Spectroscopic data may often contain unwanted extrinsic signals. For example, in the angle-resolved photoemission spectroscopy (ARPES) experiment, a wire mesh is typically placed front of charge-coupled device to block stray photoelectrons but could cause gridlike structure spectra during quick measurement mode. In past, this was removed using mathematical Fourier filtering method by erasing periodic structure. However, lead information loss and vacancies because grid not strictly linearly...

Traditional maximum entropy and sparsity-based algorithms for analytic continuation often suffer from the ill-posed kernel matrix or demand tremendous computation time parameter tuning. Here we propose a neural network method by convex optimization replace inverse problem sequence of well-conditioned surrogate problems. After training, learned optimizers are able to give solution high quality with low cost achieve higher efficiency than heuristic fully connected networks. The output can also...

We propose a static auxiliary field approximation to study the hybridization physics of Kondo systems without sign problem and use mutual information measure intersite correlations. Our method takes full account spatial fluctuations fields at all orders overcomes artificial (first-order) phase transition predicted in mean-field approximation. When applied two-impurity model, it reveals logarithmically divergent amplitude near so-called "Varma-Jones" fixed point large manifesting development...

We apply the static auxiliary field Monte Carlo approach to study phase correlations of pairing fields in a microscopic model with spin-singlet interaction. find that short- and long-range are well captured by mutual information, which allows us construct theoretical diagram containing uniform $d$-wave superconducting region, fluctuating local disordered region. show gradual development coherence has number consequences on spectroscopic measurements, such as Fermi arc anisotropy...

Torreya grandis Fort. ex Lindl. cv. “Merrillii” is an important woody oil crop, and the development of plantations relies on cultivation high-quality saplings. For this study, 6-year-old grafted T. saplings, which will soon be planted mountain, were selected to investigate regulatory effects nitrogen (N), phosphorus (P), potassium (K) their growth morphology. To determine optimal dosage ratio N–P–K fertilizer for sapling cultivation, we employed a three-factor four-level L16 (43) orthogonal...

When one searches for political candidates on Google, a panel composed of recent news stories, known as Top is commonly shown at the top search results page. These stories are selected by an algorithm that chooses from hundreds thousands articles published publishers. In our previous work, we identified 56 sources contributed 2/3 all 30 running in primaries 2020 US Presidential Election. this paper, survey voters to elicit their familiarity and trust with these outlets. We find some most...

De-noising is a prominent step in the spectra post-processing procedure. Previous machine learning-based methods are fast but mostly based on supervised learning and require training set that may be typically expensive real experimental measurements. Unsupervised algorithms slow many iterations to achieve convergence. Here, we bridge this gap by proposing training-set-free two-stage deep method. We show fuzzy fixed input previous can improved introducing an adaptive prior. Combined with more...

Solving quantum impurity problems may advance our understanding of strongly correlated electron physics, but its development in multi-impurity systems has been greatly hindered due to the presence shared bath. Here, we propose a general operation strategy disentangle bath into multiple auxiliary baths and relate problem spectral decomposition function matrix for applying numerical renormalization group (NRG). We prove exactly that such is possible models satisfying (block) circulant...

We apply the static auxiliary field Monte Carlo approach to study phase correlations of pairing fields in a microscopic model with spin-singlet interaction. find that short- and long-range are well captured by mutual information, which allows us construct theoretical diagram containing uniform $d$-wave superconducting region, fluctuating local disordered region. show gradual development coherence has number consequences on spectroscopic measurements, such as Fermi arc anisotropy...

In an increasingly information-dense web, how do we ensure that not fall for unreliable information? To design better web literacy practices assessing online information, need to understand people perceive the credibility of unfamiliar websites under time constraints. Would they be able rate real news as more credible and fake less credible? We investigated this research question through experimental study with 42 participants (mean age = 28.3) who were asked various "real news'' (n 14)...

Aiming at the problem of low wind power prediction accuracy under windy weather, this paper proposes a Local Outlier Factor (LOF) - Fast Density Based Spatial Clustering Applications with Noise (F-DBSCAN) Cluster Synthetic Minority Oversampling Technique(C-SMOTE) data augmentation method. The LOF-FDBSCAN-CSMOTE algorithm first uses LOF to eliminate outliers in sample. Then, DBSCAN is optimized by using sum variance and inscribed circumscribed squares instead original clustering unit cluster...

At the start of COVID-19 outbreak, many countries lacked personal protective equipment (PPE) to protect healthcare workers. To address this problem, open design and 3D printing technologies were adopted provide much-in-need PPEs for key This paper reports an initiative by designers engineers in UK China. The case study approach content analysis method used stakeholders, process, other relevant issues such as regulation. Good practice lessons summarised, suggestions using distributed supply...

Finding disentangled representation plays a predominant role in the success of modern deep learning applications, but results lack straightforward explanation. Here we apply information bottleneck method and its $\beta$-VAE implementation to find low-dimensional classical models. For Ising model, our reveal connection between features physical order parameters, widely-used Bernoulli decoder is found be mean-field Hamiltonian at fixed temperature. This analogy motivates us extend application...

De-noising plays a crucial role in the post-processing of spectra. Machine learning-based methods show good performance extracting intrinsic information from noisy data, but often require high-quality training set that is typically inaccessible real experimental measurements. Here, using spectra angle-resolved photoemission spectroscopy (ARPES) as an example, we develop de-noising method for spectral without need set. This possible our leverages self-correlation themselves. It preserves...

Spectroscopic data may often contain unwanted extrinsic signals. For example, in ARPES experiment, a wire mesh is typically placed front of the CCD to block stray photo-electrons, but could cause grid-like structure spectra during quick measurement mode. In past, this was removed using mathematical Fourier filtering method by erasing periodic structure. However, lead information loss and vacancies because grid not strictly linearly superimposed. Here, we propose deep learning effectively...

Transparency is an important parameter to describe the optical properties of lake water. Based on field measured data April 19, 2018 and September 8, 2019, GF-5 hyperspectral satellite images, Random Forest BPNN methods were used retrieve transparency water bodies. The study shows that algorithm performs well in waters Qiandao Lake, R2 between inversion value 0.8651, MAPE 0.16m. image spatial distribution characteristics Lake obtained by using algorithm. results show overall higher...