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Resonant spectroscopies, which involve intermediate states with finite lifetimes, provide essential insights into collective excitations in quantum materials that are otherwise inaccessible. However, theoretical understanding in this area is often limited by the numerical challenges of solving Kramers-Heisenberg-type response functions for large-scale systems. To address this, we introduce a multishifted biconjugate gradient algorithm that exploits the shared structure of Krylov subspaces across spectra with varying incident energies, effectively reducing the computational complexity to that of linear spectroscopies. Both mathematical proofs and numerical benchmarks confirm that this algorithm substantially accelerates spectral simulations, achieving constant complexity independent of the number of incident energies, while ensuring accuracy and stability. This development provides a scalable, versatile framework for simulating advanced spectroscopies in quantum materials 

We propose a new nonlinear preconditioned conjugate gradient (PCG) method in real arithmetic for computing the ground states of rotational Bose--Einstein condensate, modeled by the Gross--Pitaevskii equation. Our algorithm presents a few improvements of the PCG method in complex arithmetic studied by Antoine, Levitt, and Tang [J. Comput. Phys., 343 (2017), pp. 92--109]. We show that the special structure of the energy functional $$E(\phi)$$ and its gradient with respect to $$\phi$$ can be fully exploited in real arithmetic to evaluate them more efficiently. We propose a simple approach for fast evaluation of the energy functional, which enables exact line search. Most importantly, we derive the discrete Hessian operator of the energy functional and propose a shifted Hessian preconditioner for PCG, with which the ideal preconditioned Hessian has favorable eigenvalue distributions independent of the mesh size. This suggests that PCG with our ideal Hessian preconditioner is expected to exhibit mesh size-independent asymptomatic convergence behavior. In practice, our preconditioner is constructed by incomplete Cholesky factorization of the shifted discrete Hessian operator based on high-order finite difference discretizations. Numerical experiments in two-dimensional (2D) and three-dimensional (3D) domains show the efficiency of fast energy evaluation, the robustness of exact line search, and the improved convergence of PCG with our new preconditioner in iteration counts and runtime, notably for more challenging rotational BEC problems with high nonlinearity and rotational speed. 

The discretized Bethe-Salpeter eigenvalue (BSE) problem arises in many body physics and quantum chemistry. Discretization leads to an {\color{black}algebraic} eigenvalue problem involving a matrix $$H\in \mathbb{C}^{2n\times 2n}$$ with a Hamiltonian-like structure. With proper transformations, {\color{black}the real BSE eigenproblem of form I and the complex BSE eigenproblem of form II} can be transformed into real product eigenvalue problems of order $$n$$ and $2n$, respectively. We propose a new variant of the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) {\color{black}enhanced with polynomial filters} to improve the robustness and effectiveness of a few well-known algorithms for computing the lowest eigenvalues of the product eigenproblems. {\color{black}Furthermore, our proposed method can be easily employed to solve large sparse standard symmetric eigenvalue problems.} We show that our ideal locally optimal algorithm delivers Rayleigh quotient approximation to the desired lowest eigenvalue that satisfies a global quasi-optimality, which is similar to the global optimality of the preconditioned conjugate gradient method for the iterative solution of a symmetric positive definite linear system. The robustness and efficiency of {\color{black}our proposed method} is illustrated by numerical experiments. 

A flexible extended Krylov subspace method (F-EKSM) is considered for numerical approximation of the action of a matrix function f(A) to a vector b, where the function f is of Markov type. F-EKSM has the same framework as the extended Krylov subspace method (EKSM), replacing the zero pole in EKSM with a properly chosen fixed nonzero pole. For symmetric positive definite matrices, the optimal fixed pole is derived for F-EKSM to achieve the lowest possible upper bound on the asymptotic convergence factor, which is lower than that of EKSM. The analysis is based on properties of Faber polynomials of A and (I−A/s)−1. For large and sparse matrices that can be handled efficiently by LU factorizations, numerical experiments show that F-EKSM and a variant of RKSM based on a small number of fixed poles outperform EKSM in both storage and runtime, and usually have advantages over adaptive RKSM in runtime. 

This paper concerns the theory and development of inexact rational Krylov subspace methods for approximating the action of a function of a matrix f(A) to a column vector b. At each step of the rational Krylov subspace methods, a shifted linear system of equations needs to be solved to enlarge the subspace. For large-scale problems, such a linear system is usually solved approximately by an iterative method. The main question is how to relax the accuracy of these linear solves without negatively affecting the convergence of the approximation of f(A)b. Our insight into this issue is obtained by exploring the residual bounds for the rational Krylov subspace approximations of f(A)b, based on the decaying behavior of the entries in the first column of certain matrices of A restricted to the rational Krylov subspaces. The decay bounds for these entries for both analytic functions and Markov functions can be efficiently and accurately evaluated by appropriate quadrature rules. A heuristic based on these bounds is proposed to relax the tolerances of the linear solves arising in each step of the rational Krylov subspace methods. As the algorithm progresses toward convergence, the linear solves can be performed with increasingly lower accuracy and computational cost. Numerical experiments for large nonsymmetric matrices show the effectiveness of the tolerance relaxation strategy for the inexact linear solves of rational Krylov subspace methods. 

In ferromagnetic systems lacking inversion symmetry, an applied electric field can control the ferromagnetic order parameters through the spin-orbit torque. The prototypical example is a bilayer heterostructure composed of a ferromagnet and a heavy metal that acts as a spin current source. In addition to such bilayers, spin-orbit coupling can mediate spin-orbit torques in ferromagnets that lack bulk inversion symmetry. A recently discovered example is the two-dimensional monolayer ferromagnet Fe3GeTe2. In this paper, we use first-principles calculations to study the spin-orbit torque and ensuing magnetic dynamics in this material. By expanding the torque versus magnetization direction as a series of vector spherical harmonics, we find that higher order terms (up to ℓ=4) are significant and play important roles in the magnetic dynamics. They give rise to deterministic, magnetic field-free electrical switching of perpendicular magnetization. 

Ferromagnetic insulators (FMIs) have widespread applications in microwave devices, magnetic tunneling junctions, and dissipationless electronic and quantum-spintronic devices. However, the sparsity of the available high-temperature FMIs has led to the quest for a robust and controllable insulating ferromagnetic state. Here, we present compelling evidence of modulation of the magnetic ground state in a SrCoO2.5 (SCO) thin film via strain engineering. The SCO system is an antiferromagnetic insulator with a Neel temperature, TN, of ∼550 K. Applying in-plane compressive strain, the SCO thin film reveals an insulating ferromagnetic state with an extraordinarily high Curie temperature, TC, of ∼750 K. The emerged ferromagnetic state is associated with charge-disproportionation (CD) and spin-state-disproportionation (SSD), involving high-spin Co2+ and low-spin Co4+ ions. The density functional theory calculation also produces an insulating ferromagnetic state in the strained SCO system, consistent with the CD and SSD, which is associated with the structural ordering in the system. Transpiring the insulating ferromagnetic state through modulating the electronic correlation parameters via strain engineering in the SCO thin film will have a significant impact in large areas of modern electronic and spintronic applications.