“…where A ∈ C n×n is a large, sparse and nonsingular matrix, σ i ∈ C are t shifts given at once, I is the n × n identity matrix, x (i) and b are solutions and right-hand side vectors of the t linear systems, respectively. Problem (1.1) arises in implicit numerical solutions of partial differential (PDEs) [1,2] and fractional differential equations (FDEs) [3,4], in control theory [5,6], large-scale eigenvalue computations [7], quantum chromodynamics (QCD) applications [8] and in other computational science problems [9][10][11]. Krylov subspace methods are an efficient alternative to sparse direct methods for solving a sequence of multi-shifted linear systems, owing to the shift-invariance property where we denote by K m (A, b) := span{b, Ab, .…”