arXiv 2302.012932023-02-01astro-ph.EPastro-ph.IMastro-ph.SR

QLP Data Release Notes 003: GPU-based Transit Search

Michelle Kunimoto, Evan Tey, Willie Fong, Katharine Hesse, Glen Petitpas, Avi Shporer

备注：: 2 pages

英文摘要：

The Quick-Look Pipeline (QLP; Huang et al. 2020, Kunimoto et al. 2021 and references therein) searches for transit signals in the multi-sector light curves of several hundreds of thousand stars observed by TESS every 27.4-day sector. The computational expense of the planet search has grown considerably over time, especially as the TESS observing baseline continues to increase in the second Extended Mission. Starting in Sector 59, QLP has switched to a significantly faster GPU-based transit search capable of searching an entire sector in only ~1 day. We describe its implementation and performance.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

阅读原文

阅读 PDF ↗

arXiv 页面 ↗HTML 原文 ↗

本文内容

英文摘要相关论文

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

继续探索

相关论文

QLP Data Release Notes 002: Improved Detrending Algorithm

Light curves feature many kinds of variability, including instrumental systematics, intrinsic stellar variability such as pulsations, and flux changes caused by transiting exoplanets or eclipsing binary stars. Detrending is a key pre-planet-search data processing step that aims to remove variability not due to transits. This data release note describes improvements to the Quick-Look Pipeline's detrending algorithm via the inclusion of quaternion data to remove short-timescale systematics. We describe updates to our procedure, intermediate data products outputted by the algorithm, and improveme…

2022-11-08astro-ph.EPastro-ph.IM

QLP Data Release Notes 001: K2 + TESS Analysis

TESS will target the ecliptic plane in Sectors 42 - 46. These sectors overlap with campaigns from the K2 mission, providing a unique opportunity for multi-mission light curve analysis. This data release note describes the combined analysis of K2 and TESS light curves as part of the Quick-Look Pipeline (QLP) procedure, which processes light curves for all targets in TESS Full-Frame Images (FFIs) down to TESS magnitude T = 13.5. We describe updates to our codebase, and the planet transit search, candidate triage, and report generation that are affected by this combined analysis.

2021-10-22astro-ph.EPastro-ph.IM

The TESS Faint Star Search: 1,617 TOIs from the TESS Primary Mission

We present the detection of 1,617 new transiting planet candidates, identified in the Transiting Exoplanet Survey Satellite (TESS) full-frame images (FFIs) observed during the Primary Mission (Sectors 1 - 26). These candidates were initially detected by the Quick-Look Pipeline (QLP), which extracts FFI lightcurves for and searches all stars brighter than TESS magnitude T = 13.5 mag in each sector. However, QLP heavily relies on manual inspection for the identification of planet candidates, limiting vetting efforts to planet-hosting stars brighter than T = 10.5 mag and leaving millions of poten…

2021-12-03astro-ph.EPastro-ph.IM

Quick-Look Pipeline Lightcurves for 9.1 Million Stars Observed Over the First Year of the TESS Extended Mission

We present a magnitude-limited set of lightcurves for stars observed over the TESS Extended Mission, as extracted from full-frame images (FFIs) by MIT's Quick-Look Pipeline (QLP). QLP uses multi-aperture photometry to produce lightcurves for ~1 million stars each 27.4-day sector, which are then searched for exoplanet transits. The per-sector lightcurves for 9.1 million unique targets observed over the first year of the Extended Mission (Sectors 27 - 39) are available as High-Level Science Products (HLSP) on the Mikulski Archive for Space Telescopes (MAST). As in our TESS Primary Mission QLP HL…

2021-10-11astro-ph.EPastro-ph.IMastro-ph.SR

Photometry of 10 Million Stars from the First Two Years of TESS Full Frame Images

The Transiting Exoplanet Survey Satellite (TESS) is the first high-precision full-sky photometry survey in space. We present light curves from a magnitude limited set of stars and other stationary luminous objects from the TESS Full Frame Images, as reduced by the MIT Quick Look Pipeline (QLP). Our light curves cover the full two-year TESS Primary Mission and include $\sim$ 14,770,000 and $\sim$ 9,600,000 individual light curve segments in the Southern and Northern ecliptic hemispheres, respectively. We describe the photometry and detrending techniques we used to create the light curves, and c…

2020-11-12astro-ph.EPastro-ph.IMastro-ph.SR

TESS Discovery of Twin Planets near 2:1 Resonance around Early M-Dwarf TOI 4342

With data from the Transiting Exoplanet Survey Satellite (TESS), we showcase improvements to the MIT Quick-Look Pipeline (QLP) through the discovery and validation of a multi-planet system around M-dwarf TOI 4342 ($T_{mag}=11.032$, $M_* = 0.63 M_\odot$, $R_* = 0.60 R_\odot$, $T_{eff} = 3900$ K, $d = 61.54$ pc). With updates to QLP, including a new multi-planet search, as well as faster cadence data from TESS' First Extended Mission, we discovered two sub-Neptunes ($R_b = 2.266_{-0.038}^{+0.038} R_\oplus$ and $R_c = 2.415_{-0.040}^{+0.043} R_\oplus$; $P_b$ = 5.538 days and $P_c$ = 10.689 days) …

2023-01-03astro-ph.EP

更多相关论文收起更多论文

GTLS: 一种用于周期性凌星检测的GPU加速方法

GTLS: A GPU-accelerated method for periodic transit detection

Shanghai Astronomical Observatory, Chinese Academy of Sciences（中国科学院上海天文台）；University of Chinese Academy of Sciences（中国科学院大学）；Science Talent Training Center（科学人才培养中心）

提出GPU加速的凌星最小二乘算法GTLS，通过并行化相位折叠、凌星时长评估等步骤，在保持检测灵敏度的同时大幅降低计算时间，适用于大规模测光巡天数据。

2026-07-02astro-ph.EPastro-ph.IM

CETRA：一种面向GPU实现的快速、灵敏系外行星凌星探测算法

CETRA: A fast, sensitive exoplanet transit detection algorithm implemented for GPUs

CETRA是一种基于GPU的快速灵敏凌星探测算法，通过物理模型和相位折叠提升性能，比传统方法多识别20%低信噪比凌星，速度更快，并成功增强HD 101581系统中行星信号。

2025-03-26astro-ph.EPastro-ph.IM

UMI：用于系外行星凌星搜索的GPU加速非对称稳健估计器

UMI: GPU-Accelerated Asymmetric Robust Estimator for Photometric Detrending in Exoplanet Transit Searches

Independent Researcher

UMI是一种新型稳健定位估计器，用于消除系外行星凌星搜索中光度时间序列的噪声。通过非对称加权函数和上RMS尺度估计器，提高凌星深度检测的准确性和效率，验证了其在802颗确认系外行星上的性能。

2026-04-12astro-ph.EPastro-ph.IM

用于探测系外行星凌星的GPU相位折叠与深度学习方法

The GPU Phase Folding and Deep Learning Method for Detecting Exoplanet Transits

The Harker School（哈克学校）；Science Talent Training Center（科学人才培养中心）；Shanghai Astronomical Observatory（上海天文台）；Princeton University（普林斯顿大学）；University of Geneva（日内瓦大学）

本文提出GPU相位折叠与CNN系统GPFC，以比BLS快三个数量级的速度高效探测超短周期系外行星，并在模拟和开普勒数据中取得高精度与100%已知行星恢复率。

2024-01-21astro-ph.EPastro-ph.IMcs.LG

RoadRunner: a fast and flexible exoplanet transit model

I present RoadRunner, a fast exoplanet transit model that can use any radially symmetric function to model stellar limb darkening while still being faster to evaluate than the analytical transit model for quadratic limb darkening by Mandel & Agol (2002). CPU and GPU implementations of the model are available in the PyTransit transit modelling package, and come with platform-independent parallelisation, supersampling, and support for modelling complex heterogeneous time series. The code is written in numba-accelerated Python (and the GPU model in OpenCL) without C or Fortran dependencies, which…

2020-09-17astro-ph.EPastro-ph.IM

GPU-based framework for detecting small Solar System bodies in targeted exoplanet surveys

Small Solar System bodies are pristine remnants of Solar System formation, which provide valuable insights for planetary science and astronomy. Their discovery and cataloging also have strong practical implications to life on Earth as the nearest asteroids could pose a serious impact threat. Concurrently with dedicated observational projects, searches for small bodies have been performed on numerous archival data sets from different facilities. Here, we present a framework to increase the scientific return of an exoplanet transit-search survey by recovering serendipitous detections of small bo…

2023-03-13astro-ph.EPastro-ph.IM

使用单类 SVM 优化凌星检测

Using A One-Class SVM To Optimize Transit Detection

University of South Florida（南佛罗里达大学）

本研究提出使用单类 SVM 优化系外行星凌星检测，相比 CNNs 准确率仅低约 5%，但拟合与预测速度分别提升 84 倍和 3 倍以上，且无需 GPU 即可高效运行。

2026-10-14astro-ph.EPastro-ph.IM

TESS中的隐藏珍宝：Sherlock发现两个新的围绕附近M矮星的类地行星

Hidden Gems in TESS: sherlock finds two new rocky planets around nearby M dwarfs

University of Birmingham（伯明翰大学）；Université de Liège（列日大学）；Universidad de Granada（格拉纳达大学）；Avature；Instituto de Astrofísica de Andalucía (IAA-CSIC)（安达卢西亚天体物理研究所）；Instituto de Astrofisica de Canarias (IAC)（加那利天体物理研究所）；Massachusetts Institute of Technology（麻省理工学院）；Universidad de Tarapacá（塔拉帕卡大学）；Observatoire de Genève, Département d’Astronomie, Université de Genève（日内瓦大学天文学系天文台）；Univ. Grenoble Alpes, CNRS, IPAG（格勒诺布尔阿尔卑斯大学）；NASA Ames Research Center（美国国家航空航天局艾姆斯研究中心）

本文通过Sherlock管道在TESS数据中寻找额外的行星，发现两个新的类地行星，这些行星位于所谓的'半径谷'之下，并具有较高的兴趣值，其中TOI-237c是JWST/MIRI观测的理想候选者。

2026-01-29astro-ph.EP

Identifying Planetary Transit Candidates in TESS Full-Frame Image Light Curves via Convolutional Neural Networks

NASA Goddard Space Flight Center（美国国家航空航天局戈达德太空飞行中心）；Universities Space Research Association（大学空间研究协会）；The Catholic University of America（美国天主教大学）；Universita di Napoli Federico II（那不勒斯费德里科二世大学）；Science Systems and Applications, Inc.（科学系统与应用公司）；University of Maryland, Baltimore County（马里兰大学巴尔的摩县分校）

The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ~75% of the sky throughout its two year primary mission, resulting in millions of TESS 30-minute cadence light curves to analyze in the search for transiting exoplanets. To search this vast data trove for transit signals, we aim to provide an approach that is both computationally efficient and produces highly performant predictions. This approach minimizes the required human search effort. We present a convolutional neural network, which we train to identify planetary transit signals and dismiss false positiv…

2021-05-24astro-ph.EPastro-ph.IMcs.LG

一颗亚海王星质量系外行星的长自转周期

A long spin period for a sub-Neptune-mass exoplanet

针对低密度亚海王星HIP 41378 f，研究开发greenlantern代码并用MCMC拟合K2凌星数据，约束其扁率并推断自转周期至少为15.3小时。

2025-02-17astro-ph.EP