相关论文: Quantum Point Contact Parameter Extraction of Carb…

The use of carbon nanotube (CNT) field-effect transistors (FETs) in microwave circuit design requires an appropriate, immediate and efficient description of their performance. This work describes a technique to extract the parameters of an…

While perturbative QCD is sufficient for understanding the color, mass and energy dependences of parton energy loss and jet quenching at large transverse momentum in heavy-ion collisions, a simultaneous description of heavy flavor nuclear…

We present a variant of the recently developed quantum corrected model (QCM) for plasmonic nanoparticles [Nature Commun. 3, 825 (2012)] using non-local boundary conditions. The QCM accounts for electron tunneling in narrow gap regions of…

We employ the Boltzmann equation for describing hadron production from a quark-gluon plasma (QGP) in ultrarelativistic heavy-ion collisions. We propose resonance formation in quark-antiquark scattering as the dominant meson-production…

Quantum point contacts (QPCs) and quantum dots (QDs), two elementary building blocks of semiconducting nanodevices, both exhibit famously anomalous conductance features: the 0.7-anomaly in the former case, the Kondo effect in the latter.…

Within a neural-network-based holographic framework, we incorporate lattice QCD (LQCD) and Hadron Resonance Gas (HRG) data to train the model and predict the location of the QCD critical endpoint (CEP). The training dataset consists of the…

Parametrically driven nonlinear resonators represent a building block for realizing fault-tolerant quantum computation and are useful for critical quantum sensing. From a fundamental viewpoint, the most intriguing feature of such a system…

Quantum point contacts are fundamental building blocks for mesoscopic transport experiments and play an important role in recent interference- and fractional quantum Hall experiments. However, it is not clear how electron-electron…

We consider quantum point contacts (QPCs) defined within disordered two-dimensional electron gases as studied by scanning gate microscopy. We evaluate the conductance maps in the Landauer approach and wave function picture of electron…

We derive upper and lower bounds on the convergence behavior of certain classes of one-parameter quantum dynamical semigroups. The classes we consider consist of tensor product channels and of channels with commuting Liouvillians. We…

We have measured the transition process from the high to low resistivity states, i.e., the reset process of resistive switching based memristors based on Ni/HfO2/Si-n+ structures, and have also developed an analytical model for their…

With the help of quantum mechanics one can formulate a model of associative memory with optimal storage capacity. I generalize this model by introducing a parameter playing the role of an effective temperature. The corresponding…

This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic decryption and the reconstruction of a precise extraction path. The system integrates…

In this paper, we describe a parameterized quantum circuit that can be considered as convolutional and pooling layers for graph neural networks. The circuit incorporates the parameterized quantum Fourier circuit where the qubit connections…

Quantum machine learning is one of the most promising applications of quantum computing in the Noisy Intermediate-Scale Quantum(NISQ) era. Here we propose a quantum convolutional neural network(QCNN) inspired by convolutional neural…

Quantum point contacts (QPC) are the building blocks of quantum dot qubits and semiconducting quantum electrical metrology circuits. QPCs also make highly sensitive electrical amplifiers with the potential to operate in the quantum-limited…

Signatures of quantum transport are expected to quickly vanish as dissipation is introduced in a system. This dissipation can take several forms, including that of particle loss, which has the consequence that the total probability current…

Hybrid Quantum Neural Networks (HQNNs) combine classical learning with parameterized quantum circuits, but their practical performance is often limited by (i) the noise of Noisy Intermediate-Scale Quantum (NISQ) devices and (ii) the large,…

We propose a theoretical model for the low-frequency noise observed in a quantum point contact (QPC) electrostatically defined in the 2D electron gas at a GaAs-AlGaAs interface. In such contacts electron scattering by soft impurity- or…

The rapid development of optical technologies and applications revealed the critical role of point defects affecting device performance. One of the powerful tools to study influence of defects on charge capture and recombination processes…