First-principles calculations of phase transition, elasticity, and thermodynamic properties for TiZr alloy

tructural transformation, pressure dependent elasticity behaviors, phonon, and thermodynamic properties of the equiatomic TiZr alloy are investigated by using first-principles density-functional theory. Our calculated lattice parameters and equation of state for $\alpha$ and $\omega$ phases as well as the phase transition sequence of $\alpha$$\mathtt{\rightarrow}$$\omega$$\mathtt{\rightarrow}$$\beta$ are consistent well with experiments. Elastic constants of $\alpha$ and $\omega$ phases indicate that they are mechanically stable. For cubic $\beta$ phase, however, it is mechanically unstable at zero pressure and the critical pressure for its mechanical stability is predicted to equal to 2.19 GPa. We find that the moduli, elastic sound velocities, and Debye temperature all increase with pressure for three phases of TiZr alloy. The relatively large $B/G$ values illustrate that the TiZr alloy is rather ductile and its ductility is more predominant than that of element Zr, especially in $\beta$ phase. Elastic wave velocities and Debye temperature have abrupt increase behaviors upon the $\alpha$$\mathtt{\rightarrow}$$\omega$ transition at around 10 GPa and exhibit abrupt decrease feature upon the $\omega$$\mathtt{\rightarrow}$$\beta$ transition at higher pressure. Through Mulliken population analysis, we illustrate that the increase of the \emph{d}-band occupancy will stabilize the cubic $\beta$ phase. Phonon dispersions for three phases of TiZr alloy are firstly presented and the $\beta$ phase phonons clearly indicate its dynamically unstable nature under ambient condition. Thermodynamics of Gibbs free energy, entropy, and heat capacity are obtained by quasiharmonic approximation and Debye model.Comment: 9 pages, 10 figure

N-Gram Unsupervised Compoundation and Feature Injection for Better Symbolic Music Understanding

The first step to apply deep learning techniques for symbolic music understanding is to transform musical pieces (mainly in MIDI format) into sequences of predefined tokens like note pitch, note velocity, and chords. Subsequently, the sequences are fed into a neural sequence model to accomplish specific tasks. Music sequences exhibit strong correlations between adjacent elements, making them prime candidates for N-gram techniques from Natural Language Processing (NLP). Consider classical piano music: specific melodies might recur throughout a piece, with subtle variations each time. In this paper, we propose a novel method, NG-Midiformer, for understanding symbolic music sequences that leverages the N-gram approach. Our method involves first processing music pieces into word-like sequences with our proposed unsupervised compoundation, followed by using our N-gram Transformer encoder, which can effectively incorporate N-gram information to enhance the primary encoder part for better understanding of music sequences. The pre-training process on large-scale music datasets enables the model to thoroughly learn the N-gram information contained within music sequences, and subsequently apply this information for making inferences during the fine-tuning stage. Experiment on various datasets demonstrate the effectiveness of our method and achieved state-of-the-art performance on a series of music understanding downstream tasks. The code and model weights will be released at https://github.com/CinqueOrigin/NG-Midiformer.Comment: 8 pages, 2 figures, aaai202

Privacy-preserving communication and power injection over vehicle networks and 5G smart grid slice

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Self-organization and phase transition in financial markets with multiple choices

Market confidence is essential for successful investing. By incorporating multi-market into the evolutionary minority game, we investigate the effects of investor beliefs on the evolution of collective behaviors and asset prices. When there exists another investment opportunity, market confidence, including overconfidence and under-confidence, is not always good or bad for investment. The roles of market confidence is closely related to market impact. For low market impact, overconfidence in a particular asset makes an investor become insensitive to losses and a delayed strategy adjustment leads to a decline in wealth, and thereafter, one's runaway from the market. For high market impact, under-confidence in a particular asset makes an investor over-sensitive to losses and one's too frequent strategy adjustment leads to a large fluctuation in asset prices, and thereafter, a decrease in the number of agents. At an intermediate market impact, the phase transition occurs. No matter what the market impact is, an equilibrium between different markets exists, which is reflected in the occurrence of similar price fluctuations in different markets. A theoretical analysis indicates that such an equilibrium results from the coupled effects of strategy updating and shift in investment. The runaway of the agents trading a specific asset will lead to a decline in the asset price volatility and such a decline will be inhibited by the clustering of the strategies. A uniform strategy distribution will lead to a large fluctuation in asset prices and such a fluctuation will be suppressed by the decrease in the number of agents in the market. A functional relationship between the price fluctuations and the numbers of agents is found