A convenient approach to characterizing model uncertainty with application to early dark energy solutions of the Hubble tension

Despite increasingly precise observations and sophisticated theoretical models, the discrepancy between measurements of H0 from the cosmic microwave background or from Baryon Acoustic Oscillations combined with Big-Bang Nucleosynthesis versus those from local distance ladder probes -- commonly known as the $H_0$ tension -- continues to perplex the scientific community. To address this tension, Early Dark Energy (EDE) models have been proposed as alternatives to $\Lambda$CDM, as they can change the observed sound horizon and the inferred Hubble constant from measurements based on this. In this paper, we investigate the use of Bayesian Model Averaging (BMA) to evaluate EDE as a solution to the H0 tension. BMA consists of assigning a prior to the model and deriving a posterior as for any other unknown parameter in a Bayesian analysis. BMA can be computationally challenging in that one must approximate the joint posterior of both model and parameters. Here we present a computational strategy for BMA that exploits existing MCMC software and combines model-specific posteriors post-hoc. In application to a comprehensive analysis of cosmological datasets, we quantify the impact of EDE on the H0 discrepancy. We find an EDE model probability of $\sim$90% whenever we include the H0 measurement from Type Ia Supernovae in the analysis, whereas the other data show a strong preference for the standard cosmological model. We finally present constraints on common parameters marginalized over both cosmological models. For reasonable priors on models with and without EDE, the H0 tension is reduced by at least 20%

Mutual Information of Population Codes and Distance Measures in Probability Space

We studied the mutual information between a stimulus and a large system consisting of stochastic, statistically independent elements that respond to a stimulus. The Mutual Information (MI) of the system saturates exponentially with system size. A theory of the rate of saturation of the MI is developed. We show that this rate is controlled by a distance function between the response probabilities induced by different stimuli. This function, which we term the {\it Confusion Distance} between two probabilities, is related to the Renyi $\alpha$-Information.Comment: 11 pages, 3 figures, accepted to PR

Neural responses to facial and vocal expressions of fear and disgust

Neuropsychological studies report more impaired responses to facial expressions of fear than disgust in people with amygdala lesions, and vice versa in people with Huntington's disease. Experiments using functional magnetic resonance imaging (fMRI) have confirmed the role of the amygdala in the response to fearful faces and have implicated the anterior insula in the response to facial expressions of disgust. We used fMRI to extend these studies to the perception of fear and disgust from both facial and vocal expressions. Consistent with neuropsychological findings, both types of fearful stimuli activated the amygdala. Facial expressions of disgust activated the anterior insula and the caudate-putamen; vocal expressions of disgust did not significantly activate either of these regions. All four types of stimuli activated the superior temporal gyrus. Our findings therefore (i) support the differential localization of the neural substrates of fear and disgust; (ii) confirm the involvement of the amygdala in the emotion of fear, whether evoked by facial or vocal expressions; (iii) confirm the involvement of the anterior insula and the striatum in reactions to facial expressions of disgust; and (iv) suggest a possible general role for the perception of emotional expressions for the superior temporal gyrus

SatNOGS Project

Our project is to build and contribute improvements to an existing open source ground station design. This project called SatNOGS (Satellite Networked Open Ground Station) was started a year ago by the Libre Space Foundation in Athens, Greece to address the problem of data downlink from Low Earth Orbiting Satellites. We are most interested in improving the ease of construction of the ground station to enable more people to deploy ground stations

Co-patents’ commercialization: evidence from China

Co-patents are outcomes of R&D collaboration, which has been proven with higher-quality. Does this mean that high-quality patents should also extend their advantage to the technology market? Based on the transaction cost theory, we use the China National Intellectual Property Administration (CNIPA) database and logit model to explore the effect of co-ownership on firms’ patent commercialization and the factors of co-patents that affect their commercialization. Our findings illustrate that co-ownership has a negative impact on patent commercialization. In addition, the co-owner’s nature, country, and co-patent’s industry influence the commercialization of co-patents. Firstly, a company and a university or research institution’s co-owned co-patents are less likely to be commercialization than a company and a company coowned co-patents. Secondly, multi-countries co-owned co-patents are less likely to be commercialization than a single-country coowned co-patents. Thirdly, co-patents in high technology (hightech) industries are less likely to be commercialization than copatents in non-high-tech industries. This paper supports policymakers in implementing policies to promote the co-patents’ commercialization. Meanwhile, our paper suggests that to pursue the economic value of the R&D collaborative intellectual property fruits, R&D collaborative intellectual property fruits are not be encouraged to be applied as the co-patents.European Union (EU) TIN2016-75850-