2018 New York Scientific Data Summit (NYSDS)最新文献

Multimodal biological analysis using NLP and expression profile 使用NLP和表达谱的多模态生物学分析

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538944

Christine Kim, Peggy Yin, Carlos Soto, Ian K. Blaby, Shinjae Yoo

引用次数: 6

Simulating 0+1 Dimensional Quantum Gravity on Quantum Computers: Mini-Superspace Quantum Cosmology and the World Line Approach in Quantum Field Theory 在量子计算机上模拟 0+1 维量子引力：迷你超空间量子宇宙学和量子场论中的世界线方法

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538963

C. D. Kocher, M. McGuigan

{"title":"Simulating 0+1 Dimensional Quantum Gravity on Quantum Computers: Mini-Superspace Quantum Cosmology and the World Line Approach in Quantum Field Theory","authors":"C. D. Kocher, M. McGuigan","doi":"10.1109/NYSDS.2018.8538963","DOIUrl":"https://doi.org/10.1109/NYSDS.2018.8538963","url":null,"abstract":"Quantum computers are promising candidates to radically expand the domain of computational science by their increased computing power and more effective algorithms. In particular, quantum computing could have a tremendous impact on the field of quantum cosmology. The goal of quantum cosmology is to describe the evolution of the universe through the Wheeler-DeWitt equation or path integral methods without having to first formulate a full theory of quantum gravity. The quantum computer provides an advantage in this endeavor because it can perform path integrals directly in Lorentzian space and does not require constructing contour integrations in Euclidean gravity. Also, quantum computers can provide advantages in systems with fermions which are difficult to simulate on classical computers. In this study, we first employed classical computational methods to analyze a Friedmann-Robertson-Walker mini-superspace with a scalar field and visualize the calculated wavefunction of the universe for a variety of different values of the curvature of the universe and the cosmological constant. We then used IBM’s Quantum Information Science Kit Python library and the variational quantum eigensolver algorithm to study the same systems on a quantum computer. The framework was extended to the world line approach to quantum field theory.","PeriodicalId":366010,"journal":{"name":"2018 New York Scientific Data Summit (NYSDS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129652944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Quantum Computation and Visualization of Hamiltonians using Discrete Quantum Mechanics and IBM QISKit 使用离散量子力学和IBM QISKit的哈密顿量的量子计算和可视化

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538959

R. Miceli, M. McGuigan

{"title":"Quantum Computation and Visualization of Hamiltonians using Discrete Quantum Mechanics and IBM QISKit","authors":"R. Miceli, M. McGuigan","doi":"10.1109/NYSDS.2018.8538959","DOIUrl":"https://doi.org/10.1109/NYSDS.2018.8538959","url":null,"abstract":"Quantum computers have the potential to transform the ways in which we tackle some important problems. The efforts by companies like Google, IBM and Microsoft to construct quantum computers have been making headlines for years. Equally important is the challenge of translating problems into a state that can be fed to these machines. Because quantum computers are in essence controllable quantum systems, the problems that most naturally map to them are those of quantum mechanics. Quantum chemistry has seen particular success in the form of the variational quantum eigensolver (VQE) algorithm, which is used to determine the ground state energy of molecular systems. The goal of our work has been to use the matrix formulation of quantum mechanics to translate other systems so that they can be run through this same algorithm. We describe two ways of accomplishing this using a position basis approach and a Gaussian basis approach. We use this translation to compute finite temperature quantities such as the average energy as a function of temperature. We do this by constructing a 0+1 dimensional thermal field theory, constructing a thermal double of the system and using tensor products to construct operators in the system coupled to a heat bath. We also discuss how to include a chemical potential in the quantum computations. We then connect the 0+1 formalism to gauge theory by using an effective matrix model description used in nuclear theory. We study effective potentials for components of the gauge field and use the VQE algorithm to calculate the ground state energies. We also visualize the wave functions from the eigensolver and make comparisons to theoretical results obtained with continuous operators.","PeriodicalId":366010,"journal":{"name":"2018 New York Scientific Data Summit (NYSDS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122204861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs 分布式gpu上的高性能多模图重建

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538964

Zhihua Dong, Yao-Lung L. Fang, Xiaojing Huang, Hanfei Yan, S. Ha, W. Xu, Y. Chu, S. Campbell, Meifeng Lin

{"title":"High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs","authors":"Zhihua Dong, Yao-Lung L. Fang, Xiaojing Huang, Hanfei Yan, S. Ha, W. Xu, Y. Chu, S. Campbell, Meifeng Lin","doi":"10.1109/NYSDS.2018.8538964","DOIUrl":"https://doi.org/10.1109/NYSDS.2018.8538964","url":null,"abstract":"Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy method, a typical two-dimensional image requires a number of data frames. As a diffraction-based imaging technique, the real-space image has to be recovered through iterative reconstruction algorithms. Due to these two inherent aspects, a ptychographic reconstruction is generally a computation-intensive and time-consuming process, which limits the throughput of this method. We report an accelerated version of the multi-mode difference map algorithm for ptychography reconstruction using multiple distributed GPUs. This approach leverages available scientific computing packages in Python, including mpi4py and PyCUDA, with the core computation functions implemented in CUDA C. We find that interestingly even with MPI collective communications, the weak scaling in the number of GPU nodes can still remain nearly constant. Most importantly, for realistic diffraction measurements, we observe a speedup ranging from a factor of 10 to 103 depending on the data size, which reduces the reconstruction time remarkably from hours to typically about 1 minute and is thus critical for real-time data processing and visualization.","PeriodicalId":366010,"journal":{"name":"2018 New York Scientific Data Summit (NYSDS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116661862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Optimal Bayesian Classification When the Training Observations are Serially Dependent 训练观测值序列相关时的最优贝叶斯分类

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538943

A. Zollanvari, E. Dougherty

引用次数: 1

Predicting Available Computer Resources in Supercomputers 预测超级计算机中的可用计算机资源

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538961

Peggy Yin, Chenxiao Xu, S. Panitkin, Shinjae Yoo

引用次数: 0

A Survey of Logstash for Indexing Bioinformatics Data 生物信息学数据索引Logstash综述

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538952

Deil Cho, Arfath Parsha, Shinjae Yoo, Susan Pepper, Yonggang Cui

引用次数: 0

Visualization and Simulation of Carbon Structures with Higher Genus 高等属碳结构的可视化与模拟

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538945

B. T. Ortega, M. McGuigan

{"title":"Visualization and Simulation of Carbon Structures with Higher Genus","authors":"B. T. Ortega, M. McGuigan","doi":"10.1109/NYSDS.2018.8538945","DOIUrl":"https://doi.org/10.1109/NYSDS.2018.8538945","url":null,"abstract":"The Computational Science Initiative (CSI) department at Brookhaven National Laboratory involves varied and interdisciplinary work through out all sciences. In particular, we worked within the realm of computational chemistry through the means of studying carbon nanotori structures via their visualization and simulation. Compounds like graphene and other carbon allotropes, such as the nanotorus, have been in the eye of scientists for several years due to their unique polyhex structures which provide unique topologies and therefore possibly unique material properties. C++ code to generate Cartesian coordinates for an arbitrary torus was utilized to allow the use of molecular editing and modeling programs, such as Avogadro or Visual Molecular Dynamics (VMD) to design multiple genus nanocarbon toroidal structures. Several files were generated that contained multiple genus to them, namely a double torus, triple torus, and quadruple torus, all based off of a single genus carbon nanotorus from previous said code. Bond angle information was then utilized through.report files generated from structures files (.xyz or.cml) to allow for vertices and thereby neighboring atoms to the vertices to be identified. With these identified atoms for the above multiple genus structures, as well as for the C240 buckyball fullerene and carbon nanotorus, we wrote C++ code to generate an adjacency matrix for each respective one. These matrices were then subsequently used to generate eigenvalues and eigenvectors through a Mathmatica function for each structure. Using these values we can study the energies of these systems and thereby its functionalities and properties.","PeriodicalId":366010,"journal":{"name":"2018 New York Scientific Data Summit (NYSDS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129520971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Initial Experiments on Improving Seismic Data Inversion with Deep Learning 利用深度学习改进地震数据反演的初步实验

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538956

Lei Huang, M. Polanco, T. Clee

引用次数: 10

Optimal Bayesian Transfer Learning for Classifying Multivariate Gaussian Observations 多变量高斯观测值分类的最优贝叶斯迁移学习

2018 New York Scientific Data Summit (NYSDS) Pub Date : 2018-08-01 DOI: 10.1109/NYSDS.2018.8538958

Alireza Karbalayghareh, Xiaoning Qian, E. Dougherty

引用次数: 0