra's morning orbit.

Investigation and Modeling of DC Bias Impact on Core Losses at High Frequency

This paper aims to study the core losses behavior at high frequency (MHz range) with superimposed DC bias in ferrite. Inductive compensation method is employed in the measurement circuit to reduce sensitivity to phase errors. An addition to the circuit is proposed in this work to make easier DC bias generation. Furthermore, a detailed measurement accuracy consideration is also discussed. The tested MnZn ferrite has a nominal relative permeability of 1500 and 800, which was tested at frequency from 500 kHz to 3 MHz. The measurement results are explained thoroughly with three controlling parameters: excitation frequency, peak AC flux density, and DC bias. There are several important findings. First, a higher DC bias creates higher losses at the same frequency and AC flux density. Secondly, at the same DC bias and AC flux density, higher frequency generates a lower relative losses increase. This second point has not been seen in previous literature and is elaborated more in Section III.B. Thirdly, the measurement result shows how DC bias increases the hysteresis loop area and coercivity. The first and third findings confirm the the existing literature findings. As a final step, an improved Steinmetz Premagnetization Graph and Artificial Neural Network are used to create core loss prediction model. The measurement data and the built model can be accessed online for use by other magnetics designer.

Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere–atmosphere fluxes relevant for ozone air quality

Abstract. Ground-level ozone (O3) is a major air pollutant that adversely affects human health and ecosystem productivity. Removal of tropospheric O3 by plant stomatal uptake can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In many atmospheric and land surface models, the functionality of stomata opening is represented by a bulk stomatal conductance, which is often semi-empirically parameterized and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such as photosynthesis may render models inadequate to represent plant-mediated responses of atmospheric chemistry to long-term changes in CO2, climate, and short-lived air pollutant concentrations. A new ecophysiology module was thus developed to mechanistically simulate land−atmosphere exchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. The implementation not only allows for dry deposition to be coupled with plant ecophysiology but also enables plant and crop productivity and functions to respond dynamically to atmospheric chemical changes. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity and concentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated stomatal conductance and dry deposition velocity of O3 are close to SynFlux with root-mean-squared errors (RMSEs) below 0.3 cm s−1 across different plant functional types (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology was found to reduce the simulated biases in deposition fluxes from the prior model but worsen the positive biases in simulated O3 concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generally smaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-stomatal depositional and non-depositional processes relevant for O3 simulations. The estimated global O3 deposition flux is 864 Tg O3 yr−1 with GEOS-Chem, and the new module decreases this estimate by 92 Tg O3 yr−1. Estimated global gross primary production (GPP) without O3 damage is 119 Pg C yr−1. O3-induced reduction in GPP is 4.2 Pg C yr−1 (3.5 %). An elevated CO2 scenario (580 ppm) yields higher global GPP (+16.8 %) and lower global O3 depositional sink (−3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 317.9 Tg C yr−1, which is 31.2 Tg C yr−1 (−8.9 %) less than that calculated using the MEGAN (Model of Emissions of Gases and Aerosols from Nature) emission algorithm. This new model development dynamically represents the two-way interactions between vegetation and air pollutants and thus provides a unique capability in evaluating vegetation-mediated processes and feedbacks that can shape atmospheric chemistry and air quality, as well as pollutant impacts on vegetation health, especially for any timescales shorter than the multidecadal timescale.

Direct Radiative Effects of Aerosols on Numerical Weather Forecasts—A Comparison of Two Aerosol Datasets in the NCEP GFS

Abstract This study compares aerosol direct radiative effects on numerical weather forecasts made by the NCEP Global Forecast System (GFS) with two different aerosol datasets, the Optical Properties of Aerosols and Clouds (OPAC) and MERRA-2 aerosol climatologies. The underestimation of aerosol optical depth (AOD) by OPAC over northwest Africa, central to East Africa, the Arabian Peninsula, Southeast Asia, and the Indo-Gangetic Plain, and overestimation in the storm-track regions in both hemispheres are reduced by MERRA-2. Surface downward shortwave (SW) and longwave (LW) fluxes and the top-of-the-atmosphere SW and outgoing LW fluxes from model forecasts are compared with CERES satellite observations. Forecasts made with OPAC aerosols have large radiative flux biases, especially in northwest Africa and the storm-track regions. These biases are also reduced in the forecasts made with MERRA-2 aerosols. The improvements from MERRA-2 are most noticeable in the surface downward SW fluxes. GFS medium-range weather forecasts made with the MERRA-2 aerosols demonstrated slightly improved forecast accuracy of sea level pressure and precipitation over the Indian and East Asian summer monsoon region. A stronger Africa easterly jet is produced, associated with a low pressure over the east Atlantic Ocean and west of northwest Africa. Impacts on large-scale skill scores such as 500-hPa geopotential height anomaly correlation are generally positive in the Northern Hemisphere and the Pacific and North American regions in both the winter and summer seasons.

Entangled Frequency-Tunable Microwave Photons in a Superconducting Circuit

We propose a frequency-tunable source to emit entangled microwave photons on the platform of a superconducting circuit, in which two superconducting transmission-line resonators are coupled via a capacitor and one resonator is inserted with a superconducting quantum interference device (SQUID) in the center. By pumping the circuit appropriately with an external coherent microwave signal through the SQUID, microwave photons are emitted in pairs out of the circuit. The entanglement between the two modes is demonstrated by numerically calculating the second-order coherence function and the logarithmic negativity of the output microwave signals. Due to the tunability of SQUID’s equivalent inductance, the frequencies of the entangled microwave photons can be tuned by an external flux bias in situ. Our proposal paves a new way for obtaining entangled frequency-tunable two-mode microwave photons.

Scalability of Superconductor Electronics: Limitations Imposed by AC Clock and Flux Bias Transformers

Flux transformers are the necessary component of all superconductor digital integrated circuits utilizing ac power for logic cell excitation and clocking, and flux biasing, e.g., Adiabatic Quantum Flux Parametron (AQFP), Reciprocal Quantum Logic, superconducting sensor arrays, qubits, etc. We consider limitations to the integration scale (device number density) imposed by the critical current of the ac power transmission lines and cross coupling between the adjacent transformers. The former sets the minimum line width and the mutual coupling length in the transformer, whereas the latter sets the minimum spacing between the transformers. Decreasing linewidth of superconducting (Nb) wires increases kinetic inductance of the transformer's secondary, decreasing its length and mutual coupling to the primary. This limits the minimum size of transformers. As a result, there is a minimum linewidth ~100 nm which determines the maximum achievable scale of integration. Using AQFP circuits as an example, we calculate dependence of the AQFP number density on linewidth for various types of transformers and inductors available in the SFQ5ee fabrication process developed at MIT Lincoln Laboratory, and estimate the maximum circuit density as a few million AQFPs per cm^2. We propose an advanced fabrication process for a 10x increase in the density of AQFP and other ac-powered circuits. In this process, inductors are formed from a patterned bilayer of a geometrical inductance material (Nb) deposited over a layer of high kinetic inductance material (e.g., NbN). Individual pattering of the bilayer layers allows to create stripline inductors in a wide range of inductances, from the low values typical to Nb striplines to the high values typical for NbN thin films, and preserve sufficient mutual coupling in stripline transformers with extremely low crosstalk.

Scalable flux controllers using adiabatic superconductor logic for quantum processors

Quantum processors have the potential to accelerate specific computing tasks but are difficult to scale up due to engineering limitations, such as the number of available cables and cooling power for dilution refrigerators for quantum bits (qubits). Hence, it is very important to develop scalable, energy-efficient interface circuits that can control many qubits via a few control lines inside a dilution refrigerator. One of the most important interface circuits is the flux controller (FC), which generates arbitrary dc flux bias to adjust the characteristics of component devices such as qubits. In this paper, we propose and demonstrate FCs using an energy-efficient superconductor logic family, adiabatic quantum-flux-parametron (AQFP) logic. We develop two types of FCs: the AQFP FC and the AQFP/single-flux-quantum (AQFP/SFQ) FC. Both FCs require only a few control lines and have extremely small power dissipation, thus exhibiting high scalability. Furthermore, the AQFP/SFQ FC can control flux bias using ballistic SFQ transmission, which is crucial for integration with qubits. As a proof of concept, we demonstrate AQFP and AQFP/SFQ FCs at 4.2 K, fabricated by the AIST high-speed standard process. Our results indicate that AQFP logic is highly suitable for use as qubit interface circuits for very large-scale quantum processors, especially from the viewpoint of the control line count, power dissipation, and amount of supply currents.

Iron loss evaluation method for SiFe sheet material under PWM inverter excitation

This study proposed an iron loss evaluation method for SiFe sheet material under high-frequency current ripple caused by pulse width modulation (PWM) inverter switching. The PWM inverter switching results in dynamic minor loops on the BH plane, leading to iron loss. Furthermore, in magnetic material with wide major loops, such as SiFe sheet material, the iron loss caused by one dynamic minor loop differs based on the flux density bias difference even for the same magnetic field bias. A previous study reported an iron loss calculation error because the conventional iron loss calculation method neglected the iron loss of the flux density bias characteristic in the same magnetic field bias. Therefore, we modified the previously developed iron loss measurement system to collect the iron loss of the flux density bias characteristic and proposed an iron loss calculation method for SiFe sheet material.

Low-Cost and Compact Disposable Extracorporeal Centrifugal Blood Pump Utilizing a Homopolar Bearingless Switched Reluctance Slice Motor

The high biocompatibility and high durability of disposable extracorporeal centrifugal blood pumps (CBPs) utilizing magnetic bearing or bearingless motor technology make them perfect for supporting cardiopulmonary circulation for patients. However, the rotor incorporated in the disposable unit typically uses high-cost and environmentally-unfriendly rare-earth permanent magnets (PMs), leading to economic and environmental issues. This paper proposes a centrifugal blood pump with a PM-free impeller/rotor in the disposable pump head utilizing a 12/8 bearingless switched reluctance slice motor (BELSRM). Two axial-magnetized PM rings and two iron rings are mounted symmetrically above and below the tips of the stator poles. The biased magnetic flux generated by the PM rings forms a closed vertical magnetic circuit (homopolar flux circuit) with a PM-free rotor, providing high passive stiffness and large positioning forces independent of the rotor angle. A three-dimensional (3D) finite element analysis (FEA) model was used to evaluate the rotor support stiffness, the current-force coefficient, and the rotational torque. A prototype bearingless slice motor (BELSM) and a disposable pump head with a diameter of 50 mm PM-free impeller/rotor were fabricated. The radial magnetic levitation and the rotation were actively controlled by displacement and speed feedback control systems, respectively. A mock circulatory loop filled with 40wt% aqueous glycerol solution was set to evaluate the performance of the proposed CBP. The CBP provided a maximum flow rate of 4.59 L/min and a maximum head pressure of 214.5 mmHg at 2300 rpm and 2400 rpm, respectively.

Design and Optimization Method with Independent Radial and Axial Capacity for 3-DOF Magnetic Bearings in Flywheel

The six-pole radial–axial hybrid magnetic bearing (RAHMB) has the advantages of small space and low power consumption, making it suitable for flywheel batteries. The bearing capacity and the volume are the main specifications of magnetic bearings that should be considered comprehensively. In this work, the six-pole RAHMB was used in a horizontal flywheel battery. As the axial bearing capacity is relatively smaller than the radial bearing capacity, a design method with independent radial and axial bearing capacity is proposed, and the parameters are optimized to minimize the volume. The mathematical model of six-pole RAHMB was derived from the equivalent magnetic circuit method. The relationships between bearing capacity, biased flux density, saturation flux density and the section area of magnetic poles were analyzed. The basic principle of the design method with independent radial and axial bearing capacity is to determine which five of the variables are preferred. According to the design method, one radial or axial biased flux density should be optimized to minimize the volume, and the genetic algorithm (GA) was adopted to search for the optimal value. The structural parameters were designed based on the optimized value of biased flux density. The total volume of the six-pole RAHMB was reduced by 24%. A 3D finite element (FE) model was built. The analysis results and experimental results show that the proposed design and the optimization method are feasible and valid.

Inferring surface energy fluxes using drone data assimilation in large eddy simulations

Abstract. Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.

Phase Calibration of the Parametric Gate in the Superconducting Circuits

The quantum gate, as the foundation of quantum computation, depends on the architecture of the quantum chip, especially in superconducting systems. The parametric modulation to the flux bias is an important protocol to realize the multi‐qubit gate, which has some intrinsic advantages. Similar to other two‐qubit operations, parametric gates leave the extra phase in single‐qubit space, which is required to be corrected. In this article, the relation between the phases of the modulated pulse and the applied microwaves is experimentally characterized. By adjusting the envelope shape and phase of the applied pulses, the extra phase of the one qubit generated by the two‐qubit gate is suppressed via a simple and fast Ramsey‐like experiment. The tomography results demonstrate that this protocol is an effective calibrating method for future large‐scale quantum circuit manipulation.

An Inrush Current Suppression Strategy for UHV Converter Transformer Based on Simulation of Magnetic Bias

The Ultra High Voltage (UHV) converter transformer may generate serious inrush current during closing. It will cause commutation voltage distortion and easily result in commutation failure of converters on the same commutation bus. Due to the change of flux amplitude and phase caused by closing resistance in the Ultra High Voltage Direct Current (UHVDC) system, it is difficult to determine the closing time of the converter transformer when considering the influence of residual flux. Therefore, this paper first analyses the existing closing resistance strategy, and constructs the magnetic bias function according to the influence characteristics of closing resistance on the flux and phase. Then an inrush current suppression strategy based on magnetic bias simulation is proposed for star connection and delta connection of UHV converter transformers, which can accurately calculate the ideal closing time of mutual cancellation between the residual flux and bias flux during closing. Finally, the no-load closing model of the UHV converter transformer is established by PSCAD/EMTDC for simulation analysis of the feasibility, real-time verification is carried out using the RTDS closed-loop experimental platform. The results show that the proposed inrush current suppression strategy can effectively suppress the inrush current under different residual flux conditions.

Decoupled 2-DOF Magnetic Levitation Actuator for Single-Body High-Throughput Pick-and-Place Module

This article presents the design, control methods, and experiments of a novel two degree-of-freedom (DOF) magnetic levitation actuator, which is capable of decoupling the levitational- and lateral-direction control in a compact single-body configuration. Our single-body 2-DOF actuator is composed of an U-shaped iron-core with its legs wrapped by two actuating coils and an internal permanent magnet (PM) inserted to the core, levitating a target of 1-inch steel ball at a nominal airgap of 10 mm. We present the decoupled 2-DOF stabilization control method using a combination of common and differential current excitation modes on top of the biased flux generated from the internal PM, with the target position feedback measured by dual fiber optic sensors. For the rapid target lifting, we use a hybrid method of open- and closed-loop controls to have a robust and long-range lifting operation up to the sensing limit of −18 mm below the nominal levitation position, also achieving more than 30 % faster operation compared to a common method of lifting by a predetermined trajectory. Our decoupled lateral-position control also significantly improves both the stiffness and damping in that direction, thereby achieving approximately 82 % reduction of the lateral deviation and 99 % reduction of the target settling time during high-acceleration transportation.

Demonstration of Tunable Three-Body Interactions between Superconducting Qubits.

Nonpairwise multiqubit interactions present a useful resource for quantum information processors. Their implementation would facilitate more efficient quantum simulations of molecules and combinatorial optimization problems, and they could simplify error suppression and error correction schemes. Here, we present a superconducting circuit architecture in which a coupling module mediates two-local and three-local interactions between three flux qubits by design. The system Hamiltonian is estimated via multiqubit pulse sequences that implement Ramsey-type interferometry between all neighboring excitation manifolds in the system. The three-local interaction is coherently tunable over several MHz via the coupler flux biases and can be turned off, which is important for applications in quantum annealing, analog quantum simulation, and gate-model quantum computation.