Tridiagonalizing random matrices

被引:29
作者
Balasubramanian, Vijay [1 ,2 ,3 ]
Magan, Javier M. [1 ,3 ,4 ]
Wu, Qingyue [1 ]
机构
[1] Univ Penn, David Rittenhouse Lab, 209 S 33rd St, Philadelphia, PA 19104 USA
[2] St Fe Inst, 1399 Hyde Pk Rd, Santa Fe, NM 87501 USA
[3] Vrije Univ Brussel, Theoret Natuurkunde, Pleinlaan 2, B-1050 Brussels, Belgium
[4] Inst Balseiro, Ctr Atom Bariloche, 8400 S C de Bariloche, Rio Negro, Argentina
关键词
THERMO-FIELD-DYNAMICS; CHARACTERISTIC VECTORS; BORDERED MATRICES; REDUCTION;
D O I
10.1103/PhysRevD.107.126001
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
The Hungarian physicist Eugene Wigner introduced random matrix models in physics to describe the energy spectra of atomic nuclei. As such, the main goal of random matrix theory (RMT) has been to derive the eigenvalue statistics of matrices drawn from a given distribution. The Wigner approach gives powerful insights into the properties of complex, chaotic systems in thermal equilibrium. Another Hungarian, Cornelius Lanczos, suggested a method of reducing the dynamics of any quantum system to a one-dimensional chain by tridiagonalizing the Hamiltonian relative to a given initial state. In the resulting matrix, the diagonal and off-diagonal Lanczos coefficients control transition amplitudes between elements of a distinguished basis of states. We connect these two approaches to the quantum mechanics of complex systems by deriving analytical formulas relating the potential defining a general RMT, or, equivalently, its density of states, to the Lanczos coefficients and their correlations. In particular, we derive an integral relation between the average Lanczos coefficients and the density of states, and, for polynomial potentials, algebraic equations that determine the Lanczos coefficients from the potential. We obtain these results for generic initial states in the thermodynamic limit. As an application, we compute the time-dependent "spread complexity" in thermofield double states and the spectral form factor for Gaussian and non -Gaussian RMTs.
引用
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页数:25
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