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Quntao Zhuang

Publications and source records attributed to Quntao Zhuang.

At least 73 records · Page 4Linked to original sources

Entanglement-Enhanced Optomechanical Sensing

Optomechanical systems have been exploited in ultrasensitive measurements of force, acceleration, and magnetic fields. The fundamental limits for optomechanical sensing have been extensively studied and now well understood -- the intrinsic uncertainties of the bosonic optical and mechanical modes, together with the backaction noise arising from the interactions between the two, dictate the Standard Quantum Limit (SQL). Advanced techniques based on nonclassical probes, in-situ pondermotive squeezed light, and backaction-evading measurements have been developed to overcome the SQL for individual optomechanical sensors. An alternative, conceptually simpler approach to enhance optomechanical sensing rests upon joint measurements taken by multiple sensors. In this configuration, a pathway toward overcoming the fundamental limits in joint measurements has not been explored. Here, we demonstrate that joint force measurements taken with entangled probes on multiple optomechanical sensors can improve the bandwidth in the thermal-noise-dominant regime or the sensitivity in shot-noise-dominant regime. Moreover, we quantify the overall performance of entangled probes with the sensitivity-bandwidth product and observe a 25% increase compared to that of the classical probes. The demonstrated entanglement-enhanced optomechanical sensing could enable new capabilities for inertial navigation, acoustic imaging, and searches for new physics.

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Transceiver designs to attain the entanglement assisted communications capacity

Pre-shared entanglement can significantly boost communication rates in the high thermal noise and low-brightness transmitter regime. In this regime, for a lossy-bosonic channel with additive thermal noise, the ratio between the entanglement-assisted capacity and the Holevo capacity - the maximum reliable-communications rate permitted by quantum mechanics without any pre-shared entanglement - scales as $\log(1/{\bar N}_{\rm S})$, where the mean transmitted photon number per mode, ${\bar N}_{\rm S} \ll 1$. Thus, pre-shared entanglement, e.g., distributed by the quantum internet or a satellite-assisted quantum link, promises to significantly improve low-power radio-frequency communications. In this paper, we propose a pair of structured quantum transceiver designs that leverage continuous-variable pre-shared entanglement generated, e.g., from a down-conversion source, binary phase modulation, and non-Gaussian joint detection over a code word block, to achieve this scaling law of capacity enhancement. Further, we describe a modification to the aforesaid receiver using a front-end that uses sum-frequency generation sandwiched with dynamically-programmable in-line two-mode squeezers, and a receiver back-end that takes full advantage of the output of the receiver's front-end by employing a non-destructive multimode vacuum-or-not measurement to achieve the entanglement-assisted classical communications capacity.

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Entanglement-assisted multi-aperture pulse-compression radar for angle resolving detection

Entanglement has been known to boost target detection, despite it being destroyed by lossy-noisy propagation. Recently, [Phys. Rev. Lett. 128, 010501 (2022)] proposed a quantum pulse-compression radar to extend entanglement's benefit to target range estimation. In a radar application, many other aspects of the target are of interest, including angle, velocity and cross section. In this study, we propose a dual-receiver radar scheme that employs a high time-bandwidth product microwave pulse entangled with a pre-shared reference signal available at the receiver, to investigate the direction of a distant object and show that the direction-resolving capability is significantly improved by entanglement, compared to its classical counterpart under the same parameter settings. We identify the applicable scenario of this quantum radar to be short-range and high-frequency, which enables entanglement's benefit in a reasonable integration time.

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Entangled sensor-networks for dark-matter searches

The hypothetical axion particle (of unknown mass) is a leading candidate for dark matter (DM). Many experiments search for axions with microwave cavities, where an axion may convert into a cavity photon, leading to a feeble excess in the output power of the cavity. Recent work [Nature 590, 238 (2021)] has demonstrated that injecting squeezed vacuum into the cavity can substantially accelerate the axion search. Here, we go beyond and provide a theoretical framework to leverage the benefits of quantum squeezing in a network setting consisting of many sensor-cavities. By forming a local sensor network, the signals among the cavities can be combined coherently to boost the axion search. Furthermore, injecting multipartite entanglement across the cavities -- generated by splitting a squeezed vacuum -- enables a global noise reduction. We explore the performance advantage of such a local, entangled sensor-network, which enjoys both coherence between the axion signals and entanglement between the sensors. Our analyses are pertinent to next-generation DM-axion searches aiming to leverage a network of sensors and quantum resources in an optimal way. Finally, we assess the possibility of using a more exotic quantum state, the Gottesman-Kitaev-Preskill (GKP) state. Despite a constant-factor improvement in the scan-time relative to a single-mode squeezed-state in the ideal case, the advantage of employing a GKP state disappears when a practical measurement scheme is considered.

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Entangling remote microwave quantum computers with hybrid entanglement swap and variational distillation

Superconducting microwave circuits with Josephson junctions are a major platform for quantum computing. To unleash their full capabilities, the cooperative operation of multiple microwave superconducting circuits is required. Therefore, designing an efficient protocol to distribute microwave entanglement remotely becomes a crucial open problem. Here, we propose a continuous-variable entanglement-swap approach based on optical-microwave entanglement generation, which can boost the ultimate rate by two orders of magnitude at state-of-the-art parameter region, compared with traditional approaches. We further empower the protocol with a hybrid variational entanglement distillation component to provide huge advantage in the infidelity-versus-success-probability trade-off. Our protocol can be realized with near-term device performance, and is robust against non-perfections such as optical loss and noise. Therefore, our work provides a practical method to realize efficient quantum links for superconducting microwave quantum computers.

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Demonstration of Entanglement-Enhanced Covert Sensing

The laws of quantum physics endow superior performance and security for information processing: quantum sensing harnesses nonclassical resources to enable measurement precision unmatched by classical sensing, whereas quantum cryptography aims to unconditionally protect the secrecy of the processed information. Here, we present the theory and experiment for entanglement-enhanced covert sensing, a paradigm that simultaneously offers high measurement precision and data integrity by concealing the probe signal in an ambient noise background so that the execution of the protocol is undetectable with a high probability. We show that entanglement offers a performance boost in estimating the imparted phase by a probed object, as compared to a classical protocol at the same covertness level. The implemented entanglement-enhanced covert sensing protocol operates close to the fundamental quantum limit by virtue of its near-optimum entanglement source and quantum receiver. Our work is expected to create ample opportunities for quantum information processing at unprecedented security and performance levels.

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Quantum Computational Phase Transition in Combinatorial Problems

Quantum Approximate Optimization algorithm (QAOA) aims to search for approximate solutions to discrete optimization problems with near-term quantum computers. As there are no algorithmic guarantee possible for QAOA to outperform classical computers, without a proof that $BQP\neq NP$, it is necessary to investigate the empirical advantages of QAOA. We identify a computational phase transition of QAOA when solving hard problems such as SAT -- random instances are most difficult to train at a critical problem density. We connect the transition to the controllability and the complexity of QAOA circuits. Moreover, we find that the critical problem density in general deviates from the SAT-UNSAT phase transition, where the hardest instances for classical algorithm lies. Then, we show that the high problem density region, which limits QAOA's performance in hard optimization problems ({\it reachability deficits}), is actually a good place to utilize QAOA: its approximation ratio has a much slower decay with the problem density, compared to classical approximate algorithms. Indeed, it is exactly in this region that quantum advantages of QAOA over classical approximate algorithms can be identified.

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Quantum Receiver Enhanced by Adaptive Learning

Quantum receivers aim to effectively navigate the vast quantum-state space to endow quantum information processing capabilities unmatched by classical receivers. To date, only a handful of quantum receivers have been constructed to tackle the problem of discriminating coherent states. Quantum receivers designed by analytical approaches, however, are incapable of effectively adapting to diverse environment conditions, resulting in their quickly diminishing performance as the operational complexities increase. Here, we present a general architecture, dubbed the quantum receiver enhanced by adaptive learning (QREAL), to adapt quantum receiver structures to diverse operational conditions. QREAL is experimentally implemented in a hardware platform with record-high efficiency. Combining the QREAL architecture and the experimental advances, the error rate is reduced up to 40% over the standard quantum limit in two coherent-state encoding schemes.

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Enhancing distributed sensing with imperfect error correction

Entanglement has shown promise in enhancing information processing tasks in a sensor network, via distributed quantum sensing protocols. As noise is ubiquitous in sensor networks, error correction schemes based on Gottesman, Kitaev and Preskill (GKP) states are required to enhance the performance, as shown in [New J. Phys. 22, 022001 (2020)] assuming homogeneous noise among sensors and perfect GKP states. Here, we extend the analyses of performance enhancement to finite squeezed GKP states in a heterogeneous noise model. To begin with, we study different concatenation schemes of GKP-two-mode-squeezing codes. While traditional sequential concatenation schemes in previous works do improve the suppression of noise, we propose a balanced concatenation scheme that outperforms the sequential scheme in presence of finite GKP squeezing. We then apply these results to two specific tasks in distributed quantum sensing -- parameter estimation and hypothesis testing -- to understand the trade-off between imperfect squeezing and performance. For the former task, we consider an energy-constrained scenario and provide an optimal way to distribute the energy of the finite squeezed GKP states among the sensors. For the latter task, we show that the error probability can still be drastically lowered via concatenation of realistic finite squeezed GKP codes.

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Searches for New Particles, Dark Matter, and Gravitational Waves with SRF Cavities

This is a Snowmass white paper on the utility of existing and future superconducting cavities to probe fundamental physics. Superconducting radio frequency (SRF) cavity technology has seen tremendous progress in the past decades, as a tool for accelerator science. With advances spear-headed by the SQMS center at Fermilab, they are now being brought to the quantum regime becoming a tool in quantum science thanks to the high degree of coherence. The same high quality factor can be leveraged in the search for new physics, including searches for new particles, dark matter, including the QCD axion, and gravitational waves. We survey some of the physics opportunities and the required directions of R&D. Given the already demonstrated integration of SRF cavities in large accelerator systems, this R&D may enable larger scale searches by dedicated experiments.

hep-ph↗

Continuous-variable quantum repeaters based on bosonic error-correction and teleportation: architecture and applications

Quantum repeaters are essential ingredients for quantum networks that link distant quantum modules such as quantum computers and sensors. Motivated by distributed quantum computing and communication, quantum repeaters that relay discrete-variable quantum information have been extensively studied; while continuous-variable (CV) quantum information underpins a variety of quantum sensing and communication application, a quantum-repeater architecture for genuine CV quantum information remains largely unexplored. This paper reports a CV quantum-repeater architecture based on CV quantum teleportation assisted by the Gottesman-Kitaev-Preskill (GKP) code to significantly suppress the physical noise. The designed CV quantum-repeater architecture is shown to significantly improve the performance of CV quantum key distribution, entanglement-assisted communication, and target detection based on quantum illumination, as three representative use cases for quantum communication and sensing.

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Computable limits of optical multiple-access communications

Communication rates over quantum channels can be boosted by entanglement, via superadditivity phenomena or entanglement assistance. Superadditivity refers to the capacity improvement from entangling inputs across multiple channel uses. Nevertheless, when unlimited entanglement assistance is available, the entanglement between channel uses becomes unnecessary -- the entanglement-assisted (EA) capacity of a single-sender and single-receiver channel is additive. We generalize the additivity of EA capacity to general multiple-access channels (MACs) for the total communication rate. Furthermore, for optical communication modelled as phase-insensitive bosonic Gaussian MACs, we prove that the optimal total rate is achieved by Gaussian entanglement and therefore can be efficiently evaluated. To benchmark entanglement's advantage, we propose computable outer bounds for the capacity region without entanglement assistance. Finally, we formulate an EA version of minimum entropy conjecture, which leads to the additivity of the capacity region of phase-insensitive bosonic Gaussian MACs if it is true. The computable limits confirm entanglement's boosts in optical multiple-access communications.

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Ultimate accuracy limit of quantum pulse-compression ranging

Radars use time-of-flight measurement to infer the range to a distant target from its return's roundtrip range delay. They typically transmit a high time-bandwidth product waveform and use pulse-compression reception to simultaneously achieve satisfactory range resolution and range accuracy under a peak transmitted-power constraint. Despite the many proposals for quantum radar, none have delineated the ultimate quantum limit on ranging accuracy. We derive that limit through continuous-time quantum analysis and show that quantum illumination (QI) ranging -- a quantum pulse-compression radar that exploits the entanglement between a high time-bandwidth product transmitted signal pulse and and a high time-bandwidth product retained idler pulse -- achieves that limit. We also show that QI ranging offers mean-squared range-delay accuracy that can be 10's of dB better than a classical pulse-compression radar's of the same pulse bandwidth and transmitted energy.

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Deterministic microwave-optical transduction based on quantum teleportation

The coherent transduction between microwave and optical frequencies is critical to interconnect superconducting quantum processors over long distances. However, it is challenging to establish such a quantum interface with high efficiency and small added noise based on the standard direct conversion scheme. Here, we propose a transduction scheme based on continuous-variable quantum teleportation. Reliable quantum information transmission can be realized with an arbitrarily small cooperativity, in contrast to the direct conversion scheme which requires a large minimum cooperativity. We show that the teleportation-based scheme maintains a significant rate advantage robustly for all values of cooperativity. We further investigate the performance in the transduction of complex quantum states such as cat states and Gottesman-Kitaev-Preskill(GKP) states and show that a higher fidelity or success probability can be achieved with the teleportation-based scheme. Our scheme significantly reduces the device requirement, and makes quantum transduction between microwave and optical frequencies feasible in the near future.

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Quantum communication capacity transition of complex quantum networks

Quantum network is the key to enable distributed quantum information processing. As the single-link communication rate decays exponentially with the distance, to enable reliable end-to-end quantum communication, the number of nodes needs to grow with the network scale. For highly connected networks, we identify a threshold transition in the capacity as the density of network nodes increases---below a critical density, the rate is almost zero, while above the threshold the rate increases linearly with the density. Surprisingly, above the threshold the typical communication capacity between two nodes is independent of the distance between them, due to multi-path routing enabled by the quantum network. In contrast, for less connected networks such as scale-free networks, the end-to-end capacity saturates to constants as the number of nodes increases, and always decays with the distance. Our results are based on capacity evaluations, therefore the minimum density requirement for an appreciable capacity applies to any general protocols of quantum networks.

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Quantum Internet under random breakdowns and intentional attacks

Quantum networks will play a key role in distributed quantum information processing. As the network size increases, network-level errors like random breakdown and intentional attack are inevitable; therefore, it is important to understand the robustness of large-scale quantum networks, similar to what has been done for the classical counterpart---the Internet. For exponential networks such as Waxman networks, errors simply re-parameterize the network and lead to a linear decrease of the quantum capacity with the probability of error. The same linear decay happens for scale-free quantum networks under random breakdowns, despite the previously discovered robustness in terms of the connectivity. In presence of attack, however, the capacity of scale-free quantum networks shows a sharp exponential decay with the increasing attack fraction. Our results apply to quantum internet based on fibers for all kinds of quantum communications and provide implications for the future construction of quantum networks with regard to its robustness.

quant-ph↗

Attaining quantum limited precision of localizing an object in passive imaging

We investigate our ability to determine the mean position, or centroid, of a linear array of equally-bright incoherent point sources of light, whose continuum limit is the problem of estimating the center of a uniformly-radiating object. We consider two receivers: an image-plane ideal direct-detection imager and a receiver that employs Hermite-Gaussian (HG) Spatial-mode Demultiplexing (SPADE) in the image plane, prior to shot-noise-limited photon detection. We compare the Fisher Information (FI) for estimating the centroid achieved by these two receivers, which quantifies the information-accrual rate per photon, and compare those with the Quantum Fisher Information (QFI): the maximum attainable FI by any choice of measurement on the collected light allowed by physics. We find that focal-plane direct imaging is strictly sub-optimal, although not by a large margin. We also find that the HG mode sorter, which is the optimal measurement for estimating the separation between point sources (or the length of a line object) is not only suboptimal, but it performs worse than direct imaging. We study the scaling behavior of the QFI and direct imaging's FI for a continuous, uniformly-bright object in terms of its length, and find that both are inversely proportional to the object's length when it is sufficiently larger than the Rayleigh length. Finally, we propose a two-stage adaptive modal receiver design that attains the QFI for centroid estimation.

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Fast suppression of classification error in variational quantum circuits

Variational quantum circuits (VQCs) have shown great potential in near-term applications. However, the discriminative power of a VQC, in connection to its circuit architecture and depth, is not understood. To unleash the genuine discriminative power of a VQC, we propose a VQC system with the optimal classical post-processing -- maximum-likelihood estimation on measuring all VQC output qubits. Via extensive numerical simulations, we find that the error of VQC quantum data classification typically decay exponentially with the circuit depth, when the VQC architecture is extensive -- the number of gates does not shrink with the circuit depth. This fast error suppression ends at the saturation towards the ultimate Helstrom limit of quantum state discrimination. On the other hand, non-extensive VQCs such as quantum convolutional neural networks are sub-optimal and fail to achieve the Helstrom limit. To achieve the best performance for a given VQC, the optimal classical post-processing is crucial even for a binary classification problem. To simplify VQCs for near-term implementations, we find that utilizing the symmetry of the input properly can improve the performance, while oversimplification can lead to degradation.

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