arXiv subjects

D. L. Zhou

Publications and source records attributed to D. L. Zhou.

At least 19 recordsLinked to original sources

arXiv2026

Quantum-geometry stabilization of dilute fractional Chern insulators

Fractional Chern insulators have attracted broad interest as lattice analogs of fractional quantum Hall states without Landau levels. However, low-filling fractional Chern insulators are fragile because charge-ordered phases can compete strongly with the fractional topological liquid. Here, we propose a center-decorated kagome model, motivated by geometry-tunable artificial lattices, in which the center-site hopping $t_2$ provides a direct knob for the quantum geometry of an isolated $C=1$ flat band. Here quantum geometry refers to the Berry curvature and Fubini--Study metric, which determine the form factors of interactions projected into the Chern band. Exact diagonalization shows that tuning $t_2$ away from the flatness-optimized kagome limit reduces the trace-condition deviation, suppresses competing charge order, and enhances the many-body stability at both $ν=1/3$ and the more fragile $ν=1/5$ filling. At $ν=1/5$, this stability-enhanced window persists under nearby interaction profiles, including variations of the dominant third-neighbor repulsion and weak nearest-neighbor admixtures. Low-energy spectra, spectral flow, quasihole and entanglement counting, static structure factors, and the quantized total many-body Chern number $C_{\mathrm{tot}}=1$ consistently support Laughlin-like fractional Chern insulators. These results identify quantum-geometry engineering as a route to stabilizing dilute fractional Chern insulators beyond band-flatness optimization alone.

cond-mat.str-el↗

arXiv2026

Quantum Topological Analysis on Digraphs

Quantum algorithms for topological data analysis provide significant advantages over the best known classical algorithms. Unlike previous work on simplicial complexes built from point clouds, path homology on digraphs is defined for directed graphs and provides a natural topological framework for analyzing data with intrinsic directional structures. Path homology has become an emerging area in Topological Data Analysis (TDA), attracting increasing attention in recent years. We propose a quantum algorithm for path homology on digraphs that offers a significant advantage over the best known classical algorithms. We design a universal encoding protocol for the paths and boundary operators of digraphs on quantum systems. We prove a property of path homology that provides the theoretical guarantee for the algorithm. The speedup of the quantum algorithm for path homology depends on input-access assumptions. The exponential speedup arises when the path space can be efficiently accessed, while for standard digraph input the algorithm provides polynomial speedup.

quant-ph↗

arXiv2026

Generating photons from vacuum with counter rotating wave interaction

We propose a bang-bang control scheme to enhance photon generation from the vacuum via the counter-rotating wave (CRW) interaction, and develop a pruning greedy algorithm (PGA) to identify the optimal control sequence. Our numerical results demonstrate that the maximum number of photons generated within a given evolution time is increased by several orders of magnitude compared with that achieved by continuous activation of the CRW interaction.

quant-ph↗

arXiv2026

Tangent Space Excitation Ansatz for Quantum Circuits

Computing excitation spectra of quantum many-body systems is a promising avenue to demonstrate the practical utility of current noisy quantum devices, especially as we move toward the ``megaquop'' regime. For this task, here we introduce a \textit{tangent space excitation ansatz} for quantum circuits, motivated by the quasi-particle picture of many-body systems and the structural similarity between quantum circuits and tensor networks. Increasing circuit depth by one layer to construct tangent space around the variational optimum of a parametrized quantum circuit, we show that massive low-energy single-particle states can be captured. Our ansatz relies on a distinct mechanism from that of excitation ansatz in matrix product state and projected entangled-pair state, and avoids intrinsic limitations of the latter. Comparing our approach with existing quantum excited-state algorithms, we find that with similar computational cost, both the number of excited states and accuracy are significantly improved. We demonstrate our ansatz in both one and two dimensions, and further show that this approach, implementable using Hadamard test, is scalable and suitable for current quantum processors.

quant-ph↗

arXiv2026

Reliability Dynamics in a Two-Site Dissipative Quantum Spin Chain

As a key index for applications of a device, the device's reliability is its ability to survive (function normally over time) under the influence of some environment. In this paper we present a quantum energy-storing device model with a quantum spin chain, whose environment influence is described by the Lindblad master equation. Here the device survives if the spin system stays in the state with nonzero excitations; otherwise, it fails. Because the Lindblad dynamics enforces one-way energy decay and strict irreversibility of the failure state, we can investigate the reliability of the quantum device directly using classical reliability theory. Focusing on the minimal nontrivial case -- a two-site spin-1/2 chain -- we derive closed-form expressions for the reliability and the hazard rate. The dynamics exhibit an overdamped-underdamped crossover controlled by the competition between coherent exchange and dissipation inhomogeneity. The exact analytical formulas are in excellent agreement with numerical simulations. More importantly, we establish an experimentally accessible protocol for assessing reliability based on first-passage time statistics.

quant-ph↗

arXiv2025

Insufficiency of Pure-State Ensembles in Characterizing Transformations of Entangled States under LOCC

The conditions for transforming pure entangled states under local operations and classical communication (LOCC) are well understood. A natural question then arises: Can we determine the transformation conditions for mixed entangled states under LOCC based on the properties of their pure-state ensembles? While much effort has been devoted to this issue, in this paper, we rule out this possibility. Our findings address several open questions, including: (i) The conditions $ E_f^{cr}(ρ) \geq E_f^{cr}(σ) $ for all convex roof entanglement measures $E_f^{cr}$ is insufficient to guarantee the existence of an LOCC transformation $Λ^L(\cdot)$ from $ρ$ to $σ$; and (ii) The inequalities $\sum_j p_j E(φ_j) \geq \sum_l q_l E(ψ_l)$ for all entanglement monotones $E$ are not sufficient to ensure the existence of an LOCC transformation from $\{p_j, \ket{φ_j}\}$ to $\{q_l, \ket{ψ_l}\}$.

quant-ph↗

arXiv2025

Learning Symmetric Hamiltonian

Hamiltonian Learning is a process of recovering system Hamiltonian from measurements, which is a fundamental problem in quantum information processing. In this study, we investigate the problem of learning the symmetric Hamiltonian from its eigenstate. Inspired by the application of group theory in block diagonal secular determination, we have derived a method to determine the number of linearly independent equations about the Hamiltonian unknowns obtained from an eigenstate. This number corresponds to the degeneracy of the associated irreducible representation of the Hamiltonian symmetry group. To illustrate our approach, we examine the XXX Hamiltonian and the XXZ Hamiltonian. We first determine the Hamiltonian symmetry group, then work out the decomposition of irreducible representation, which serves as foundation for analyzing the uniqueness of recovered Hamiltonian. Our numerical findings consistently align with our theoretical analysis.

quant-ph↗

arXiv2025

Measuring Incompatible Observables with Quantum Neural Networks

The Heisenberg uncertainty principle imposes a fundamental restriction in quantum mechanics, stipulating that measuring one observable completely erases the information on its conjugate one, thereby preventing simultaneous measurements of incompatible observables. Quantum neural networks (QNNs) is one of the most significant applications on near-term devices in noisy intermediate-scale quantum era. Here, we demonstrate that by implementing a multiple-output QNN that emulates a unital quantum channel, one can measure the expectation values of many incompatible observables simultaneously by Pauli-$Z$ measurements on distinct output qubits. We prove the existence of such quantum channel, derive analytical scaling constraints of the measured expectation values, and validate this framework by numerical simulations of observables learning tasks. Notably, our analysis reveals that it requires fewer copies of state when measuring some incompatible observables by the multiple-output QNNs, which demonstrates a resource efficiency advantage compared to separately applying projective measurements.

quant-ph↗

arXiv2025

Searching Axion-like Dark Matter by Amplifying Weak Magnetic Field with Quantum Zeno effect

The enhancement of weak signals and the detection of hypothetical particles, facilitated by quantum amplification, are crucial for advancing fundamental physics and its practical applications. Recently, it was experimentally observed that magnetic field can be amplified by using nuclear spins under Markovian noise, [H. Su, et al., Phys. Rev. Lett. 133, 191801 (2024)]. Here, we theoretically propose amplifying the magnetic-field signal by using nuclear spins by the quantum Zeno effect (QZE). Under identical conditions, we demonstrate that compared to the Markovian case the amplification of the weak magnetic field can be enhanced by a factor about $e^{1/2}$ under a Gaussian noise. Moreover, through numerical simulations we determine the optimal experimental parameters for amplification conditions. This work shows that the combination of the QZE and spin amplification effectively enhances the amplification of the weak magnetic field. Our findings may provide valuable guidance for the design of experiments on establishing new constraints of dark matter and exotic interactions in the near future.

quant-ph↗

arXiv2024

Learning quantum phases via single-qubit disentanglement

Identifying phases of matter presents considerable challenges, particularly within the domain of quantum theory, where the complexity of ground states appears to increase exponentially with system size. Quantum many-body systems exhibit an array of complex entanglement structures spanning distinct phases. Although extensive research has explored the relationship between quantum phase transitions and quantum entanglement, establishing a direct, pragmatic connection between them remains a critical challenge. In this work, we present a novel and efficient quantum phase transition classifier, utilizing disentanglement with reinforcement learning-optimized variational quantum circuits. We demonstrate the effectiveness of this method on quantum phase transitions in the transverse field Ising model (TFIM) and the XXZ model. Moreover, we observe the algorithm's ability to learn the Kramers-Wannier duality pertaining to entanglement structures in the TFIM. Our approach not only identifies phase transitions based on the performance of the disentangling circuits but also exhibits impressive scalability, facilitating its application in larger and more complex quantum systems. This study sheds light on the characterization of quantum phases through the entanglement structures inherent in quantum many-body systems.

quant-ph↗

arXiv2024

Active Quantum Distillation

Quantum distillation is a modern technology to decrease the von Neumann entropy of a subsystem by coherent system dynamics. Here we propose an active quantum distillation protocol, in which a bang-bang theme is applied to actively control the coherent dynamics of our system in order to obtain a subsystem with the von Neumann entropy as low as possible. For a bipartite Bosonic system, we derive the analytical expression of lower bound of the entropy of subsystem under any unitary transformation with conservation of particles. The lower bound is validated by numerical simulations on the Bose-Hubbard model, where the coherent evolution is controlled by tuning one interaction term of the Hamiltonian. Our protocol can be used to decrease the entropy of one subsystem lower than the total bipartite state and increase the number of Bosons or only distill out very few Bosons in the subsystem.

quant-ph↗

arXiv2024

Optimized Quantum Autoencoder

Quantum autoencoder (QAE) compresses a bipartite quantum state into its subsystem by a self-checking mechanism. How to characterize the lost information in this process is essential to understand the compression mechanism of QAE\@. Here we investigate how to decrease the lost information in QAE for any input mixed state. We theoretically show that the lost information is the quantum mutual information between the remaining subsystem and the ignorant one, and the encoding unitary transformation is designed to minimize this mutual information. Further more, we show that the optimized unitary transformation can be decomposed as the product of a permutation unitary transformation and a disentanglement unitary transformation, and the permutation unitary transformation can be searched by a regular Young tableau algorithm. Finally we numerically identify that our compression scheme outperforms the quantum variational circuit based QAE\@.

quant-ph↗

arXiv2023

Recovery of a generic local Hamiltonian from a degenerate steady state

Hamiltonian Learning (HL) is essential for validating quantum systems in quantum computing. Not all Hamiltonians can be uniquely recovered from a steady state. HL success depends on the Hamiltonian model and steady state. Here, we analyze HL for a specific type of steady state composed of eigenstates with degenerate mixing weight, making these Hamiltonian's eigenstates indistinguishable. To overcome this challenge, we utilize the orthogonality relationship between the eigenstate space and its complement space, constructing the orthogonal space equation. By counting the number of linearly independent equations derived from a steady state, we determine the recoverability of a generic local Hamiltonian. Our scheme is applicable for generic local Hamiltonians under various steady state, therefore offering a way of measuring the degree to which a steady state characterizes a Hamiltonian.

quant-ph↗

arXiv2023

Disassociation of a one-dimensional cold molecule via quantum scattering

Motivated by the recent experimental developments on ultracold molecules and atoms, we propose a simplest theoretical model to address the disassociation, reflection and transmission probability of a 1-dimensional cold molecule via quantum scattering. First, we give the Born approximation results in the weak interaction regime. Then, employing the Lippmann-Schwinger equation, we give the numerical solution and investigate the disassociation's dependence on the injection momentum and the interaction strengths. We find that the maximum disassociation rate has a limit as increasing the interaction strengths and injection momentum. We expect that our model can be realized in experiments in the near future.

cond-mat.quant-gas↗

arXiv2023

Quantum mutual information redistribution by Number Partitioning algorithm

Quantum information distribution in a tripartite state plays a fundamental role in quantum information processes. Here we investigate how a bipartite unitary transformation $U_{AB}$ redistributes the quantum mutual information with the third party $C$ in a tripartite pure state $|ψ\rangle_{ABC}$ in a $d_A\times d_B\times d_C$ dimensional Hilbert space. In particular, we focus on finding out the optimal unitary transformation $U_{AB}^{\ast}$ that maximizes the quantum mutual entropy between party $A$ and party $C$, $I(A:C)=S(ρ_A)-S(ρ_B)+S(ρ_C)$. We show that the mutual entropy $I(A:C)$ is upper bounded by $2S(ρ_C)$ derived from the Araki-Lieb inequality. This upper bound can be realized via an optimal unitary transformation for any pure state with the rank $r_{C}$ of $ρ_C$ satisfying $r_C\le d_A$. For a generic pure state with $r_C> d_A$, the upper bound can not be realized by any bipartite unitary transformation. To maximize the mutual entropy in the latter case, we propose a fast numerical algorithm to produce an approximate optimal unitary transformation, where our optimization is transformed into a modified number partition problem. The validness of our algorithm is confirmed by its comparison with the results from the Adam algorithm for parameterized unitary transformations. Our approximate algorithm thus provides a practical protocol to implement redistribution of quantum mutual information for a tripartite quantum state with high dimensions.

quant-ph↗

arXiv2023

Topological correlation: anyonic states cannot be determined by local operations and classical communication

Anyonic system not only has potential applications in the construction of topological quantum computer, but also presents a unique property known as topological entanglement entropy in quantum many-body systems. How to understand topological entanglement entropy is one of the most concerned problems for physicists. For an anyonic bipartite system, we define an operational measure of topological correlation based on the principle of maximal entropy, where the topological correlation is the information that cannot be accessed by local operations constrained by anyonic superselection rules and classical communication. This measure can be extended to measure non-local resources of other compound quantum systems in the presence of superselection rules. For a given anyonic bipartite state with maximal rank, we prove that its topological correlation is equal to its entropy of anyonic charge entanglement that has been shown in the literature to be able to derive topological entanglement entropy. This measure provides a more refined classification of correlations in a multipartite system with superselection rules and an illuminating approach to topological phase classification.

quant-ph↗

arXiv2023

Preparing highly entangled states of nanodiamond rotation and NV center spin

A nanodiamond with an embedded nitrogen-vacancy (NV) center is one of the experimental systems that can be coherently manipulated within current technologies. Entanglement between NV center electron spin and mechanical rotation of the nanodiamond plays a fundamental role in building a quantum network connecting these microscopic and mesoscopic degrees of motions. Here we present a protocol to asymptotically prepare a highly entangled state of the total quantum angular momentum and electron spin by adiabatically boosting the external magnetic field.

quant-ph↗

arXiv2023

Unified Quantum State Tomography and Hamiltonian Learning Using Transformer Models: A Language-Translation-Like Approach for Quantum Systems

Schrödinger's equation serves as a fundamental component in characterizing quantum systems, wherein both quantum state tomography and Hamiltonian learning are instrumental in comprehending and interpreting quantum systems. While numerous techniques exist for carrying out state tomography and learning Hamiltonians individually, no method has been developed to combine these two aspects. In this study, we introduce a new approach that employs the attention mechanism in transformer models to effectively merge quantum state tomography and Hamiltonian learning. By carefully choosing and preparing the training data, our method integrates both tasks without altering the model's architecture, allowing the model to effectively learn the intricate relationships between quantum states and Hamiltonian. We also demonstrate the effectiveness of our approach across various quantum systems, ranging from simple 2-qubit cases to more involved 2D antiferromagnetic Heisenberg structures. The data collection process is streamlined, as it only necessitates a one-way generation process beginning with state tomography. Furthermore, the scalability and few-shot learning capabilities of our method could potentially minimize the resources required for characterizing and optimizing quantum systems. Our research provides valuable insights into the relationship between Hamiltonian structure and quantum system behavior, fostering opportunities for additional studies on quantum systems and the advancement of quantum computation and associated technologies.

quant-ph↗