<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Lilian Lee's personal website]]></title><description><![CDATA[Lilian Lee's personal website]]></description><link>http://github.com/dylang/node-rss</link><generator>GatsbyJS</generator><lastBuildDate>Sat, 18 Apr 2026 16:58:59 GMT</lastBuildDate><item><title><![CDATA[The ALPINE-CRISTAL-JWST Survey: Gas-phase abundance gradients of main sequence star-forming galaxies and their kinematics at 4<z<6]]></title><description><![CDATA[We present gas-phase radial metallicity profiles for main-sequence galaxies at 4<z<6, primarily based on JWST NIRSpec IFU observations obtained as part of the JWST-ALPINE-CRISTAL programme. Our study aims to connect the metallicity gradients of these galaxies with their kinematic properties from [CII]158μm ALMA observations. We map the radial profiles of oxygen abundance using the strong-line method leveraging the rich set of rest-frame optical emission lines. ...]]></description><link>https://lilianlylee.com//posts/metals</link><guid isPermaLink="false">https://lilianlylee.com//posts/metals</guid><pubDate>Tue, 07 Oct 2025 22:40:32 GMT</pubDate><content:encoded>&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;We present gas-phase radial metallicity profiles for main-sequence galaxies at 4&amp;#x3C;z&amp;#x3C;6, primarily based on JWST NIRSpec IFU observations obtained as part of the JWST-ALPINE-CRISTAL programme. Our study aims to connect the metallicity gradients of these galaxies with their kinematic properties from [CII]158μm ALMA observations. We map the radial profiles of oxygen abundance using the strong-line method leveraging the rich set of rest-frame optical emission lines. Linear fits to the annular-binned radial profiles show that, on average, the metallicity gradients are slightly positive with a median of +0.039 +/- 0.010 dex kpc-1. There are no substantial systematic offsets in gradients when using different line diagnostics. However, only three galaxies show a gradient &gt;0.05 dex kpc-1 at 1σ, and none have a significant negative gradient. We investigate the correlation between the metallicity gradients and the intrinsic gas velocity dispersion σ_0, as well as the ratio V_rot/σ_0 of the disks. Combining our sample with mass-matched literature samples at 3&amp;#x3C;~z&amp;#x3C;~7, we find a negative shallow correlation between V_rot /σ_0 and the metallicity gradients, but no strong relationships with σ_0. As V_rot/σ_0 increases towards later cosmic times, the observed negative trend with V_rot/σ_0 is consistent with the overall cosmic evolution of metallicity gradients from high to low redshifts. This suggests that disk maturity plays a crucial role in shaping the radial metallicity gradients. We do not find the metallicity gradients of disk galaxies significantly different from non-disk galaxies, which could be attributed to the frequent accretion events that took place in these gas-rich systems. Additionally, we find no strong dependence of metallicity gradients on stellar mass and only a marginal positive dependence on specific star-formation rate. Our study extends the efforts to connect the internal kinematics of galaxies with their gas-phase chemical enrichment at kpc scales from cosmic noon to z&gt;4.&lt;/p&gt;
&lt;p&gt;[&lt;strong&gt;Click &lt;a href=&quot;https://arxiv.org/pdf/2603.13493&quot; target=&quot;_blank&quot; rel=&quot;nofollow noopener noreferrer&quot;&gt;here&lt;/a&gt; for the full article&lt;/strong&gt;]&lt;/p&gt;
&lt;!-- **Key Figure** --&gt;
&lt;!-- ![](/oneoneplot_dygpbb_ratio_disp_v8.png) --&gt;</content:encoded></item><item><title><![CDATA[The ALMA-CRISTAL survey: Resolved kinematic studies of main sequence star-forming galaxies at 4 < z < 6]]></title><description><![CDATA[We present a detailed kinematic study of a sample of 32 massive (9.5 ⩽ log(M*/M⊙) ⩽ 10.9) main sequence star-forming galaxies (MS SFGs) at 4 < z < 6 from the ALMA-CRISTAL programme. The data consist of deep (up to 15 hr observing time per target), high-resolution (∼1 kpc) ALMA observations of [C II]158 μm line emission. This dataset allowed us to carry out the first systematic, kiloparsec-scale (kpc-scale) characterisation of the kinematics nature of typical massive SFGs at these epochs... ]]></description><link>https://lilianlylee.com//posts/alma-cristal</link><guid isPermaLink="false">https://lilianlylee.com//posts/alma-cristal</guid><pubDate>Mon, 01 Sep 2025 23:46:37 GMT</pubDate><content:encoded>&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;We present a detailed kinematic study of a sample of 32 massive (9.5 ⩽ log(M*/M⊙) ⩽ 10.9) main sequence star-forming galaxies (MS SFGs) at 4 &amp;#x3C; z &amp;#x3C; 6 from the ALMA-CRISTAL programme. The data consist of deep (up to 15 hr observing time per target), high-resolution (∼1 kpc) ALMA observations of [C II]158 μm line emission. This dataset allowed us to carry out the first systematic, kiloparsec-scale (kpc-scale) characterisation of the kinematics nature of typical massive SFGs at these epochs. We find that &lt;strong&gt;∼50% of the sample are disk-like&lt;/strong&gt;, with a number of galaxies located in systems of multiple components. Kinematic modelling reveals these main sequence disks exhibit high-velocity dispersions (σ0), with a median disk velocity dispersion of &lt;strong&gt;∼70 km s‑1 and Vrot/σ0 ∼ 2, which is consistent with dominant gravity driving&lt;/strong&gt;. The elevated disk dispersions are in line with the predicted evolution based on Toomre theory and the extrapolated trends from z ∼ 0–2.5 MS star-forming disks. The inferred dark matter (DM) mass fraction within the effective radius &lt;strong&gt;fDM(&amp;#x3C; Re) for the disk systems decreases with the central baryonic mass surface density&lt;/strong&gt;. This is consistent with the trend reported by kinematic studies at z ≲ 3; roughly half the disks display fDM(&amp;#x3C; Re)≲ 30%. The CRISTAL sample of massive MS SFGs provides a reference of the kinematics of a representative population and extends the view onto typical galaxies beyond previous kpc-scale studies at z ≲ 3.&lt;/p&gt;
&lt;p&gt;[&lt;strong&gt;Click &lt;a href=&quot;https://www.aanda.org/articles/aa/pdf/2025/09/aa55362-25.pdf&quot; target=&quot;_blank&quot; rel=&quot;nofollow noopener noreferrer&quot;&gt;here&lt;/a&gt; for the full article&lt;/strong&gt;]&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Key Figures&lt;/strong&gt;&lt;/p&gt;
&lt;figure style=&quot;max-width:400px;margin:0 auto 1rem auto;text-align:center;&quot;&gt;
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  &lt;figcaption style=&quot;font-size:0.9em;color:#555;text-align:center;&quot;&gt;Figure 1. Velocity fields of the CRISTAL sources.&lt;/figcaption&gt;
&lt;/figure&gt;
&lt;figure style=&quot;max-width:400px;margin:0 auto 1rem auto;text-align:center;&quot;&gt;
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  &lt;figcaption style=&quot;font-size:0.9em;color:#555;text-align:center;&quot;&gt;Figure 2. Redshift evolution of rotational support of disk galaxies.&lt;/figcaption&gt;
&lt;/figure&gt;</content:encoded></item><item><title><![CDATA[Disk Kinematics at High Redshift: DysmalPy's Extension to 3D Modeling and Comparison with Different Approaches]]></title><description><![CDATA[Spatially resolved emission-line kinematics are invaluable for investigating fundamental galaxy properties and have become increasingly accessible for galaxies at z ≳0.5 through sensitive near-infrared imaging spectroscopy and millimeter interferometry. Kinematic modeling is at the core of the analysis and interpretation of such data sets, which at high z present challenges due to the lower signal-to-noise ratio (S/N) and resolution compared to the data of local galaxies. We present and test the 3D fitting functionality of DysmalPy, examining how well it recovers the intrinsic disk rotation velocity and velocity dispersion, using a large suite of axisymmetric models, covering a range of galaxy properties and observational parameters typical of z ∼ 1‑3 star-forming galaxies. We also compare DysmalPy's recovery performance to that of two other commonly used codes, GalPak 3D and 3D Barolo, which we use in turn to create additional sets of models to benchmark DysmalPy...]]></description><link>https://lilianlylee.com//posts/dysmalpy</link><guid isPermaLink="false">https://lilianlylee.com//posts/dysmalpy</guid><pubDate>Wed, 01 Jan 2025 22:40:32 GMT</pubDate><content:encoded>&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;Spatially resolved emission-line kinematics are invaluable for investigating fundamental galaxy properties and have become increasingly accessible for galaxies at z ≳0.5 through sensitive near-infrared imaging spectroscopy and millimeter interferometry. Kinematic modeling is at the core of the analysis and interpretation of such data sets, which at high z present challenges due to the lower signal-to-noise ratio (S/N) and resolution compared to the data of local galaxies. We present and test the 3D fitting functionality of DysmalPy, examining how well it recovers the intrinsic disk rotation velocity and velocity dispersion, using a large suite of axisymmetric models, covering a range of galaxy properties and observational parameters typical of z ∼ 1‑3 star-forming galaxies. We also compare DysmalPy’s recovery performance to that of two other commonly used codes, GalPak 3D and 3D Barolo, which we use in turn to create additional sets of models to benchmark DysmalPy. Over the ranges of S/N, resolution, mass, and velocity dispersion explored, the rotation velocity is accurately recovered by all tools. The velocity dispersion is recovered well at high S/N, but the impact of methodology differences is more apparent. In particular, template differences for parametric tools and S/N sensitivity for the nonparametric tool can lead to differences of up to a factor of 2. Our tests highlight and the importance of deep, high-resolution data and the need for careful consideration of (i) the choice of priors (parametric approaches); and (ii) the masking (all approaches); and (iii), more generally, the evaluating of the suitability of each approach to the specific data at hand. This paper accompanies the public release of DysmalPy.&lt;/p&gt;
&lt;p&gt;[&lt;strong&gt;Click &lt;a href=&quot;https://iopscience.iop.org/article/10.3847/1538-4357/ad90b5/pdf&quot; target=&quot;_blank&quot; rel=&quot;nofollow noopener noreferrer&quot;&gt;here&lt;/a&gt; for the full article&lt;/strong&gt;]&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Key Figure&lt;/strong&gt;&lt;/p&gt;
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            style=&quot;width:100%;height:100%;margin:0;vertical-align:middle;position:absolute;top:0;left:0;&quot;
          /&gt;
        &lt;/picture&gt;
  &lt;/a&gt;
    &lt;/span&gt;&lt;/p&gt;
&lt;!-- 
**Pellentesque habitant morbi tristique** senectus et netus et malesuada fames ac turpis egestas. Vestibulum tortor quam, feugiat vitae, ultricies eget, tempor sit amet, ante. Donec eu libero sit amet quam egestas semper. _Aenean ultricies mi vitae est._ Mauris placerat eleifend leo. Quisque sit amet est et sapien ullamcorper pharetra.

Vestibulum erat wisi, condimentum sed, commodo vitae, ornare sit amet, wisi. Aenean fermentum, elit eget tincidunt condimentum, eros ipsum rutrum orci, sagittis tempus lacus enim ac dui. [Donec non enim](#) in turpis pulvinar facilisis.

![Nulla faucibus vestibulum eros in tempus. Vestibulum tempor imperdiet velit nec dapibus](/image.jpg)

## Aenean viverra

- Lorem ipsum dolor sit amet, consectetuer adipiscing elit.
- Aliquam tincidunt mauris eu risus.

Donec non enim in turpis pulvinar facilisis. Ut felis. Praesent dapibus, neque id cursus faucibus, tortor neque egestas augue, eu vulputate magna eros eu erat. Aliquam erat volutpat.

&lt;figure&gt;
	&lt;blockquote&gt;
		&lt;p&gt;Lorem ipsum dolor sit amet, consectetur adipiscing elit. Vivamus magna. Cras in mi at felis aliquet congue. Ut a est eget ligula molestie gravida. Curabitur massa. Donec eleifend, libero at sagittis mollis, tellus est malesuada tellus, at luctus turpis elit sit amet quam. Vivamus pretium ornare est.&lt;/p&gt;
		&lt;footer&gt;
			&lt;cite&gt;— Aliquam tincidunt mauris eu risus.&lt;/cite&gt;
		&lt;/footer&gt;
	&lt;/blockquote&gt;
&lt;/figure&gt;

### Vivamus pretium

- Lorem ipsum dolor sit amet, consectetuer adipiscing elit.
- Aliquam tincidunt mauris eu risus.

Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Vestibulum tortor quam, feugiat vitae, ultricies eget, tempor sit amet, ante. Donec eu libero sit amet quam egestas semper. Aenean ultricies mi vitae est. Mauris placerat eleifend leo. Quisque sit amet est et sapien ullamcorper pharetra.
Vestibulum erat wisi, condimentum sed, commodo vitae, ornare sit amet, wisi. Aenean fermentum, elit eget tincidunt condimentum, eros ipsum rutrum orci, sagittis tempus lacus enim ac dui. Donec non enim in turpis pulvinar facilisis. Ut felis. Praesent dapibus, neque id cursus faucibus, tortor neque egestas augue, eu vulputate magna eros eu erat. Aliquam erat volutpat. Nam dui mi, tincidunt quis, accumsan porttitor, facilisis luctus, metus. --&gt;</content:encoded></item></channel></rss>