arXiv subjects

Dongjin Lee

Publications and source records attributed to Dongjin Lee.

41 records · Page 3Linked to original sources

arXiv2021

SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams

Consider traffic data (i.e., triplets in the form of source-destination-timestamp) that grow over time. Tensors (i.e., multi-dimensional arrays) with a time mode are widely used for modeling and analyzing such multi-aspect data streams. In such tensors, however, new entries are added only once per period, which is often an hour, a day, or even a year. This discreteness of tensors has limited their usage for real-time applications, where new data should be analyzed instantly as it arrives. How can we analyze time-evolving multi-aspect sparse data 'continuously' using tensors where time is'discrete'? We propose SLICENSTITCH for continuous CANDECOMP/PARAFAC (CP) decomposition, which has numerous time-critical applications, including anomaly detection, recommender systems, and stock market prediction. SLICENSTITCH changes the starting point of each period adaptively, based on the current time, and updates factor matrices (i.e., outputs of CP decomposition) instantly as new data arrives. We show, theoretically and experimentally, that SLICENSTITCH is (1) 'Any time': updating factor matrices immediately without having to wait until the current time period ends, (2) Fast: with constant-time updates up to 464x faster than online methods, and (3) Accurate: with fitness comparable (specifically, 72 ~ 100%) to offline methods.

cs.LG↗

arXiv2020

Telecom C-Band Photon-Pair Generation using Standard SMF-28 Fiber

Photon-pair generation must satisfy both the energy conservation and phase-matching conditions with a specific pump wavelength and dispersion of nonlinear optical medium, but finding a photon-pair, which has a desired specific wavelength, generation medium is challenging. Here, we present a method to create photon pairs that functions efficiently even the pump wavelength is much larger than the zero GVD wavelength of medium. In this study, we employ short SMF-28 fibers having ~1310 nm zero GVD wavelength and C-band pump (1552.52 nm) to generate C-band photon pairs. The measured pair generation rate and coincidence-to-accidental ratios are comparable to those from a long dispersion-shifted fiber. Polarization-entangled states are prepared, and an S value of 2.659 +- 0.094 is achieved from Bell inequality measurements. Our results indicate that the use of a short SFWM medium yields adequate photon-pair generation rates regardless of its dispersion properties in almost any material at any pump wavelength.

quant-ph↗

arXiv2020

Evaluating reliability of complex systems for Predictive maintenance

Predictive Maintenance (PdM) can only be implemented when the online knowledge of system condition is available, and this has become available with deployment of on-equipment sensors. To date, most studies on predicting the remaining useful lifetime of a system have been focusing on either single-component systems or systems with deterministic reliability structures. This assumption is not applicable on some realistic problems, where there exist uncertainties in reliability structures of complex systems. In this paper, a PdM scheme is developed by employing a Discrete Time Markov Chain (DTMC) for forecasting the health of monitored components and a Bayesian Network (BN) for modeling the multi-component system reliability. Therefore, probabilistic inferences on both the system and its components status can be made and PdM can be scheduled on both levels.

eess.SY↗

arXiv2018

Solution of the $k$-th eigenvalue problem in large-scale electronic structure calculations

We consider computing the $k$-th eigenvalue and its corresponding eigenvector of a generalized Hermitian eigenvalue problem of $n\times n$ large sparse matrices. In electronic structure calculations, several properties of materials, such as those of optoelectronic device materials, are governed by the eigenpair with a material-specific index $k.$ We present a three-stage algorithm for computing the $k$-th eigenpair with validation of its index. In the first stage of the algorithm, we propose an efficient way of finding an interval containing the $k$-th eigenvalue $(1 \ll k \ll n)$ with a non-standard application of the Lanczos method. In the second stage, spectral bisection for large-scale problems is realized using a sparse direct linear solver to narrow down the interval of the $k$-th eigenvalue. In the third stage, we switch to a modified shift-and-invert Lanczos method to reduce bisection iterations and compute the $k$-th eigenpair with validation. Numerical results with problem sizes up to 1.5 million are reported, and the results demonstrate the accuracy and efficiency of the three-stage algorithm.

math.NA↗

arXiv2014

Novel linear algebraic theory and one-hundred-million-atom quantum material simulations on the K computer

The present paper gives a review of our recent progress and latest results for novel linear-algebraic algorithms and its application to large-scale quantum material simulations or electronic structure calculations. The algorithms are Krylov-subspace (iterative) solvers for generalized shifted linear equations, in the form of (zS-H)x=b,in stead of conventional generalized eigen-value equation. The method was implemented in our order-$N$ calculation code ELSES (http://www.elses.jp/) with modelled systems based on ab initio calculations. The code realized one-hundred-million-atom, or 100-nm-scale, quantum material simulations on the K computer in a high parallel efficiency with up to all the built-in processor cores. The present paper also explains several methodological aspects, such as use of XML files and 'novice' mode for general users. A sparse matrix data library in our real problems (http://www.elses.jp/matrix/) was prepared. Internal eigen-value problem is discussed as a general need from the quantum material simulation. The present study is a interdisciplinary one and is sometimes called 'Application-Algorithm-Architecture co-design'. The co-design will play a crucial role in exa-scale scientific computations.

cond-mat.mtrl-sci↗