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Lu-Ming Duan

Publications and source records attributed to Lu-Ming Duan.

At least 19 recordsLinked to original sources
arXiv2026

Machine learning the arrow of time in solid-state spins

Understanding the emergence of the thermodynamic arrow of time in microscopic systems is of fundamental importance, particularly given that unitary evolution preserves time-reversal symmetry. While projective measurements introduce temporal irreversibility, identifying this asymmetry from single evolution trajectories in the presence of stochastic fluctuations presents a considerable challenge. Here, we harness machine learning to identify the arrow of time from individual trajectories generated by a programmable ten-qubit quantum processor based on a nitrogen-vacancy center in diamond. We implement quantum circuits that realize unitary evolutions where heat flows from hotter to colder subsystems and their time-reversed counterparts. Projective measurements inserted in these processes induce entropy production, and their outcomes constitute the evolution trajectory. We demonstrate that an unsupervised clustering algorithm autonomously divides the experimental trajectories into two distinct groups without prior knowledge, while a convolutional neural network identifies the temporal direction of these trajectories with approximately 92% accuracy. In addition, we show that a diffusion-based generative model reproduces essential signatures of directional energy flow and entropy production. Our results establish machine learning as a powerful tool for uncovering underlying physical processes from complex experimental data, advancing the interface between quantum thermodynamics and artificial intelligence.

quant-ph↗
arXiv2025

Dynamical freezing and enhanced magnetometry in an interacting spin ensemble

Understanding and controlling non-equilibrium dynamics in quantum many-body systems is a fundamental challenge in modern physics, with profound implications for advancing quantum technologies. Typically, periodically driven systems in the absence of conservation laws thermalize to a featureless "infinite-temperature" state, erasing all memory of their initial conditions. However, this paradigm can break down through mechanisms such as integrability, many-body localization, quantum many-body scars, and Hilbert space fragmentation. Here, we report the experimental observation of dynamical freezing, a distinct mechanism of thermalization breakdown in driven systems, and demonstrate its application in quantum sensing using an ensemble of approximately $10^4$ interacting nitrogen-vacancy spins in diamond. By precisely controlling the driving frequency and detuning, we observe emergent long-lived spin magnetization and coherent oscillatory micromotions, persisting over timescales exceeding the interaction-limited coherence time ($T_2$) by more than an order of magnitude. Leveraging these unconventional dynamics, we develop a dynamical-freezing-enhanced ac magnetometry that extends optimal sensing times far beyond $T_2$, outperforming conventional dynamical decoupling magnetometry with a 4.3 dB sensitivity enhancement. Our results not only provide clear experimental observation of dynamical freezing -- a peculiar mechanism defying thermalization through emergent conservation laws -- but also establish a robust control method generally applicable to diverse physical platforms, with broad implications in quantum metrology and beyond.

quant-ph↗
arXiv2024

Hybrid entanglement and error correction in a scalable quantum network node

Recent breakthroughs have ushered the quantum network into a new era, where quantum information can be stored, transferred, and processed across multiple nodes on a metropolitan scale. A key challenge in this new era is enhancing the capabilities of individual nodes, providing precise and robust control over multiple qubits and advanced functionality for scalable quantum networks. Here, we report on precise and complex control in a hybrid quantum node based on a diamond color center. We demonstrate hybrid coherent control by entangling three types of qubits: an electron spin as an interface qubit, a nuclear spin with long memory time, and a flying photonic qubit, with their qubit frequencies spanning three distinct regimes from the optical domain to the rf domain. By incorporating two additional memory qubits, we encode three memory qubits into a logical state using the three-qubit repetition code and entangle this logical qubit with a photonic qubit. Leveraging hybrid qubits and precise control, we repeatedly read out the error syndromes of memory qubits through the electron spin, serving as an auxiliary qubit, then apply a real-time feedback operation to correct bit-flip errors. We execute and verify active error correction for up to twelve rounds and demonstrate the improvement over the uncorrected counterpart. Our results demonstrate the feasibility of several key functionalities for next-generation quantum repeaters, paving the way towards full-fledged metropolitan-scale quantum networks for a wide range of practical applications.

quant-ph↗
arXiv2022

Quantum-Memory-Enhanced Preparation of Nonlocal Graph States

Graph states are an important class of multipartite entangled states. Previous experimental generation of graph states and in particular the Greenberger-Horne-Zeilinger (GHZ) states in linear optics quantum information schemes is subjected to an exponential decay in efficiency versus the system size, which limits its large-scale applications in quantum networks. Here we demonstrate an efficient scheme to prepare graph states with only a polynomial overhead using long-lived atomic quantum memories. We generate atom-photon entangled states in two atomic ensembles asynchronously, retrieve the stored atomic excitations only when both sides succeed, and further project them into a four-photon GHZ state. We measure the fidelity of this GHZ state and further demonstrate its applications in the violation of Bell-type inequalities and in quantum cryptography. Our work demonstrates the prospect of efficient generation of multipartite entangled states in large-scale distributed systems with applications in quantum information processing and metrology.

quant-ph↗
arXiv2019

Quantum Adversarial Machine Learning

Adversarial machine learning is an emerging field that focuses on studying vulnerabilities of machine learning approaches in adversarial settings and developing techniques accordingly to make learning robust to adversarial manipulations. It plays a vital role in various machine learning applications and has attracted tremendous attention across different communities recently. In this paper, we explore different adversarial scenarios in the context of quantum machine learning. We find that, similar to traditional classifiers based on classical neural networks, quantum learning systems are likewise vulnerable to crafted adversarial examples, independent of whether the input data is classical or quantum. In particular, we find that a quantum classifier that achieves nearly the state-of-the-art accuracy can be conclusively deceived by adversarial examples obtained via adding imperceptible perturbations to the original legitimate samples. This is explicitly demonstrated with quantum adversarial learning in different scenarios, including classifying real-life images (e.g., handwritten digit images in the dataset MNIST), learning phases of matter (such as, ferromagnetic/paramagnetic orders and symmetry protected topological phases), and classifying quantum data. Furthermore, we show that based on the information of the adversarial examples at hand, practical defense strategies can be designed to fight against a number of different attacks. Our results uncover the notable vulnerability of quantum machine learning systems to adversarial perturbations, which not only reveals a novel perspective in bridging machine learning and quantum physics in theory but also provides valuable guidance for practical applications of quantum classifiers based on both near-term and future quantum technologies.

quant-ph↗
arXiv2019

Machine Learning Topological Phases with a Solid-state Quantum Simulator

We report an experimental demonstration of a machine learning approach to identify exotic topological phases, with a focus on the three-dimensional chiral topological insulators. We show that the convolutional neural networks---a class of deep feed-forward artificial neural networks with widespread applications in machine learning---can be trained to successfully identify different topological phases protected by chiral symmetry from experimental raw data generated with a solid-state quantum simulator. Our results explicitly showcase the exceptional power of machine learning in the experimental detection of topological phases, which paves a way to study rich topological phenomena with the machine learning toolbox.

cond-mat.dis-nn↗
arXiv2017

Quantum Supremacy for Simulating A Translation-Invariant Ising Spin Model

We introduce an intermediate quantum computing model built from translation-invariant Ising-interacting spins. Despite being non-universal, the model cannot be classically efficiently simulated unless the polynomial hierarchy collapses. Equipped with the intrinsic single-instance-hardness property, a single fixed unitary evolution in our model is sufficient to produce classically intractable results, compared to several other models that rely on implementation of an ensemble of different unitaries (instances). We propose a feasible experimental scheme to implement our Hamiltonian model using cold atoms trapped in a square optical lattice. We formulate a procedure to certify the correct functioning of this quantum machine. The certification requires only a polynomial number of local measurements assuming measurement imperfections are sufficiently small.

quant-ph↗
arXiv2017

Efficient Representation of Quantum Many-body States with Deep Neural Networks

The challenge of quantum many-body problems comes from the difficulty to represent large-scale quantum states, which in general requires an exponentially large number of parameters. Recently, a connection has been made between quantum many-body states and the neural network representation (\textit{arXiv:1606.02318}). An important open question is what characterizes the representational power of deep and shallow neural networks, which is of fundamental interest due to popularity of the deep learning methods. Here, we give a rigorous proof that a deep neural network can efficiently represent most physical states, including those generated by any polynomial size quantum circuits or ground states of many body Hamiltonians with polynomial-size gaps, while a shallow network through a restricted Boltzmann machine cannot efficiently represent those states unless the polynomial hierarchy in computational complexity theory collapses.

cond-mat.dis-nn↗
arXiv2016

Experimental Preparation of High NOON States for Phonons

Multi-party entangled states have important applications in quantum metrology and quantum computation. Experimental preparation of large entangled state, in particular, the NOON states, however, remains challenging as the particle number $N$ increases. Here we develop a deterministic method to generate arbitrarily high NOON states for phonons and experimentally create the states up to $N=9$ phonons in two radial modes of a single trapped \Yb ion. We demonstrate that the fidelity of the NOON states are significantly above the classical limit by measuring the interference contrast and the population through the projective phonon measurement of two motional modes. We also measure the quantum Fisher information of the generated NOON state and observe the Heisenberg scaling in the lower bounds of the phase sensitivity as the $N$ increases. Our scheme is generic and applicable to other photonic or phononic systems.

quant-ph↗
arXiv2016

Experimental Test of Entangled Histories

We propose and demonstrate experimentally a scheme to create entangled history states of the Greenberger-Horne-Zeilinger (GHZ) type. In our experiment, the polarization states of a single photon at three different times are prepared as a GHZ entangled history state. We define a GHZ functional which attains a maximum value $1$ on the ideal GHZ entangled history state and is bounded above by $1/16$ for any three-time history state lacking tripartite entanglement. We have measured the GHZ functional on a state we have prepared experimentally, yielding a value of $0.656\pm 0.005$, clearly demonstrating the contribution of entangled histories.

quant-ph↗
arXiv2016

Certification of Boson Sampling Devices with Coarse-Grained Measurements

A boson sampling device could efficiently sample from the output probability distribution of noninteracting bosons undergoing many-body interference. This problem is not only classically intractable, but its solution is also believed to be classically unverifiable. Hence, a major difficulty in experiment is to ensure a boson sampling device performs correctly. We present an experimental friendly scheme to extract useful and robust information from the quantum boson samplers based on coarse-grained measurements. The procedure can be applied to certify the equivalence of boson sampling devices while ruling out alternative fraudulent devices. We perform numerical simulations to demonstrate the feasibility of the method and consider the effects of realistic noise. Our approach is expected to be generally applicable to other many-body certification tasks beyond the boson sampling problem.

quant-ph↗
arXiv2015

Hamiltonian tomography for quantum many-body systems with arbitrary couplings

Characterization of qubit couplings in many-body quantum systems is essential for benchmarking quantum computation and simulation. We propose a tomographic measurement scheme to determine all the coupling terms in a general many-body Hamiltonian with arbitrary long-range interactions, provided the energy density of the Hamiltonian remains finite. Different from quantum process tomography, our scheme is fully scalable with the number of qubits as the required rounds of measurements increase only linearly with the number of coupling terms in the Hamiltonian. The scheme makes use of synchronized dynamical decoupling pulses to simplify the many-body dynamics so that the unknown parameters in the Hamiltonian can be retrieved one by one. We simulate the performance of the scheme under the influence of various pulse errors and show that it is robust to typical noise and experimental imperfections.

quant-ph↗
arXiv2015

Quantum Computation under Micromotion in a Planar Ion Crystal

We propose a scheme to realize scalable quantum computation in a planar ion crystal confined by a Paul trap. We show that the inevitable in-plane micromotion affects the gate design via three separate effects: renormalization of the equilibrium positions, coupling to the transverse motional modes, and amplitude modulation in the addressing beam. We demonstrate that all of these effects can be taken into account and high-fidelity gates are possible in the presence of micromotion. This proposal opens the prospect to realize large-scale fault-tolerant quantum computation within a single Paul trap.

quant-ph↗
arXiv2015

Quantized electromagnetic response of three-dimensional chiral topological insulators

Protected by the chiral symmetry, three dimensional chiral topological insulators are characterized by an integer-valued topological invariant. How this invariant could emerge in physical observables is an important question. Here we show that the magneto-electric polarization can identify the integer-valued invariant if we gap the system without coating a quantum Hall layer on the surface. The quantized response is demonstrated to be robust against weak perturbations. We also study the topological properties by adiabatically coupling two nontrivial phases, and find that gapless states appear and are localized at the boundary region. Finally, an experimental scheme is proposed to realize the Hamiltonian and measure the quantized response with ultracold atoms in optical lattices.

cond-mat.mes-hall↗
arXiv2014

Direct Probe of Topological Order for Cold Atoms

Cold-atom experiments in optical lattices offer a versatile platform to realize various topological quantum phases. A key challenge in those experiments is to unambiguously probe the topological order. We propose a method to directly measure the characteristic topological invariants (order) based on the time-of-flight imaging of cold atoms. The method is generally applicable to detection of topological band insulators in one, two, or three dimensions characterized by integer topological invariants. Using detection of the Chern number for the 2D anomalous quantum Hall states and the Chern-Simons term for the 3D chiral topological insulators as examples, we show that the proposed detection method is practical, robust to typical experimental imperfections such as limited imaging resolution, inhomogeneous trapping potential, and disorder in the system.

cond-mat.quant-gas↗
arXiv2014

An experimental proposal to observe non-abelian statistics of Majorana-Shockley fermions in an optical lattice

We propose an experimental scheme to observe non-abelian statistics with cold atoms in a two dimensional optical lattice. We show that the Majorana-Schockley modes associated with line defects obey non-abelian statistics and can be created, braided, and fused, all through adiabatic shift of the local chemical potentials. The detection of the topological qubit is transformed to local measurement of the atom number on a single lattice site. We demonstrate the robustness of the braiding operation by incorporating noise and experiential imperfections in numerical simulations, and show that the requirement fits well with the current experimental technology.

quant-ph↗
arXiv2014

Probe of Three-Dimensional Chiral Topological Insulators in an Optical Lattice

We propose a feasible experimental scheme to realize a three-dimensional chiral topological insulator with cold fermionic atoms in an optical lattice, which is characterized by an integer topological invariant distinct from the conventional $Z_2$ topological insulators and has a remarkable macroscopic zero-energy flat band. To probe its property, we show that its characteristic surface states---the Dirac cones---can be probed through time-of-flight imaging or Bragg spectroscopy and the flat band can be detected via measurement of the atomic density profile in a weak global trap. The realization of this novel topological phase with a flat band in an optical lattice will provide a unique experimental platform to study the interplay between interaction and topology and open new avenues for application of topological states.

cond-mat.str-el↗