We compute the Krylov Complexity of a light operator $\mathcal{O}_L$ in an eigenstate of a $2d$ CFT at large central charge $c$. The eigenstate corresponds to a primary operator $\mathcal{O}_H$ under the state-operator correspondence. We observe that the behaviour of K-complexity is different (either bounded or exponential) depending on whether the scaling dimension of $\mathcal{O}_H$ is below or above the critical dimension $h_H=c/24$, marked by the $1st$ order Hawking-Page phase transition point in the dual $AdS_3$ geometry. Based on this feature, we hypothesize that the notions of operator growth and K-complexity for primary operators in $2d$ CFTs are closely related to the underlying entanglement structure of the state in which they are computed, thereby demonstrating explicitly their state-dependent nature. To provide further evidence for our hypothesis, we perform an analogous computation of K-complexity in a model of free massless scalar field theory in $2d$, and in the integrable $2d$ Ising CFT, where there is no such transition in the spectrum of states.
Krylov operator complexity in holographic CFTs: Smeared boundary reconstruction and the dual proper radial momentum
Okinawa Institute of Science and Technology Graduate University（冲绳科学技术大学院大学）；Gwangju Institute of Science and Technology（光州科学技术院）；National Institute of Technology, Yuge College（国立丰桥技术大学宇部学院）
Krylov complexity, or K-complexity for short, has recently emerged as a new probe of chaos in quantum systems. It is a measure of operator growth in Krylov space, which conjecturally bounds the operator growth measured by the out of time ordered correlator (OTOC). We study Krylov complexity in conformal field theories by considering arbitrary 2d CFTs, free field, and holographic models. We find that the bound on OTOC provided by Krylov complexity reduces to bound on chaos of Maldacena, Shenker, and Stanford. In all considered examples including free and rational CFTs Krylov complexity grows ex…
Krylov complexity from a simple quantum mechanical model for a radiating black hole
Instituto de Física Teórica, UNESP-Universidade Estadual Paulista（圣保罗州立大学理论物理研究所）；The Laboratory for Quantum Gravity and Strings, Department of Mathematics and Applied Mathematics, University of Cape Town（开普敦大学数学与应用数学系量子引力与弦实验室）
Holographic Krylov complexity in confining gauge theories
Institute for Theoretical and Mathematical Physics, Lomonosov Moscow State University（莫斯科国立大学理论与数学物理研究所）；Instituto de Física Teórica, UNESP-Universidade Estadual Paulista（圣保罗州立大学理论物理研究所）；Centre for Quantum Fields and Gravity, Department of Physics, Swansea University（斯旺西大学物理系量子场与引力中心）；Department of Physics, Indian Institute of Technology Roorkee（鲁尔基印度理工学院物理系）
Holographic Krylov Complexity for Conformal Quiver Gauge Theories
Institute for Theoretical and Mathematical Physics, Lomonosov Moscow State University（莫斯科国立大学理论与数学物理研究所）；Centre for Quantum Fields and Gravity, Department of Physics, Swansea University（斯旺西大学物理系量子场与引力中心）；Instituto de Física Teórica, UNESP-Universidade Estadual Paulista（圣保罗州立大学理论物理研究所）；Department of Physics, Indian Institute of Technology Roorkee（鲁尔基印度理工学院物理系）
Krylov complexity is a novel observable for detecting quantum chaos, and an indicator of a possible gravity dual. In this paper, we compute the Krylov complexity and the associated Lanczos coefficients in the SU(2) Yang-Mills theory, which can be reduced to a nonlinearly coupled harmonic oscillators (CHO) model. We show that there exists a chaotic transition in the growth of Krylov complexity. The Krylov complexity shows a quadratic growth in the early time stage and then grows linearly. The corresponding Lanczos coefficient satisfies the universal operator growth hypothesis, i.e., grows linea…
Holographic Krylov Complexity for Charged, Composite and Extended Probes
Instituto de Física Teórica, UNESP-Universidade Estadual Paulista（圣保罗州立大学理论物理研究所）；Centre for Quantum Fields and Gravity, Department of Physics, Swansea University（斯旺西大学物理系量子场与引力中心）；Department of Physics, Indian Institute of Technology Roorkee（鲁尔基印度理工学院物理系）
Holographic Krylov spread complexity for a confining multi-charge AdS soliton
Instituto de Física Teóretica, UNESP - Universidade Estadual Paulista（圣保罗州立大学理论物理研究所）；Centre for Quantum Fields and Gravity, Department of Physics, Swansea University（斯旺西大学物理学院量子场与引力中心）
Krylov Complexity for Open Quantum System: Dissipation and Decoherence
Indian Institute of Technology, Gandhinagar（印度理工学院甘德纳格尔分校）；University of Cape Town（开普敦大学）；The National Institute for Theoretical and Computational Sciences（理论与计算科学国家研究所）
Krylov complexity has emerged as a new probe of operator growth in a wide range of non-equilibrium quantum dynamics. However, a fundamental issue remains in such studies: the definition of the distance between basis states in Krylov space is ambiguous. Here, we show that Krylov complexity can be rigorously established from circuit complexity when dynamical symmetries exist. Whereas circuit complexity characterizes the geodesic distance in a multi-dimensional operator space, Krylov complexity measures the height of the final operator in a particular direction. The geometric representation of ci…
Explicit Connections Between Krylov and Nielsen Complexity
The International Solvay Institutes（索尔维国际研究所）；School of Physics, Peking University（北京大学物理学院）；Center of High Energy Physics, Peking University（北京大学高能物理中心）
Geometric-phase control of Krylov complexity in adiabatic dynamics
Beihang University（北京航空航天大学）；China West Normal University（西华师范大学）；Jishou University（吉首大学）；Peng Huanwu Collaborative Center for Research and Education, Beihang University（北京航空航天大学彭桓武研究院）
Krylov complexity and oscillatory quantum dynamics in two-field inflation
Department of Physics, Guizhou Minzu University（贵州民族大学物理系）；Department of Physics, College of Physics, Mechanical and Electrical Engineering, Jishou University（吉首大学物理科学与机械电子工程学院物理系）
Krylov complexity measures operator growth with respect to a basis, which is adapted to the Heisenberg time evolution. The construction of that basis relies on the Lanczos algorithm, also known as the recursion method. The mathematics of Krylov complexity can be described in terms of orthogonal polynomials. We provide a pedagogical introduction to the subject and work out analytically a number of examples involving the classical orthogonal polynomials, polynomials of the Hahn class, and the Tricomi-Carlitz polynomials.
We study the spectral properties of two classes of random matrix models: non-Gaussian RMT with quartic and sextic potentials, and RMT with Gaussian noise. We compute and analyze the quantum Krylov complexity and the spectral form factor for both of these models. We find that both models show suppression of the spectral form factor at short times due to decoherence effects, but they differ in their long-time behavior. In particular, we show that the Krylov complexity for the non-Gaussian RMT and RMT with noise deviates from that of a Gaussian RMT. We discuss the implications and limitations of …
We develop computational tools necessary to extend the application of Krylov complexity beyond the simple Hamiltonian systems considered thus far in the literature. As a first step toward this broader goal, we show how the Lanczos algorithm that iteratively generates the Krylov basis can be augmented to treat coherent states associated with the Jacobi group, the semi-direct product of the 3-dimensional real Heisenberg-Weyl group $H_{1}$, and the symplectic group, $Sp(2,\mathbb{R})\simeq SU(1,1)$. Such coherent states are physically realized as squeezed states in, for example, quantum optics. W…
