TianQin is a future space-based gravitational wave observatory targeting the frequency window of $10^{-4}$ Hz $\sim 1$ Hz. A large variety of gravitational wave sources are expected in this frequency band, including the merger of massive black hole binaries, the inspiral of extreme/intermediate mass ratio systems, stellar-mass black hole binaries, Galactic compact binaries, and so on. TianQin will consist of three Earth orbiting satellites on nearly identical orbits with orbital radii of about $10^5$ km. The satellites will form a normal triangle constellation whose plane is nearly perpendicular to the ecliptic plane. The TianQin project has been progressing smoothly following the ``0123" technology roadmap. In step ``0", the TianQin laser ranging station has been constructed and it has successfully ranged to all the five retro-reflectors on the Moon. In step ``1", the drag-free control technology has been tested and demonstrated using the TianQin-1 satellite. In step ``2", the inter-satellite laser interferometry technology will be tested using the pair of TianQin-2 satellites. The TianQin-2 mission has been officially approved and the satellites will be launched around 2026. In step ``3", i.e., the TianQin-3 mission, three identical satellites will be launched around 2035 to form the space-based gravitational wave detector, TianQin, and to start gravitational wave detection in space.
The rapid advancement of image analysis methods in time-domain astronomy, particularly those leveraging AI algorithms, has highlighted efficient image pre-processing as a critical bottleneck affecting algorithm performance. Image pre-processing, which involves standardizing images for training or deployment of various AI algorithms, encompasses essential steps such as image quality evaluation, alignment, stacking, background extraction, gray-scale transformation, cropping, source detection, astrometry, and photometry. Historically, these algorithms were developed independently by different research groups, primarily based on CPU architecture for small-scale data processing. This paper introduces a novel framework for image pre-processing that integrates key algorithms specifically modified for GPU architecture, enabling large-scale image pre-processing for different algorithms. To prepare for the new algorithm design paradigm in the AI era, we have implemented two operational modes in the framework for different application scenarios: Eager mode and Pipeline mode. The Eager mode facilitates real-time feedback and flexible adjustments, which could be used for parameter tuning and algorithm development. The pipeline mode is primarily designed for large scale data processing, which could be used for training or deploying of artificial intelligence models. We have tested the performance of our framework using simulated and real observation images. Results demonstrate that our framework significantly enhances image pre-processing speed while maintaining accuracy levels comparable to CPU based algorithms. To promote accessibility and ease of use, a Docker version of our framework is available for download in the PaperData Repository powered by China-VO, compatible with various AI algorithms developed for time-domain astronomy research.
Projects aiming to detect gravitational waves (GWs) in space in the millihertz range will utilize interferometers to measure the separations between free-falling test masses. The phasemeter measures the phase changes of the interference signals caused by the test masses' relative movements. The measurement sensitivity of the phasemeter is one of the key factors in the detection. In this work, we reviewed the core metrology of the phasemeter and evaluated the ultra-low noise performance of the phasemeter with analog signals. Frequency readout noise related to the bit width of the numerically controlled oscillator (NCO) inside the phasemeter is identified as one of the main noise sources of phase measurement theoretically and experimentally. After increasing the NCO bit widths, the single-channel phase noise of the phasemeter reached 2.0 {\mu}rad/Hz^{1/2} at 6 mHz, and the differential phase noise reached 0.4 {\mu}rad/Hz^{1/2} at 6 mHz. The phase noise performances remained consistent within the carrier frequency range of 4.9 MHz to 25.1 MHz.
More than 200 A- and F-type stars observed with Kepler exhibit a distinctive 'hump & spike' feature in their Fourier spectra. The hump is commonly interpreted as unresolved Rossby modes, while the spike has been linked to rotational modulation. Two competing interpretations exist for the spike: magnetic phenomena, such as stellar spots, or Overstable Convective (OsC) modes resonantly exciting low-frequency g modes within the stellar envelope. We analysed photometric data from Kepler and TESS for HR 7495, the brightest 'hump & spike' star (V=5.06), covering 4.5 years and four seasons, respectively. Additionally, radial velocity measurements and spectropolarimetric data were used to investigate magnetic fields and surface features. Furthermore, we analysed model-based artificial light and radial velocity curves to examine the influence of OsC modes on the phase-folded light curves. The phase-folded light curves show that the spike characteristics of HR 7495 align more closely with rotational modulation by stellar spots than with OsC modes. No significant magnetic fields were detected, limiting the field's possible amplitude and geometry. This supports the hypothesis of a subsurface convective layer operating a dynamo, producing low-amplitude, complex magnetic fields. The variability patterns suggest multiple evolving spots. A comparison of contemporaneously observed light and RV data with modelled OsC modes reveals a 0.5 phase offset, strongly disfavouring pulsations as the cause of the spike. While the evolutionary stage of HR 7495 does not entirely preclude the possibility of OsC modes, the observational data overwhelmingly support the stellar spots hypothesis. Our analysis, combined with previous literature, suggests that if not all A- and F-type, at least the 'hump & spike' stars, harbour an undetected weak magnetic field, likely driven by a dynamo mechanism.
this https URL . 18+2 pages, 11+4 figures, comments are welcomed!