Optimizing Quantum Programs against Decoherence: Delaying Qubits into Quantum Superposition

Quantum computing technology has reached a second renaissance in the last decade. However, in the NISQ era pointed out by John Preskill in 2018, quantum noise and decoherence, which affect the accuracy and execution effect of quantum programs, cannot be ignored and corrected by the near future NISQ computers. In order to let users more easily write quantum programs, the compiler and runtime system should consider underlying quantum hardware features such as decoherence. To address the challenges posed by decoherence, in this paper, we propose and prototype QLifeReducer to minimize the qubit lifetime in the input OpenQASM program by delaying qubits into quantum superposition. QLifeReducer includes three core modules, i.e.,the parser, parallelism analyzer and transformer. It introduces the layered bundle format to express the quantum program, where a set of parallelizable quantum operations is packaged into a bundle. We evaluate quantum programs before and after transformed by QLifeReducer on both real IBM Q 5 Tenerife and the self-developed simulator. The experimental results show that QLifeReducer reduces the error rate of a quantum program when executed on IBMQ 5 Tenerife by 11%; and can reduce the longest qubit lifetime as well as average qubit lifetime by more than 20% on most quantum workloads.Comment: To appear in TASE2019 - the 13th International Symposium on Theoretical Aspects of Software Engineering (submitted on Jan 25, 2019, and this is camera-ready version

CODAR: A Contextual Duration-Aware Qubit Mapping for Various NISQ Devices

Quantum computing devices in the NISQ era share common features and challenges like limited connectivity between qubits. Since two-qubit gates are allowed on limited qubit pairs, quantum compilers must transform original quantum programs to fit the hardware constraints. Previous works on qubit mapping assume different gates have the same execution duration, which limits them to explore the parallelism from the program. To address this drawback, we propose a Multi-architecture Adaptive Quantum Abstract Machine (maQAM) and a COntext-sensitive and Duration-Aware Remapping algorithm (CODAR). The CODAR remapper is aware of gate duration difference and program context, enabling it to extract more parallelism from programs and speed up the quantum programs by 1.23 in simulation on average in different architectures and maintain the fidelity of circuits when running on Origin Quantum noisy simulator.Comment: arXiv admin note: substantial text overlap with arXiv:2001.0688

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

QSynth artifact evaluation

<p>QSynth's source code for POPL24 artifact evaluation. </p&gt

A Fast Response Robust Deadbeat Predictive Current Control for Permanent Magnet Synchronous Motor

Deadbeat predictive current control (DBPCC) has the characteristic of fast current response, but it is sensitive to motor parameters. Observer-based DBPCC can eliminate the steady state current tracking error when parameter mismatch exists. However, the actual current will deviate from the reference current during transient state in the case of inductance mismatch. In this paper, a fast response robust deadbeat predictive current control (FRRDBPCC) method is proposed for surface mounted permanent magnet synchronous motor (SPMSM). Firstly, the current tracking error caused by inductance mismatch during transient state is analyzed in detail. Then, an extended state observer (ESO) is proposed to estimate the lumped disturbance caused by parameter mismatch. Based on discrete time ESO, the predicted currents are used to replace the sampled currents to compensate for one-step delay caused by calculation and sampling. Furthermore, an online inductance identification algorithm and a modified prediction model are proposed. The dq-axis currents can be completely decoupled by updating the inductance in the modified prediction model online, ensuring that the current can track the reference value in two control periods. The proposed method improves robustness against parameter mismatch and guarantees dynamic response performance simultaneously. The experimental results verify the effectiveness of the proposed method

Spatial Pattern of Water Footprints for Crop Production in Northeast China

Water is an important resource for crop production; identifying the spatial pattern of the crop water footprint (WF) is of great significance for the optimization of water resource consumption and management in agricultural production. This study quantified the green, blue and grey water footprints (GWF, BWF and GRWF) and water consumption (GWC, BWC and GRWC) of rice, maize and soybean at the 1 km grid level and city level in Northeast China in 2019 based on the CROPWAT 8.0 model. The results showed that the average total water footprints of rice (TWFr), maize (TWFm) and soybean (TWFs) were 624.31 m3·ton−1, 527.26 m3·ton−1 and 1298.21 m3·ton−1, respectively. The spatial differences in the WF of each crop were obvious in Northeast China, with the highest values of TWFr mainly occurring in Baicheng, Dalian and Qitaihe; the highest TWFm values were mainly found in Baicheng, Yingkou and Hulundao, and the highest TWFs were mainly found in Baicheng, Chifeng and Tongliao. The total water consumption of all three crops (TWCc) in Northeast China was 94 billion m3·yr−1 (42% green, 26% blue and 32% grey), in which the total water consumption of maize production (TWCm) accounted for 60%. The production of rice, maize and soybean in Northeast China mainly depends on green water, grey water and blue water, respectively. Combining the results of the spatial patterns of crop TWF and TWC, the study revealed that the planting pattern of crops in Northeast China was relatively reasonable for sustainable water use. Meanwhile, cities that have the potential to enhance crop production and cities that should improve their water use efficiency and reduce fertilizer application were also identified

Automating NISQ Application Design with Meta Quantum Circuits with Constraints (MQCC)

Near-term intermediate scale quantum (NISQ) computers are likely to have very restricted hardware resources, where precisely controllable qubits are expensive, error-prone, and scarce. Programmers of such computers must therefore balance trade-offs among a large number of (potentially heterogeneous) factors specific to the targeted application and quantum hardware. To assist them, we propose Meta Quantum Circuits with Constraints (MQCC), a meta-programming framework for quantum programs. Programmers express their application as a succinct collection of normal quantum circuits stitched together by a set of (manually or automatically) added meta-level choice variables, whose values are constrained according to a programmable set of quantitative optimization criteria. MQCC’s compiler generates the appropriate constraints and solves them via an SMT solver, producing an optimized, runnable program. We showcase a few MQCC’s applications for its generality including an automatic generation of efficient error syndrome extraction schemes for fault-tolerant quantum error correction with heterogeneous qubits and an approach to writing approximate quantum Fourier transformation and quantum phase estimation that smoothly trades off accuracy and resource use. We also illustrate that MQCC can easily encode prior one-off NISQ application designs-–multi-programming (MP), crosstalk mitigation (CM)—as well as a combination of their optimization goals (i.e., a combined MP-CM).https://doi.org/10.1145/357936

Occurrence and Removal of Triazine Herbicides during Wastewater Treatment Processes and Their Environmental Impact on Aquatic Life

Wastewater treatment plants (WWTPs) represent a major point source for pesticide residue entry to aquatic environment and may threaten ecosystems and biodiversity in urban area. Triazine herbicides should be paid attention to for their ubiquitous occurrence in the environment and long-term residue. The present study aimed to quantify eleven compounds of triazine herbicides during wastewater treatment processes. The solid phase extraction and gas-chromatography mass spectrometry (GC-MS) determination method were developed to identify the target herbicides with approving sensitivity. The pollution levels, removal rates of eleven triazine herbicides along five different treatment stages in WWTP were investigated. The results showed that three herbicides including atrazine, simetryn and prometryn were detected. Their concentrations in influent were among 28.79 to 104.60 ng/L. Their total removal rates from influent to effluent were 14.92%, 10.79% and 4.41%, respectively indicating that they were difficult to be effectively remove during wastewater treatment. Regarding the negative impact of triazine herbicides discharged from WWTPs on downstream water quality and aquatic life, the environmental risks were assessed by calculating the Environmental Relevance of Pesticides from Wastewater Treatment Plants Index (ERPWI) and water cycle spreading index (WCSI). The risk assessment results denoted the possible high risks for atrazine and simetryn to alage, and simetryn concurrently posed a high risk for the daphnia, while prometryn was at medium risk to alage. Atrazine and simetryn in effluent posed high risk for algae, meanwhile, simetryn had high risk for Daphnia. These results suggested a possible threat to the aquatic environment, rendering in this way the ERPWI method as a useful assessment tool. Further extensive study is needed for atrazine and simetryn in order to better understand their migration mechanism in aquatic environment

Microstructure and Mechanical Properties of AlSi7Mg0.6 Aluminum Alloy Fabricated by Wire and Arc Additive Manufacturing Based on Cold Metal Transfer (WAAM-CMT)

Wire and arc additive manufacturing based on cold metal transfer (WAAM-CMT) has aroused wide public concern in recent years as one of the most advanced technologies for manufacturing components with complex geometries. However, the microstructure and mechanical properties of the parts fabricated by WAAM-CMT technology mostly are intolerable for engineering application and should be improved necessarily. In this study, heat treatment was proposed to optimize the microstructure and enhance mechanical properties in the case of AlSi7Mg0.6 alloy. After heat treatment, the division between coarse grain zone and fine grain zone of as-deposited samples seemed to disappear and the distribution of Si and Mg elements was more uniform. What is more, the yield strength and ultimate tensile strength were improved significantly, while the ductility could be sustained after heat treatment. The improvement of strength is attributed to precipitation strengthening, and the shape change of Si phase. No reduction in ductility is due to the higher work hardening rate caused by nanostructured precipitate. It is proved that heat treatment as an effective method can control the microstructure and enhance comprehensive mechanical properties, which will boost rapid development of WAAM industrial technology