arXiv subjects

Lulu Zhang

Publications and source records attributed to Lulu Zhang.

47 records · Page 3Linked to original sources

arXiv2022

The Contribution of Evolved Stars to PAH Heating and Implications for Estimating Star Formation Rates

Emission from polycyclic aromatic hydrocarbons (PAHs) is a promising tool for estimating star formation rate (SFR) in galaxies, but the origin of its sources of excitation, which include not only young but possibly also old stars, remains uncertain. We analyze Spitzer mid-infrared mapping-mode spectroscopic observations of the nuclear and extra-nuclear regions of 33 nearby galaxies to study the contribution of evolved stars to PAH emission. In combination with photometric measurements derived from ultraviolet, Hα, and infrared images, the spatially resolved spectral decomposition enables us to characterize the PAH emission, SFR, and stellar mass of the sample galaxies on sub-kpc scales. We demonstrate that the traditional empirical correlation between PAH luminosity and SFR has a secondary dependence on specific SFR, or, equivalently, stellar mass. Ultraviolet-faint regions with lower specific SFRs and hence greater fraction of evolved stars emit stronger PAH emission at fixed SFR than ultraviolet-bright regions. We reformulate the PAH-based SFR estimator by explicitly introducing stellar mass as a second parameter to account for the contribution of evolved stars to PAH excitation. The influence of evolved stars can explain the sub-linear correlation between PAH emission and SFR, and it can partly account for the PAH deficit in dwarf galaxies and low-metallicity environments.

astro-ph.GA↗

arXiv2022

Crises Do Not Cause Lower Short-Term Growth

It is commonly believed that financial crises "lead to" lower growth of a country during the two-year recession period, which can be reflected by their post-crisis GDP growth. However, by contrasting a causal model with a standard prediction model, this paper argues that such a belief is non-causal. To make causal inferences, we design a two-stage staggered difference-in-differences model to estimate the average treatment effects. Interpreting the residuals as the contribution of each crisis to the treatment effects, we astonishingly conclude that cross-sectional crises are often limited to providing relevant causal information to policymakers.

econ.EM↗

arXiv2021

MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs

In this paper, we propose a a machine learning approach via model-operator-data network (MOD-Net) for solving PDEs. A MOD-Net is driven by a model to solve PDEs based on operator representation with regularization from data. For linear PDEs, we use a DNN to parameterize the Green's function and obtain the neural operator to approximate the solution according to the Green's method. To train the DNN, the empirical risk consists of the mean squared loss with the least square formulation or the variational formulation of the governing equation and boundary conditions. For complicated problems, the empirical risk also includes a few labels, which are computed on coarse grid points with cheap computation cost and significantly improves the model accuracy. Intuitively, the labeled dataset works as a regularization in addition to the model constraints. The MOD-Net solves a family of PDEs rather than a specific one and is much more efficient than original neural operator because few expensive labels are required. We numerically show MOD-Net is very efficient in solving Poisson equation and one-dimensional radiative transfer equation. For nonlinear PDEs, the nonlinear MOD-Net can be similarly used as an ansatz for solving nonlinear PDEs, exemplified by solving several nonlinear PDE problems, such as the Burgers equation.

math.NA↗

arXiv2021

Quantum-enhanced rubidium atomic magnetometer based on Faraday rotation via 795-nm Stokes operator squeezed light

With the help of Stokes operator S2 squeezed state (also called polarization squeezed state (PSS)) of 795-nm light, rubidium-87 (87Rb) atomic magnetometer based on Faraday rotation has been implemented and characterized.The PSS of Stokes operator S2 of 795-nm light has been prepared by means of coherently combining the polarization coherent state (PCS) of a linearly p-polarized bright 795-nm light beam and a linearly s-polarized squeezed vacuum state (SVS) generated by a 397.5-nm ultraviolet laser pumped sub-threshold optical parametric oscillator (OPO) with a PPKTP bulk crystal inside the OPO cavity.PSS with a squeezing level of -3.7 has been achieved around the analysis frequency of 10 kHz. At different transitions of D1 line, various frequency detuning, and reasonable atomic vapor cells temperature, Faraday rotation has been measured and compared.To decrease absorption (scattering) losses and the back-action from atomic spin noise to the probe beams polarization noise for maintaining the quantum properties of PSS of Stokes operator S2 of 795-nm light, we had to run our magnetometer with 87Rb vapor cells temperature below 60, at which the PSS was almost destroyed.The sensitivities of magnetic field measurement were characterized via measuring signal-to-noise ratio of the alternating current (AC) calibrated magnetic field signal with a balanced polarimeter. Under the conditions of the atomic number density of 5.8*1010 /cm3 and the probe beam with a detuning of - 400 MHz relative to the 5S1/2 (Fg=2) - 5P1/2 (Fe=1) transition of 87Rb D1 line, a typical sensitivity of 19.5 pT/Hz1/2 has been achieved employing PSS of Stokes operator S2 as the probe, compared with a sensitivity of 28.3 pT/Hz1/2 using PCS as the probe.We preliminarily demonstrated that the quantum-enhanced sensitivity in a Faraday-rotation-based 87Rb atomic magnetometer with the help of PSS of 795-nm light.

quant-ph↗

arXiv2021

Enhancement of spin noise spectroscopy of rubidium atomic ensemble by using of the polarization squeezed light

We measured the spin noise spectroscopy (SNS) of rubidium atomic ensemble with two different atomic vapor cells (filled with the buffer gases or coated with paraffin film on the inner wall), and demonstrated the enhancement of signal to noise ratio (SNR) by using of the polarization squeezed state (PSS) of 795 nm light field with Stokes operator S2 squeezed. PSS is prepared by locking the relative phase between the squeezed vacuum state of light obtained by a sub-threshold optical parametric oscillator and the orthogonal polarized local oscillator beam by means of the quantum noise lock. Under the same conditions, PSS can be employed not only to improve SNR, but also to keep the full width at half maximum (FWHM) of SNS unchanged, compared with the case of using polarization coherent state (PCS), and the enhancement of SNR is positively correlated with the squeezing level of PSS. With the increase of probe laser power and atomic number density, the SNR and FWHM of SNS will increase correspondingly. With the help of PSS of Stokes operator S2, quantum enhancement of both SNR and FWHM of SNS signal has been demonstrated by controlling optical power of the S2 polarization squeezed light beam or atomic number density in our experiments.

quant-ph↗

arXiv2021

Data-informed Deep Optimization

Complex design problems are common in the scientific and industrial fields. In practice, objective functions or constraints of these problems often do not have explicit formulas, and can be estimated only at a set of sampling points through experiments or simulations. Such optimization problems are especially challenging when design parameters are high-dimensional due to the curse of dimensionality. In this work, we propose a data-informed deep optimization (DiDo) approach as follows: first, we use a deep neural network (DNN) classifier to learn the feasible region; second, we sample feasible points based on the DNN classifier for fitting of the objective function; finally, we find optimal points of the DNN-surrogate optimization problem by gradient descent. To demonstrate the effectiveness of our DiDo approach, we consider a practical design case in industry, in which our approach yields good solutions using limited size of training data. We further use a 100-dimension toy example to show the effectiveness of our model for higher dimensional problems. Our results indicate that the DiDo approach empowered by DNN is flexible and promising for solving general high-dimensional design problems in practice.

math.OC↗

arXiv2020

A Method to Extract Spatially Resolved Polycyclic Aromatic Hydrocarbon Emission from Spitzer Spectra: Application to M51

The mid-infrared spectrum contains rich diagnostics to probe the physical properties of galaxies, among which the pervasive emission features from polycyclic aromatic hydrocarbons (PAHs) offer a promising means of estimating the star formation rate (SFR) relatively immune from dust extinction. This paper investigates the effectiveness of PAH emission as a SFR indicator on sub-kpc scales by studying the Spitzer/IRS mapping-mode observations of the nearby grand-design spiral galaxy M51. We present a new approach of analyzing the spatial elements of the spectral datacube that simultaneously maximizes spatial resolution and spatial coverage, while yielding reliable measurements of the total, integrated $5-20\,μ$m PAH emission. We devise a strategy of extracting robust PAH emission using spectra with only partial spectral coverage, complementing missing spectral regions with properly combined mid-infrared photometry. We find that in M51 the PAH emission correlates tightly with the extinction-corrected far-ultraviolet, near-ultraviolet, and H$α$ emission, from scales$\sim 0.4$ kpc close to the nucleus to 6 kpc out in the disk of the galaxy, indicating that PAH serves as an excellent tracer of SFR over a wide range of galactic environments. But regional differences exist. Close to the active nucleus of M51 the 6.2 $μ$m feature is weaker, and the overall level of PAH emission is suppressed. The spiral arms and the central star-forming region of the galaxy emit stronger 7.7 and 8.6 $μ$m PAH features than the inter-arm regions.

astro-ph.GA↗

arXiv2020

Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy

Millions of drivers worldwide have enjoyed financial benefits and work schedule flexibility through a ride-sharing economy, but meanwhile they have suffered from the lack of a sense of identity and career achievement. Equipped with social identity and contest theories, financially incentivized team competitions have been an effective instrument to increase drivers' productivity, job satisfaction, and retention, and to improve revenue over cost for ride-sharing platforms. While these competitions are overall effective, the decisive factors behind the treatment effects and how they affect the outcomes of individual drivers have been largely mysterious. In this study, we analyze data collected from more than 500 large-scale team competitions organized by a leading ride-sharing platform, building machine learning models to predict individual treatment effects. Through a careful investigation of features and predictors, we are able to reduce out-sample prediction error by more than 24%. Through interpreting the best-performing models, we discover many novel and actionable insights regarding how to optimize the design and the execution of team competitions on ride-sharing platforms. A simulated analysis demonstrates that by simply changing a few contest design options, the average treatment effect of a real competition is expected to increase by as much as 26%. Our procedure and findings shed light on how to analyze and optimize large-scale online field experiments in general.

cs.CY↗

arXiv2019

On the 2-adic complexity of a class of binary sequences of period $4p$ with optimal autocorrelation magnitude

Via interleaving Ding-Helleseth-Lam sequences, a class of binary sequences of period $4p$ with optimal autocorrelation magnitude was constructed in \cite{W. Su}. Later, Fan showed that the linear complexity of this class of sequences is quite good \cite{C. Fan}. Recently, Sun et al. determined the upper and lower bounds of the 2-adic complexity of such sequences \cite{Y. Sun3}. We determine the exact value of the 2-adic complexity of this class of sequences. The results show that the 2-adic complexity of this class of binary sequences is close to the maximum.

cs.IT↗

arXiv2019

On the 2-Adic Complexity of the Ding-Helleseth-Martinsen Binary Sequences

We determine the 2-adic complexity of the Ding-Helleseth-Martinsen (DHM) binary sequences by using cyclotomic numbers of order four, "Gauss periods" and "quadratic Gauss sum" on finite field $\mathbb{F}_q$ and valued in $\mathbb{Z}_{2^N-1}$ where $q \equiv 5\pmod 8$ is a prime number and $N=2q$ is the period of the DHM sequences.

cs.IT↗

arXiv2018

Highly efficient visible colloidal lead-halide perovskite nanocrystal light-emitting diodes

Lead-halide perovskites have been attracting attention for potential use in solid-state lighting. Following the footsteps of solar cells, the field of perovskite light-emitting diodes (PeLEDs) has been growing rapidly. Their application prospects in lighting, however, remain still uncertain due to a variety of shortcomings in device performance including their limited levels of luminous efficiency achievable thus far. Here we show high-efficiency PeLEDs based on colloidal perovskite nanocrystals (PeNCs) synthesized at room temperature possessing dominant first-order excitonic radiation (enabling a photoluminescence quantum yield of 71% in solid film), unlike in the case of bulk perovskites with slow electron-hole bimolecular radiative recombination (a second-order process). In these PeLEDs, by reaching charge balance in the recombination zone, we find that the Auger nonradiative recombination, with its significant role in emission quenching, is effectively suppressed in low driving current density range. In consequence, these devices reach a record high maximum external quantum efficiency of 12.9% reported to date and an unprecedentedly high power efficiency of 30.3 lm W-1 at luminance levels above 1000 cd m-2 as required for various applications. These findings suggest that, with feasible levels of device performance, the PeNCs hold great promise for their use in LED lighting and displays.

physics.app-ph↗