Related papers: Quantum Point Contact Parameter Extraction of Carb…
A complex approach phonon quantum discrete model (PQDM) was developed to describe dynamics, kinetics and statistics of phonons in carbon nanostructures with zero-chirality of both zig-zag and armchair geometry. The model allows include into…
Using a quantum processor to embed and process classical data enables the generation of correlations between variables that are inefficient to represent through classical computation. A fundamental question is whether these correlations…
Transport through semiconductor nanostructures is a quantum-coherent process. This paper focuses on systems in which the electron's dynamics is ballistic and the transport is dominated by the scattering from structure boundaries. Opposite…
We present a comprehensive study of the properties of the off-resonant conductance spectrum in oligomer nanojunctions between graphitic electrodes. By employing first-principle-based methods and the Landauer approach of quantum transport,…
We investigate the perturbative and non-perturbative aspects of heavy quark transport in a thermal QCD medium. Based on the Soft-Hard Factorized Model (SHFM), we extend the original perturbative framework to the near-critical temperature…
The efficiency of Quantum Characterisation, Verification, and Validation (QCVV) protocols highly hinges on the agreement between the assumed noise model and the underlying error mechanisms. As a matter of fact, errors in Quantum Processing…
Most pattern recognition models are developed on pre-proce\-ssed data. In computer vision, for instance, RGB images processed through image signal processing (ISP) pipelines designed to cater to human perception are the most frequent input…
Channel estimation is of crucial importance for tomorrow's wireless mobile communication systems. This paper focuses on the solution of channel parameters estimation problem in a scenario involving multiple paths in the presence of additive…
We present a quantum-native approach to quantum feature selection (QFS) based on analog quantum simulation with neutral atom arrays, adaptable to a variety of academic and industrial applications. In our method, feature relevance-measured…
Variational training of parameterized quantum circuits (PQCs) underpins many workflows employed on near-term noisy intermediate scale quantum (NISQ) devices. It is a hybrid quantum-classical approach that minimizes an associated cost…
We investigate the transport properties of the strongly interacting quark-gluon plasma (sQGP) by comparing the role of elastic and inelastic (radiative) processes in the sQGP medium within the effective dynamical quasi-particle model…
Parameterized quantum circuits (PQCs) are fundamental to quantum machine learning (QML), quantum optimization, and variational quantum algorithms (VQAs). The expressibility of PQCs is a measure that determines their capability to harness…
The inverse design of metasurfaces poses a considerable challenge because of the intricate interdependencies that exist between structural characteristics and electromagnetic responses. Traditional optimization methods require significant…
Quantum control plays an irreplaceable role in practical use of quantum computers. However, some challenges have to be overcome to find more suitable and diverse control parameters. We propose a promising and generalizable…
We study $S$-wave interactions in the $I\left(J^{p}\right)=1/2\left(1/2^{-}\right)$ $\Lambda_{c}K^{+}-pD_{s}$ system on the basis of the coupled-channel HAL QCD method. The potentials which are faithful to QCD S-matrix below the $ pD^{*} $…
We propose a learning-based method for the joint design of a transmit and receive filter, the constellation geometry and associated bit labeling, as well as a neural network (NN)-based detector. The method maximizes an achievable…
Variational Quantum Circuits (VQC) lie at the forefront of quantum machine learning research. Still, the use of quantum networks for real data processing remains challenging as the number of available qubits cannot accommodate a large…
A microscopic theory of the transport properties of quantum point contacts giving a unified description of the normal conductor- superconductor (N-S) and superconductor-superconductor (S-S) cases is presented. It is based on a model…
Quantum memory is the core device for the construction of large-scale quantum networks. For scalable and convenient practical applications, integrated optical memories, especially on-chip optical memories, are crucial requirements because…
We propose a hybrid photonic quantum reservoir computing (QRC) framework for swaption surface prediction. The pipeline compresses 224-dimensional surfaces to a 20-dimensional latent space via a sparse denoising autoencoder, extracts 1,215…