动力学椭圆代数Aq,p,(^π)(∧gln)的Drinfeld流

从推广的Yang-Baxter关系"RLL=LLR*"出发,利用高秩高斯分解,得到了动力学椭圆代数Aq,p,^π(∧gln)及其对应的Drinfeld流.其中R,R*是A(1)n-1面模型对应的谱参数有一关于代数中心平移的动力学R矩阵.     

动力学椭圆代数A_(q,p,)()的Drinfeld流

从推广的Yang -Baxter关系“RLL =LLR ”出发 ,利用高秩高斯分解 ,得到了动力学椭圆代数Aq,p ,^π(gln〈)及其对应的Drinfeld流 .其中R ,R 是A(1)n -1面模型对应的谱参数有一关于代数中心平移的动力学R矩阵     

SUPERSYMMETRIC SU(1|2) GAUDIN MODEL

In this paper, we propose a supersymmetric SU(1|2) Gaudin model and have derived its eigenvalues. We also present the well-defined eigenstates through the quasi-classical limit of the eigenstates in the supersymmetric t-J model.     

TRIGONOMETRIC SU(N) GAUDIN MODEL

In this paper, we obtain the eigenstates and the eigenvalues of the Hamiltonians of the trigonometric SU(N) Gaudin model based on the quasi-classical limit of the trigonometric SU(N) chain with the periodic boundary condition. By using the quantum inverse scattering method, we also obtain the eigenvalues of the generating function of the trigonometric SU(N) Gaudin model.     

Exact surface energy and elementary excitations of the XXX spin-1/2 chain with arbitrary non-diagonal boundary fields

We study the physical properties of the XXX spin-1/2 chain with arbitrary non-diagonal boundary fields. By using a combination of numerical analysis and analytical method, we obtain the surface energy and elementary excitations of the model. It shows that the contributions of the two boundary fields to the surface energy are additive. We also find that there exists a kind of excitations related to the boundary string.     

Dynamical learning of non-Markovian quantum dynamics

We study the non-Markovian dynamics of an open quantum system with machine learning.The observable physical quantities and their evolutions are generated by using the neural network.After the pre-training is completed,we fix the weights in the subsequent processes thus do not need the further gradient feedback.We find that the dynamical properties of physical quantities obtained by the dynamical learning are better than those obtained by the learning of Hamiltonian and time evolution operator.The dynamical learning can be applied to other quantum many-body systems,non-equilibrium statistics and random processes.     

Exact solution of an integrable quantum spin chain with competing interactions

We construct an integrable quantum spin chain that includes the nearest-neighbor, next-nearest-neighbor, chiral three-spin couplings, Dzyloshinsky-Moriya interactions and unparallel boundary magnetic fields. Although the interactions in bulk materials are isotropic, the spins nearby the boundary fields are polarized, which induce the anisotropic exchanging interactions of the first and last bonds. The U(1) symmetry of the system is broken because of the off-diagonal boundary reflections. Using the off-diagonal Bethe ansatz, we obtain an exact solution to the system. The inhomogeneous T-Q relation and Bethe ansatz equations are given explicitly. We also calculate the ground state energy. The method given in this paper provides a general way to construct new integrable models with certain interesting interactions.     

推广t-J模型的坐标Bethe Ansatz方法

利用坐标Bethe Ansatz方法,研究了推广的t—J模型的精确解,导出了两组Bethe Ansatz方程;同时证明了在两体散射问题中的散射矩阵正是三角型的非对称六顶角R矩阵.