1331 papers
This paper presents an automated framework using large language models to categorize atomic spectroscopy literature for NIST databases, achieving high precision in identifying elemental species while highlighting that granular subject code assignment remains the primary source of error.
This paper presents a simulation-driven framework that identifies optimal coupling coefficients for maximizing entanglement in engineered positronic substrates and proposes a prototype architecture with adaptive feedback to maintain this state under dynamic perturbations.
This paper resolves the long-standing problem of finite-copy optimal cloning for mixed qudit states by formulating it as a concave program over Young-label transitions, providing exact numerical optima, demonstrating that asymptotic cloners can suffer significant fidelity losses, and introducing a closed-form "Knothe–Rosenblatt" cloner that achieves near-optimal performance without semidefinite programming.
This paper introduces Optimal Quantum Measurement Decoding (OQMD), a method that optimizes the mapping of quantum outcomes to classical labels via trainable single-qubit rotations to significantly improve multiclass classification accuracy while avoiding the error and latency associated with two-qubit CNOT gates.
This study presents a hybrid multiscale framework combining experimental photoacoustic measurements, molecular dynamics simulations, and physics-informed neural networks to characterize the doping-dependent thermal conductivity of porous silicon and derive a generalized analytical model linking nanoscale phonon mechanics to macroscopic heat transport properties.
This study utilizes SCAPS-1D numerical simulations to optimize the design of amorphous/crystalline silicon heterojunction (HIT) solar cells by analyzing the effects of layer thickness, doping, band gap, and defect density to establish optimal structural parameters for high efficiency.
This study demonstrates that a binary-informed Maxwell–Garnett mixing-law framework, utilizing fixed effective constituent parameters derived from binary PANI/PU and PANI/paraffin systems, enables high-accuracy, calibration-free prediction of the complex permittivity for ternary PANI/CIP/PU composites across the 2–18 GHz frequency range.
This paper proposes a high-sensitivity, label-free hemoglobin biosensor utilizing a reconfigurable plus-shaped gold metasurface integrated with a Germanium Antimony Tellurium (GST) layer, which achieves a maximum sensitivity of 766.67 nm/RIU in its crystalline state, surpassing existing metasurface-based sensors and offering a compact alternative to bulky laboratory infrastructure for clinical diagnosis.
This paper introduces a quantum control protocol for a single spin-based sensor that enables intrinsic vectorial gradiometry to overcome the limitations of traditional multi-sensor architectures, demonstrating high-precision differential sensing for applications like magnetic anomaly detection and neuronal action potential monitoring.
This study presents a finite-time analysis of a driven five-level atom coupled to a Kerr nonlinear optical mode and a mechanical oscillator, revealing that while stronger atom-field coupling enhances entanglement, it does not preserve phase sensitivity, and that energy exchange metrics like ergotropy and signed work respond distinctively to system parameters without constituting a completed thermodynamic cycle.