LIGO Document T1900127-x0
Home
Recent Changes
Topics
Login
Final reports from LIGO SURF program, Summer 2018
Document #:
LIGO-T1900127-x0
Document type:
T - Technical notes
Abstract:
Final reports from the 2018 Summer Undergraduate Research Fellowship (SURF) program.
Files in Document:
None
Topics:
Detector
Data Analysis
Education, Outreach
Authors:
Alan Weinstein
Keywords:
SURF18
REU
Related Documents:
LIGO-T1800266:
Visualizing 2PN Binary Black Hole Spin Precession
LIGO-T1800256:
Thermal State of the test masses of the LIGO interferometer
LIGO-T1800230:
A Study of Gravitational Wave Memory and Its Detectability With LIGO Using Bayesian Inference
LIGO-T1800184:
Real-time Universal Transfer Function Synthesizer
LIGO-T1800312:
Real-Time Temperature Monitoring of Mechanical Oscillators
LIGO-T1800238:
Project Stabilization of a 2um Laser Using an all-Fiber Delay Line Mach-Zehnder Interferometer
LIGO-T1800265:
RF Noise Sources and GPS Jitter at LHO
LIGO-T1800200:
In-Situ Laser Mode Spectroscopy for Mirror Phase Mapping
LIGO-T1800280:
Design and Testing of Composite Mirror Adaptive Optics
LIGO-T1800201:
Developing Phase Map of Cavity Mirrors using Laser Mode Spectroscopy.
LIGO-T1800245:
Optical Loss Characterization
LIGO-T1800287:
Searches and Parameter Estimation for Kilonova Light Curves
LIGO-P1800130:
Improving earthquake monitoring for gravitational-wave detectors with historical seismic data
LIGO-T1800224:
Scattered Light in the LIGO Livingston Arm Cavities
LIGO-T1800281:
Searching for a Galactic Excess of Gravitational Waves
LIGO-T1800288:
Sub-Classification of Blip Glitches Using Q-Transforms and Convolutional Neural Networks with GravitySpy
LIGO-T1800296:
Constructing a Balanced Homodyne Detector for Low Quantum Noise Gravitational Wave Interferometry
LIGO-T1800231:
Modeling and Measuring Eccentricity in Binary Black Hole Inspirals
LIGO-T1800282:
Utilizing Machine Learning to Improve Searches for LIGO Sources
LIGO-T1800273:
Seismic Cloaking for LIGO
LIGO-P1800129:
Extending the reach of gravitational-wave detectors with machine learning
Referenced by:
Home
Recent Changes
Topics
Login
DCC
Version 3.4.3
, contact
Document Database Administrators