Implication of pulsar timing array experiments on cosmological gravitational wave detection

Yokoyama, Jun′ichi

doi:10.1007/s43673-021-00020-5

Cited by 12 publications

(5 citation statements)

References 75 publications

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“…Therefore, it is possible to have a theory which produce large fluctuations with the amplitude of power spectrum O(0.01) that satisfy observational constraints and many models have been proposed to realize such a feature [7,8,. Peaks of such fluctuations may collapse into PBHs with appreciable abundance [89,90] after entering the horizon, which also produce large stochastic gravitational wave background [91][92][93][94][95] that can be probed by future gravitational wave observations as well as pulsar timing array experiments [96].…”

mentioning

confidence: 99%

Ruling Out Primordial Black Hole Formation From Single-Field Inflation

Kristiano¹,

Yokoyama²

2022

Preprint

139

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mentioning

confidence: 99%

Ruling Out Primordial Black Hole Formation From Single-Field Inflation

Kristiano¹,

Yokoyama²

2022

Preprint

139

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“…Therefore, we now propose a machine learning-based CNN decoder to determine the best syndrome more quickly, and continue to optimize the conditions to achieve the maximum good threshold. Given error 𝒬 and stabilizer element 𝒮, when the errors 𝒬 and 𝒮𝒬 lead to the same measurement result (produce the same syndrome), we need to automatically select the error correction operator from a set of stabilizer measurement results, which is called a decoder, [43][44][45] as shown in Fig. 4.…”

Section: Error Correctionmentioning

confidence: 99%

Determination of quantum toric error correction code threshold using convolutional neural network decoders

Wang

Xue

et al. 2022

Chinese Phys. B

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Quantum error correction technology is an important solution to solve the noise interference generated during the operation of quantum computers. In order to find the best syndrome of the stabilizer code in quantum error correction, we need to find a fast and close to the optimal threshold decoder. In this work, we build a convolutional neural network (CNN) decoder to correct errors in the toric code based on the system research of machine learning. We analyze and optimize various conditions that affect CNN, and use the RestNet network architecture to reduce the running time. It is shortened by 30%–40%, and we finally design an optimized algorithm for CNN decoder. In this way, the threshold accuracy of the neural network decoder is made to reach 10.8%, which is closer to the optimal threshold of about 11%.The previous threshold of 8.9%–10.3% has been slightly improved, and there is no need to verify the basic noise.

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“…The frequency range of PTAs correspond to scales k ∼ (10 6 − 10 8 ) Mpc −1 , which entered the Hubble horizon around and below the epoch of the QCD crossover in the hot Universe. Therefore, large deviations from scale invariance at such scales can be indirectly probed by PTAs, via the induced GW signal [32,33] (see also [34][35][36]). Additionally, as mentioned above, the same large perturbations that source GWs may also lead to a significant fraction of PBHs, with masses ∼ (0.001 − 1000)M ⊙ , encompassing the binary BH mass range currently observed at the LIGO/Virgo/KAGRA interferometers.…”

Section: Introductionmentioning

confidence: 99%

Search for scalar induced gravitational waves in the international pulsar timing array data release 2 and NANOgrav 12.5 years datasets

Dandoy,

Domcke,

Rompineve

2023

SciPost Phys. Core

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We perform a Bayesian search in the latest Pulsar Timing Array (PTA) datasets for a stochastic gravitational wave (GW) background sourced by curvature perturbations at scales 10^5105 Mpc^{-1}\lesssim−1≲ k\lesssim 10^8≲108 Mpc^{-1}−1. These re-enter the Hubble horizon at temperatures around and below the QCD crossover phase transition in the early Universe. We include a stochastic background of astrophysical origin in our search and properly account for constraints on the curvature power spectrum from the overproduction of primordial black holes (PBHs). We find that the International PTA Data Release 2 significantly favors the astrophysical model for its reported common-spectrum process, over the curvature-induced background. On the other hand, the two interpretations fit the NANOgrav 12.5 years dataset equally well. We then set new upper limits on the amplitude of the curvature power spectrum at small scales. These are independent from, and competitive with, indirect astrophysical bounds from the abundance of PBH dark matter. Upcoming PTA data releases will provide the strongest probe of the curvature power spectrum around the QCD epoch.

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Implication of pulsar timing array experiments on cosmological gravitational wave detection

Cited by 12 publications

References 75 publications

Ruling Out Primordial Black Hole Formation From Single-Field Inflation

Ruling Out Primordial Black Hole Formation From Single-Field Inflation

Determination of quantum toric error correction code threshold using convolutional neural network decoders

Search for scalar induced gravitational waves in the international pulsar timing array data release 2 and NANOgrav 12.5 years datasets

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