Scalable Quantum Monte Carlo with Direct-Product Trial Wave Functions

The computational demand posed by applying multi-Slater determinant trials in phaseless auxiliary-field quantum Monte Carlo methods (MSD-AFQMC) is particularly significant for molecules exhibiting strong correlations. Here, we propose using direct-product wave functions as trials for MSD-AFQMC, aiming to reduce computational overhead by leveraging the compactness of multi-Slater determinant trials in direct-product form (DP-MSD). This efficiency arises when the active space can be divided into non-coupling subspaces, a condition we term "decomposable active space". By employing localized-active space self-consistent field wave functions as an example of such trials, we demonstrate our proposed approach in various molecular systems. Our findings indicate that the compact DP-MSD trials can reduce computational costs substantially, by up to 36 times for the \ce{C2H6N4} molecule where the two double bonds between nitrogen \ce{N=N} are clearly separated by a \ce{C-C} single bond, while maintaining accuracy when active spaces are decomposable. However, for systems where these active subspaces strongly couple, a scenario we refer to as "strong subspace coupling", the method's accuracy decreases compared to that achieved with a complete active space approach. We anticipate that our method will be beneficial for systems with non-coupling to weakly-coupling subspaces that require local multireference treatments.Comment: 12 pages, 9 figure

Nanophotonic cavity cooling of a single atom

We investigate external and internal dynamics of a two-level atom strongly coupled to a weakly pumped nanophotonic cavity. We calculate the dipole force, friction force, and stochastic force due to the cavity pump field, and show that a three-dimensional cooling region exists near the surface of a cavity. Using a two-color evanescent field trap as an example, we perform three-dimensional Monte-Carlo simulations to demonstrate efficient loading of single atoms into a trap by momentum diffusion, and the stability of cavity cooling near the trap center. Our analyses show that cavity cooling can be a promising method for directly loading cold atoms from free-space into a surface micro-trap. We further discuss the impact of pump intensity on atom trapping and loading efficiency.Comment: 14 pages, 11 figures, 1 tabl

Synthesis and crystal structure of a trihydrate of dinuclear benzimidazole-2-pyridinecarboxylate- cadmium(II)

A new compound, [Cd2(C7H6N2)3(C6H4O2N)4]·3H2O (1), has been prepared under mild hydrothermal conditions and structurally characterized by single crystal X-ray diffraction. The two cadmium(II) ions are bridged by a carboxyl group from one 2-pyridinecarboxylate ligand. The thermal gravimetry (TG) data indicate three steps of decomposition, and the final thermal decomposition product is CdO

Recent Progress in Transformer-based Medical Image Analysis

The transformer is primarily used in the field of natural language processing. Recently, it has been adopted and shows promise in the computer vision (CV) field. Medical image analysis (MIA), as a critical branch of CV, also greatly benefits from this state-of-the-art technique. In this review, we first recap the core component of the transformer, the attention mechanism, and the detailed structures of the transformer. After that, we depict the recent progress of the transformer in the field of MIA. We organize the applications in a sequence of different tasks, including classification, segmentation, captioning, registration, detection, enhancement, localization, and synthesis. The mainstream classification and segmentation tasks are further divided into eleven medical image modalities. A large number of experiments studied in this review illustrate that the transformer-based method outperforms existing methods through comparisons with multiple evaluation metrics. Finally, we discuss the open challenges and future opportunities in this field. This task-modality review with the latest contents, detailed information, and comprehensive comparison may greatly benefit the broad MIA community.Comment: Computers in Biology and Medicine Accepte

Ab initio Quantum Simulation of Strongly Correlated Materials with Quantum Embedding

Quantum computing has shown great potential in various quantum chemical applications such as drug discovery, material design, and catalyst optimization. Although significant progress has been made in quantum simulation of simple molecules, ab initio simulation of solid-state materials on quantum computers is still in its early stage, mostly owing to the fact that the system size quickly becomes prohibitively large when approaching the thermodynamic limit. In this work, we introduce an orbital-based multi-fragment approach on top of the periodic density matrix embedding theory, resulting in a significantly smaller problem size for the current near-term quantum computer. We demonstrate the accuracy and efficiency of our method compared with the conventional methodologies and experiments on solid-state systems with complex electronic structures. These include spin polarized states of a hydrogen chain (1D-H), the equation of states of a boron nitride layer (h-BN) as well as the magnetic ordering in nickel oxide (NiO), a prototypical strongly correlated solid. Our results suggest that quantum embedding combined with a chemically intuitive fragmentation can greatly advance quantum simulation of realistic materials, thereby paving the way for solving important yet classically hard industrial problems on near-term quantum devices.Comment: 14 pages, 5 figures, and 3 table

MFA-Conformer: Multi-scale Feature Aggregation Conformer for Automatic Speaker Verification

In this paper, we present Multi-scale Feature Aggregation Conformer (MFA-Conformer), an easy-to-implement, simple but effective backbone for automatic speaker verification based on the Convolution-augmented Transformer (Conformer). The architecture of the MFA-Conformer is inspired by recent state-of-the-art models in speech recognition and speaker verification. Firstly, we introduce a convolution sub-sampling layer to decrease the computational cost of the model. Secondly, we adopt Conformer blocks which combine Transformers and convolution neural networks (CNNs) to capture global and local features effectively. Finally, the output feature maps from all Conformer blocks are concatenated to aggregate multi-scale representations before final pooling. We evaluate the MFA-Conformer on the widely used benchmarks. The best system obtains 0.64%, 1.29% and 1.63% EER on VoxCeleb1-O, SITW.Dev, and SITW.Eval set, respectively. MFA-Conformer significantly outperforms the popular ECAPA-TDNN systems in both recognition performance and inference speed. Last but not the least, the ablation studies clearly demonstrate that the combination of global and local feature learning can lead to robust and accurate speaker embedding extraction. We will release the code for future works to do comparison.Comment: submitted to INTERSPEECH 202

Characterising personal, household, and community PM2.5 exposure in one urban and two rural communities in China

Background: Cooking and heating in households contribute importantly to air pollution exposure worldwide. However, there is insufficient investigation of measured fine particulate matter (PM2.5) exposure levels, variability, seasonality, and inter-spatial dynamics associated with these behaviours. Methods: We undertook parallel measurements of personal, household (kitchen and living room), and community PM2.5 in summer (May-September 2017) and winter (November 2017-Janauary 2018) in ∼480 participants from one urban and two rural communities in China. These recorded ∼61,000-81,000 person-hours of processed data per microenvironment. Age- and sex-adjusted geometric means of PM2.5 were calculated by key participant characteristics, overall and by season. Spearman correlation coefficients between PM2.5 levels across different microenvironments were computed. Findings: Overall, 25.1% reported use of solid fuel for both cooking and heating. Solid fuel users had ∼90% higher personal and kitchen 24-hour average PM2.5 exposure than clean fuel users. Similarly, they also had a greater increase (∼75% vs ∼20%) in personal and household PM2.5 from summer to winter, whereas community levels of PM2.5 were 2-3 times higher in winter regardless of fuel use. Compared with clean fuel users, solid fuel users had markedly higher weighted annual average PM2.5 exposure at personal (77.8 [95% CI 71.1-85.2] vs ∼40 µg/m3), kitchen (103.7 [91.5-117.6] vs ∼50 µg/m3) and living room (62.0 [57.1-67.4] vs ∼40 µg/m3) microenvironments. There was a remarkable diurnal variability in PM2.5 exposure among the participants, with 5-minute moving average 700-1,200µg/m3 in typical meal times. Personal PM2.5 was moderately correlated with living room (Spearman r: 0.64-0.66) and kitchen (0.52-0.59) levels, but only weakly correlated with community levels, especially in summer (0.15-0.34) and among solid fuel users (0.11-0.31). Conclusion: Solid fuel use for cooking and heating was associated with substantially higher personal and household PM2.5 exposure than clean fuel users. Household PM2.5 appeared a better proxy of personal exposure than community PM2.5 in this setting

Characterising personal, household, and community PM2.5 exposure in one urban and two rural communities in China

Background Cooking and heating in households contribute importantly to air pollution exposure worldwide. However, there is insufficient investigation of measured fine particulate matter (PM2.5) exposure levels, variability, seasonality, and inter-spatial dynamics associated with these behaviours. Methods We undertook parallel measurements of personal, household (kitchen and living room), and community PM2.5 in summer (May–September 2017) and winter (November 2017-Janauary 2018) in 477 participants from one urban and two rural communities in China. After stringent data cleaning, there were 67,326–80,980 person-hours (ntotal = 441; nsummer = 384; nwinter = 364; 307 had repeated PM2.5 data in both seasons) of processed data per microenvironment. Age- and sex-adjusted geometric means of PM2.5 were calculated by key participant characteristics, overall and by season. Spearman correlation coefficients between PM2.5 levels across different microenvironments were computed. Findings Overall, 26.4 % reported use of solid fuel for both cooking and heating. Solid fuel users had 92 % higher personal and kitchen 24-h average PM2.5 exposure than clean fuel users. Similarly, they also had a greater increase (83 % vs 26 %) in personal and household PM2.5 from summer to winter, whereas community levels of PM2.5 were 2–4 times higher in winter across different fuel categories. Compared with clean fuel users, solid fuel users had markedly higher weighted annual average PM2.5 exposure at personal (78.2 [95 % CI 71.6–85.3] μg/m3 vs 41.6 [37.3–46.5] μg/m3), kitchen (102.4 [90.4–116.0] μg/m3 vs 52.3 [44.8–61.2] μg/m3) and living room (62.1 [57.3–67.3] μg/m3 vs 41.0 [37.1–45.3] μg/m3) microenvironments. There was a remarkable diurnal variability in PM2.5 exposure among the participants, with 5-min moving average from 10 μg/m3 to 700–1200 μg/m3 across different microenvironments. Personal PM2.5 was moderately correlated with living room (Spearman r: 0.64–0.66) and kitchen (0.52–0.59) levels, but only weakly correlated with community levels, especially in summer (0.15–0.34) and among solid fuel users (0.11–0.31). Conclusion Solid fuel use for cooking and heating was associated with substantially higher personal and household PM2.5 exposure than clean fuel users. Household PM2.5 appeared a better proxy of personal exposure than community PM2.5

Reproductive factors and risk of lung cancer among 300,000 Chinese female never-smokers: evidence from the China Kadoorie Biobank study

Background Lung cancer is the leading cause of cancer mortality among Chinese females despite the low smoking prevalence among this population. This study assessed the roles of reproductive factors in lung cancer development among Chinese female never-smokers. Methods The prospective China Kadoorie Biobank (CKB) recruited over 0.5 million Chinese adults (0.3 million females) from 10 geographical areas in China in 2004–2008 when information on socio-demographic/lifestyle/environmental factors, physical measurements, medical history, and reproductive history collected through interviewer-administered questionnaires. Cox proportional hazard regression was used to estimate adjusted hazard ratios (HRs) of lung cancer by reproductive factors. Subgroup analyses by menopausal status, birth year, and geographical region were performed. Results During a median follow-up of 11 years, 2,284 incident lung cancers occurred among 282,558 female never-smokers. Ever oral contraceptive use was associated with a higher risk of lung cancer (HR = 1.16, 95% CI: 1.02–1.33) with a significant increasing trend associated with longer duration of use (p-trend = 0.03). Longer average breastfeeding duration per child was associated with a decreased risk (0.86, 0.78–0.95) for > 12 months compared with those who breastfed for 7–12 months. No statistically significant association was detected between other reproductive factors and lung cancer risk. Conclusion Oral contraceptive use was associated with an increased risk of lung cancer in Chinese female never-smokers. Further studies are needed to assess lung cancer risk related to different types of oral contraceptives in similar populations

The first genome sequences of human bocaviruses from Vietnam.

As part of an ongoing effort to generate complete genome sequences of hand, foot and mouth disease-causing enteroviruses directly from clinical specimens, two complete coding sequences and two partial genomic sequences of human bocavirus 1 (n=3) and 2 (n=1) were co-amplified and sequenced, representing the first genome sequences of human bocaviruses from Vietnam. The sequences may aid future study aiming at understanding the evolution of the pathogen