arXiv subjects

Liang Jiang

Publications and source records attributed to Liang Jiang.

At least 73 records · Page 4Linked to original sources

arXiv2025

Optimal scheme for distributed quantum metrology

Optimal strategies for local quantum metrology -- including the preparation of optimal probe states, implementation of optimal control and measurement strategies, are well established. However, for distributed quantum metrology, where the goal is to estimate global properties of multiple spatially distributed parameters, the optimal scheme -- particularly the role of optimal control -- remains poorly understood. In this work, we address this challenge by developing optimal schemes for distributed quantum metrology that characterize the ultimate precision limits in distributed systems. We derive the optimal probe state, optimal control protocols, and measurement strategies in estimating a linear combination of $N$ independent unknown parameters coupled to $d$ networked sensors. Crucially, we prove that the optimal control operations can be implemented locally on each sensor, eliminating the need for non-local control operations across distant nodes. This result significantly reduces the complexity of implementing optimal strategies in distributed quantum metrology. To demonstrate the power of our framework, we apply it to several key scenarios.

quant-ph↗

arXiv2025

Coordinating Decisions via Quantum Telepathy

Quantum telepathy is the phenomenon where two non-communicating parties can exhibit correlated behaviors that are impossible to achieve using classical resources. This is also known as Bell inequality violation and is made possible by quantum entanglement. In this work, we present a conceptual framework for applying quantum telepathy to real-world problems. In general, the problems involve multiple parties making local observations that need to coordinate their decisions but are unable to communicate. We argue this inability is actually quite prevalent in the modern era where the decision-making timescales of computer processors are so short that the speed of light delay is appreciable in comparison. We highlight the example of high-frequency trading (HFT), where trades are made at microsecond timescales, but the speed of light delay between different stock exchanges are on the order of 100 microseconds to 10 milliseconds. Due to the maturity of Bell inequality violation experiments, experimental realization of quantum telepathy schemes that can attain a quantum advantage for real-world problems $\textit{is already almost immediately possible}$. We demonstrate this by conducting a case study for a concrete HFT scenario that gives rise to a generalization of the CHSH game and evaluate different possible physical implementations for achieving a quantum advantage. It is well known that Bell inequality violation is a rigorous mathematical proof of a quantum advantage over any classical strategy and does not need any complexity-theoretic assumptions such as $\text{BQP}\neq\text{BPP}$. Moreover, fault tolerance is not necessary to realize a quantum advantage: for example, violating the CHSH inequality only requires single-qubit operations on two entangled physical qubits.

quant-ph↗

arXiv2025

Recycling Reflections for Perfect Photon Capture

Efficient photon capture in optical cavities is essential for quantum networks and computing, yet single-pass methods suffer from uncaptured reflections due to finite capture windows and coupling strengths, precluding perfect transfer of arbitrary photonic states. We introduce a two-pass `pitch-and-catch' method that recycles initial reflections to achieve perfect capture of arbitrary pulses in the noiseless regime and enhances fidelity under intrinsic losses. The method extends to photon emission, enabling arbitrary pulse shaping. This advance offers significant improvements for quantum repeaters, memories, and transduction, enhancing the toolkit for quantum information processing.

quant-ph↗

arXiv2025

All-mechanical coherence protection and fast control of a spin qubit

In a phononic quantum network, quantum information is stored and processed within stationary nodes defined by solid-state spins, and the information is routed between nodes by phonons. The phonon holds distinct advantages over its electromagnetic counterpart the photon, including smaller device footprints, reduced crosstalk, long coherence times at low temperatures, and strong interactions with both solid-state spins and electromagnetic waves. Enhanced interactions between a phononic cavity and a stationary qubit have been demonstrated in multiple platforms including superconducting qubits, spins in silicon carbide and spins in diamond. However, an outstanding issue is the compatibility between the spin's coupling to the resonant phononic cavity and the simultaneous use of pulse sequences to extend the coherence time of the spin by suppressing the low-frequency environmental noise. Here we demonstrate all-mechanical coherence protection of a solid-state spin qubit, where optical initialization, quantum operations, and readout are performed in a dressed basis that is highly immune to low-frequency noise and compatible with a phononic cavities. We additionally show record-high Rabi frequencies reaching 800 MHz, which allows for ultrafast quantum control. Our results establish a first step for high-fidelity, phonon-mediated quantum gates and represent a crucial advance toward robust on-chip quantum phononic networks.

quant-ph↗

arXiv2025

Quantum-data-driven dynamical transition in quantum learning

Quantum neural networks, parameterized quantum circuits optimized under a specific cost function, provide a paradigm for achieving near-term quantum advantage in quantum information processing. Understanding QNN training dynamics is crucial for optimizing their performance, however, the role of quantum data in training for supervised learning such as classification and regression remains unclear. We reveal a quantum-data-driven dynamical transition where the target values and data determine the convergence of the training. Through analytical classification over the fixed points of the dynamical equation, we reveal a comprehensive `phase diagram' featuring seven distinct dynamics originating from a bifurcation with multiple codimension. Perturbative analyses identify both exponential and polynomial convergence class. We provide a non-perturbative theory to explain the transition via generalized restricted Haar ensemble. The analytical results are confirmed with numerical simulations and experimentation on IBM quantum devices. Our findings provide guidance on constructing the cost function to accelerate convergence in QNN training.

quant-ph↗

arXiv2025

Pilot-reference-free continuous-variable quantum key distribution with efficient decoy-state analysis

Continuous-variable quantum key distribution (CV QKD) using optical coherent detectors is practically favorable due to its low implementation cost, flexibility of wavelength division multiplexing, and compatibility with standard coherent communication technologies. However, the security analysis and parameter estimation of CV QKD are complicated due to the infinite-dimensional latent Hilbert space. Also, the transmission of strong reference pulses undermines the security and complicates the experiments. In this work, we tackle these two problems by presenting a time-bin-encoding CV protocol with a simple phase-error-based security analysis valid under general coherent attacks. With the key encoded into the relative intensity between two optical modes, the need for global references is removed. Furthermore, phase randomization can be introduced to decouple the security analysis of different photon-number components. We can hence tag the photon number for each round, effectively estimate the associated privacy using a carefully designed coherent-detection method, and independently extract encryption keys from each component. Simulations manifest that the protocol using multi-photon components increases the key rate by two orders of magnitude compared to the one using only the single-photon component. Meanwhile, the protocol with four-intensity decoy analysis is sufficient to yield tight parameter estimation with a short-distance key-rate performance comparable to the best Bennett-Brassard-1984 implementation.

quant-ph↗

arXiv2025

Enhancing quantum noise characterization via extra energy levels

Noise is a major challenge for building practical quantum computing systems. Precise characterization of quantum noise is crucial for developing effective error mitigation and correction schemes. However, state preparation and measurement (SPAM) errors on many current platforms can introduce large ambiguity into conventional noise characterization methods. In this work, we propose a scheme for enhancing quantum noise characterization using additional energy levels. We first develop a comprehensive theory on the identifiability of n-qudit SPAM noise given high-quality single-qudit control, showing the existence of gauge freedoms which can be completely described using subsystem depolarizing maps. We then show how to use these extra energy levels to reduce the gauge ambiguity in characterizing both SPAM and gate noise in the qubit subspace. We experimentally implement these ideas on a superconducting quantum computing device and demonstrate a qutrit-enabled enhancement in noise characterization precision.

quant-ph↗

arXiv2025

Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning for LLMs

We present Ring-lite, a Mixture-of-Experts (MoE)-based large language model optimized via reinforcement learning (RL) to achieve efficient and robust reasoning capabilities. Built upon the publicly available Ling-lite model, a 16.8 billion parameter model with 2.75 billion activated parameters, our approach matches the performance of state-of-the-art (SOTA) small-scale reasoning models on challenging benchmarks (e.g., AIME, LiveCodeBench, GPQA-Diamond) while activating only one-third of the parameters required by comparable models. To accomplish this, we introduce a joint training pipeline integrating distillation with RL, revealing undocumented challenges in MoE RL training. First, we identify optimization instability during RL training, and we propose Constrained Contextual Computation Policy Optimization(C3PO), a novel approach that enhances training stability and improves computational throughput via algorithm-system co-design methodology. Second, we empirically demonstrate that selecting distillation checkpoints based on entropy loss for RL training, rather than validation metrics, yields superior performance-efficiency trade-offs in subsequent RL training. Finally, we develop a two-stage training paradigm to harmonize multi-domain data integration, addressing domain conflicts that arise in training with mixed dataset. We will release the model, dataset, and code.

cs.CL↗

arXiv2025

Quantum random access memory with transmon-controlled phonon routing

Quantum random access memory (QRAM) promises simultaneous data queries at multiple memory locations, with data retrieved in coherent superpositions, essential for achieving quantum speedup in many quantum algorithms. We introduce a transmon-controlled phonon router and propose a QRAM implementation by connecting these routers in a tree-like architecture. The router controls the motion of itinerant surface acoustic wave phonons based on the state of the control transmon, implementing the core functionality of conditional routing for QRAM. Our QRAM design is compact, supports fast routing operations, and avoids frequency crowding. Additionally, we propose a hybrid dual-rail encoding method to detect dominant loss errors without additional hardware, a versatile approach applicable to other QRAM platforms. Our estimates indicate that the proposed QRAM platform can achieve high heralding rates using current device parameters, with heralding fidelity primarily limited by transmon dephasing.

quant-ph↗

arXiv2025

Resonance-enhanced Floquet cavity electromagnonics

Floquet engineering has been recently recognized as an important tool for manipulating the coherent magnon-photon interaction in cavity electromagnonics systems at microwave frequencies. In spite of the novel hybrid magnonic functionalities that have been demonstrated, the effect of the Floquet drive has been relatively weak due to the limited driving efficiency, limiting its broader application. This work shows that by utilizing LC resonances, the Floquet drive in our cavity electromagnonic device can be drastically enhanced, giving rise to drastically boosted interaction between hybrid modes with fundamentally different spectral characteristics compared with previous demonstrations. In addition, the Floquet drives can also be obtained from GHz signals on such a system, allowing the demonstration of more advanced signal operations. Our novel resonance-enhanced Floquet cavity electromagnonics points to a new direction to fully unleash the potential of Floquet hybrid magnonics.

cond-mat.mes-hall↗

arXiv2025

Optimized four-qubit quantum error correcting code for amplitude damping channel

Quantum error correction (QEC) is essential for reliable quantum information processing. Targeting a particular error channel, both the encoding and the recovery channel can be optimized through a biconvex optimization to give a high-performance, noise-adapted QEC scheme. We solve the biconvex optimization by the technique of alternating semi-definite programming and identify a new four-qubit code for amplitude damping channel, one major noise in superconducting circuits and a good model for spontaneous emission and energy dissipation. We also construct analytical encoding and recovery channels that are close to the numerically optimized ones. We show that the new code notably outperforms the Leung-Nielsen-Chuang-Yamamoto four-qubit code in terms of the entanglement fidelity over an amplitude damping channel.

quant-ph↗

arXiv2025

Achievable rates for concatenated square Gottesman-Kitaev-Preskill codes

The Gottesman-Kitaev-Preskill (GKP) codes are known to achieve optimal rates under displacement noise and pure loss channels, which establishes theoretical foundations for its optimality. However, such optimal rates are only known to be achieved at a discrete set of noise strength with the current self-dual symplectic lattice construction. In this work, we develop a new coding strategy using concatenated continuous variable - discrete variable encodings to go beyond past results and establish GKP's optimal rate over all noise strengths. In particular, for displacement noise, the rate is obtained through a constructive approach by concatenating GKP codes with a quantum polar code and analog decoding. For pure loss channel, we prove the existence of capacity-achieving GKP codes through a random coding approach. These results highlight the capability of concatenation-based GKP codes and provides new methods for constructing good GKP lattices.

quant-ph↗

arXiv2025

Generalized Quantum Repeater Graph States

All-photonic quantum repeaters are essential for establishing long-range quantum entanglement. Within repeater nodes, reliably performing entanglement swapping is a key component of scalable quantum communication. To tackle the challenge of probabilistic Bell state measurement in linear optics, which often leads to information loss, various approaches have been proposed to ensure the loss tolerance of distributing a single ebit. We have generalized previous work regarding repeater graph states with elaborate connectivity, enabling the efficient establishment of exploitable ebits at a finite rate with high probability. We demonstrate that our new scheme significantly outperforms the previous work with much flexibility and discuss the generation overhead of such resource states. These findings offer new insights into the scalability and reliability of loss-tolerant quantum networks.

quant-ph↗

arXiv2025

Timescales, Squeezing and Heisenberg Scalings in Many-Body Continuous Sensing

The continuous monitoring of driven-dissipative systems offers new avenues for quantum advantage in metrology. This approach mixes temporal and spatial correlations in a manner distinct from traditional metrology, leading to ambiguities in how one identifies Heisenberg scalings (e.g.~standard asymptotic metrics like the sensitivity are not bounded by system size). Here, we propose a new metric for continuous sensing, the optimized finite-time environmental quantum Fisher information (QFI), that remedies the above issues by simultaneously treating time and system size as finite resources. In addition to having direct experimental relevance, this quantity is rigorously bounded by both system size and integration time, allowing for a precise formulation of Heisenberg scaling. We also introduce two many-body continuous sensors: the high-temperature superradiant sensor, and the dissipative spin squeezer. Both exhibit Heisenberg scaling of a collective magnetic field for multiple directions. The spin squeezed sensor has a striking advantage over previously studied many-body continuous sensors: the optimal measurement achieving the full QFI does not require the construction of a complex decoder system, but can be achieved using direct photodetection of the cavity output field.

quant-ph↗

arXiv2025

Enhancing Microwave-Optical Bell Pairs Generation for Quantum Transduction Using Kerr Nonlinearity

Microwave-optical quantum transduction can be achieved via quantum teleportation using microwave-optical photon Bell pairs. The standard spontaneous parametric down-conversion (SPDC) has to trade off between generation fidelity and probability due to unwanted higher-excitation pairs in the output. In this work, we propose a pulsed SPDC scheme that employs strong Kerr nonlinearity in the microwave mode. This nonlinearity causes significant detuning of higher excitations due to the anharmonicity of energy levels, and the system can be pulse-driven to produce single-photon pairs in the output. Our pulsed nonlinear approach can generate high-fidelity Bell pairs with high probability, alleviating the trade-off between fidelity and probability inherent in traditional SPDC schemes. We optimize both the pulse width and driving strength, demonstrating that our protocol outperforms the SPDC scheme in a realistic setting of finite nonlinearity and intrinsic photon loss.

quant-ph↗

arXiv2025

Efficient self-consistent learning of gate set Pauli noise

Understanding quantum noise is an essential step towards building practical quantum information processing systems. Pauli noise is a useful model that has been widely applied in quantum benchmarking, error mitigation, and error correction. Despite intensive study, most existing works focus on learning Pauli noise channels associated with some specific gates rather than treating the gate set as a whole. A learning algorithm that is self-consistent, complete, and efficient at the same time is yet to be established. In this work, we study the task of gate set Pauli noise learning, where a set of quantum gates, state preparation, and measurements all suffer from unknown Pauli noise channels with a customized noise ansatz. Using tools from algebraic graph theory, we analytically characterize the self-consistently learnable degrees of freedom for Pauli noise models with arbitrary linear ansatz, and design experiments to efficiently learn all the learnable information. Specifically, we show that all learnable information about the gate noise can be learned to relative precision, under mild assumptions on the noise ansatz. We then demonstrate the flexibility of our theory by applying it to concrete physically motivated ansatzs (such as spatially local or quasi-local noise) and experimentally relevant gate sets (such as parallel CZ gates). These results not only enhance the theoretical understanding of quantum noise learning, but also provide a feasible recipe for characterizing existing and near-future quantum information processing devices.

quant-ph↗

arXiv2025

Stochastic noise can be helpful for variational quantum algorithms

Saddle points constitute a crucial challenge for first-order gradient descent algorithms. In notions of classical machine learning, they are avoided for example by means of stochastic gradient descent methods. In this work, we provide evidence that the saddle points problem can be naturally avoided in variational quantum algorithms by exploiting the presence of stochasticity. We prove convergence guarantees and present practical examples in numerical simulations and on quantum hardware. We argue that the natural stochasticity of variational algorithms can be beneficial for avoiding strict saddle points, i.e., those saddle points with at least one negative Hessian eigenvalue. This insight that some levels of shot noise could help is expected to add a new perspective to notions of near-term variational quantum algorithms.

quant-ph↗

arXiv2025

Passive environment-assisted quantum communication with GKP states

Bosonic pure-loss channel, which represents the process of photons decaying into a vacuum environment, has zero quantum capacity when the channel's transmissivity is less than 50%. Modeled as a beam splitter interaction between the system and its environment, the performance of bosonic pure-loss channel can be enhanced by controlling the environment state. We show that by choosing the ideal Gottesman-Kitaev-Preskill (GKP) states for the system and its environment, perfect transmission of quantum information through a beam splitter is achievable at arbitrarily low transmissivities. Our explicit constructions allow for experimental demonstration of the improved performance of a quantum channel through passive environment assistance, which is potentially useful for quantum transduction where the environment state can be naturally controlled. In practice, it is crucial to consider finite-energy constraints, and high-fidelity quantum communication through a beam splitter remains achievable with GKP states at the few-photon level.

quant-ph↗