arXiv subjects

Zhen Shang

Publications and source records attributed to Zhen Shang.

4 recordsLinked to original sources

arXiv2026

Robust device-independent characterization of sharpness and incompatibility of unsharp instruments

Unsharp measurements are key resources for tasks that balance information gain and disturbance, but certifying them without device assumptions remains a challenge. We propose a fully device-independent protocol for characterizing unsharp instruments, based on an entanglement-assisted sequential quantum random access code, where the first decoder is allowed to communicate her measurement setting to the second. This communication-enhanced scheme creates a decoding regime in which both decoders surpass classical bounds, enabling tight quantification of sharpness and direct quantification of measurement incompatibility beyond noncommunicating protocols. Experimentally, we implement tunable unsharp measurements using a Mach-Zehnder interferometer, observing the predicted sequential enhancement in decoding probability. Additionally, we achieve significantly narrower sharpness intervals and incompatibility quantification across multiple target sharpness values. Our results show that communication is a powerful operational resource for certifying precisely unsharp instruments and advancing device-independent quantum information protocols.

quant-ph↗

arXiv2026

Defeating Barren Plateaus with Task-Aligned Symmetry

Barren plateaus -- the exponential vanishing of gradients -- are a fundamental obstacle to training scalable quantum neural networks. Whether they arise in quantum recurrent neural networks (QRNNs), a natural architecture for sequential data, remains a pressing question. Here we show that the decisive ingredient for trainability in QRNNs is not the recurrent circuit topology per se, but enforcing time-translation symmetry through parameter sharing across time steps. We prove that, without parameter sharing, QRNNs suffer from barren plateaus, with gradient variance decaying exponentially with sequence length. Imposing parameter sharing across time steps fundamentally alters this scaling, transforming it into a polynomial dependence and thereby suppressing the barren plateau. Numerical simulations corroborate these analytical predictions. By rigorously showing how time-translation symmetry suppresses barren plateaus and enhances learning capability in QRNNs, our work establishes task-aligned symmetry as a constructive resolution to the expressivity-trainability tension in quantum neural networks.

quant-ph↗

arXiv2023

A double-decomposition based parallel exact algorithm for the feedback length minimization problem

Product development projects usually contain many interrelated activities with complex information dependences, which induce activity rework, project delay and cost overrun. To reduce negative impacts, scheduling interrelated activities in an appropriate sequence is an important issue for project managers. This study develops a double-decomposition based parallel branch-and-prune algorithm, to determine the optimal activity sequence that minimizes the total feedback length (FLMP). This algorithm decomposes FLMP from two perspectives, which enables the use of all available computing resources to solve subproblems concurrently. In addition, we propose a result-compression strategy and a hash-address strategy to enhance this algorithm. Experimental results indicate that our algorithm can find the optimal sequence for FLMP up to 27 activities within 1 hour, and outperforms state of the art exact algorithms.

cs.DS↗

arXiv2016

Layer compression and enhanced optical properties of few-layer graphene nanosheets induced by ion irradiation

Graphene has been recognized as an attractive two-dimensional material for fundamental research and wide applications in electronic and photonic devices owing to its unique properties. The technologies to modulate the properties of graphene are of continuous interest to researchers in multidisciplinary areas. Herein, we report on the first experimental observation of the layer-to-layer compression and enhanced optical properties of few-layer graphene nanosheets by applying the irradiation of energetic ion beams. After the irradiation, the space between the graphene layers was reduced, resulting in a tighter contact between the few-layer graphene nanosheet and the surface of the substrate. This processing also enhanced the interaction between the graphene nanosheets and the evanescent-field wave near the surface, thus reinforcing the polarization-dependent light absorption of the graphene layers (with 3-fold polarization extinction ratio increment). Utilizing the ion-irradiated graphene nanosheets as saturable absorbers, the passively Q-switched waveguide lasing with considerably improved performances was achieved, owing to the enhanced interactions between the graphene nanosheets and evanescent field of light. The obtained repetition rate of waveguide laser was up to 2.3 MHz with a pulse duration of 101 ns.

physics.optics↗