The efficient numerical simulation of nonequilibrium real-time evolution in isolated quantum matter constitutes a key challenge for current computational methods. This holds particular the regime two spatial dimensions, whose experimental exploration is currently pursued with strong efforts simulators. In this work we present versatile and machine learning inspired approach based on recently introduced artificial neural network encoding many-body wave functions. We identify resolve...

The notion of a dynamical quantum phase transition (DQPT) was recently introduced in [Heyl et al., Phys. Rev. Lett. 110, 135704 (2013)] as the non-analytic behavior Loschmidt echo at critical times thermodynamic limit. In this work quench dynamics ground state sector two-dimensional Kitaev honeycomb model are studied regarding occurrence DQPTs. For general systems BCS-type it is demonstrated how zeros coalesce to areas limit, implying that DQPTs occur discontinuities second derivative....

Strongly interacting quantum systems described by non-stoquastic Hamiltonians exhibit rich low-temperature physics. Yet, their study poses a formidable challenge, even for state-of-the-art numerical techniques. Here, we investigate systematically the performance of class universal variational wave-functions based on artificial neural networks, considering frustrated spin-$1/2$ $J_1-J_2$ Heisenberg model square lattice. Focusing network architectures without physics-informed input, argue in...

Disorder-free localization has been recently introduced as a mechanism for ergodicity breaking in low-dimensional homogeneous lattice gauge theories caused by local constraints imposed invariance. We show that also genuinely interacting systems two spatial dimensions can become nonergodic consequence of this mechanism. Specifically, we prove behavior the quantum link model obtaining rigorous bound on localization-delocalization transition through classical correlated percolation problem...

The quantum Kibble-Zurek mechanism (QKZM) predicts universal dynamical behavior near the phase transitions (QPTs). It is now well understood for one-dimensional matter. Higher-dimensional systems, however, remain a challenge, complicated by fundamentally different character of associated QPTs and their underlying conformal field theories. In this work, we take first steps toward theoretical exploration QKZM in two dimensions interacting We study crossing QPT paradigmatic Ising model joint...

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 two spatial dimensions. Since their introduction wide variety different network architectures has been employed to study paradigmatic models many-body physics particular focus on spin models. Nonetheless, many questions remain about effect that choice architecture performance given task. In this work, we present unified...

The efficient representation of quantum many-body states with classical resources is a key challenge in theory. In this work we analytically construct networks for the description dynamics transverse-field Ising models that can be solved efficiently using Monte Carlo techniques. Our perturbative construction encodes time-evolved spin-1/2 systems network spins local couplings and directly generalized to other spin higher spins. Using compute transient one, two, three dimensions including...

We develop a variational approach to simulating the dynamics of open quantum many-body systems using deep autoregressive neural networks. The parameters compressed representation mixed state are adapted dynamically according Lindblad master equation by employing time-dependent principle. illustrate our solving dissipative Heisenberg model in one dimension for up 40 spins and two dimensions 4×4 system applying it simulation confinement presence dissipation.

The existence of a quantum butterfly effect in the form exponential sensitivity to small perturbations has been under debate for long time. Lately, this question gained increased interest due proposal probe chaotic dynamics and scrambling using out-of-time-order correlators. In work we study echo Sachdev-Ye-Kitaev model effective time reversal semiclassical approach. We demonstrate that imperfections introduced time-reversal procedure result an divergence from perfect echo, which allows...

In this paper we present the results of a user study comparing readability force-directed, orthogonal, and hierarchical graph layouts. To end identified prototypical tasks which are solved using visual representations graphs. Based on correctness answers related response time evaluated for each task layout is better suited. addition, found possible explanations these by analyzing eye-tracking data. Finally, discuss some implications our findings algorithm designers application developers.

We study the Hall conductance of a Chern insulator after global quench Hamiltonian. The in long time limit is obtained by applying linear response theory to diagonal ensemble. It expressed as integral Berry curvature weighted occupation number over Brillouin zone. identify topologically driven nonequilibrium phase transition, which indicated nonanalyticity function energy gap ${m}_{f}$ post-quench Hamiltonian ${\stackrel{\ifmmode \hat{}\else \^{}\fi{}}{H}}_{f}$. topological invariant for...

For the characterization of dynamics in quantum many-body systems question how information spreads and becomes distributed over constituent degrees freedom is fundamental interest. The delocalization under has been dubbed scrambling, out-of-time-order correlators were proposed to probe this behavior. In work we investigate time evolution tripartite as a natural operator-independent measure which quantifies what extent initially localized can be recovered only by global measurements. Studying...

By means of the discrete truncated Wigner approximation, we study dynamical phase transitions arising in steady state transverse-field Ising models after a quantum quench. Starting from fully polarized ferromagnetic initial condition, these separate with nonvanishing magnetization along ordering direction disordered symmetric upon increasing transverse field. We consider two paradigmatic cases, one-dimensional long-range model power-law interactions...

Programmable quantum devices are now able to probe wave functions at unprecedented levels. This is based on the ability project many-body state of atom and qubit arrays onto a measurement basis which produces snapshots system function. Extracting processing information from such observations remains, however, an open quest. One often resorts analyzing low-order correlation - i.e., discarding most available content. Here, we introduce function networks mathematical framework describe network...

Spectral functions are central to link experimental probes theoretical models in condensed matter physics. However, performing exact numerical calculations for interacting quantum has remained a key challenge especially beyond one spatial dimension. In this work, we develop versatile approach using neural states obtain spectral properties based on simulations of the dynamics excitations initially localized real or momentum space. We apply compute dynamical structure factor vicinity critical...

Reconstructing Hamiltonians from local measurements is key to enabling reliable quantum simulations: both validating the implemented model and identifying any leftover terms with sufficient precision a problem of increasing importance. Here we propose deep-learning-assisted variational algorithm for Hamiltonian reconstruction by preprocessing dataset that diagnosed contain thermal operators. We demonstrate efficient precise Hamiltonians, while long-range interacting are reconstructed...

Programmable quantum devices are now able to probe wave functions at unprecedented levels. This is based on the ability project many-body state of atom and qubit arrays onto a measurement basis which produces snapshots system function. Extracting processing information from such observations remains, however, an open quest. One often resorts analyzing low-order correlation functions—that is, discarding most available content. Here, we introduce wave-function networks—a mathematical framework...

Abstract The utility of a quantum computer is highly dependent on the ability to reliably perform accurate logic operations. For finding optimal control solutions, it particular interest explore model-free approaches, since their quality not constrained by limited accuracy theoretical models for processor—in contrast many established gate implementation strategies. In this work, we utilize continuous reinforcement learning algorithm design entangling two-qubit gates superconducting qubits;...

The vast complexity is a daunting property of generic quantum states that poses significant challenge for theoretical treatment, especially in non-equilibrium setups. Therefore, it vital to recognize which are locally less complex and thus describable with (classical) effective theories. We use unsupervised learning autoencoder neural networks detect the local time-evolved by determining minimal number parameters needed reproduce observations. latter can be used as probe thermalization,...

The introduction of Neural Quantum States (NQS) has recently given a new twist to variational Monte Carlo (VMC). ability systematically reduce the bias wave function ansatz renders approach widely applicable. However, performant implementations are crucial reach numerical state art. Here, we present Python codebase that supports arbitrary NQS architectures and model Hamiltonians. Additionally leveraging automatic differentiation, just-in-time compilation accelerators, distributed computing,...

Through the use of a SCID transfer system, we have demonstrated that under certain conditions, production Ig by Ly-1 B cells can be modulated T cells. This modulation take form enhanced isotype or isotype-switch induction and to some extent appears dependent on activation state Furthermore shown mount an idiotypically restricted cell-dependent immune response antigen PC-KLH. result suggests previous failure observe responses has been due these being "blind" antigens used is not inherent...

The concept of irreversibility is necessary to justify the statistical description many-body systems. Here, authors study dynamics observable echoes in quantum systems occurring when time-evolution effectively inverted. For nonintegrable they find that small imperfections time-reversal procedure alter state system lead exponentially decaying echoes. As corresponding decay rate largely independent strength perturbation, an intrinsic sensitivity perturbation revealed. This implies for all...

Dynamics in correlated quantum matter is a hard problem, as its exact solution generally involves computational effort that grows exponentially with the number of constituents. While remarkable progress has been witnessed recent years for one-dimensional systems, much less achieved interacting models higher dimensions, since they incorporate an additional layer complexity. In this work, we employ variational method allows efficient and controlled computation dynamics many-body systems one...

Studying the zeroes of partition functions in space complex control parameters allows to understand formally how critical behavior a many-body system can arise thermodynamic limit despite various no-go theorems for finite systems. In this work we propose protocols that be realized quantum simulators measure location function classical Ising models. The are solely based on implementation simple two-qubit gates, local spin rotations, and projective measurements along two orthogonal...