Fault-tolerant quantum computers that can solve hard problems rely on quantum error correction
. One of the most promising error correction codes is the surface code
, which requires universal gate ...fidelities exceeding an error correction threshold of 99 per cent
. Among the many qubit platforms, only superconducting circuits
, trapped ions
and nitrogen-vacancy centres in diamond
have delivered this requirement. Electron spin qubits in silicon
are particularly promising for a large-scale quantum computer owing to their nanofabrication capability, but the two-qubit gate fidelity has been limited to 98 per cent owing to the slow operation
. Here we demonstrate a two-qubit gate fidelity of 99.5 per cent, along with single-qubit gate fidelities of 99.8 per cent, in silicon spin qubits by fast electrical control using a micromagnet-induced gradient field and a tunable two-qubit coupling. We identify the qubit rotation speed and coupling strength where we robustly achieve high-fidelity gates. We realize Deutsch-Jozsa and Grover search algorithms with high success rates using our universal gate set. Our results demonstrate universal gate fidelity beyond the fault-tolerance threshold and may enable scalable silicon quantum computers.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Optical properties of clouds and heavy aerosol retrieved from satellite measurements are the most important elements for calculating surface solar radiation (SSR). The Himawari-8/Advanced Himawari ...Imager (AHI) satellite measurements receive high spatial, temporal and spectral signals, which provides an opportunity to estimate cloud, aerosol and SSR accurately.
In this study, we developed the AHI official cloud property product (version 1.0) for JAXA P-Tree system. A look-up table (LUT) method was used to calculate high-temporal (10 min) and high-spatial (5 km) SSR from AHI cloud properties. First, the LUT of the SSR estimation was optimized through a radiative transfer model to account for solar zenith angle, cloud optical thickness (COT), effective particle radius (CER), aerosol optical thickness and surface albedo. Following this, COT and CER were retrieved from the AHI data, with ice cloud parameters being retrieved from an extended Voronoi ice crystal scattering database and water cloud parameters being retrieved from the Mie–Lorenz scattering model. The retrieved COT and CER for water clouds were compared well with MODIS collection 6 cloud property products, with correlation coefficients of 0.77 and 0.82, respectively. The COT of ice cloud also shows good consistency, with a correlation coefficient of 0.85. Finally, the SSR was calculated based on the SSR LUT and the retrieved cloud optical parameters. The estimated SSR was validated at 122 radiation stations from several observing networks covering the disk region of Himawari-8. The root-mean-square error (RMSE) at CMA (China Meteorological Administration) stations was 101.86 Wm−2 for hourly SSR and 31.42 Wm−2 for daily SSR; RMSE at non-CMA stations was 119.07 Wm−2 for instantaneous SSR, 81.10 Wm−2 for hourly SSR and 26.58 Wm−2 for daily SSR. Compared with the SSR estimated from conventional geostationary satellites, the accuracy of the SSR obtained in this study was significantly improved.
•The AHI official cloud algorithm (version 1.0) is developed for the JAXA P-Tree system.•The Voronoi ice crystal scattering model is used to develop the ice cloud product.•High-accuracy SSR is estimated using the AHI cloud parameters.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Common requirements for cloud detection methods including the adjustability with respect to incorrect results are clarified, and a method is proposed that satisfies the requirements by applying the ...support vector machine (SVM). Because the conditions of clouds and Earth's surfaces vary widely, incorrect results in actual cloud detection operations are unavoidable. Cloud detection methods therefore should be adjustable to easily reduce the frequency of incorrect results under certain conditions, without causing new incorrect results under other conditions. Cloud detection methods are also required to resolve a characteristic issue: the boundary between clear-sky and cloudy-sky areas in nature is vague, because the density of the cloud particles continuously varies. This vagueness makes the cloud definition subjective. Furthermore, the training dataset preparation for machine learning should avoid circular arguments. The SVM learning is generally less likely to result in overfitting: this study suggests that only typical data are sufficient for the SVM training dataset. By incorporating the discriminant analysis (DA), it is possible to subjectively determine the definition of typical cloudy and clear sky and to obtain typical cloud data without direct cloud detection. In an approach to adjust the classifier, data typical of certain conditions that lead to incorrect results are added to the training dataset. In this study, an adjustment procedure is proposed, which quantitatively judges, whether an addition is actually effective for reduction of the frequency of incorrect results. Another approach for the adjustment is improving feature space used for cloud detection. Indices as quantitative guidance to estimate whether an addition or elimination of a feature actually reduces the frequency of incorrect results can be obtained from the analysis of the support vectors. The cloud detection method incorporating the SVM is therefore able to integrate practical adjustment procedures. Applications of this method to Moderate Resolution Imaging Spectroradiometer (MODIS) data demonstrate that the concept of the method satisfies the requirements and the adjustability to various conditions can be realized.
•Requirements for cloud detection methods including adjustability are clarified.•Support vector machine is incorporated to satisfy the requirements.•Training dataset preparation without the circular argument is enabled.•Practical adjustment procedures with quantitative guidance are provided.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Abstract
Control of entanglement between qubits at distant quantum processors using a two-qubit gate is an essential function of a scalable, modular implementation of quantum computation. Among the ...many qubit platforms, spin qubits in silicon quantum dots are promising for large-scale integration along with their nanofabrication capability. However, linking distant silicon quantum processors is challenging as two-qubit gates in spin qubits typically utilize short-range exchange coupling, which is only effective between nearest-neighbor quantum dots. Here we demonstrate a two-qubit gate between spin qubits via coherent spin shuttling, a key technology for linking distant silicon quantum processors. Coherent shuttling of a spin qubit enables efficient switching of the exchange coupling with an on/off ratio exceeding 1000, while preserving the spin coherence by 99.6% for the single shuttling between neighboring dots. With this shuttling-mode exchange control, we demonstrate a two-qubit controlled-phase gate with a fidelity of 93%, assessed via randomized benchmarking. Combination of our technique and a phase coherent shuttling of a qubit across a large quantum dot array will provide feasible path toward a quantum link between distant silicon quantum processors, a key requirement for large-scale quantum computation.
Quantum entanglement is a fundamental property of coherent quantum states and an essential resource for quantum computing1. In large-scale quantum systems, the error accumulation requires concepts ...for quantum error correction. A first step toward error correction is the creation of genuinely multipartite entanglement, which has served as a performance benchmark for quantum computing platforms such as superconducting circuits2,3, trapped ions4 and nitrogen-vacancy centres in diamond5. Among the candidates for large-scale quantum computing devices, silicon-based spin qubits offer an outstanding nanofabrication capability for scaling-up. Recent studies demonstrated improved coherence times6–8, high-fidelity all-electrical control9–13, high-temperature operation14,15 and quantum entanglement of two spin qubits9,11,12. Here we generated a three-qubit Greenberger–Horne–Zeilinger state using a low-disorder, fully controllable array of three spin qubits in silicon. We performed quantum state tomography16 and obtained a state fidelity of 88.0%. The measurements witness a genuine Greenberger–Horne–Zeilinger class quantum entanglement that cannot be separated into any biseparable state. Our results showcase the potential of silicon-based spin qubit platforms for multiqubit quantum algorithms.Among the candidates for large-scale quantum computing devices, silicon-based spin qubits offer an outstanding nanofabrication capability for scaling-up. In an array of three spin qubits in silicon, high-fidelity state preparation and control enable the creation of a three-qubit Greenberger–Horne–Zeilinger state with 88% state fidelity.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
With a global aerosol transport‐radiation model coupled to a general circulation model, changes in the meteorological parameters of clouds, precipitation, and temperature caused by the direct and ...indirect effects of aerosols are simulated, and its radiative forcing are calculated. A microphysical parameterization diagnosing the cloud droplet number concentration based on the Köhler theory is introduced into the model, which depends not only on the aerosol particle number concentration but also on the updraft velocity, size distributions, and chemical properties of each aerosol species and saturation condition of the water vapor. The simulated cloud droplet effective radius, cloud radiative forcing, and precipitation rate, which relate to the aerosol indirect effect, are in reasonable agreement with satellite observations. The model results indicate that a decrease in the cloud droplet effective radius by anthropogenic aerosols occurs globally, while changes in the cloud water and precipitation are strongly affected by a variation of the dynamical hydrological cycle with a temperature change by the aerosol direct and first indirect effects rather than the second indirect effect itself. However, the cloud water can increase and the precipitation can simultaneously decrease in regions where a large amount of anthropogenic aerosols and cloud water exist, which is a strong signal of the second indirect effect. The global mean radiative forcings of the direct and indirect effects at the tropopause by anthropogenic aerosols are calculated to be −0.1 and −0.9 W m−2, respectively. It is suggested that aerosol particles approximately reduce 40% of the increase in the surface air temperature by anthropogenic greenhouse gases on the global mean.
Spin qubits in silicon quantum dots offer a promising platform for a quantum computer as they have a long coherence time and scalability. The charge sensing technique plays an essential role in ...reading out the spin qubit as well as tuning the device parameters, and therefore, its performance in terms of measurement bandwidth and sensitivity is an important factor in spin qubit experiments. Here we demonstrate fast and sensitive charge sensing by radio frequency reflectometry of an undoped, accumulation-mode Si/SiGe double quantum dot. We show that the large parasitic capacitance in typical accumulation-mode gate geometries impedes reflectometry measurements. We present a gate geometry that significantly reduces the parasitic capacitance and enables fast single-shot readout. The technique allows us to distinguish between the singly- and doubly occupied two-electron states under the Pauli spin blockade condition in an integration time of 0.8 μs, the shortest value ever reported in silicon, by the signal-to-noise ratio of 6. These results provide a guideline for designing silicon spin qubit devices suitable for the fast and high-fidelity readout.
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IJS, KILJ, NUK, PNG, UL, UM
Using deadjectival psych verbs with
in Japanese, this study shows that agglutinative complex predicate formation is done by recursive application of Merge to roots and functional heads. This process ...creates a layered syntactic structure, with each layer providing the computational system with (i) specific semantic features, (ii) arguments, and (iii) phonetic form (PF) exponents at conceptual–intentional (CI)/sensory motor (SM) Interfaces. The whole amalgam of the root and the functional heads is interpreted as a “word” at PF. Following the general architecture of Distributed Morphology, I will show that the morpheme that derives deadjectival verbs
is underlyingly
(
-Copula-T), where
is “little” v that originates in the verbal root
“come” and
is a copula. They are now grammaticalized functional heads that extend adjectival roots. Crucially, this
is homophonous with “little” a, which makes
and the adjective-deriving morpheme
(
-Copula-T) parallel.
is voiced in
due to a structurally conditioned assimilation rule (Embick
). This analysis reveals the mechanisms of agglutinative predicate formation in a precise and detailed manner. Similarly, it gives natural solutions to some of the long-standing problems including how adjectives modify N such as
“beautiful dancer,” which is ambiguous between attributive modification and a relative clause.
A new concept for cloud detection from observations by multispectral spaceborne imagers is proposed, and an algorithm comprising many pixel‐by‐pixel threshold tests is developed. Since in nature the ...thickness of clouds tends to vary continuously and the border between cloud and clear sky is thus vague, it is unrealistic to label pixels as either cloudy or clear sky. Instead, the extraction of ambiguous areas is considered to be useful and informative. We refer to the multiple threshold method employed in the MOD35 algorithm that is used for Moderate Resolution Imaging Spectroradiometer (MODIS) standard data analysis, but drastically reconstruct the structure of the algorithm to meet our aim of sustaining the neutral position. The concept of a clear confidence level, which represents certainty of the clear or cloud condition, is applied to design a neutral cloud detection algorithm that is not biased to either clear or cloudy. The use of the clear confidence level with neutral position also makes our algorithm structure very simple. Several examples of cloud detection from satellite data are tested using our algorithm and are validated by visual inspection and comparison to previous cloud mask data. The results indicate that our algorithm is capable of reasonable discrimination between cloudy and clear‐sky areas over ocean with and without Sun glint, forest, and desert, and is able to extract areas with ambiguous cloudiness condition.
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