Testing the coupling of dark radiations in light of the Hubble tension

Self-interacting dark radiations (SIdr) can have significant implications in the evolution of the universe, affecting the cosmic microwave background (CMB) and the clustering of large-scale structures. In this work, we analyze the implications of SIdr on the CMB power spectrum and explore its potential in resolving the Hubble tension. SIdr exhibits two distinct behaviors based on the interacting strength: strongly self-coupled and medium self-coupled. These behaviors are evident in the analysis of CMB data. According to Planck data, the dark radiation component consists of both free-streaming neutrinos and possible SIdr. The total contribution from these components yields relativistic species with $N_{\rm eff}=3.046$. In the framework of universal coupling between dark radiations, a consistent value of $N_{\rm eff}=3.27_{-0.31}^{+0.23}$ is obtained. Additionally, this coupling results in an increase in the Hubble constant ($H_0$) to $70.1_{-1.6}^{+1.3}, \text{km/s/Mpc}$. However, when considering the number of free-streaming neutrinos as a parameter, the existence of SIdr is not supported. This makes its fraction in radiation to be $R_x=0.047^{+0.025}_{-0.053}$. Although the Hubble constant is still enhanced, it comes at the expense of a higher $N_{\rm eff}=3.52\pm0.25$. Our findings reveal that the ACT and SPT data provide support for the presence of SIdr, particularly when considering a variable number of free-streaming species. In this case, SIdr accounts for approximately 12.7\% of the total radiation content. However, it is important to note that relying solely on SIdr is insufficient to completely resolve the Hubble tension. Finally, we investigate the constraints on SIdr imposed by future experiments, which improve the limits on scaled interacting strength $\log_{10}\tilde G_{\rm eff}$ by a factor of 4.5 compared to the current constraints.Comment: 23 pages, 8 figures, 4 table

Expanding the Resolution Boundary of Outcome-Based Imperfect-Recall Abstraction in Games with Ordered Signals

In the development of advanced Texas Hold'em AI systems, abstraction technology has garnered widespread attention due to its significant effect in simplifying game complexity. This study adopts a more specific model, the games of ordered signal, to describe Texas Hold'em-style games and optimizes this model to streamline its mathematical representation and broaden its applicability. By transitioning from a broad imperfect information game model to a game with ordered signals model, we have separated the previously intertwined infoset abstraction and action abstraction into independent signal abstraction and action abstraction. Importantly, this signal abstraction provides a mathematical framework for the hand abstraction task, which is emphatically discussed in this paper. Additionally, a novel common refinement principle is introduced, revealing the limit performance of hand abstraction algorithms. We introduce potential outcome isomorphism (POI) and pinpoint that it suffers from the issue of excessive abstraction. Futher, We demonstrate that POI serves as a common refinement for leading outcome-based hand abstraction algorithms, such as E[HS] and PA\&PAEMD. Consequently, excessive abstraction also inherently affects these algorithms, leading to suboptimal performance. Our investigation reveals the omission of historical data as a primary contributor to excessive abstraction. To remedy this, we propose the K-Recall Outcome Isomorphism (KROI) to incorporate the missing information. Compared with POI, KROI more accurately mirrors lossless isomorphism (LI), the ground truth, offering enhanced signal abstraction resolution. Experimental results in the Numeral211 Hold'em indicate that strategies developed through KROI approximate the exploitability of those developed through LI more closely than those trained through POI.Comment: 36 pages, 7 figure

Molecular Dynamics Simulation Insights into Rejuvenating Aged Asphalt with Waste Soybean Oil and Polymers

This study utilized molecular dynamics simulations to assess the rejuvenation of aged asphalt (AA) with waste soybean oil (WSO) and functionalized SBS polymers, focusing on: 1) constructing and validating models for virgin asphalt (VA), AA, and composite rejuvenated asphalt with WSO and polymers; 2) analyzing diffusion effects and binding abilities in these rejuvenated models; 3) evaluating interface binding and diffusion behaviors in composite rejuvenated models. The addition of functionalized SBS molecules and WSO improved the diffusion rates of various components within these models. Specifically, functionalized linear-SBS (LSBS) molecules demonstrated superior diffusion performance compared to star-SBS (SSBS) molecules. Incorporating WSO and polymers into the AA model increased the occupied volume of all rejuvenated models. The free volume fraction (FFV) in rejuvenated asphalt models exceeded that in AA at 433 K, suggesting that the inclusion of WSO and polymers enhances molecular mobility. As temperature increased, the interaction energy between polymers and asphalt components decreased. LSBS molecules exhibited stronger interactions with asphalt components than SSBS molecules, whose interaction energy was significantly enhanced by hydrogenation treatment. In rejuvenated-rejuvenated asphalt models, the interface interaction energy was higher than in VA–VA models, suggesting improved interface stability. However, diffusion rates of various components in rejuvenated-rejuvenated asphalt models were lower than those in VA–VA models

Rejuvenation Effect of Aged SBS-Modified Asphalt Utilizing Molecule Analysis

The Performance of Styrene-Butadiene-Styrene Modified Asphalt (SBSMA) is Significantly Impacted by its Aging and Regeneration. in This Research, the Molecular Dynamics Simulation Was Utilized to Investigate the Rejuvenation Effect of Active Reagents on Aged SBS Modified Asphalt through the Following Tasks: 1) Verifying the Accuracy of the Asphalt Model by Density and Solubility Parameters; 2) Assessing the Changes in the Rejuvenated Asphalt Model\u27s Energetic Parameters and Volume Parameters, 3) Studying the Interaction Energy between SBS Molecules and Asphalt Molecule Models, and 4) Evaluating the Relative Concentration, Interfacial Interaction Energy, and Diffusion Effect of the Asphalt-Asphalt Models. the Results Indicated that the Restored Broken SBS Molecule Substantially Impacted the Functionality of the Rejuvenated Asphalt Binder. for Methylene-Bis(4-Cyclohexylisocyanate) (HMDI) and 1,6-Hexanediol Diglycidyl Ether (HDE) Rejuvenated Asphalts, the Non-Bond Energy Decreased Gradually with the Repair of Broken SBS Molecular Structures. the Free Volume Fraction of Rejuvenated Binders Was Lower Than that of SBSMA, indicating that the Compactness and Packing Degree of the Rejuvenated Asphalt Were Increased. the Interaction Energy between SBS and Asphalt Molecules in Rejuvenated Asphalt Increased Because of the Enhanced Van Der Waals Interaction between the Reconstructed SBS Molecule and Rejuvenated Binders. the Free HDE Molecular Chain Reduced the Interaction Energy between SBS and Asphalt Molecules. for the Asphalt-Asphalt Models, the Diffusion Coefficient of the SBSMA-Rejuvenated Asphalt Model Was Lower Than that of the SBSMA-SBSMA Model. the HDE Rejuvenated Asphalt Showed Better Diffusion Behavior Than SBSMA, and SBS Molecules Repaired by HDE Had Excellent Fluidity. the Interfacial Interaction Energy of the SBSMA-Rejuvenated Asphalt Model Was Higher Than that of the SBSMA-SBSMA Model. with the Repair of the Broken SBS Molecular Chain, the Interfacial Interaction Energy between HMDI Rejuvenated Asphalt and SBSMA Increased Gradually. in Contrast, the Interfacial Interaction Energy between HDE Rejuvenated Asphalt and SBSMA Decreased Gradually. the Fully Restored SBS Molecular Structure Had Stable Thermodynamic Properties and Could Accelerate the Diffusion Effect of Rejuvenated Asphalt

A narrow-band parameterization for the stochastic gravitational wave background

In light of the non-perturbative resonance effects that may occur during inflation, we introduce a parametrization for the power spectrum of the stochastic gravitational wave background (SGWB) characterized by narrow-band amplification. We utilize the universal $\Omega_\text{GW}\propto k^3$ infrared limit, applicable to a wide array of gravitational wave sources, to devise a robust yet straightforward parameterization optimized for Markov Chain Monte Carlo (MCMC) analyses. This parameterization is demonstrated through select examples where its application is pertinent, and we discuss the advantages of this approach over traditional parametrizations for narrow-band scenarios. To evaluate the sensitivity of our proposed model parameters, we apply a mock likelihood based on the CMB-Stage4 data. Furthermore, we explicate the computational process for the mapping relationship between the foundational model parameters and our parameterized framework, using a two-field inflation model that resonantly amplifies gravitational waves (GWs) as an example

Evolution Of SBS-Modified Asphalt Performance Under Aging And Rejuvenation Cycle Conditions

Improving the poor long-term service performance of rejuvenated SBS-modified asphalt (REF-LT) is highly challenging. In this study, a blend of aged and virgin binders was used to rejuvenate REF-LT and the evolution of the asphalt performance was observed during regeneration and reaging processes. An SBS-modified asphalt (SBM) and base asphalt (BA) were mixed with REF-LT in specified ratios to prepare SBM- and BA-rejuvenated asphalts. The rejuvenated asphalts were subjected to short- and long-term aging. The high/low-temperature rheological properties, fatigue resistance, rejuvenation mechanism, and changes in the functional groups of the rejuvenated and reaged asphalts were characterized using a dynamic shear rheometer (DSR) and Fourier transform infrared spectroscopy (FTIR). The antiaging performance of the rejuvenated asphalt was evaluated. Temperature sweep results showed that both SBM and BA mitigated hardening in REF-LT. BA had a stronger softening effect on REF-LT than SBM. However, the BA-rejuvenated asphalt was more temperature sensitive than the SBM-rejuvenated asphalt. The BA-rejuvenated asphalt had poor resistance to reaging, whereas the SBM-rejuvenated asphalt demonstrated outstanding resistance to long-term aging. The Glover–Rowe (G-R) parameters indicated that after short-term aging, the rejuvenated asphalts remained in the no cracking zone, demonstrating outstanding resistance to thermal cracking. A total of 20 h of long-term aging of the rejuvenated asphalts decreased the crossover frequency and increased the rheological index, suggesting an increased risk of cracking. Relaxation tests showed that the BA-rejuvenated asphalt had a lower peak stress than that of the SBM-rejuvenated asphalt; however, the durability of the BA-rejuvenated asphalt was compromised because of the peak stress rapidly increased after reaging. Although the BA-rejuvenated asphalt exhibited good short-term crack resistance, its poor durability resulted in inferior thermal crack resistance to that of the SBM-rejuvenated asphalt after long-term aging. Linear amplitude sweep (LAS) tests indicated that the SBM-rejuvenated asphalt had a lower damage rate than the BA-rejuvenated asphalt, suggesting that the polymer network structure provided excellent damage resistance. The fatigue life of the BA-rejuvenated asphalt decreased considerably after reaging, indicating insufficient long-term fatigue resistance. The FTIR results indicated that the REF-LT rejuvenation process involved physical blending and the SBM-rejuvenated asphalt exhibited superior antiaging capability to the BA-rejuvenated asphalt. Increasing the BA content did not improve the long-term antiaging performance of the BA-rejuvenated asphalt. The higher antiaging performance of the SBM-rejuvenated asphalt resulted from the polymer network structure

Transformer based Pluralistic Image Completion with Reduced Information Loss

Transformer based methods have achieved great success in image inpainting recently. However, we find that these solutions regard each pixel as a token, thus suffering from an information loss issue from two aspects: 1) They downsample the input image into much lower resolutions for efficiency consideration. 2) They quantize $256^3$ RGB values to a small number (such as 512) of quantized color values. The indices of quantized pixels are used as tokens for the inputs and prediction targets of the transformer. To mitigate these issues, we propose a new transformer based framework called "PUT". Specifically, to avoid input downsampling while maintaining computation efficiency, we design a patch-based auto-encoder P-VQVAE. The encoder converts the masked image into non-overlapped patch tokens and the decoder recovers the masked regions from the inpainted tokens while keeping the unmasked regions unchanged. To eliminate the information loss caused by input quantization, an Un-quantized Transformer is applied. It directly takes features from the P-VQVAE encoder as input without any quantization and only regards the quantized tokens as prediction targets. Furthermore, to make the inpainting process more controllable, we introduce semantic and structural conditions as extra guidance. Extensive experiments show that our method greatly outperforms existing transformer based methods on image fidelity and achieves much higher diversity and better fidelity than state-of-the-art pluralistic inpainting methods on complex large-scale datasets (e.g., ImageNet). Codes are available at https://github.com/liuqk3/PUT.Comment: Accepted by TPAMI (2024). arXiv admin note: text overlap with arXiv:2205.0507