Related papers: Deep Learning Accelerated Quantum Transport Simula…
Considering von Neumann expression for reduced density matrix as thermodynamic entropy of a system strongly coupled to baths, we use nonequilibrium Green's function (NEGF) techniques to derive bath and energy resolved expressions for…
Efficient all-photonic quantum teleportation requires fast and deterministic sources of highly indistinguishable and entangled photons. Solid-state-based quantum emitters--notably semiconductor quantum dots--are a promising candidate for…
We propose a simple scheme that describes accurately essential non-equilibrium effects in nanoscale electronics devices using equilibrium transport theory. The scheme, which is based on the alignment and dealignment of the junction…
We propose an efficient approach for simultaneous prediction of thermal and electronic transport properties in complex materials. Firstly, a highly efficient machine-learned neuroevolution potential is trained using reference data from…
Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale…
We study the electron transport in metallic carbon nanotubes (CNTs) with realistic defects of different types. We focus on large CNTs with many defects in the mesoscopic range. In a recent paper we demonstrated that the electronic transport…
Materials engineering using atomistic modeling is an essential tool for the development of qubits and quantum sensors. Traditional density-functional theory (DFT) does however not adequately capture the complete physics involved, including…
Finding efficient decoders for quantum error correcting codes adapted to realistic experimental noise in fault-tolerant devices represents a significant challenge. In this paper we introduce several decoding algorithms complemented by deep…
Simulations of nuclear magnetic resonance (NMR) experiments can be an important tool for extracting information about molecular structure and optimizing experimental protocols but are often intractable on classical computers for large…
Precise scientific analysis in collider-based particle physics is possible because of complex simulations that connect fundamental theories to observable quantities. The significant computational cost of these programs limits the scope,…
Quantum signal processing (QSP), which enables systematic polynomial transformations on quantum data through sequences of qubit rotations, has emerged as a fundamental building block for quantum algorithms and data re-uploading quantum…
This article reviews the application of the non-equilibrium Green's function formalism to the simulation of novel photovoltaic devices utilizing quantum confinement effects in low dimensional absorber structures. It covers well-known…
We combine the linearized Boltzmann Transport Equation (LBTE) and quantum transport by means of the Non-equilibrium Green's Functions (NEGF) to simulate single-layer MoS2 and WS2 ultra-scaled transistors with carrier mobilities extracted…
Widely employed Near-Edge X-Ray Absorption Fine Structure (NEXAFS) spectroscopy probes a system by excitation of core electrons to unoccupied states. A variety of different methodologies are available to simulate corresponding spectra from…
Real-time nonequilibrium Green functions (NEGF) have been very successful to simulate the dynamics of correlated many-particle systems far from equilibrium. However, NEGF simulations are computationally expensive since the effort scales…
Quantum simulation offers a route to study open-system molecular dynamics in non-perturbative regimes by programming the interactions among electronic, vibrational, and environmental degrees of freedom on similar energy scales. Trapped-ion…
A new approximate computational framework is proposed for computing the non-equilibrium charge density in the context of the non-equilibrium Green's function (NEGF) method for quantum mechanical transport problems. The framework consists of…
We introduce Transformer-based Neural Quantum Digital Twins (Tx-NQDTs) to simulate full adiabatic dynamics of many-body quantum systems, including ground and low-lying excited states, at low computational cost. Tx-NQDTs employ a…
With recent developments in spintronics, it is now possible to envision spin-driven devices with magnets and interconnects that require a new class of transport models using generalized Fermi functions and currents, each with four…
The performance potential for simulating quantum electron transport on graphical processing units (GPUs) is studied. Using graphene ribbons of realistic sizes as an example it is shown that GPUs provide significant speed-ups in comparison…