arXiv subjects

E. Lin

Publications and source records attributed to E. Lin.

5 recordsLinked to original sources

arXiv2025

DESI Strong Lens Foundry V: A Sample of HST-Observed Strong Lenses Modeled with GIGA-Lens

We present six galaxy-scale strong lenses with HST imaging modeled using GIGA-Lens. This is Paper V of the DESI Strong Lens Foundry series. These systems were discovered in the DESI Legacy Imaging Surveys using ML/AI methods and confirmed with DESI, Keck/NIRES, and VLT/MUSE spectroscopy. They span $z_d = 0.39 - 1.1$ and $z_s = 1.4 - 3.3$. This is the first HST strong lens sample modeled with full forward modeling -- all lens and source parameters sampled simultaneously in a single inference -- with explicit convergence validation using both $\widehat{R}$ and effective sample size (ESS) for each system. All inferred parameters satisfy $\widehat{R} < 1.1$ and ${\rm ESS} \gtrsim 10,000$, demonstrating that GIGA-Lens achieves statistically robust inference even for some of the most complex galaxy-scale lenses known. These results pave the way for scaling to much larger, high-resolution strong lens samples from HST, Euclid, JWST, and Roman. Convergence-validated modeling will be critical for key science goals, including constraining the mass-density profile of galaxies, detecting low-mass dark matter (sub)halos, and delivering precise and accurate cosmological constraints.

astro-ph.CO↗

arXiv2020

Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects

In this paper we investigate how implementing machine learning could improve the efficiency of the search for Trans-Neptunian Objects (TNOs) within Dark Energy Survey (DES) data when used alongside orbit fitting. The discovery of multiple TNOs that appear to show a similarity in their orbital parameters has led to the suggestion that one or more undetected planets, an as yet undiscovered "Planet 9", may be present in the outer Solar System. DES is well placed to detect such a planet and has already been used to discover many other TNOs. Here, we perform tests on eight different supervised machine learning algorithms, using a dataset consisting of simulated TNOs buried within real DES noise data. We found that the best performing classifier was the Random Forest which, when optimised, performed well at detecting the rare objects. We achieve an area under the receiver operating characteristic (ROC) curve, (AUC) $= 0.996 \pm 0.001$. After optimizing the decision threshold of the Random Forest, we achieve a recall of 0.96 while maintaining a precision of 0.80. Finally, by using the optimized classifier to pre-select objects, we are able to run the orbit-fitting stage of our detection pipeline five times faster.

astro-ph.EP↗

arXiv2018

The Diverse Science Return from a Wide-Area Survey of the Galactic Plane

The overwhelming majority of objects visible to LSST lie within the Galactic Plane. Though many previous surveys have avoided this region for fear of stellar crowding, LSST's spatial resolution combined with its state-of-the-art Difference Image Analysis mean that it can conduct a high cadence survey of most of the Galaxy for the first time. Here we outline the many areas of science that would greatly benefit from an LSST survey that included the Galactic Plane, Magellanic Clouds and Bulge at a cadence of 2-3 d. Particular highlights include measuring the mass spectrum of black holes, and mapping the population of exoplanets in the Galaxy in relation to variations in star forming environments. But the same survey data will provide a goldmine for a wide range of science, and we explore possible survey strategies which maximize the scientific return for a number of fields including young stellar objects, cataclysmic variables and Neptune Trojans.

astro-ph.IM↗

arXiv2003

Measurement of Electron Backscattering in the Energy Range of Neutron $β$-Decay

We report on the first detailed measurements of electron backscattering from low Z targets at energies up to 124 keV. Both energy and angular distributions of the backscattered electrons are measured and compared with electron transport simulations based on the Geant4 and Penelope Monte Carlo simulation codes. Comparisons are also made with previous, less extensive, measurements and with measurements at lower energies.

nucl-ex↗

arXiv2002

Wakefield Band Partitioning In Linac Structures

In the NLC project multiple bunches of electrons and positrons will be accelerated initially to a centre of mass of 500 GeV and later to 1 TeV or more. In the process of accelerating 192 bunches within a pulse train, wakefields are excited which kick the trailing bunches off axis and can cause luminosity dilution and BBU (Beam Break Up). Several structures to damp the wakefield have been designed and tested at SLAC and KEK and these have been found to successfully damp the wakefield [1]. However, these 2pi/3 structures suffered from electrical breakdown and this has prompted us to explore lower group velocity structures operating at higher fundamental mode phase advances. The wakefield partitioning amongst the bands has been found to change markedly with increased phase advance. Here we report on general trends in the kick factor and associated wakefield band partitioning in dipole bands as a function of phase advance of the synchronous mode in linacs. These results are applicable to both TW (travelling wave) and SW (standing wave) structures [1] R.M. Jones et al, PAC99, also SLAC-PUB-8103

physics.acc-ph↗