arXiv subjects

Hyunwoo Lee

Publications and source records attributed to Hyunwoo Lee.

63 records · Page 4Linked to original sources

arXiv2020

Orbital Variational Adiabatic Hyperspherical Method Applied to Bose-Einstein Condensates

A variational basis set motivated by mean-field theory is utilized to describe the Bose-Einstein condensate within the adiabatic hyperspherical coordinate framework. The simplest single-orbital variant of this treatment reproduces many of the ground state properties predicted by the Gross-Pitaevskii equation. But a multi-orbital improvement to the basis set yields a better representation of particle correlations and of the critical number where the condensate collapses for a negative two-body scattering length. The method also produces systematic deviations from Bogoliubov theory for the fundamental monopole excitation frequency.

physics.atom-ph↗

arXiv2019

Randomized Computation of Continuous Data: Is Brownian Motion Computable?

We consider randomized computation of continuous data in the sense of Computable Analysis. Our first contribution formally confirms that it is no loss of generality to take as sample space the Cantor space of infinite FAIR coin flips. This extends [Schröder&Simpson'05] and [Hoyrup&Rojas'09] considering sequences of suitably and adaptively BIASED coins. Our second contribution is concerned with 1D Brownian Motion (aka Wiener Process), a probability distribution on the space of continuous functions f:[0,1]->R with f(0)=0 whose computability has been conjectured [Davie&Fouché'13; arXiv:1409.4667,S6]. We establish that this (higher-type) random variable is computable iff some/every computable family of moduli of continuity (as ordinary random variables) has a computable probability distribution with respect to the Wiener Measure.

math.NA↗

arXiv2017

Embedded Real-Time Fall Detection Using Deep Learning For Elderly Care

This paper proposes a real-time embedded fall detection system using a DVS(Dynamic Vision Sensor) that has never been used for traditional fall detection, a dataset for fall detection using that, and a DVS-TN(DVS-Temporal Network). The first contribution is building a DVS Falls Dataset, which made our network to recognize a much greater variety of falls than the existing datasets that existed before and solved privacy issues using the DVS. Secondly, we introduce the DVS-TN : optimized deep learning network to detect falls using DVS. Finally, we implemented a fall detection system which can run on low-computing H/W with real-time, and tested on DVS Falls Dataset that takes into account various falls situations. Our approach achieved 95.5% on the F1-score and operates at 31.25 FPS on NVIDIA Jetson TX1 board.

stat.ML↗

arXiv2017

Anisotropic blockade using pendular Rydberg butterfly molecules

We propose an experiment to demonstrate a novel blockade mechanism caused by long-range anisotropic interactions in an ultracold dipolar gas composed of the recently observed "butterfly" Rydberg molecules. At the blockade radius, the strong intermolecular interaction between two adjacent molecules shifts their molecular states out of resonance with the photoassociation laser, preventing their simultaneous excitation. When the molecules are prepared in a quasi-one-dimensional (Q1D) trap, the interaction's strength can be tuned via a weak external field. The molecular density thus depends strongly on the angle between the trap axis and the field. The available Rydberg and molecular states provide a wide range of tunability.

physics.atom-ph↗

arXiv2016

Position Estimation of Robotic Mobile Nodes in Wireless Testbed using GENI

We present a low complexity experimental RF-based indoor localization system based on the collection and processing of WiFi RSSI signals and processing using a RSS-based multi-lateration algorithm to determine a robotic mobile node's location. We use a real indoor wireless testbed called w-iLab.t that is deployed in Zwijnaarde, Ghent, Belgium. One of the unique attributes of this testbed is that it provides tools and interfaces using Global Environment for Network Innovations (GENI) project to easily create reproducible wireless network experiments in a controlled environment. We provide a low complexity algorithm to estimate the location of the mobile robots in the indoor environment. In addition, we provide a comparison between some of our collected measurements with their corresponding location estimation and the actual robot location. The comparison shows an accuracy between 0.65 and 5 meters.

cs.NI↗

arXiv1995

Current fluctuations in a single tunnel junction

We study noise spectra of currents through a tunnel junction in weak tunneling limit. We introduce effective capacitance to take into account the interaction effect and explicitly incorporate the electromagnetic environment of the junction into the formulation. We study the effect of charging energy and macroscopic environment on noise spectra. We calculate current fluctuations at tunneling barrier and fluctuations measured at leads. It is shown that two fluctuations have different noise spectra and the relation between them is nontrivial. We provide an explanation for the origin of the difference. Experimental implications are discussed.

cond-mat↗

arXiv1995

Estimate of Minimal Noise in a Quantum Conductor

We study zero temperature fluctuations of charge flow in a metallic loop induced by time dependent magnetic flux, and solve for the optimal way of varying flux in order to minimize noise. Optimal time dependence of the flux is a sum of ``solitons,'' each corresponding to quantized flux change. Minimal noise coincides with that for the binomial distribution with the number of attempts equal to the number of solitons and with the probabilies defined by the scattering matrix of the system.

cond-mat↗

arXiv1995

Coherent States of Alternating Current,

We study counting statistics of electric current pumped by pulses of an external field. The fluctuations depend on the pulse shape, and can be minimized by choosing the pulse shape properly. For an optimal pulse shape, the fluctuations are reduced to the {\it dc} level, i.e., they do not depend on the duty cycle of the signal. We develop an approach that allows to calculate all counting statistics for various driving fields, optimal and non-optimal. The statistics depend in an interesting way on the analytic structure of the field time dependence, and display an analogy with coherent states and instantons.

cond-mat↗

arXiv1994

Universal Statistics of Transport in Disordered Conductors

In low temperature limit, we study electron counting statistics of a disordered conductor. We derive an expression for the distribution of charge transmitted over a finite time interval by using a result from the random matrix theory of quasi one dimensional disordered conductors. In the metallic regime, we find that the peak of the distribution is Gaussian and shows negligible sample to sample variations. We also find that the tails of the distribution are neither Gaussian nor Poisson and exhibit strong sample to sample variations.

cond-mat↗