Evaluation of Governance Risk in Industry-University-Research Collaborative Innovation Project: Based on BP Neural Networks

Funding: This research was funded by [Projects of the National Social Science Foundation of China] grant number [18BGL020] Abstract Effective evaluation of project governance risks is of great significance to the successful implementation of industry-university-research collaborative innovation project. By introducing the idea of project governance into risk management in industry-university-research collaborative innovation project, this paper analyzes governance risk sources from four aspects, based on the project characteristics, which include the background of participators, organizational structure, project objectives and the relationship of the main participators from the view of project governance. The governance risks are categorized as structure risk, morality risk and behavior risk. The evaluation system of governance risk in Industry-University-Research collaborative innovation project is established. The BP neural network model is applied to assess risk and the MATLAB is used to process data according to the features of project governance risk and theory analysis. Finally, the model is checked by empirical test. This model solves the problem that the risks are difficult to quantify. Scientific nature of the feasibility of the evaluation is improved by the model. At the same time, not only the research field of project governance risk but also risk research of industry-university-research collaborative innovation project is extended. Keywords: industry-university-research, collaborative innovation, project governance risk, risk origin, BP neural network

A comprehensive forecast for cosmological parameter estimation using joint observations of gravitational-wave standard sirens and short γ\gamma-ray bursts

In the third-generation (3G) gravitational-wave (GW) detector era, the multi-messenger GW observation for binary neutron star (BNS) merger events can exert great impacts on exploring the cosmic expansion history. In this work, we comprehensively explore the potential of 3G GW standard siren observations in cosmological parameter estimations by considering the 3G GW detectors and the future short $\gamma$-ray burst (GRB) detector THESEUS-like telescope joint observations. Based on the 10-year observation of different detection strategies, we predict that the numbers of detectable GW-GRB events are 277-685 with the redshifts $z<4$ and the inclination angles $\iota<17^{\circ}$. For the cosmological analysis, we consider five typical dark energy models, i.e., the $\Lambda$CDM, $w$CDM, $w_0w_a$CDM models, and interacting dark energy (IDE) models (I$\Lambda$CDM and I$w$CDM). We find that GW can tightly constrain the Hubble constant with precisions of $0.09\%$-$0.37\%$, but perform not well in constraining other cosmological parameters. Fortunately, GW could effectively break the cosmological parameter degeneracies generated by the mainstream EM observations, CMB+BAO+SN (CBS). When combining the mock GW data with the CBS data, CBS+GW can tightly constrain the equation of state parameter of dark energy $w$ with a precision of $1.36\%$, close to the standard of precision cosmology. Meanwhile, the addition of GW to CBS could improve constraints on cosmological parameters by $35.3\%$-$92.0\%$. In conclusion, GW standard siren observations from 3G GW detectors could play a crucial role in helping solve the Hubble tension and probe the fundamental nature of dark energy.Comment: 16 pages, 11 figure

A path to precision cosmology: synergy between four promising late-universe cosmological probes

In the next decades, it is necessary to forge new late-universe cosmological probes to precisely constrain the Hubble constant and the equation of state of dark energy simultaneously. In this work, we show that the four typical late-universe cosmological probes, the 21 cm intensity mapping (IM), fast radio burst (FRB), gravitational wave (GW) standard siren, and strong gravitational lensing (SGL), are expected to be forged into useful tools in solving the Hubble tension and exploring dark energy. We propose that the synergy of them is rather important in cosmology. We simulate the 21 cm IM, FRB, GW, and SGL data based on the hypothetical observations of the Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX), the Square Kilometre Array (SKA), the Einstein Telescope (ET), and the Large Synoptic Survey Telescope (LSST), respectively. We find that the four probes show obviously different parameter degeneracy orientations in cosmological constraints, so any combination of them can break the parameter degeneracies and thus significantly improve the constraint precision. The joint 21 cm IM+FRB+GW+SGL data can provide the constraint errors of $\sigma(\Omega_{\rm m})=0.0022$ and $\sigma(H_0)=0.16\ \rm km\ s^{-1}\ Mpc^{-1}$ in the $\Lambda$CDM model, which meet the standard of precision cosmology, i.e., the constraint precision of parameters is better than 1%. In addition, the joint data give $\sigma(w)=0.020$ in the $w$CDM model, and $\sigma(w_0)=0.066$ and $\sigma(w_a)=0.25$ in the $w_0w_a$CDM model, which are all better than the constraints obtained by the CMB+BAO+SN data. We show that the synergy between the four late-universe cosmological probes has magnificent prospects.Comment: 28 pages, 9 figures; accepted for publication in JCA

5-Arc transitive cubic Cayley graphs on finite simple groups

AbstractIn this paper, we determine all connected 5-arc transitive cubic Cayley graphs on the alternating group A47; there are only two such graphs (up to isomorphism). By earlier work of the authors, these are the only two non-normal connected cubic arc-transitive Cayley graphs for finite nonabelian simple groups, and so this paper completes the classification of such non-normal Cayley graphs

Joint constraints on cosmological parameters using future multi-band gravitational wave standard siren observations

Gravitational waves (GWs) from the compact binary coalescences can be used as standard sirens to explore the cosmic expansion history. In the next decades, it is anticipated that we could obtain the multi-band GW standard siren data (from nanohertz to a few hundred hertz), which are expected to play an important role in cosmological parameter estimation. In this work, we give for the first time the joint constraints on cosmological parameters using the future multi-band GW standard siren observations. We simulate the multi-band GW standard sirens based on the SKA-era pulsar timing array (PTA), the Taiji observatory, and the Cosmic Explorer (CE) to perform cosmological analysis. In the $\Lambda$CDM model, we find that the joint PTA+Taiji+CE data could provide a tight constraint on the Hubble constant with a $0.5\%$ precision. Moreover, PTA+Taiji+CE could break the cosmological parameter degeneracies generated by CMB, especially in the dynamical dark energy models. When combining the PTA+Taiji+CE data with the CMB data, the constraint precisions of $\Omega_{\rm m}$ and $H_0$ are $1.0\%$ and $0.3\%$, meeting the standard of precision cosmology. The joint CMB+PTA+Taiji+CE data give $\sigma(w)=0.028$ in the $w$CDM model and $\sigma(w_0)=0.11$ and $\sigma(w_a)=0.32$ in the $w_0w_a$CDM model, which are comparable with or close to the latest constraint results by CMB+BAO+SN. In conclusion, it is worth expecting to use the future multi-band GW observations to explore the nature of dark energy and measure the Hubble constant.Comment: 12 pages, 6 figures; accepted for publication in Chinese Physics

Prospects for probing the interaction between dark energy and dark matter using gravitational-wave dark sirens with neutron star tidal deformation

Gravitational wave (GW) standard siren observations provide a rather useful tool to explore the evolution of the universe. In this work, we wish to investigate whether the dark sirens with neutron star (NS) deformation from third-generation (3G) GW detectors could help probe the interaction between dark energy and dark matter. We simulate the GW dark sirens of four detection strategies based on the three-year observation and consider four phenomenological interacting dark energy models to perform cosmological analysis. We find that GW dark sirens could provide tight constraints on $\Omega_{\rm m}$ and $H_0$ in the four IDE models, but perform not well in constraining the dimensionless coupling parameter $\beta$ with the interaction proportional to the energy density of cold dark matter. Nevertheless, the parameter degeneracy orientations of CMB and GW are almost orthogonal, and thus the combination of them could effectively break cosmological parameter degeneracies, with the constraint errors of $\beta$ being 0.00068-0.018. In addition, we choose three typical equation of states (EoSs) of NS, i.e., SLy, MPA1, and MS1, to investigate the effect of NS's EoS in cosmological analysis. The stiffer EoS could give tighter constraints than the softer EoS. Nonetheless, the combination of CMB and GW dark sirens (using different EoSs of NS) shows basically the same constraint results of cosmological parameters. We conclude that the dark sirens from 3G GW detectors would play a crucial role in helping probe the interaction between dark energy and dark matter, and the CMB+GW results are basically not affected by the EoS of NS.Comment: 12 pages, 9 figure

Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Recent developments in deep learning techniques have offered an alternative and complementary approach to traditional matched filtering methods for the identification of gravitational wave (GW) signals. The rapid and accurate identification of GW signals is crucial for the progress of GW physics and multi-messenger astronomy, particularly in light of the upcoming fourth and fifth observing runs of LIGO-Virgo-KAGRA. In this work, we use the 2D U-Net algorithm to identify the time-frequency domain GW signals from stellar-mass binary black hole (BBH) mergers. We simulate BBH mergers with component masses from 5 to 80 $M_{\odot}$ and account for the LIGO detector noise. We find that the GW events in the first and second observation runs could all be clearly and rapidly identified. For the third observation run, about $80\%$ GW events could be identified and GW190814 is inferred to be a BBH merger event. Moreover, since the U-Net algorithm has advantages in image processing, the time-frequency domain signals obtained through U-Net can preliminarily determine the masses of GW sources, which could help provide the mass priors for future parameter inferences. We conclude that the U-Net algorithm could rapidly identify the time-frequency domain GW signals from BBH mergers and provide great help for future parameter inferences.Comment: 11 pages, 9 figure