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In this work we study the treatment of asymmetric open quantum systems with neural networks based on the restricted Boltzmann machine. In particular, we are interested in the non-equilibrium steady state current in the boundary-driven (anisotropic) Heisenberg spin chain. We address previously published difficulties in treating asymmetric dissipative systems with neural-network quantum states and Monte-Carlo sampling and present an optimization method and a sampling technique that can be used to obtain high-fidelity steady state approximations of such systems. We point out some inherent symmetries of the Lindblad operator under consideration and exploit them during sampling. We show that local observables are not always a good indicator of the quality of the approximation and finally present results for the spin current that are in agreement with known results of simple open Heisenberg chains., Comment: 10 pages, 9 figures

By developing a cluster sampling of stochastic series expansion quantum Monte Carlo method, we investigate a spin-$1/2$ model on a bilayer square lattice with intra-layer ferromagnetic (FM) Ising coupling and inter-layer antiferromagnetic Heisenberg interaction. The continuous quantum phase transition which occurs at $g_c=3.045(2)$ between the FM Ising phase and the dimerized phase is studied via large scale simulations. From the analyzes of critical exponents we show that this phase transition belongs to the (2+1)-dimensional Ising universality class. Besides, the quantum entanglement is strong between the two layers, especially in dimerized phase. The effective Hamiltonian of single layer seems like a transverse field Ising model. However, we found the quantum entanglement Hamiltonian is a pure classical Ising model without any quantum fluctuations. Furthermore, we give a more general explanation about how a classical entanglement Hamiltonian emerges.

Quantum measurements are our eyes to the quantum systems consisting of a multitude of microscopic degrees of freedom. However, the intrinsic uncertainty of quantum measurements and the exponentially large Hilbert space pose natural barriers to simple interpretations of the measurement outcomes. We propose a nonlinear "measurement energy" based upon the measurement outcomes and an iterative effective-Hamiltonian approach to extract the most probable states (maximum likelihood estimates) in an efficient and general fashion, thus reconciling the non-commuting observables and getting more out of the quantum measurements. We showcase the versatility and accuracy of our perspective on random long-range fermion models and Kitaev quantum spin liquid models, where smoking-gun signatures were lacking. Our study also paves the way towards concepts such as nonlinear-operator Hamiltonian and applications such as parent Hamiltonian reconstruction., 6 pages, 5 figures

Neural quantum states are a new family of variational ans\"atze for quantum-many body wave functions with advantageous properties in the notoriously challenging case of two spatial dimensions. Since their introduction a wide variety of different network architectures has been employed to study paradigmatic models in quantum many-body physics with a particular focus on quantum spin models. Nonetheless, many questions remain about the effect that the choice of architecture has on the performance on a given task. In this work, we present a unified comparison of a selection of popular network architectures and symmetrization schemes employed for ground state searches of prototypical spin Hamiltonians, namely the two-dimensional transverse-field Ising model and the J1-J2 model. In the presence of a non-trivial sign structure of the ground states, we find that the details of symmetrization crucially influence the performance. We describe this effect in detail and discuss its consequences, especially for autoregressive models, as their direct sampling procedure is not compatible with the symmetrization procedure that we found to be optimal., Comment: 7 + 3 pages, 3 figures; Fixed references and a typo in table 1

Vortices are topological defects associated with superfluids and superconductors, which, when mobile, dissipate energy destroying the dissipation-less nature of the superfluid. The nature of this "quantum dissipation" is rooted in the quantum physical nature of the problem, which has been subject of an extensive literature. However, this has mostly be focused on the measures applicable in weakly interacting systems wherein they are tractable via conventional methods. Recently it became possible to address such dynamical quantum thermalization problems in very strongly interacting systems using the holographic duality discovered in string theory, mapping the quantum problem on a gravitational problem in one higher dimension, having as benefit offering a more general view on how dissipation emerges from such intricate quantum physical circumstances. We study here the elementary problem of a single vortex in two space dimensions, set in motion by a sudden quench in the background superflow formed in a finite density "Reissner-Nordstrom" holographic superconductor. This reveals a number of surprising outcomes addressing questions of principle. By fitting the trajectories unambiguously to the Hall-Vinen-Iordanskii phenomenological equation of motion we find that these are characterized by a large inertial mass at low temperature that however diminishes upon raising temperature. For a weak drive the drag is found to increase when temperature is lowered which reveals a simple shear drag associated with the viscous metallic vortex cores, supplemented by a conventional normal fluid component at higher temperatures. For a strong drive we discover a novel dynamical phenomenon: the core of the vortex deforms accompanied by a large increase of the drag force., Comment: 19 pages, 13 figures

The quantum skyrmionic phase is modeled in a two-dimensional helical spin lattice. This topological skyrmionic phase retains its nature in a large parameter space before moving to a ferromagnetic phase. Next -nearest-neighbor interaction improves the stability and it also causes a shift of the topological phase in the parameter space. Nonanalytic behavior of the rate function observed, when the system which is initially in a quantum skyrmion phase is quenched to a trivial quantum ferromagnetic phase, indicates a dynamical quantum phase transition. Dynamical quantum phase transition is absent when the system initially in a skyrmion phase is quenched to a helical phase.

Inspired by the advancements in large language models based on transformers, we introduce the transformer quantum state (TQS): a versatile machine learning model for quantum many-body problems. In sharp contrast to Hamiltonian/task specific models, TQS can generate the entire phase diagram, predict field strengths with experimental measurements, and transfer such a knowledge to new systems it has never been trained on before, all within a single model. With specific tasks, fine-tuning the TQS produces accurate results with small computational cost. Versatile by design, TQS can be easily adapted to new tasks, thereby pointing towards a general-purpose model for various challenging quantum problems., 12 pages, 13 figures

Motivated by the recent success of realizing the topologically ordered ground state of the exactly solvable toric code model by a quantum circuit on the real quantum device [K. J. Satzinger {\it et al}., Science \textbf{374}, 1237 (2021)], here we propose a parametrized quantum circuit (PQC) with the same real-device-performable optimal structure to represent quantum loop gas states with adjustably weighted loop configurations. Combining such a PQC with the variational quantum eigensolver, we obtain the accurate quantum circuit representation for the toric code model in an external magnetic field with any field strength, where the system is not exactly solvable. The topological quantum phase transition in this system is further observed in the optimized circuits by measuring the magnetization and topological entanglement entropy., Comment: 5 pages, 4 figures

The multi-terminal generalization of the steady-state density functional theory for the description of electronic and thermal transport (iq-DFT) is presented. The linear response regime of the framework is developed leading to exact expressions for the many-body transport coefficients and thermoelectric efficiency purely in terms of quantities accessible to the framework. The theory is applied to a multi-terminal interacting quantum dot in the Coulomb blockade regime for which accurate parametrizations of the exchange-correlation kernel matrix are given. The thermoelectric efficiency and output power of the multi-terminal system are studied. Surprisingly, the strong-interaction limit of these quantities can be understood in terms of the non-interacting one., 9 pages, 8 figures

Strong coupling between matter and quantized electromagnetic fields in a cavity has emerged as a possible route toward controlling the phase of matter in the absence of an external drive. We develop a faithful and efficient theoretical framework to analyze quantum geometry and topology in materials ultrastrongly coupled to cavity electromagnetic fields in two dimensions. The formalism allows us to accurately evaluate geometrical and topological quantities, such as Berry phase and Chern number, in ultrastrong and deep strong coupling regimes. We apply our general framework to analyze a concrete model of massive Dirac fermions coupled to a circularly polarized cavity mode. Surprisingly, in addition to an ordinary transition to the topological phase, our analysis reveals a qualitatively new feature in deep strong coupling regimes, namely, the emergence of reentrant transition to the topologically trivial phase. We also present its intuitive understanding by showing the unitary mapping between the low-energy effective theory of strongly coupled light-matter systems and the Haldane honeycomb model., Comment: 13 pages, 6 figures