arXiv subjects

Jae Joon Lee

Publications and source records attributed to Jae Joon Lee.

5 recordsLinked to original sources

arXiv2025

Dynamical generation of geometric squeezing in interacting Bose-Einstein condensates

When the rotating frequency of a non-interacting Bose-Einstein condensate (BEC) confined in a weak anisotropic harmonic potential is suddenly quenched to its trapping frequency, the condensate evolves from its ground state to a single-mode squeezed state with exponentially growing quantum fluctuation anisotropy. Such a squeezed state is called the geometrically squeezed state. However, for interacting BECs with two-body collisions, a similar quench only results in quantum fluctuations oscillating periodically without squeezing. In this work, we identify superfluid stability as the key factor behind this non-squeezing phenomenon, with the periodic oscillations arising from collective excitations of a stable collective excitation mode. By strategically breaking the stability criteria, we propose a dynamical approach for generating squeezing that can exponentially suppress quantum fluctuations in a relatively short time, surpassing the efficiency of existing experimental preparation schemes.

cond-mat.quant-gas↗

arXiv2025

The SPHEREx Sky Simulator: Science Data Modeling for the First All-Sky Near-Infrared Spectral Survey

We describe the SPHEREx Sky Simulator, a software tool designed to model science data for NASA's SPHEREx mission that will carry out a series of all-sky spectrophotometric surveys at $\sim$6'' spatial resolution in 102 spectral channels spanning 0.75 to 5 $μ$m. The Simulator software implements models for astrophysical emission, instrument characteristics, and survey strategy to generate realistic infrared sky scenes as they will be observed by SPHEREx. The simulated data includes a variety of realistic noise and systematic effects that are estimated using up-to-date astrophysical measurements and information from pre-launch instrument characterization campaigns. Through the pre-flight mission phases the Simulator has been critical in predicting the impact of various effects on SPHEREx science performance, and has played an important role guiding the development of the SPHEREx data analysis pipeline. In this paper, we describe the \skysim\ architecture, pre-flight instrument and sky models, and summarize high-level predictions from the Simulator, including a pre-launch prediction for the 5$σ$ point source sensitivity of SPHEREx, which we estimate to be $m_{\rm AB}$ 18.5--19 from 0.75 to 3.8~$μ$m and $m_{\rm AB}$ 16.6--18 from 3.8 to 5 $μ$m, with the sensitivity limited by the zodiacal light background at all wavelengths. In the future, on-orbit data will be used to improve the Simulator, which will form the basis of a variety of forward-modeling tools that will be used to model myriad instrumental and astrophysical processes to characterize their systematic effects on our final data products and analyses.

astro-ph.IM↗

arXiv2021

IGRINS RV: A Precision RV Pipeline for IGRINS Using Modified Forward Modeling in the Near-Infrared

Application of the radial velocity (RV) technique in the near infrared is valuable because of the diminished impact of stellar activity at longer wavelengths, making it particularly advantageous for the study of late-type stars but also for solar-type objects. In this paper, we present the IGRINS RV open source python pipeline for computing infrared RV measurements from reduced spectra taken with IGRINS, a R ~ 45,000 spectrograph with simultaneous coverage of the H band (1.49--1.80 $μ$m) and K band (1.96--2.46 $μ$m). Using a modified forward modeling technique, we construct high resolution telluric templates from A0 standard observations on a nightly basis to provide a source of common-path wavelength calibration while mitigating the need to mask or correct for telluric absorption. Telluric standard observations are also used to model the variations in instrumental resolution across the detector, including a yearlong period when the K band was defocused. Without any additional instrument hardware, such as a gas cell or laser frequency comb, we are able to achieve precisions of 26.8 $\rm m\,s^{-1}$ in the K band and 31.1 $\rm m\,s^{-1}$ in the H band for narrow-line hosts. These precisions are empirically determined by a monitoring campaign of two RV standard stars as well as the successful retrieval of planet-induced RV signals for both HD 189733 and $τ$ Boo A; furthermore, our results affirm the presence of the Rossiter-McLaughlin effect for HD 189733. The IGRINS RV pipeline extends another important science capability to IGRINS, with publicly available software designed for widespread use.

astro-ph.IM↗

arXiv2021

Supervised Machine Learning for Eliciting Individual Demand

Direct elicitation, guided by theory, is the standard method for eliciting latent preferences. The canonical direct-elicitation approach for measuring individuals' valuations for goods is the Becker-DeGroot-Marschak procedure, which generates willingness-to-pay (WTP) values that are imprecise and systematically biased by understating valuations. We show that enhancing elicited WTP values with supervised machine learning (SML) can substantially improve estimates of peoples' out-of-sample purchase behavior. Furthermore, swapping WTP data with choice data generated from a simple task, two-alternative forced choice, leads to comparable performance. Combining all the data with the best-performing SML methods yields large improvements in predicting out-of-sample purchases. We quantify the benefit of using various SML methods in conjunction with using different types of data. Our results suggest that prices set by SML would increase revenue by 28% over using the stated WTP, with the same data.

econ.GN↗

arXiv2018

Kinematic evidence for feedback-driven star formation in NGC 1893

OB associations are the prevailing star forming sites in the Galaxy. Up to now, the process of how OB associations were formed remained a mystery. A possible process is self-regulating star formation driven by feedback from massive stars. However, although a number of observational studies uncovered various signposts of feedback-driven star formation, the effectiveness of such feedback has been questioned. Stellar and gas kinematics is a promising tool to capture the relative motion of newborn stars and gas away from ionizing sources. We present high-resolution spectroscopy of stars and gas in the young open cluster NGC 1893. Our findings show that newborn stars and the tadpole nebula Sim 130 are moving away from the central cluster containing two O-type stars, and that the timescale of sequential star formation is about 1 Myr within a 9 parsec distance. The newborn stars formed by feedback from massive stars account for at least 18 per cent of the total stellar population in the cluster, suggesting that this process can play an important role in the formation of OB associations. These results support the self-regulating star formation model.

astro-ph.SR↗