Related papers: Single-particle entanglement dynamics in complex systems

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We consider physical Hamiltonians that can be represented by the multiparametric Gaussian ensembles.<n>We analyze the effect of varying system conditions on its bipartite entanglement entropy.
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This paper formalizes the concept that best synthesizes our intuitive understanding of quantum mechanics.<n>We introduce a second important hypothesis: if a measurement closely approximates an ideal one in terms of experimental precision, the information it provides about a physical system is independent of the measurement method.
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State-Based Quantum Simulation: Releasing the Powers of Quantum States and Copies [0.0]
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We show that the thermodynamic limit of a many-body system can reveal entanglement properties that are hard to detect in finite-size systems.<n>In particular, we show that every gapped phase of matter, even the trivial one, in $Dgeq 2$ dimensions contains models with the strongest possible bipartite large-scale entanglement.
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Absolute dimensionality of quantum ensembles [41.94295877935867]
The dimension of a quantum state is traditionally seen as the number of superposed distinguishable states in a given basis.<n>We propose an absolute, i.e.basis-independent, notion of dimensionality for ensembles of quantum states.
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arXiv Detail & Related papers (2024-07-31T15:37:06Z)
Deep thermalization in Gaussian continuous-variable quantum systems [2.979579757819132]
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Quantum Chaos on Edge [36.136619420474766]
We identify two different classes: the near edge physics of sparse'' and the near edge of dense'' chaotic systems. The distinction lies in the ratio between the number of a system's random parameters and its Hilbert space dimension. While the two families share identical spectral correlations at energy scales comparable to the level spacing, the density of states and its fluctuations near the edge are different.
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We show that in Gaussian Linear Time-Invariant (LTI) systems, the system parameters can be identified by introducing diverse intervention signals. We show that Hidden Markov Models, in general, and (Gaussian) LTI systems, fulfil a generalization of the Causal de Finetti theorem with continuous parameters.
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Predictive complexity of quantum subsystems [0.0]
We define predictive states and predictive complexity for quantum systems composed of distinct subsystems. Predictions are formed by equivalence classes of state vectors in the exterior Hilbert space. It can also serve as a local order parameter that can distinguish long and short range entanglement.
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Simplicity of mean-field theories in neural quantum states [0.0]
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Entanglement dynamics of multi-parametric random states: a single parametric formulation [0.0]
A non-ergodic quantum state of a many body system is in general random as well as multi-parametric, former due to a lack of exact information due to complexity and latter reflecting its varied behavior in different parts of the Hilbert space. Our theoretical analysis of these ensembles not only resolves the controversy about the growth rates of the average information entropies of the generic states but also leads to new insights in their entanglement dynamics.
arXiv Detail & Related papers (2022-08-25T13:39:37Z)
Entanglement Features of Random Neural Network Quantum States [0.0]
We develop an analytic method to study quantum many-body spin states encoded by random RBMs. We discover qualitatively distinct wave functions by varying RBM parameters, which correspond to distinct phases in the equivalent statistical mechanics model.
arXiv Detail & Related papers (2022-02-28T19:00:03Z)
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Unavoidable coupling of quantum systems to external degrees of freedom leads to dissipative (non-unitary) dynamics. We introduce a method to deal with these systems based on the calculation of (dissipative) lattice Green's function. We illustrate the power of this method with several examples of driven-dissipative bosonic chains of increasing complexity.
arXiv Detail & Related papers (2022-02-15T19:00:09Z)
Neural-Network Quantum States for Periodic Systems in Continuous Space [66.03977113919439]
We introduce a family of neural quantum states for the simulation of strongly interacting systems in the presence of periodicity. For one-dimensional systems we find very precise estimations of the ground-state energies and the radial distribution functions of the particles. In two dimensions we obtain good estimations of the ground-state energies, comparable to results obtained from more conventional methods.
arXiv Detail & Related papers (2021-12-22T15:27:30Z)
Non-Equilibrium Many-Body Dynamics Following A Quantum Quench [0.40357531559576965]
We study analytically and numerically the non-equilibrium dynamics of an isolated interacting many-body quantum system following a random quench. We obtain a generic formulation for describing relaxation dynamics of survival probabilities as a function of rank of interactions.
arXiv Detail & Related papers (2021-11-17T18:55:11Z)
On the properties of the asymptotic incompatibility measure in multiparameter quantum estimation [62.997667081978825]
Incompatibility (AI) is a measure which quantifies the difference between the Holevo and the SLD scalar bounds. We show that the maximum amount of AI is attainable only for quantum statistical models characterized by a purity larger than $mu_sf min = 1/(d-1)$.
arXiv Detail & Related papers (2021-07-28T15:16:37Z)
Sensing quantum chaos through the non-unitary geometric phase [62.997667081978825]
We propose a decoherent mechanism for sensing quantum chaos. The chaotic nature of a many-body quantum system is sensed by studying the implications that the system produces in the long-time dynamics of a probe coupled to it.
arXiv Detail & Related papers (2021-04-13T17:24:08Z)
Extremal quantum states [0.41998444721319206]
We peruse quantumness from a variety of viewpoints, concentrating on phase-space formulations. The symmetry-transcending properties of the Husimi $Q$ function make it our basic tool. We use these quantities to formulate extremal principles and determine in this way which states are the most and least "quantum"
arXiv Detail & Related papers (2020-10-09T18:00:02Z)
Maximum Geometric Quantum Entropy [0.0]
We propose the Maximum Geometric Quantum Entropy Principle to exploit the notions of Information Dimension and Quantum Entropy. These allow us to quantify the entropy of fully arbitrary ensembles and select the one that maximizes it.
arXiv Detail & Related papers (2020-08-19T21:43:58Z)
Gaussian Process States: A data-driven representation of quantum many-body physics [59.7232780552418]
We present a novel, non-parametric form for compactly representing entangled many-body quantum states. The state is found to be highly compact, systematically improvable and efficient to sample. It is also proven to be a universal approximator' for quantum states, able to capture any entangled many-body state with increasing data set size.
arXiv Detail & Related papers (2020-02-27T15:54:44Z)

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