Determining the Thin Film Thickness of Two Phase Flow using Optics and Image Processing

Gas- Liquid flows are by far the most important type of multiphase flow. This can be attributed to the wide range of industrial applications that the gas-liquid flow is discerned in. Popular examples of Gas-liquid flows are oil-gas mixtures, evaporators, boilers, condensers, refrigeration and cryogenics. The measurement of the liquid film thickness in two phase flows is prominent in various heat and mass transfer applications such as in boilers. To determine the thin film thickness is the aim of this study. A glass tube of diameter 4.7 mm is used for conducting the experiment and a laser pointer is used to obtain an image pattern on the screen. Using the principles of Optics, a method has been proposed to determine the thin film thickness and also to characterize the different types of flow. The thin film thickness obtained in the proposed method is validated using Image Processing

Optimizing machine learning methods to discover strong gravitational lenses in the Deep Lens Survey

Machine learning models can greatly improve the search for strong gravitational lenses in imaging surveys by reducing the amount of human inspection required. In this work, we test the performance of supervised, semi-supervised, and unsupervised learning algorithms trained with the ResNetV2 neural network architecture on their ability to efficiently find strong gravitational lenses in the Deep Lens Survey (DLS). We use galaxy images from the survey, combined with simulated lensed sources, as labeled data in our training datasets. We find that models using semi-supervised learning along with data augmentations (transformations applied to an image during training, e.g., rotation) and Generative Adversarial Network (GAN) generated images yield the best performance. They offer 5--10 times better precision across all recall values compared to supervised algorithms. Applying the best performing models to the full 20 deg$^2$ DLS survey, we find 3 Grade-A lens candidates within the top 17 image predictions from the model. This increases to 9 Grade-A and 13 Grade-B candidates when $1$% ($\sim2500$ images) of the model predictions are visually inspected. This is $\gtrsim10\times$ the sky density of lens candidates compared to current shallower wide-area surveys (such as the Dark Energy Survey), indicating a trove of lenses awaiting discovery in upcoming deeper all-sky surveys. These results suggest that pipelines tasked with finding strong lens systems can be highly efficient, minimizing human effort. We additionally report spectroscopic confirmation of the lensing nature of two Grade-A candidates identified by our model, further validating our methods.Comment: 23 pages, 15 figures (including appendix), published in MNRA

Kinematics of the Circumgalactic Medium of a z=0.77z = 0.77 Galaxy from MgII Tomography

Galaxy evolution is thought to be driven in large part by the flow of gas between galaxies and the circumgalactic medium (CGM), a halo of metal-enriched gas extending out to $\gtrsim100$ kpc from each galaxy. Studying the spatial structure of the CGM holds promise for understanding these gas flow mechanisms; however, the common method using background quasar sightlines provides minimal spatial information. Recent works have shown the utility of extended background sources such as giant gravitationally lensed arcs. Using background lensed arcs from the CSWA 38 lens system, we continuously probed, at a resolution element of about 15 kpc$^2$, the spatial and kinematic distribution of MgII absorption in a star-forming galaxy at $z=0.77$ (stellar mass $\approx 10^{9.7}$ M$_\odot$, star formation rate $\approx 10$ M$_\odot$ yr$^{-1}$) at impact parameters $D=5-40$ kpc. Our results present an anisotropic, optically thick medium whose absorption strength decreases with increasing impact parameter, in agreement with the statistics towards quasars and other gravitational arcs. Furthermore, we detect low line-of-sight velocities ($v\approx-25-80$ km s$^{-1}$) and relatively high velocity dispersion ($\sigma\approx50\pm30$ km s$^{-1}$) in the MgII gas. These measures provide evidence of a mainly pressure-supported, metal-enriched diffuse gas recycling through the CGM rather than an active galactic outflow.Comment: 19 pages, 8 figures, 5 table

Resolved velocity profiles of galactic winds at Cosmic Noon

We study the kinematics of the interstellar medium (ISM) viewed "down the barrel" in 20 gravitationally lensed galaxies during Cosmic Noon ($z=1.5 - 3.5$). We use moderate-resolution spectra ($R\sim4000$) from Keck/ESI and Magellan/MagE to spectrally resolve the ISM absorption in these galaxies into $\sim$10 independent elements and use double Gaussian fits to quantify the velocity structure of the gas. We find that the bulk motion of gas in this galaxy sample is outflowing, with average velocity centroid \left=-141 km$\,$s$^{-1}$ ($\pm111$ km$\,$s$^{-1}$ scatter) measured with respect to the systemic redshift. 16 out of the 20 galaxies exhibit a clear positive skewness, with a blueshifted tail extending to $\sim -500$ km$\,$s$^{-1}$. We examine scaling relations in outflow velocities with galaxy stellar mass and star formation rate (SFR), finding correlations consistent with a momentum-driven wind scenario. Our measured outflow velocities are also comparable to those reported for FIRE-2 and TNG50 cosmological simulations at similar redshift and galaxy properties. We also consider implications for interpreting results from lower-resolution spectra. We demonstrate that while velocity centroids are accurately recovered, the skewness, velocity width, and probes of high velocity gas (e.g., $v_{95}$) are subject to large scatter and biases at lower resolution. We find that $R\gtrsim1700$ is required for accurate results for the gas kinematics of our sample. This work represents the largest available sample of well-resolved outflow velocity structure at $z>2$, and highlights the need for good spectral resolution to recover accurate properties.Comment: 42 pages, 37 figures (including appendix), Accepted for publication, Ap

A Glimpse of the Stellar Populations and Elemental Abundances of Gravitationally Lensed, Quiescent Galaxies at z≳1z\gtrsim 1 with Keck Deep Spectroscopy

Gravitational lenses can magnify distant galaxies, allowing us to discover and characterize the stellar populations of intrinsically faint, quiescent galaxies that are otherwise extremely difficult to directly observe at high redshift from ground-based telescopes. Here, we present the spectral analysis of two lensed, quiescent galaxies at $z\gtrsim 1$ discovered by the ASTRO 3D Galaxy Evolution with Lenses survey: AGEL1323 ($M_*\sim 10^{11.1}M_{\odot}$, $z=1.016$, $\mu \sim 14.6$) and AGEL0014 ($M_*\sim 10^{11.3}M_{\odot}$, $z=1.374$, $\mu \sim 4.3$). We measured the age, [Fe/H], and [Mg/Fe] of the two lensed galaxies using deep, rest-frame-optical spectra (S/N $\gtrsim$ 40\AA$^{-1}$) obtained on the Keck I telescope. The ages of AGEL1323 and AGEL0014 are $5.6^{+0.8}_{-0.8}$ Gyr and $3.1^{+0.8}_{-0.3}$ Gyr, respectively, indicating that most of the stars in the galaxies were formed less than 2 Gyr after the Big Bang. Compared to nearby quiescent galaxies of similar masses, the lensed galaxies have lower [Fe/H] and [Mg/H]. Surprisingly, the two galaxies have comparable [Mg/Fe] to similar-mass galaxies at lower redshifts, despite their old ages. Using a simple analytic chemical evolution model connecting the instantaneously recycled element Mg with the mass-loading factors of outflows averaged over the entire star formation history, we found that the lensed galaxies may have experienced enhanced outflows during their star formation compared to lower-redshift galaxies, which may explain why they quenched early.Comment: 18 pages, 11 figures, submitted to ApJ; comments welcom

The AGEL Survey: Spectroscopic Confirmation of Strong Gravitational Lenses in the DES and DECaLS Fields Selected Using Convolutional Neural Networks

We present spectroscopic confirmation of candidate strong gravitational lenses using the Keck Observatory and Very Large Telescope as part of our ASTRO 3D Galaxy Evolution with Lenses (AGEL) survey. We confirm that 1) search methods using Convolutional Neural Networks (CNN) with visual inspection successfully identify strong gravitational lenses and 2) the lenses are at higher redshifts relative to existing surveys due to the combination of deeper and higher resolution imaging from DECam and spectroscopy spanning optical to near-infrared wavelengths. We measure 104 redshifts in 77 systems selected from a catalog in the DES and DECaLS imaging fields (r<22 mag). Combining our results with published redshifts, we present redshifts for 68 lenses and establish that CNN-based searches are highly effective for use in future imaging surveys with a success rate of 88% (defined as 68/77). We report 53 strong lenses with spectroscopic redshifts for both the deflector and source (z_src>z_defl), and 15 lenses with a spectroscopic redshift for either the deflector (z_defl>0.21) or source (z_src>1.34). For the 68 lenses, the deflectors and sources have average redshifts and standard deviations of 0.58+/-0.14 and 1.92+/-0.59 respectively, and corresponding redshift ranges of (0.21<z_defl<0.89) and (0.88<z_src<3.55). The AGEL systems include 41 deflectors at zdefl>0.5 that are ideal for follow-up studies to track how mass density profiles evolve with redshift. Our goal with AGEL is to spectroscopically confirm ~100 strong gravitational lenses that can be observed from both hemispheres throughout the year. The AGEL survey is a resource for refining automated all-sky searches and addressing a range of questions in astrophysics and cosmology.Comment: Submitted to AJ, revised version in response to referee repor