Related papers: Particle swarm optimization of the sensitivity of …
The detection and estimation of gravitational wave (GW) signals belonging to a parameterized family of waveforms requires, in general, the numerical maximization of a data-dependent function of the signal parameters. Due to noise in the…
Upgrades to improve the sensitivity of gravitational wave detectors enable more frequent detections and more precise source parameter estimation. Unlike other advanced interferometric detectors such as Advanced LIGO and Advanced Virgo,…
A vacuum compatible cryogenic accelerometer is presented which will reach $<0.5$ p$g$ Hz$^{-1/2}$ sensitivity from 1 mHz to 10 Hz with a maximum sensitivity of 10 f$g$ Hz$^{-1/2}$ around 10 Hz. This figure can be translated to a…
We provide brief notes on a particle swarm-optimisation approach to constraining the properties of a stochastic gravitational-wave background in the first International Pulsar Timing Array data-challenge. The technique employs many…
KAGRA is the first large-scale gravitational-wave detector with cryogenic test masses. Its target sensitivity is limited mostly by quantum noise in the observation frequency band owing to the remarkable reduction of thermal noise at…
We report the mirror suspension design for Large-scale Cryogenic Gravitational wave Telescope, KAGRA, during bKAGRA Phase 1. Mirror thermal noise is one of the fundamental noises for room-temperature gravitational-wave detectors such as…
KAGRA is the first km-scale gravitational wave detector to be constructed underground and employ cryogenics to cool down its test masses. While the underground location provides a quiet site with low seismic noise, the cooling…
This short paper presents a work on the design of low noise microwave amplifiers using particle swarm optimization (PSO) technique. Particle Swarm Optimization is used as a method that is applied to a single stage amplifier circuit to meet…
KAGRA uses cryogenics to cool its sapphire test masses down to 20 K to reduce the thermal noise. However, cryocooler vibration and structural resonances of the cryostat couple to test mass and can contaminate the detector sensitivity. We…
Reducing the impact of seismic activity on the motion of suspended optics is essential for the operation of ground-based gravitational wave detectors. During periods of increased seismic activity, low-frequency ground translation and tilt…
Particle swarm optimisation is a metaheuristic algorithm which finds reasonable solutions in a wide range of applied problems if suitable parameters are used. We study the properties of the algorithm in the framework of random dynamical…
While a fully-coherent all-sky search is known to be optimal for detecting gravitational wave signals from compact binary coalescences, its high computational cost has limited current searches to less sensitive coincidence-based schemes.…
Fully-coherent all-sky search for gravitational wave (GW) signals from the coalescence of compact object binaries is a computationally expensive task. Approximations, such as semi-coherent coincidence searches, are currently used to…
While a fully-coherent all-sky search is known to be optimal for detecting signals from compact binary coalescences (CBCs), its high computational cost has limited current searches to less sensitive coincidence-based schemes. For a network…
This paper provides a formalization of the energy disaggregation problem for particle swarm optimization and shows the successful application of particle swarm optimization for disaggregation in a multi-tenant commercial building. The…
The article presents a study of the Particle Swarm optimization method for scheduling problem. To improve the method's performance a restriction of particles' velocity and an evolutionary meta-optimization were realized. The approach…
The LIGO gravitational wave (GW) detectors will begin collecting data in 2015, with Virgo following shortly after. The use of squeezing has been proposed as a way to reduce the quantum noise without increasing the laser power, and has been…
State-of-the-art physics experiments require high-resolution, low-noise, and low-threshold detectors to achieve competitive scientific results. However, experimental environments invariably introduce sources of noise, such as electrical…
Particle swarm optimization is used in several combinatorial optimization problems. In this work, particle swarms are used to solve quadratic programming problems with quadratic constraints. The approach of particle swarms is an example for…
In this study we address existing deficiencies in the literature on applications of Particle Swarm Optimization to generate optimal designs. We present the results of a large computer study in which we bench-mark both efficiency and…