DATA ANALYSIS FOR GRAVITATIONAL WAVES USING NEURAL NETWORKS ON QUANTUM COMPUTERS

2023

Author(s): Isfan, MC (Isfan, Maria-Catalina); Caramete, LI (Caramete, Laurentiu-Ioan); Caramete, A (Caramete, Ana); Basceanu, VA (Basceanu, Vlad-Andrei); Popescu, T (Popescu, Traian)

Source: ROMANIAN REPORTS IN PHYSICS  Volume: 75  Issue: 2  Article Number: 113  Published Date: 2023   

Abstract: In this study, we evaluate the feasibility of using quantum neural networks for classifying gravitational waveforms, using both simulators and quantum computers. The analysis is quite interdisciplinary in its nature, combining knowledge involving astrophysics, quantum information as well as quantum and classical machine learning. We showed that the quantum classifiers and hybrid classical-quantum layers give highly accurate results when tested on a simple dataset and ran on a simulator; also, adding a quantum layer to poorly performing classical neural network can highly improve its accuracy. When running on a real quantum computer, error minimizing algorithms need to be implemented in order to obtain a satisfying accuracy.

Accession Number: WOS:001023561900001

Characterization of Gravitational Waves Signals Using Neural Networks

2020

Authors: A. Caramete, A. I. Constantinescu, L. I. Caramete, T. Popescu, R. A. Balasov, D. Felea, M. V. Rusu, P. Stefanescu, O. M. Tintareanu

Abstract: Gravitational wave astronomy has been already a well-established research domain for many years. Moreover, after the detection by LIGO/Virgo collaboration, in 2017, of the first gravitational wave signal emitted during the collision of a binary neutron star system, that was accompanied by the detection of other types of signals coming from the same event, multi-messenger astronomy has claimed its rights more assertively. In this context, it is of great importance in a gravitational wave experiment to have a rapid mechanism of alerting about potential gravitational waves events other observatories capable to detect other types of signals (e.g. in other wavelengths) that are produce by the same event. In this paper, we present the first progress in the development of a neural network algorithm trained to recognize and characterize gravitational wave patterns from signal plus noise data samples. We have implemented two versions of the algorithm, one that classifies the gravitational wave signals into 2 classes, and another one that classifies them into 4 classes, according to the mass ratio of the emitting source. We have obtained promising results, with 100% training and testing accuracy for the 2-class network and approximately 95% for the 4-class network. We conclude that the current version of the neural network algorithm demonstrates the ability of a well-configured and calibrated Bidirectional Long-Short Term Memory software to classify with very high accuracy and in an extremely short time gravitational wave signals, even when they are accompanied by noise. Moreover, the performance obtained with this algorithm qualifies it as a fast method of data analysis and can be used as a low-latency pipeline for gravitational wave observatories like the future LISA Mission.

Source: arXiv:2009.06109 [astro-ph.IM], https://doi.org/10.48550/arXiv.2009.06109

Cosmological evidence for leptonic asymmetry after Planck

2014

Author(s): Caramete, A (Caramete, A.); Popa, LA (Popa, L. A.)

Source: JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS  Issue: 2  Article Number: 012  DOI: 10.1088/1475-7516/2014/02/012  Published Date: 2014 FEB  

Abstract: Recently, the Planck satellite found a larger and most precise value of the matter energy density, that impacts on the present values of other cosmological parameters such as the Hubble constant H-0, the present cluster abundances S-8, and the age of the Universe t(U). The existing tension between PLANCK determination of these parameters in the frame of the base Lambda CDM model and their determination from other measurements generated lively discussions, one possible interpretation being that some sources of systematic errors in cosmological measurements are not completely understood. An alternative interpretation is related to the fact that the CMB observations, that probe the high redshift Universe are interpreted in terms of cosmological parameters at present time by extrapolation within the base Lambda CDM model that can be inadequate or incomplete. In this paper we quantify this tension by exploring several extensions of the base Lambda CDM model that include the leptonic asymmetry. We set bounds on the radiation content of the Universe and neutrino properties by using the latest cosmological measurements, imposing also self-consistent BBN constraints on the primordial helium abundance. For all asymmetric cosmological models we find the preference of cosmological data for smaller values of active and sterile neutrino masses. This increases the tension between cosmological and short baseline neutrino oscillation data that favors a sterile neutrino with the mass of around 1 eV. For the case of degenerate massive neutrinos, we find that the discrepancies with the local determinations of H-0, and t(U) are alleviated at similar to 1.3 sigma level while S-8 is in agreement with its determination from CFHTLenS survey data at similar to 1 sigma and with the prediction of cluster mass-observation relation at similar to 0.5 sigma. We also find 2 sigma statistical preference of the cosmological data for the leptonic asymmetric models involving three massive neutrino species and neutrino direct mass hierarchy. We conclude that the current cosmological data favor the leptonic asymmetric extension of the base Lambda CDM model and normal neutrino mass hierarchy over the models with additional sterile neutrino species and/or inverted neutrino mass hierarchy.

Accession Number: WOS:000332711400012

LOOKBACK TIME AND CHANDRA CONSTRAINS ON COSMOLOGICAL PARAMETERS

2011

Author(s): Tonoiu, D (Tonoiu, D.); Caramete, A (Caramete, A.); Popa, LA (Popa, L. A.)

Source: ROMANIAN REPORTS IN PHYSICS  Volume: 63  Issue: 3  Pages: 879-889  Published Date: 2011   

Abstract: In this paper we compare the WMAP7 with lookback time and Chandra gas fraction data to constrain the main cosmological parameters and the equation of state for the dark energy. We find that the lookback time is a good measurement that can improve the determination of the equation of state for the dark energy with regard to other external data sets. We conclude that larger lookback time data set will further improve our determination of the cosmological parameters.

Accession Number: WOS:000293992000023