arXiv subjects

Yu-Xin Wang

Publications and source records attributed to Yu-Xin Wang.

At least 37 records · Page 2Linked to original sources

arXiv2026

An Approach to Probing Particles and Quasi-particles in the Condensed Bose-Hubbard Model

Measurement plays a crucial role in a quantum system beyond just learning about the system state: it changes the post-measurement state and hence influences the subsequent time evolution; further, measurement can even create entanglement in the post-measurement conditional state. In this work, we study how careful choice of parameters for a typical measurement process on cold atoms systems -- phase contrast imaging -- has a strong impact on both what the experimentalist observes but also on the backaction the measurement has on the system, including the creation and diffusion of quasiparticles emerging from the quantum many-body dynamics. We focus on the case of a Bose-Einstein-condensate array, in the low-temperature and low-momentum limit. Our theoretical investigation reveals regimes where the imaging light probes either the bare particle or quasiparticle dynamics. Moreover, we find a path to selectively measuring quasiparticle modes directly, as well as controlling over the measurement-induced creation and diffusion of quasiparticles into different momentum states. This lays a foundation for understanding the effects of both experimental approaches for probing many-body systems, but also more speculative directions such as observable consequences of `spontaneous collapse' predictions from novel models of quantum gravity on aspects of the Standard Model.

cond-mat.quant-gas↗

arXiv2026

Entanglement advantage in sensing power-law spatiotemporal noise correlations

Noise sensing underlies many physical applications including tests of non-classicality, thermometry, verification of correlated phases of quantum matter, and characterization of criticality. While previous works have shown that quantum resources such as entanglement and squeezing can enhance the sensitivity in estimating deterministic signals, less is known about the entanglement advantage in sensing correlated stochastic signals (noise). In this work, we compute the fundamental sensitivity limits of quantum sensors in probing spatiotemporally correlated noise. We first prove the fundamental quantum limits in sensing spatially correlated Markovian noise using entangled and unentangled sensors, respectively. Focusing on power-law spatial noise correlations, which naturally arise in condensed matter systems with long-range interactions and/or near criticality, we further derive a scalable entanglement advantage when the power-law decays slowly. Then, considering a target signal with a $1/f^{p}$-type spectrum, we demonstrate that non-Markovianity may entirely modify the nature of entanglement advantage in estimating spatial noise correlations. Our protocols can be implemented using state-of-the-art quantum sensing platforms including solid-state defects, superconducting circuits, and neutral atoms.

quant-ph↗

arXiv2026

Assessing the robustness of amortized simulation-based inference to transient noise in gravitational-wave ringdowns

Gravitational waves (GW) emitted by binary systems allow us to perform precision tests of general relativity in the strong field regime. Ringdown signals allow for probing black hole mass and spin with high precision in GW astronomy. With improvements in current and next-generation GW detectors, developing likelihood-free parameter inference methods is crucial. This is especially important when facing challenges such as non-standard noise, partial data, or incomplete signal models that prevent the use of analytical likelihood functions. In this work, we propose an amortized simulation-based inference strategy to estimate ringdown parameters directly. Specifically, our method is based on amortized neural posterior estimation, which trains a neural density estimator of the posterior for all data segments within the prior range. The results show that our trained amortized network achieves statistically consistent parameter estimates with valid confidence coverage compared to established Markov-chain methods, while offering inference speeds that are orders of magnitude faster. Furthermore, we evaluate the robustness of the method against transient noise contamination. Our analysis reveals that the timing of glitch injection has a decisive impact on estimation bias, particularly during the tail of a signal with sparse information. Glitch strength is positively correlated with estimation error, but has limited effect at low signal-to-noise ratios. Mass and spin parameters are most sensitive to noise. This study not only provides an efficient and accurate inference framework for ringdown analysis but also lays a foundation for developing robust data-processing pipelines for future GW astronomy in realistic noise environments.

gr-qc↗

arXiv2026

In-situ Characterization of Light-Matter Coupling in Multimode Circuit-QED Systems

Multimode cavity-QED systems can be leveraged to explore a wide range of physical phenomena; however, a complex multimode environment makes systematic characterization of light-matter interactions challenging. Here we present a general measurement protocol, applicable to both atomic and synthetic cavity-QED systems, that enables the determination of coupling to individual photonic modes. The method leverages measurements of the AC-Stark and Kerr effects, along with known detuning dependencies, to eliminate the need for single-photon resolution, independent photon-number calibration, or insertion-loss calibration. We demonstrate the method using a superconducting transmon qubit coupled to a one-dimensional microwave resonator lattice. We validate the consistency of the extracted light-matter couplings $g$ determined at multiple qubit detunings, and from the self-Kerr and cross-Kerr shifts for three photon modes, which provide separate measurements of $g$ for each of the three modes.

quant-ph↗

arXiv2026

Correlated Noise Estimation with Quantum Sensor Networks

We address the metrological problem of estimating collective stochastic properties imprinted on a network of quantum sensors. Canonical examples include center-of-mass quadrature fluctuations in a system of bosonic modes and correlated dephasing in an ensemble of qubits (e.g., spins), bosons, or fermions. We develop a theoretical framework to determine the limits of correlated (weak) noise estimation with quantum sensor networks and reveal the requirements for entanglement advantage. Notably, an advantage emerges from the synergistic interplay between quantum correlations of the sensors and ``classical'' correlations of the noises. We determine optimal entangled probe states and identify a sensing protocol -- reminiscent of a many-body echo -- that achieves the fundamental limits of measurement sensitivity for a broad class of problems, unveiling a route towards entanglement-enhanced metrology of correlated many-body phenomena.

quant-ph↗

arXiv2026

Quantum metrology enhanced by effective time reversal

Quantum metrology involves the application of quantum resources to enhance measurements. Several communities have developed quantum-metrology strategies that leverage effective time reversals. These strategies, we posit, form four classes. First, echo metrology begins with a preparatory unitary and ends with that unitary's time-reverse. The protocol amplifies the visibility of a small parameter to be sensed. Similarly, weak-value amplification enhances a weak coupling's detectability. The technique exhibits counterintuitive properties captured by a retrocausal model. Using the third strategy, one simulates closed timelike curves, worldlines that loop back on themselves in time. The fourth strategy involves indefinite causal order, which characterises channels applied in a superposition of orderings. We review these four strategies, which we unify under the heading of time-reverse metrology. We also outline opportunities for this toolkit in quantum metrology; quantum information science; quantum foundations; atomic, molecular, and optical physics; and solid-state physics.

quant-ph↗

arXiv2026

A Surface-Scaffolded Molecular Qubit

Fluorescent spin qubits are central building blocks of quantum technologies. Placing these qubits at surfaces maximizes coupling to nearby spins and fields, enabling nanoscale sensing and facilitating integration with photonic and superconducting devices. However, reducing the dimensions or size of established qubit systems without sacrificing the qubit performance or degrading the coherence lifetime remains challenging. Here, we introduce a surface molecular qubit formed by pentacene molecules scaffolded on a two-dimensional (2D) material, hexagonal boron nitride (hBN). The qubit exhibits stable fluorescence and optically detected magnetic resonance (ODMR) from cryogenic to ambient conditions. With fully deuterated pentacene, the Hahn-echo coherence reaches 22 $μ$s and further extends to 214 $μ$s under dynamical decoupling, outperforming state-of-the-art shallow NV centers in diamond, despite being positioned directly on the surface. We map the local spin environment, resolving couplings to nearby nuclear and electron spins that can serve as auxiliary quantum resources. This platform combines true surface integration, long qubit coherence, and scalable fabrication, opening routes to quantum sensing, quantum simulation, and hybrid quantum devices. It also paves the way for a broader family of 2D material-supported molecular qubits.

quant-ph↗

arXiv2025

Instability of steady-state mixed-state symmetry-protected topological order to strong-to-weak spontaneous symmetry breaking

Recent experimental progress in controlling open quantum systems enables the pursuit of mixed-state nonequilibrium quantum phases. We investigate whether open quantum systems hosting mixed-state symmetry-protected topological states as steady states retain this property under symmetric perturbations. Focusing on the decohered cluster state -- a mixed-state symmetry-protected topological state protected by a combined strong and weak symmetry -- we construct a parent Lindbladian that hosts it as a steady state. This Lindbladian can be mapped onto exactly solvable reaction-diffusion dynamics, even in the presence of certain perturbations, allowing us to solve the parent Lindbladian in detail and reveal previously-unknown steady states. Using both analytical and numerical methods, we find that typical symmetric perturbations cause strong-to-weak spontaneous symmetry breaking at arbitrarily small perturbations, destabilize the steady-state mixed-state symmetry-protected topological order. However, when perturbations introduce only weak symmetry defects, the steady-state mixed-state symmetry-protected topological order remains stable. Additionally, we construct a quantum channel which replicates the essential physics of the Lindbladian and can be efficiently simulated using only Clifford gates, Pauli measurements, and feedback.

quant-ph↗

arXiv2025

Optimally learning functions in interacting quantum sensor networks

Estimating extensive combinations of local parameters in distributed quantum systems is a central problem in quantum sensing, with applications ranging from magnetometry to timekeeping. While optimal strategies are known for sensing non-interacting Hamiltonians in quantum sensor networks, fundamental limits in the presence of uncontrolled interactions remain unclear. Here, we establish optimal bounds and protocols for estimating a linear combination of local parameters of Hamiltonians with arbitrary, unknown interactions. In the process, we more generally establish bounds for learning any linear combination of Hamiltonian coefficients for arbitrary, commuting terms. Our results unify and extend existing bounds for non-interacting qubits and multimode interferometers, providing a general framework for distributed sensing and Hamiltonian learning in realistic many-body systems.

quant-ph↗

arXiv2025

Search for exotic gravitational wave signals beyond general relativity using deep learning

The direct detection of gravitational waves by LIGO has confirmed general relativity (GR) and sparked rapid growth in gravitational wave (GW) astronomy. However, subtle post-Newtonian (PN) deviations observed during the analysis of high signal-to-noise ratio events from the observational runs suggest that standard waveform templates, which assume strict adherence to GR, might overlook signals from alternative theories of gravity. Incorporating these exotic signals into traditional search algorithms is computationally infeasible due to the vast template space required. This paper introduces a proof-of-principle deep learning framework for detecting exotic GW signals, leveraging neural networks trained on GR-based templates. Through their generalization ability, neural networks learn intricate features from the data, enabling the detection of signals that deviate from GR. We present the first study evaluating the capability of deep learning to detect beyond-GR signals, including a variety of PN orders. Our model achieves rapid and accurate identification of exotic GW signals across different luminosity distances, with performance comparable to GR-based detections. In particular, applying the model to the GW150914 event demonstrates excellent performance, highlighting the potential of AI-driven methods for detecting previously overlooked signals beyond GR. This work paves the way for new discoveries in gravitational wave astronomy, enabling the detection of signals that might escape traditional search pipelines.

gr-qc↗

arXiv2025

Error mitigation of shot-to-shot fluctuations in analog quantum simulators

Analog quantum simulators have provided key insights into quantum many-body dynamics. However, in such systems, both coherent and incoherent errors limit their scalability, hindering simulations in regimes that challenge classical simulations. In this work, we introduce an error mitigation technique that addresses and effectively suppresses a key source of error in leading simulator platforms: shot-to-shot fluctuations in the parameters for the Hamiltonian governing the system dynamics. We rigorously prove that amplifying this shot-to-shot noise and extrapolating to the zero-noise limit recovers noiseless results for realistic noise distributions. Experimentally, we demonstrate this technique on a 27-ion trapped-ion quantum simulator, extending the two-qubit exchange oscillation lifetime threefold. Numerically, we predict a significant enhancement in the effective many-body coherence time for Rydberg atom arrays under realistic conditions. Our scheme provides a possible route towards extending the effective coherence time in analog quantum experiments, enabling deeper explorations of quantum many-body dynamics.

quant-ph↗

arXiv2025

Average Rényi Entanglement Entropy in Gaussian Boson Sampling

Recently, many experiments have been conducted with the goal of demonstrating a quantum advantage over classical computation. One popular framework for these experiments is Gaussian Boson Sampling, where quadratic photonic input states are interfered via a linear optical unitary and subsequently measured in the Fock basis. In this work, we study the modal entanglement of the output states in this framework just before the measurement stage. Specifically, we compute Page curves as measured by various Rényi-$α$ entropies, where the Page curve describes the entanglement between two partitioned groups of output modes averaged over all linear optical unitaries. We derive these formulas for $α= 1$ (i.e. the von Neumann entropy), and, more generally, for all positive integer $α$, in the asymptotic limit of infinite number of modes and for input states that are composed of single-mode-squeezed-vacuum state with equal squeezing strength. We then analyze the limiting behaviors when the squeezing is small and large. Having determined the averages, we then explicitly calculate the Rényi-$α$ variance for integers $α> 1$, and we are able to show that these entropies are weakly typical.

quant-ph↗

arXiv2025

Optical engineering and detection of magnetism in moiré semiconductors

We present a general framework for optically inducing, controlling, and probing spin states in moiré systems. In particular, we demonstrate that applying Raman optical drives to moiré transition metal dichalcogenide bilayers can realize a class of spin models, with magnetic interactions tunable via the optical parameters. The resulting interaction anisotropy, controlled by the polarizations of the drives, enables access to magnetic states that are inaccessible in undriven moiré bilayers. Furthermore, we establish direct connections between the resulting spin correlations and experimentally observable optical signals. Our work paves the way for future studies on the optical control and detection on strongly correlated quantum systems.

cond-mat.str-el↗

arXiv2025

Collective optical properties of moiré excitons

We propose that excitons in moiré transition metal dichalcogenide bilayers offer a promising platform for investigating collective radiative properties. While some of these optical properties resemble those of cold atom arrays, moiré excitons extend to the deep subwavelength limit, beyond the reach of current optical lattice experiments. Remarkably, we show that the collective optical properties can be exploited to probe certain correlated electron states without requiring subwavelength spatial resolution. Specifically, we illustrate that the Wigner crystal states of electrons doped into these bilayers act as an emergent periodic potential for excitons. Moreover, the collective dissipative excitonic bands and their associated Berry curvature can reveal various charge orders that emerge at the corresponding electronic doping. Our study provides a promising pathway for future research on the interplay between collective effects and strong correlations involving moiré excitons.

cond-mat.mes-hall↗

arXiv2024

Robust analog quantum simulators by quantum error-detecting codes

Achieving noise resilience is an outstanding challenge in Hamiltonian-based quantum computation. To this end, energy-gap protection provides a promising approach, where the desired quantum dynamics are encoded into the ground space of a penalty Hamiltonian that suppresses unwanted noise processes. However, existing approaches either explicitly require high-weight penalty terms that are not directly accessible in current hardware, or utilize non-commuting $2$-local Hamiltonians, which typically leads to an exponentially small energy gap. In this work, we provide a general recipe for designing error-resilient Hamiltonian simulations, making use of an excited encoding subspace stabilized by solely $2$-local commuting Hamiltonians. Our results thus overcome a no-go theorem previously derived for ground-space encoding that prevents noise suppression schemes with such Hamiltonians. Importantly, our method is scalable as it only requires penalty terms that scale polynomially with system size. To illustrate the utility of our approach, we further apply this method to a variety of $1$- and $2$-dimensional many-body spin models, potentially extending the duration of high-fidelity simulation by orders of magnitude in current hardware.

quant-ph↗

arXiv2024

Uncovering measurement-induced entanglement via directional adaptive dynamics and incomplete information

The rich entanglement dynamics and transitions exhibited by monitored quantum systems typically only exist in the conditional state, making observation extremely difficult. In this work we construct a general recipe for mimicking the conditional entanglement dynamics of a monitored system in a corresponding measurement-free dissipative system involving directional interactions between the original system and a set of auxiliary register modes. This mirror setup autonomously implements a measurement-feedforward dynamics that effectively retains a coarse-grained measurement record. We illustrate our ideas in a bosonic system featuring a competition between entangling measurements and local unitary dynamics, and also discuss extensions to qubit systems and truly many-body systems.

quant-ph↗

arXiv2024

Efficient preparation of Dicke states

We present an algorithm utilizing mid-circuit measurement and feedback that prepares Dicke states with polylogarithmically many ancillas and polylogarithmic depth. Our algorithm uses only global mid-circuit projective measurements and adaptively-chosen global rotations. This improves over prior work that was only efficient for Dicke states of low weight, or was not efficient in both depth and width. Our algorithm can also naturally be implemented in a cavity QED context using polylogarithmic time, zero ancillas, and atom-photon coupling scaling with the square root of the system size.

quant-ph↗

arXiv2024

Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Recent developments in deep learning techniques have offered an alternative and complementary approach to traditional matched filtering methods for the identification of gravitational wave (GW) signals. The rapid and accurate identification of GW signals is crucial for the progress of GW physics and multi-messenger astronomy, particularly in light of the upcoming fourth and fifth observing runs of LIGO-Virgo-KAGRA. In this work, we use the 2D U-Net algorithm to identify the time-frequency domain GW signals from stellar-mass binary black hole (BBH) mergers. We simulate BBH mergers with component masses from 5 to 80 $M_{\odot}$ and account for the LIGO detector noise. We find that the GW events in the first and second observation runs could all be clearly and rapidly identified. For the third observing run, about $80\%$ GW events could be identified. In particular, GW190814, currently unknown, is a special case that can be identified by the network, while other binary neutron star mergers and neutron star-black hole mergers can not be identified. Compared to the traditional convolutional neural network, the U-Net algorithm can output the time-frequency domain signal images rather than probabilities, providing a more intuitive investigation. Moreover, some of the results through U-Net can provide preliminary inference on the chirp mass information. In conclusion, the U-Net algorithm can rapidly identify the time-frequency domain GW signals from BBH mergers and potentially be helpful for future parameter inferences.

gr-qc↗