Various quantum applications can be reduced to estimating expectation values, which are inevitably deviated by operational and environmental errors. Although errors can be tackled by quantum error ...correction, the overheads are far from being affordable for near-term technologies. To alleviate the detrimental effects of errors on the estimation of expectation values, quantum error mitigation techniques have been proposed, which require no additional qubit resources. Here we benchmark the performance of a quantum error mitigation technique based on probabilistic error cancellation in a trapped-ion system. Our results clearly show that effective gate fidelities exceed physical fidelities, i.e., we surpass the break-even point of eliminating gate errors, by programming quantum circuits. The error rates are effectively reduced from (1.10 ± 0.12) × 10
to (1.44 ± 5.28) × 10
and from (0.99 ± 0.06) × 10
to (0.96 ± 0.10) × 10
for single- and two-qubit gates, respectively. Our demonstration opens up the possibility of implementing high-fidelity computations on a near-term noisy quantum device.
A new and simple strategy towards electric‐field‐driven multiple chirality switching device has been designed and fabricated by combining a newly synthesized base‐responsive chiroptical polymer ...switch (R‐FLMA) and p‐benzoquinone (p‐BQ) via proton‐coupled electron transfer (PCET) mechanism. Clear and stable triple chirality states (silence, positive, negative) of this device in visible band can be regulated reversibly (>1000 cycles) by adjusting voltage programs. Furthermore, such chiral switching phenomena are also accompanied by apparent changes of color and fluorescence. More importantly, the potential application of this device for a spatial light modulator has also been demonstrated.
A simple and new strategy towards electric‐field‐driven multiple chirality switching material and device for spatial light modulators has been developed successfully based on the proton‐coupled electron transfer (PCET) mechanism.
This paper proposes the metafrontier non-radial Malmquist CO2 emission performance index (MNMCPI) for measuring dynamic changes in total-factor CO2 emission performance over time. The MNMCPI method ...allows for the incorporation of group heterogeneity and non-radial slack into the previously introduced Malmquist CO2 emission performance index (MCPI). We derive the MNMCPI by solving several non-radial data envelopment analysis (DEA) models. We decompose the MNMCPI into an efficiency change (EC) index, a best-practice gap change (BPC) index, and a technology gap change (TGC) index, and based on the proposed indices, we examine the dynamic changes in CO2 emission performance and its decomposition of fossil fuel power plants in China for the 2005–2010 period. The empirical results show a 0.38% increase in total-factor CO2 emission performance as a whole and a U-shaped MNMCPI curve for the sample period. Because companies owned by the central government lack innovation and technological leadership, the results suggest a missing link in the role of the central government in promoting CO2 emission performance.
•The metafrontier non-radial Malmquist CO2 emission performance index is proposed.•The dynamic changes in CO2 emission performance and its decomposition can be studied using the proposed model.•An empirical study of fossil fuel power plants in China are conducted for the 2005–2010 period.
As a crucial indicator of modernization, urbanization has significant effects on carbon dioxide emissions. Using a panel data of 141 countries over the period of 1961–2011, this paper analyzes the ...impact of urbanization on carbon dioxide emissions empirically. We employ two-way fixed effects model based on the extended STIRPAT theoretical frameworks. Our results show that there is an inverted U-shaped relationship between urbanization and carbon emissions and the turn point is around 73.80%. But excessive urban concentration can claim the benefits of high-level urbanization. These findings can also help policy makers to use efficient urbanization to curb the carbon emissions, especially for the Asian countries that with high density of population.
•It uses a cross-country panel data of 141 countries over the period 1961–2011.•It employs two-way fixed effects model based on the extended STIRPAT framework.•There is inverted U-shaped relationship between urbanization and carbon emissions.•The turning point for OECD countries is 73.80% on urbanization.•Excessive urban concentration can claim the benefits of urban agglomeration.
Lossless compression of color mosaic images poses a unique and interesting problem of spectral decorrelation of spatially interleaved R, G, B samples. We investigate reversible lossless ...spectral-spatial transforms that can remove statistical redundancies in both spectral and spatial domains and discover that a particular wavelet decomposition scheme, called Mallat wavelet packet transform, is ideally suited to the task of decorrelating color mosaic data. We also propose a low-complexity adaptive context-based Golomb-Rice coding technique to compress the coefficients of Mallat wavelet packet transform. The lossless compression performance of the proposed method on color mosaic images is apparently the best so far among the existing lossless image codecs.
Recently, a relatively new methodology named directional distance function (DDF) has been attracting positive attention in the field of energy and environmental (E&E) modeling. However, there is ...still no literature review on the application of DDF in E&E studies. This paper is intended to fill this gap. First, the most widely used DDF techniques and its extensions are briefly introduced. Second, this article attempts a classification of typical publications in this field. The main issues raised by the previous studies are discussed. Some guidelines for model selection and future directions are proposed for DDF related research in E&E studies.
•Total factor carbon emissions performance change for Chinese transportation sector is investigated.•The impact of regional heterogeneity is incorporated.•Metafrontier non-radial Luenberger carbon ...emission performance index is proposed.•Carbon emissions performance growth is mainly driven by technological innovation.
This study examines and decomposes dynamic changes in total factor carbon emissions performance within the transportation sector in China, incorporating the impact of regional heterogeneity. For this purpose, we combine the metafrontier approach with the non-radial Luenberger productivity indicator to propose a new definition named the metafrontier non-radial Luenberger carbon emission performance index (MNLCPI). This total factor index includes the efficiency change, best-practice gap change, and metafrontier technology gap change indexes. This method is capable of measuring dynamic changes in total factor carbon emissions performance over time via the production frontier framework and can incorporate group heterogeneity and non-radial slack into its measurement of total factor carbon emission performance. Empirical results applying this method show a 6.2% increase in overall total factor carbon emissions performance for the 2000–2012 period. This growth in carbon emissions performance is mainly driven by technological innovation, and different growth patterns are observed across China’s three main areas in transport sector.
Superlattice materials offer new opportunities to modify optical and electrical properties of recently emerging 2D materials. The insertion of tetraethylbenzidine (EtDAB) into interlamination of the ...established 2D PbI2 semiconductor through a mild solution method yielded the first lead iodide superlattice, EtDAB⋅4PbI2 (EtDAB=tetraethylbenzidine), with radical and non‐radical forms. The non‐radical form has a non‐ionic structure that differs from the common ionic structures for inorganic–organic hybrid lead halides. The radical form shows five orders of magnitude greater conductance and broader photoconductive response range (UV/Vis → UV/Vis‐IR), than pure PbI2 and the non‐radical form of the superlattice.
Lead the way: The first lead‐iodide superlattice constructed from non‐ionic organic molecules and PbI2 through van der Waals interactions is a new type of inorganic–organic hybrid and has a radical and a non‐radical form. The radical form has an almost five orders of magnitude greater conductivity and broader band photoconductive response than that of the non‐radical form or pure PbI2.
“Spatial contraindication” is what exactly landslide susceptibility models have been seeking. They are designed for depicting perilous land activities, be it natural or anthropological. To find this ...pattern, three well-known machine learning models namely maximum entropy (MaxEnt), support vector machine (SVM), and Artificial Neural Network (ANN) were used accompanied by their ensembles (i.e. ANN-SVM, ANN-MaxEnt, ANN-MaxEnt-SVM, and SVM-MaxEnt) in Wanyuan area, China. The models were designed by eleven conditioning factors such as elevation, slope degree, slope aspect, profile and plan curvatures, topographic wetness index, distance to roads, distance to rivers, normalized difference vegetation index (NDVI), land use/land cover (LU/LC), and lithology along with two sets of training (213#) and testing (91#) landslide data. A statistical index (SI) model was implemented to examine the mutual relationship between classes of each factor and the landslide occurrences. Concerning the areal differentiation, the chi-square test was used where SVM and MaxEnt gained the highest and the lowest values, respectively. Afterward, the practicality — as an indicator of producing a focused susceptibility map and addressing highly susceptible classes (IV and V) in a compendious manner with a reduced spatial area — was calculated for models. Accordingly, SVM and MaxEnt were found to be the most and the least practical models having the highest and the lowest spatial area in highly susceptible classes, respectively. The receiver operating characteristic (ROC) curve was used to examine generalization and prediction accuracy of the models. As a result, in the case of validating models separately, ANN gained the highest area under the curve (AUC) with a value of 0.824, followed by SVM (0.819), and MaxEnt (0.75). In the case of validating ensemble models, the ANN-SVM had the highest AUC of all (0.826), followed by ANN-MaxEnt (0.803), SVM-MaxEnt (0.792), and ANN-MaxEnt-SVM (0.811). With regard to the premier model results, three factors namely distance from roads, elevation, and distance from rivers had the highest effect on landslide occurrence. The results of the SI values showed that the spatial combination of the main drivers namely farmlands, −0.06–0.2 range in NDVI, rocks with inter-bedded limestone and other susceptible classes therein can make at least a prone area of about 30% to landsliding. Such spatial combination of environmental condition and human-made activities can be considered as a contraindication for the residents of the study area, especially at highly susceptible locations. This also addresses areas that further mitigation plans should be taken into account with urgency.
•Landslide spatial modeling using machine learning techniques•Introducing some new ensemble models of ANN, MaxEnt, and SVM machine learning techniques•Selection of the best single or ensemble models for regional modeling of landslide
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