A system of equations is derived which must be satisfied by multiparticle matrix elements of any local operator in field theories with soliton behaviour. Form factors of various operators of interest are calculated exactly by means of the known exact S-matrices in the sine-Gordon, massive Thirring, non-linear a-, and Gross-Neveu models. The finite sine-Gordon wave function renormalization const...

Abstract. We point out an interesting occurrence of the sine kernel in connection with the shifted moments of the Riemann zeta function along the critical line. We discuss rigorous results in this direction for the shifted second moment and for the shifted fourth moment. Furthermore, we conjecture that the sine kernel also occurs in connection with the higher (even) shifted moments and show tha...

We study bosonization of the sine-Gordon theory in the presence of boundary interactions at the free fermion point. In this way we obtain the boundary S-matrix as a function of physical parameters in the boundary sine-Gordon Lagrangian. The boundary S-matrix can be matched onto the solution of Ghoshal and Zamolodchikov, thereby relating the formal parameters in the latter solution to the physic...

This paper proposes a modified sine cosine algorithm (MSCA) for discrete sizing optimization of truss structures. The original sine cosine algorithm (SCA) is a population-based metaheuristic that fluctuates the search agents about the best solution based on sine and cosine functions. The efficiency of the original SCA in solving standard optimization problems of well-known mathematical function...

This paper is dedicated to study the sine version of polar bodies and establish Lp-sine Blaschke-Santaló inequality for centroid body. The body ΛpK a star K⊂Rn convex based on transform, its associated provides an upper bound volume Λp∘K, ΛpK, in terms K. Thus, this can be viewed as “sine cousin” Lp established by Lutwak Zhang. As p→∞, limit Λp∘K becomes K⋄ hence reduces polarity naturally lead...

We propose a new modeling strategy to build efficient neural network representations of chemical kinetics. Instead fitting the logarithm rates, we embed hyperbolic sine function into neural...