We report on electrostatic measurements made on board the European Space Agency mission LISA Pathfinder. Detailed measurements of the charge-induced electrostatic forces exerted on free-falling test masses (TMs) inside the capacitive gravitational reference sensor are the first made in a relevant environment for a space-based gravitational wave detector. Employing a combination of charge control and electric-field compensation, we show that the level of charge-induced acceleration noise on a single TM can be maintained at a level close to 1.0  fm s^{-2} Hz^{-1/2} across the 0.1-100 mHz frequency band that is crucial to an observatory such as the Laser Interferometer Space Antenna (LISA). Using dedicated measurements that detect these effects in the differential acceleration between the two test masses, we resolve the stochastic nature of the TM charge buildup due to interplanetary cosmic rays and the TM charge-to-force coupling through stray electric fields in the sensor. All our measurements are in good agreement with predictions based on a relatively simple electrostatic model of the LISA Pathfinder instrument.

Download full-text PDF

Source
http://dx.doi.org/10.1103/PhysRevLett.118.171101DOI Listing

Publication Analysis

Top Keywords

test masses
12
lisa pathfinder
12
free-falling test
8
charge-induced force
4
force noise
4
noise free-falling
4
lisa
4
masses lisa
4
pathfinder report
4
report electrostatic
4

Similar Publications

Early childhood education and care (ECEC) settings are key for improving health behaviors, including physical activity (PA) and nutrition. In 2017, the province of British Columbia (BC) implemented a provincial-level Active Play policy supported by a capacity-building intervention. Significant improvements in all PA policies and practices and the majority of nutrition policies were observed post-implementation.

View Article and Find Full Text PDF

Antibiotic resistance genes in the coastal atmosphere under varied weather conditions: distribution, influencing factors, and transmission mechanisms.

Environ Pollut

January 2025

Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao 266100, PR China; College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, PR China. Electronic address:

Antibiotic resistance genes (ARGs) have escalated to levels of concern worldwide as emerging environmental pollutants. Increasing evidence suggests that non-antibiotic antimicrobial substances expedite the spread of ARGs. However, the drivers and mechanisms involved in the generation and spread of ARGs in the atmosphere remain inadequately elucidated.

View Article and Find Full Text PDF

Band Tailoring Enabled Perovskite Devices for X-Ray to Near-Infrared Photodetection.

Adv Sci (Weinh)

January 2025

School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.

Perovskite semiconductors have shown significant promise for photodetection due to their low effective carrier masses and long carrier lifetimes. However, achieving balanced detection across a broad spectrum-from X-rays to infrared-within a single perovskite photodetector presents challenges. These challenges stem from conflicting requirements for different wavelength ranges, such as the narrow bandgap needed for infrared detection and the low dark current necessary for X-ray sensitivity.

View Article and Find Full Text PDF

Causal Association between Arm Fat, Left Leg Fat, and Trunk Fat Masses and Risk of Polycystic Ovarian Syndrome: A Mendelian Randomization Study.

Comb Chem High Throughput Screen

January 2025

Department of Obstetrics and Gynecology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.

Background: Observational studies have reported that arm fat, left leg fat, and trunk fat masses have different effects on polycystic ovarian syndrome (PCOS). However, the causal relationship between them remains unknown.

Materials And Methods: A two-sample Mendelian randomization (MR) study was conducted by utilizing pooled data from the largest Genome-Wide Association Study (GWAS).

View Article and Find Full Text PDF

Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).

Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!