Thermodynamics and phase transitions for the Heisenberg model on the pinwheel distorted kagome lattice

We study the Heisenberg model on the pinwheel distorted kagome lattice as observed in the material Rb_2Cu_3SnF_12. Experimentally relevant thermodynamic properties at finite temperatures are computed utilizing numerical linked-cluster expansions. We also develop a Lanczos-based, zero-temperature, numerical linked cluster expansion to study the approach of the pinwheel distorted lattice to the uniform kagome-lattice Heisenberg model. We find strong evidence for a phase transition before the uniform limit is reached, implying that the ground state of the kagome-lattice Heisenberg model is likely not pinwheel dimerized and is stable to finite pinwheel-dimerizing perturbations.Comment: 6 pages, 6 figures, 1 tabl

Classification and Retrieval of Digital Pathology Scans: A New Dataset

In this paper, we introduce a new dataset, \textbf{Kimia Path24}, for image classification and retrieval in digital pathology. We use the whole scan images of 24 different tissue textures to generate 1,325 test patches of size 1000$\times$1000 (0.5mm$\times$0.5mm). Training data can be generated according to preferences of algorithm designer and can range from approximately 27,000 to over 50,000 patches if the preset parameters are adopted. We propose a compound patch-and-scan accuracy measurement that makes achieving high accuracies quite challenging. In addition, we set the benchmarking line by applying LBP, dictionary approach and convolutional neural nets (CNNs) and report their results. The highest accuracy was 41.80\% for CNN.Comment: Accepted for presentation at Workshop for Computer Vision for Microscopy Image Analysis (CVMI 2017) @ CVPR 2017, Honolulu, Hawai

A perspective on machine learning and data science for strongly correlated electron problems

Numerical approaches to the correlated electron problem have achieved considerable success, yet are still constrained by several bottlenecks, including high order polynomial or exponential scaling in system size, long autocorrelation times, challenges in recognizing novel phases, and the Fermion sign problem. Methods in machine learning (ML), artificial intelligence, and data science promise to help address these limitations and open up a new frontier in strongly correlated quantum system simulations. In this paper, we review some of the progress in this area. We begin by examining these approaches in the context of classical models, where their underpinnings and application can be easily illustrated and benchmarked. We then discuss cases where ML methods have enabled scientific discovery. Finally, we will examine their applications in accelerating model solutions in state-of-the-art quantum many-body methods like quantum Monte Carlo and discuss potential future research directions

No persistent effect of intravenous immunoglobulins in patients with narcolepsy with cataplexy

We report on four patients with narcolepsy with cataplexy (NC), who were treated with high-dose intravenous immunoglobulins (IVIg). Although in some patients transient effects were seen of both objective (multiple sleep latency test and maintenance of wakefulness test) and subjective symptoms (Epworth Sleepiness Scale and frequency of cataplexy), these effects lasted at the most for a few weeks and did not persist. Our report challenges the recent observations of a favorable and persistent effect of IVIg in NC patient

Analisis Kinerja Keuangan Perusahaan Sebelum Dan Sesudah Initial Public Offering (Ipo) Di Bursa Efek Indonesia (Studi Pada Perusahaan Non Finansial Yang Listing Di Bei Tahun 2011)

The purpose of this study is to explain the differences in financial performance of non-financial companies before and after the Initial Public Offering (IPO) at the Indonesia Stock Exchange (BEI). This study uses a quantitative approach with statistical methods. The research variables consisted of Current Ratio (CR), Debt to Equity Ratio (DER), Debt Ratio (DR), Total Assets Turnover Ratio (TATO), Net Profit Margin (NPM), Return on Investment (ROI) and Return on Equity (ROE). Data analysis is descriptive statistical analysis and inferential statistical analysis consisting of normality test and test hypotheses using SPSS version 20. The results of testing the hypothesis by using paired sample t-test showed that there were significant differences in the company's financial performance before and after the IPO when viewed from the mean CR and ROE. Meanwhile, if viewed from the mean DER, DR, TATO, NPM, and ROI, there are no significant differences in the company's financial performance before and after the IPO. When viewed as a whole, the company's financial performance was not increased after an IPO. This can happen due to a short observation period and also the condition that the company is still in the adjustment phase after an IPO

The Craig Interpolation Property in First-order G\"odel Logic

In this article, a model-theoretic approach is proposed to prove that the first-order G\"odel logic, $\mathbf{G}$, as well as its extension $\mathbf{G}^\Delta$ associated with first-order relational languages enjoy the Craig interpolation property. These results partially provide an affirmative answer to a question posed in [Aguilera, Baaz, 2017, Ten problems in G\"odel logic]

Spin Transport in a Mott Insulator of Ultracold Fermions

Strongly correlated materials are expected to feature unconventional transport properties, such that charge, spin, and heat conduction are potentially independent probes of the dynamics. In contrast to charge transport, the measurement of spin transport in such materials is highly challenging. We observed spin conduction and diffusion in a system of ultracold fermionic atoms that realizes the half-filled Fermi-Hubbard model. For strong interactions, spin diffusion is driven by super-exchange and doublon-hole-assisted tunneling, and strongly violates the quantum limit of charge diffusion. The technique developed in this work can be extended to finite doping, which can shed light on the complex interplay between spin and charge in the Hubbard model.Comment: 16 pages, 10 figure