Ds+ -- Ds- Asymmetry in Photoproduction

Considering of the possible difference in strange and antistrange quark distributions inside nucleon, we investigate the Ds+ -- Ds- asymmetry in photoproduction in the framework of heavy-quark recombination mechanism. We adopt two distribution models of strange sea, those are the light-cone meson-baryon fluctuation model and the effective chiral quark model. Our results show that the asymmetry induced by the strange quark distributions is distinct, which is measurable in experiments. And, there are evident differences between the predictions of our calculation and previous estimation. Therefore, the experimental measurements on the Ds+ -- Ds- asymmetry may impose a unique restriction on the strange-antistrange distribution asymmetry models.Comment: 11 page, 5 figure

DsD_s Asymmetry in Photoproduction

By adopting two models of strange and antistrange quark distributions inside nucleon, the light-cone meson-baryon fluctuation model and the effective chiral quark model, we calculate the $D_s^+ - D_s^-$ asymmetry in photoproduction in the framework of heavy-quark recombination mechanism. We find that the effect of asymmetry of strange sea to the $D_s$ asymmetry is considerable and depending on the different models. Therefore, we expect that with the further study in electroproduction, e.g. at HERA and CEBAF, the experimental measurements on the $D_s^+ - D_s^-$ asymmetry may impose a strong restriction on the strange-antistrange distribution asymmetry models.Comment: 4 pages, talk presented by I. Caprini at the International Conference on QCD and Hadronic Physics, June 16-20 2005, Beijin

Correlated flat bands in the paramagnetic phase of triangular antiferromagnets Na2_2BaX(PO4_4)2_2 (X = Mn, Co, Ni)

Flat band systems in condensed matter physics are intriguing because they can exhibit exotic phases and unconventional properties. In this work, we studied three correlated magnetic systems, Na$_2$BaX(PO$_4$)$_2$ (X = Mn, Co, Ni), and revealed their unusual electronic structure and magnetic properties. Despite their different effective angular momentum, our first-principles calculations showed a similar electronic structure among them. However, their different valence configurations led to different responses to electronic correlations in the high-temperature paramagnetic phase. Using the dynamical mean-field method, we found that all systems can be understood as a multi-band Hubbard model with Hund'ss coupling. Our calculations of spin susceptibility and the {\it ab-initio} estimation of magnetic exchange coupling indicated strong intra-plane antiferromagnetic coupling and weak inter-plane coupling in all systems. The ground states of these systems are largely degenerate. It is likely that none of these magnetic states would dominate over the others, leading to the possibility of quantum spin liquid states in these systems. Our work unifies the understanding of these three structurally similar systems and opens new avenues for exploring correlated flat bands with distinct electronic and magnetic responses.Comment: 11 pages and 4 figure

Multiple Positive Solutions to Multipoint Boundary Value Problem for a System of Second-Order Nonlinear Semipositone Differential Equations on Time Scales

We study a system of second-order dynamic equations on time scales (p1u1∇)Δ(t)-q1(t)u1(t)+λf1(t,u1(t),u2(t))=0,t∈(t1,tn),(p2u2∇)Δ(t)-q2(t)u2(t)+λf2(t,u1(t), u2(t))=0, satisfying four kinds of different multipoint boundary value conditions, fi is continuous and semipositone. We derive an interval of λ such that any λ lying in this interval, the semipositone coupled boundary value problem has multiple positive solutions. The arguments are based upon fixed-point theorems in a cone

DSPGAN: a GAN-based universal vocoder for high-fidelity TTS by time-frequency domain supervision from DSP

Recent development of neural vocoders based on the generative adversarial neural network (GAN) has shown their advantages of generating raw waveform conditioned on mel-spectrogram with fast inference speed and lightweight networks. Whereas, it is still challenging to train a universal neural vocoder that can synthesize high-fidelity speech from various scenarios with unseen speakers, languages, and speaking styles. In this paper, we propose DSPGAN, a GAN-based universal vocoder for high-fidelity speech synthesis by applying the time-frequency domain supervision from digital signal processing (DSP). To eliminate the mismatch problem caused by the ground-truth spectrograms in training phase and the predicted spectrograms in inference phase, we leverage the mel-spectrogram extracted from the waveform generated by a DSP module, rather than the predicted mel-spectrogram from the Text-to-Speech (TTS) acoustic model, as the time-frequency domain supervision to the GAN-based vocoder. We also utilize sine excitation as the time-domain supervision to improve the harmonic modeling and eliminate various artifacts of the GAN-based vocoder. Experimental results show that DSPGAN significantly outperforms the compared approaches and can generate high-fidelity speech based on diverse data in TTS.Comment: Submitted to ICASSP 202