arXiv subjects

Hui Zhai

Publications and source records attributed to Hui Zhai.

At least 73 records · Page 4Linked to original sources

arXiv2019

Realizing the Hayden-Preskill Protocol with Coupled Dicke Models

Hayden and Preskill proposed a thought experiment that Bob can recover the information Alice throws into a black hole if he has a quantum computer entangled with the black hole, and Yoshida and Kitaev recently proposed a concrete decoding scheme. The parallel question is that after a small system is thermalized with a large system, how one can decode the initial state information with the help of two entangled many-body systems. Here we propose to realize this protocol in a physical system of two Dicke models, with two cavity fields prepared in a thermofield double state. We show that the Yoshida-Kitaev protocol allows us to read out the initial spin information after it is scrambled into the cavity. We show that the readout efficiency reaches a maximum when the model parameter is tuned to the regime where the system is the most chaotic, characterized by the shortest scrambling time in the out-of-time-ordered correlation function. Our proposal opens up the possibility of discussing this profound thought experiment in a realistic setting.

cond-mat.quant-gas↗

arXiv2019

Many-Body Echo

In this letter we propose a protocol to reverse a quantum many-body dynamical process. We name it "many-body echo" because the underlying physics is closely related to the spin echo effect in nuclear magnetic resonance systems. We consider a periodical modulation of the interaction strength in a weakly interacting Bose condensate, which resonantly excites quasi-particles from the condensate. A dramatic phenomenon is that, after pausing the interaction modulation for half a period and then continuing on with the same modulation, nearly all the excited quasi-particles in the resonance modes will be absorbed back into the condensate. During the intermediate half period, the free evolution introduces a $π$ phase, which plays a role reminiscent of that played by the $π$-pulse in the spin echo. Comparing our protocol with another one implemented by the Chicago group in a recent experiment, we find that ours is more effective at reversing the many-body process. The difference between these two schemes manifests the physical effect of the micro-motion in the Floquet theory. Our scheme can be generalised to other periodically driven many-body systems.

cond-mat.quant-gas↗

arXiv2019

Interaction Control of Ultracold Alkaline-Earth Atoms

Ultracold alkaline-earth atoms have now been widely explored for precision measurements and quantum simulation. Because of its unique atomic structure, alkaline earth atoms possess great advantages for quantum simulation and studying quantum many-body matters, such as simulating synthetic gauge field, Kondo physics and $SU(N)$ physics. To fully explore the potential of ultracold alkaline-earth atoms, these systems also need to be equipped with the capability of tuning the inter-atomic interaction to the strongly interacting regime. Recently several theoretical proposals and experimental demonstrations have shown that both spin-independent and spin-exchanging interaction can be tuned to resonance. In this perspective, we will review these progress and discuss the new opportunities brought by these interaction control tools for future quantum simulation studies with ultracold alkaline-earth atoms.

cond-mat.quant-gas↗

arXiv2019

Dynamics and Density Correlations in Matter Wave Jet Emission of a Driven Condensate

Emission of matter wave jets has been recently observed in a Bose-Einstein condensate confined by a cylindrical box potential, induced by a periodically modulated inter-particle interaction (Nature {\bf 551}, 356 (2017)). In this paper we apply the time-dependent Bogoliubov theory to study the quantum dynamics and the correlation effects observed in this highly non-equilibrium phenomenon. Without any fitting parameter, our theoretical calculations on the number of ejected atoms and the angular density correlations are in excellent quantitative agreement with the experimental measurements. The exponential growth in time of the ejected atoms can be understood in terms of a dynamical instability associated with the modulation of the interaction. We interpret the angular density correlation of the jets as the Hanbury-Brown-Twiss effect between the excited quasi-particles with different angular momenta, and our theory explains the puzzling observation of the asymmetric density correlations between the jets with the same and opposite momenta. Our theory can also identify the main factors that control the height and width of the peaks in the density correlation function, which can be directly verified in future experiments.

cond-mat.quant-gas↗

arXiv2019

Emergent Quantum Mechanics in an Introspective Machine Learning Architecture

Can physical concepts and laws emerge in a neural network as it learns to predict the observation data of physical systems? As a benchmark and a proof-of-principle study of this possibility, here we show an introspective learning architecture that can automatically develop the concept of the quantum wave function and discover the Schrödinger equation from simulated experimental data of the potential-to-density mappings of a quantum particle. This introspective learning architecture contains a machine translator to perform the potential to density mapping, and a knowledge distiller auto-encoder to extract the essential information and its update law from the hidden states of the translator, which turns out to be the quantum wave function and the Schrödinger equation. We envision that our introspective learning architecture can enable machine learning to discover new physics in the future.

cond-mat.dis-nn↗

arXiv2019

The Quantum Cocktail Party Problem

The cocktail party problem refers to the famous selective attention problem of how to find out the signal of each individual sources from signals of a number of detectors. In the classical cocktail party problem, the signal of each source is a sequence of data such as the voice from a speaker, and each detector detects signal as a linear combination of all sources. This problem can be solved by a unsupervised machine learning algorithm known as the independent component analysis. In this work we propose a quantum analog of the cocktail party problem. Here each source is a density matrix of a pure state and each detector detects a density matrix as a linear combination of all pure state density matrix. The quantum cocktail party problem is to recover the pure state density matrix from a number observed mixed state density matrices. We propose the physical realization of this problem, and how to solve this problem through either classical Newton's optimization method or by mapping the problem to the ground state of an Ising type of spin Hamiltonian.

quant-ph↗

arXiv2019

Generalized Independent Component Analysis for Extracting Eigen-Modes of a Quantum System

In many dynamical probes of a quantum system, quite often multiple eigenmodes are excited. Therefore, the experimental data can be quite messy due to the mixing of different modes, as well as the background noise, despite that each mode manifests itself as a single frequency oscillation. Here we develop an unsupervised machine learning algorithm to extract the frequencies of these oscillations from such measurement data, that is, the eigenenergies of these modes. This method is particularly useful when the measurement time is not long enough to perform the Fourier transformation. Our method is inspired by the independent component analysis method and its application to the cocktail party problem. In that problem, the goal is to recover each voice from detectors that detect signals of many mixed voices, and the principle is to find out signals that possess features and are away from a Gaussian distribution. Instead, our generalization is to find out signals that are close to a single frequency oscillation. We demonstrate the advantage of our method by an example of analyzing the collective mode of cold atoms. We believe this method can find broad applications in analyzing data from dynamical experiments in quantum systems.

quant-ph↗

arXiv2019

Dynamical Fractal in Quantum Gases with Discrete Scaling Symmetry

Inspired by the similarity between the fractal Weierstrass function and quantum systems with discrete scaling symmetry, we establish general conditions under which the dynamics of a quantum system will exhibit fractal structure in the time domain. As an example, we discuss the dynamics of the Loschmidt amplitude and the zero-momentum occupation of a single particle moving in a scale invariant $1/r^2$ potential. In order to show these conditions can be realized in ultracold atomic gases, we perform numerical simulations with practical experimental parameters, which shows that the dynamical fractal can be observed in realistic time scales. The predication can be directly verified in current cold atom experiments.

cond-mat.quant-gas↗

arXiv2018

On the Equivalence between Spin and Charge Dynamics of the Fermi Hubbard Model

Utilizing the Fermi gas microscope, recently the MIT group has measured the spin transport of the Fermi Hubbard model starting from a spin-density-wave state, and the Princeton group has measured the charge transport of the Fermi Hubbard model starting from a charge-density-wave state. Motivated by these two experiments, we prove a theorem that shows under certain conditions, the spin and charge transports can be equivalent to each other. The proof makes use of the particle-hole transformation of the Fermi Hubbard model and a recently discovered symmetry protected dynamical symmetry. Our results can be directly verified in future cold atom experiment with the Fermi gas microscope.

cond-mat.quant-gas↗

arXiv2018

Efimov Enhanced Kondo Effect in Alkaline and Alkaline-Earth Atomic Gas Mixture

Recent experiment has observed Feshbach resonances between alkaline and alkaline-earth atoms. These Feshbach resonances are insensitive to the nuclear spin of alkaline-earth atoms. Ultilizing this feature, we propose to take this system as a candidate to perform quantum simulation of the Kondo effect. An alkaline atom can form a molecule with an alkaline-earth atom with different nuclear spins, which plays the role of spin-exchange scattering responsible for the Kondo effect. Furthermore, we point out that the existence of three-body bound state and atom-molecule resonance due to the Efimov effect can enhance this spin-exchange scattering, and therefore enhance the Kondo effect. We discuss this mechanism first with a three-body problem in free space, and then demonstrate that the same mechanism still holds when the alkaline atom is localized by an external trap and becomes an impurity embedded in the alkaline-earth atomic gases.

cond-mat.quant-gas↗

arXiv2018

Resonant Driving induced Ferromagnetism in the Fermi Hubbard Model

In this letter we consider quantum phases and the phase diagram of a Fermi Hubbard model under periodic driving that has been realized in recent cold atom experiments, in particular, when the driving frequency is resonant with the interaction energy. Due to the resonant driving, the effective Hamiltonian contains a correlated hopping term where the density occupation strongly modifies the hopping strength. Focusing on half filling, in addition to the charge and spin density wave phases, large regions of ferromagnetic phase and phase separation are discovered in the weakly interacting regime. The mechanism of this ferromagnetism is attributed to the correlated hopping because the hopping strength within a ferromagnetic domain is normalized to a larger value than the hopping strength across the domain. Thus, the kinetic energy favors a large ferromagnetic domain and consequently drives the system into a ferromagnetic phase. We note that this is a different mechanism in contrast to the well-known Stoner mechanism for ferromagnetism where the ferromagnetism is driven by interaction energy.

cond-mat.quant-gas↗

arXiv2018

Three-Body Problem of Bosons nearby a d-wave Resonance

Motivated by recent experimental progresses, we investigate few-body properties of interacting spinless bosons nearby a d-wave resonance. Using the Skorniakov-Ter-Martirosion (STM) equations, we calculate the scattering length between an atom and a d-wave dimer, and we find that the atom-dimer scattering length is positive and is much smaller the result from the mean-field approximation. We also reveal unique properties of the three-body recombination rate for a degenerate Bose condensate nearby the d-wave resonance. We find that the total recombination rate is nearly a constant at the quasi-bound side, in contrast to the behavior of a thermal gas nearby high-partial wave resonance. We also find that the recombination rate monotonically increases across the unitary point toward the bound side, which is due to the largely enhanced coupling between the atom and the d-wave dimer with deeper binding energy. This monotonic behavior is also qualitatively different from that of a degenerate gas nearby an s-wave resonance counterpart.

cond-mat.quant-gas↗

arXiv2018

Hall Conductance of a Non-Hermitian Chern Insulator

In this letter we study the Hall conductance for a non-Hermitian Chern insulator and quantitatively describe how the Hall conductance deviates from a quantized value. We show the effects of the non-Hermitian terms on the Hall conductance are two folds. On one hand, it broadens the density-of-state of each band, because of which there always exists a non-universal bulk contribution. On the other hand, it adds decay term to the edge state, because of which the topological contribution also deviates from the quantized Chern number. We provides a simple formula for the topological contribution for a general two-band non-Hermitian Chern insulator, as a non-Hermitian version of the Thouless-Kohmoto-Nightingale-de Nijs formula. It shows that the derivation from quantized value increases either when the strength of the non-Hermitian term increases, or when the momentum dependence of the non-Hermitian term increases. Our results can be directly verified in synthetic non-Hermitian topological systems where the strength of the non-Hermitian terms can be controlled.

cond-mat.mes-hall↗

arXiv2018

Deep Learning Topological Invariants of Band Insulators

In this work we design and train deep neural networks to predict topological invariants for one-dimensional four-band insulators in AIII class whose topological invariant is the winding number, and two-dimensional two-band insulators in A class whose topological invariant is the Chern number. Given Hamiltonians in the momentum space as the input, neural networks can predict topological invariants for both classes with accuracy close to or higher than 90%, even for Hamiltonians whose invariants are beyond the training data set. Despite the complexity of the neural network, we find that the output of certain intermediate hidden layers resembles either the winding angle for models in AIII class or the solid angle (Berry curvature) for models in A class, indicating that neural networks essentially capture the mathematical formula of topological invariants. Our work demonstrates the ability of neural networks to predict topological invariants for complicated models with local Hamiltonians as the only input, and offers an example that even a deep neural network is understandable.

cond-mat.str-el↗

arXiv2018

Visualizing Neural Network Developing Perturbation Theory

In this letter, motivated by the question that whether the empirical fitting of data by neural network can yield the same structure of physical laws, we apply the neural network to a simple quantum mechanical two-body scattering problem with short-range potentials, which by itself also plays an important role in many branches of physics. We train a neural network to accurately predict $ s $-wave scattering length, which governs the low-energy scattering physics, directly from the scattering potential without solving Schrödinger equation or obtaining the wavefunction. After analyzing the neural network, it is shown that the neural network develops perturbation theory order by order when the potential increases. This provides an important benchmark to the machine-assisted physics research or even automated machine learning physics laws.

physics.comp-ph↗

arXiv2018

Topological Sachdev-Ye-Kitaev Model

In this letter we construct a large-N exactly solvable model to study the interplay between interaction and topology, by connecting Sacheve-Ye-Kitaev (SYK) model with constant hopping. The hopping forms a band structure that can exhibit both topological trivial and nontrivial phases. Starting from a topologically trivial insulator with zero Hall conductance, we show that interaction can drive a phase transition to topological nontrivial insulator with quantized non-zero Hall conductance, and a single gapless Dirac fermion emerges when the interaction is fine tuned to the critical point. The finite temperature effect is also considered and we show that the topological phase with stronger interaction is less stable against temperature. Our model provides a concrete example to illustrate interacting topological phases and phase transition, and can shed light on similar problems in physical systems.

cond-mat.str-el↗

arXiv2018

Machine Learning of Frustrated Classical Spin Models. II. Kernel Principal Component Analysis

In this work we apply the principal component analysis (PCA) method with kernel trick to study classification of phases and phase transition in classical XY models in frustrated lattices. Comparing to our previous work with linear PCA method, the kernel PCA can capture non-linear function. In this case, the Z2 chiral order of classical spins in these lattices are indeed a non-linear function of the input spin configurations. In addition to the principal component revealed by linear PCA, the kernel PCA can find out two more principal components using data generated by Monte Carlo simulation at various temperatures at input. One of them relates to the strength of the U(1) order parameter and the other directly manifests the chiral order parameter that characterizes the Z2 symmetry breaking. For a temperature resolved study, the temperature dependence of the principal eigenvalue associated with the Z2 symmetry breaking clearly shows a second order phase transition behavior.

cond-mat.stat-mech↗

arXiv2018

Machine Learning Topological Invariants with Neural Networks

In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.

cond-mat.mes-hall↗