Zhenyu Du

Efficient and high-performance quantum error correction is essential for achieving fault-tolerant quantum computing. Low-depth random circuits offer a promising approach to identifying effective and practical encoding strategies. In this work, we rigorously prove through information-theoretic analysis that one-dimensional logarithmic-depth random Clifford encoding circuits can achieve high quantum error correction performance. We demonstrate that these random codes typically exhibit good approximate quantum error correction capability by proving that their encoding rate achieves the hashing bound for Pauli noise and the channel capacity for erasure errors. We show that the error correction inaccuracy decays once a threshold of logarithmic depth is exceeded, resulting in negligible recovery errors. This threshold is shown to be lower than that of the simple separate block encoding, and the decay rate is higher. We further establish that these codes are optimal by proving that logarithmic depth is necessary to maintain a constant encoding rate and high error correction performance. To prove our results, we propose new decoupling theorems for one-dimensional low-depth circuits. These results also imply strong decoupling and rapid thermalization properties in low-depth random circuits and have potential applications in quantum information science and physics.

Characterizing increasingly complex quantum systems is a central task in quantum information science, yet experimental costs often scale prohibitively with system size. Certifying key properties---such as entanglement, circuit complexity, and quantum magic---using simple local measurements is highly desirable but challenging. In this work, we introduce a highly general certification framework based on a physical phenomenon that we call localizable quantumness: for generic many-body states, essential quantum properties are robustly preserved within the projected ensembles on small subsystems after performing local projective measurements on the rest of the system. Leveraging this insight, we develop certification protocols that certify global properties by witnessing them on a small, accessible subsystem. Our method dramatically reduces experimental cost by relying solely on local Pauli measurements, while achieving constant sample complexity, constant-level robustness, and soundness for mixed states---exponentially improving the sample complexity and overcoming major limitations of previous methods. We further present a random-basis variant to certify state fidelity, with numerical evidence strongly suggesting it maintains constant sample complexity and robustness for generic states, representing a substantial improvement over existing methods. Our results provide a practical, scalable toolkit for certifying large-scale quantum processors and offer a novel lens for understanding complex many-body quantum systems.

We prove that the linearity and positivity of quantum mechanics impose general restrictions on quantum purification, unveiling a new fundamental limitation of quantum information processing. In particular, no quantum operation can transform a finite number of copies of an unknown quantum state or channel into a pure state or channel that depends on the input, thereby ruling out an important form of universal purification in both static and dynamical settings. Relaxing the requirement of exact pure output, we further extend our result to establish quantitative sample complexity bounds for approximate purification, independent of any task details or operational constraints. To illustrate the practical consequences of this principle, we examine the task of approximately preparing pure dilation and, for the first time, prove an exponential lower bound on the required sample complexity.

Quantum learning encounters fundamental challenges when estimating non-linear properties, owing to the inherent linearity of quantum mechanics. Although recent advances in single-copy randomized measurement protocols have achieved optimal sample complexity for specific tasks like state purity estimation, generalizing these protocols to estimate broader classes of non-linear properties without sacrificing optimality remains an open problem. In this work, we introduce the observable-driven randomized measurement (ORM) protocol enabling the estimation of Tr(Oρ^2) for an arbitrary observable O---an essential quantity in quantum computing and many-body physics. We establish an upper bound for ORM's sample complexity and show its optimality for observables with a large trace-norm, including Pauli and local observables, closing a gap in the literature. For these observables, ORM admits an efficient implementation with Clifford circuits. Numerical experiments validate that ORM requires substantially fewer state samples to achieve the same precision compared to classical shadows. Additionally, we introduce a braiding randomized measurement protocol for multiple low-rank non-linear observables, reducing circuit complexities in practical applications.

Enhancing the performance of quantum key distribution is crucial, driving the exploration of various key distillation techniques to increase the key rate and tolerable error rate. It is imperative to develop a comprehensive framework to encapsulate and enhance the existing methods. In this work, we propose an advantage distillation framework for quantum key distribution. Building on the entanglement distillation protocol, our framework integrates all the existing key distillation methods and offers better generalization and performance. Using classical linear codes, our framework can achieve higher key rates, particularly without one-time pad encryption for postprocessing. Our approach provides insights into existing protocols and offers a systematic way for future enhancements of quantum key distribution protocols.