We present an efficient strategy for controlling a vast range of nonintegrable quantum many-body one-dimensional systems that can be merged with state-of-the-art tensor network simulation methods such as the density matrix renormalization group. To demonstrate its potential, we employ it to solve a major issue in current optical-lattice physics with ultracold atoms: we show how to reduce by about 2 orders of magnitude the time needed to bring a superfluid gas into a Mott insulator state, while suppressing defects by more than 1 order of magnitude as compared to current experiments [T. Stöferle et al., Phys. Rev. Lett. 92, 130403 (2004)]. Finally, we show that the optimal pulse is robust against atom number fluctuations.
We present an efficient strategy for controlling a vast range of nonintegrable quantum many-body one-dimensional systems that can be merged with state-of-the-art tensor network simulation methods such as the density matrix renormalization group. To demonstrate its potential, we employ it to solve a major issue in current optical-lattice physics with ultracold atoms: we show how to reduce by about 2 orders of magnitude the time needed to bring a superfluid gas into a Mott insulator state, while suppressing defects by more than 1 order of magnitude as compared to current experiments [T. Stöferle et al., Phys. Rev. Lett. 92, 130403 (2004)]. Finally, we show that the optimal pulse is robust against atom number fluctuations.
We present an efficient strategy for controlling a vast range of non-integrable quantum many body one-dimensional systems that can be merged with state-of-the-art tensor network simulation methods like the density Matrix Renormalization Group. To demonstrate its potential, we employ it to solve a major issue in current optical-lattice physics with ultra-cold atoms: we show how to reduce by about two orders of magnitudes the time needed to bring a superfluid gas into a Mott insulator state, while suppressing defects by more than one order of magnitude as compared to current experiments [1]. Finally, we show that the optimal pulse is robust against atom number fluctuations.
We apply recent state-of-the-art optimal control techniques to a challenging many-body problem: driving the superfluid-Mott insulator transition in an optical lattice. At system sizes well beyond the reach of exact diagonalization approaches, and thus requiring a matrix product state ansatz, we obtain fidelities in the range 0.99-0.9999 and beyond with associated quantum speed limit estimates. Whereas previous efforts yielded lower fidelity solutions with smooth, monotonic controls, we efficiently identify a rich hierarchy of bang-bang-like solutions. These facilitate the non-adiabatic quantum interference pathways using sequential tunneling and phase-imprinting dynamics necessary for high fidelity. Mapping out the optimal solutions at various process durations, we observe a characteristic, exponential dependence for the fidelity across several orders of magnitude. Overall, we achieve these results by utilizing the counter-intuitive fact that appropriate dynamical approximations lead to a more precise and significantly cheaper implementation of optimal control than a full dynamical solution. In discussing the technique's generality, this demonstration may pave the way for fulfilling the comprehensive demands for efficient high-fidelity control in very high-dimensional systems which has hitherto not been feasible.
We apply recent state-of-the-art optimal control techniques to a challenging many-body problem: driving the superfluid-Mott insulator transition in an optical lattice. At system sizes well beyond the reach of exact diagonalization approaches, and thus requiring a matrix product state ansatz, we obtain fidelities in the range 0.99-0.9999 and beyond with associated quantum speed limit estimates. Whereas previous efforts yielded lower fidelity solutions with smooth, monotonic controls, we efficiently identify a rich hierarchy of bang-bang-like solutions. These facilitate the non-adiabatic quantum interference pathways using sequential tunneling and phase-imprinting dynamics necessary for high fidelity. Mapping out the optimal solutions at various process durations, we observe a characteristic, exponential dependence for the fidelity across several orders of magnitude. Overall, we achieve these results by utilizing the counter-intuitive fact that appropriate dynamical approximations lead to a more precise and significantly cheaper implementation of optimal control than a full dynamical solution. In discussing the technique's generality, this demonstration may pave the way for fulfilling the comprehensive demands for efficient high-fidelity control in very high-dimensional systems which has hitherto not been feasible.
Ultracold atoms in optical lattices provide an extremely clean and controllable setting to explore quantum many-body phases of matter. Here we give a brief review of the strong-correlation physics that has been realized using such ultracold atoms in optical lattices ranging from the realization of Hubbard models to studies of quantum magnetism and the detection of single atoms with lattice site resolution. All this has opened up fundamentally new opportunities for the investigation of quantum many-body systems. Introduction Over the past years, ultracold atoms in optical lattices have emerged as versatile new systems to explore the physics of quantum many-body systems. On the one hand, they can be helpful in gaining a better understanding of known phases of matter and their dynamical behavior; on the other hand, they allow one to realize completely novel quantum systems that have not been studied before in nature [1, 2, 3]. Commonly, the approach of exploring quantum many-body systems in such a way is referred to as “quantum simulations.” Examples of some of the first strongly interacting many-body phases that have been realized both in lattices and in the continuum include the quantum phase transition from a superfluid to a Mott insulator [4, 5, 6], fermionic Mott insulators [7, 8], the achievement of a Tonks- Girardeau gas [9, 10], and the realization of the Bose-Einsten condensate (BEC)– Bardeen-Cooper-Schrieffer (BCS) crossover (see also Chapter 12) in Fermi gas mixture [11] using Feshbach resonances [12]. In almost all of these experiments, detection was limited to time-of-flight imaging or more refined derived techniques that mainly characterized the momentum distribution of the quantum gas [2]. For several years, researchers in the field have therefore aspired to employ in situ single-particle detection methods for the analysis of ultracold quantum gases. Only recently has it become possible to implement such imaging techniques, marking a milestone for the characterization and manipulation of ultracold quantum gases [13, 14, 15, 16, 17]. In our discussion, we will focus on one of the most successful of these techniques based on high-resolution fluorescence imaging. Despite being a rather new technique, such quantum gas microscopy has already proven to be an enabling technology for probing and manipulating quantum many-body systems. For the first time, controllable and strongly interacting many-body systems, as realized with ultracold atoms, could be observed on a local scale [17, 16].
We present experimental evidence of the successful closed-loop optimization of the dynamics of cold atoms in an optical lattice. We optimize the loading of an ultracold atomic gas minimizing the excitations in an array of one-dimensional (1D) tubes (3D-1D crossover) and we perform an optimal crossing of the quantum phase-transition from a superfluid to a Mott insulator in a 3D lattice. In both cases we enhance the experiment performances with respect to those obtained via adiabatic dynamics, effectively speeding up the process by more than a factor three while improving the quality of the desired transformation.
Strongly correlated quantum systems are one of the most interesting and challenging phenomena in modern condensed matter physics. Unfortunately, the theoretical access even to their low energy properties is limited by the exponential growth of the Hilbert space in a many-body setting. To mitigate this computational barrier, tensor network methods are one of the most competitive approaches to classically simulate complex quantum systems. In this thesis we will discuss recent developments in the field of tensor networks to efficiently and accurately simulate two-dimensional quantum many-body states in the thermodynamic limit. Hereby, we introduce the variational update globally optimizing the wave-function, encoded as tensor network in the form of an infinite projected entangled pair state (iPEPS), in order to obtain ground states of many-body Hamiltonian models. We focus in the discussion on the well-established method to approximately contract this two-dimensional structure, the corner transfer matrix renormalization group (CTMRG), and discuss its native application on square lattice and triangular lattice based models. Furthermore, we report the development of a refined numerical algorithm, the split-CTMRG, to significantly reduce its computational complexity, pushing the limits of feasible simulations within modern hardware capabilities. Finally, the method advancements are applied to a currently widely studied model of frustrated magnetism, the Heisenberg maple-leaf antiferromagnet. We are able to find a large phase of vanishing magnetization in contradiction to previous works and, to the best of our knowledge, the lowest reported variational ground state energy at the isotropic point of the model. As an outlook, we describe a potential adaption of the previously developed methods to variationally simulate two-dimensional many-body thermal states.