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We have developed and implemented a self-consistent density functional method using standard norm-conserving pseudopotentials and a flexible, numerical LCAO basis set, which includes multiple-zeta and polarization orbitals. Exchange and…
Current and near-term quantum hardware is constrained by limited qubit counts, circuit depth, and the high cost of repeated measurements. We address these challenges for solid state Hamiltonians by introducing a logarithmic-qubit encoding…
Advancing complementary metal-oxide-semiconductor (CMOS) technology into the sub-1-nm angstr\"om-scale technology nodes is expected to involve alternative semiconductor channel materials, as silicon transistors encounter severe performance…
We present a two-dimensional electron heterostructure field effect device of simplistic design and ease of fabrication that displays high mobility electron transport. This is accomplished using a high efficacy contacting scheme and simple…
This thesis develops advanced Tensor Network (TN) methods to address Hamiltonian Lattice Gauge Theories (LGTs), overcoming limitations in real-time dynamics and finite-density regimes. A novel dressed-site formalism is introduced, enabling…
A universal family of Hamiltonians can be used to simulate any local Hamiltonian by encoding its full spectrum as the low-energy subspace of a Hamiltonian from the family. Many spin-lattice model Hamiltonians -- such as Heisenberg or XY…
A structure preserving proper orthogonal decomposition reduce-order modeling approach has been developed in [Gong et al. 2017] for the Hamiltonian system, which uses the traditional framework of Galerkin projection-based model reduction but…
We propose an efficient reduced-order technique for electronic structure calculations of semiconductor nanostructures, suited for inclusion in full-band quantum transport simulators. The model is based on the linear combination of bulk…
Accurate orthogonal tight-binding Hamiltonians are constructed for ferromagnetic SrRuO$_3$ and the layered perovskite superconductor, Sr$_2$RuO$_4$ by fitting to all-electron full-potential local density band structures obtained by the…
We present an implementation in a linear-scaling density-functional theory code of an electronic enthalpy method, which has been found to be natural and efficient for the ab initio calculation of finite systems under hydrostatic pressure.…
Two-dimensional electron or hole systems in semiconductors offer the unique opportunity to investigate the physics of strongly interacting fermions. We have measured the 1/f resistance noise of two-dimensional hole systems in high mobility…
Controlling the Mott transition through strain engineering is crucial for advancing the development and application of memristive and neuromorphic computing devices. Yet, Mott insulators are heterogeneous due to intrinsic phase boundaries…
Reducing the contact resistance of field-effect transistors based on two-dimensional materials is one of the key improvements required to enable the integration of such transistors in an advanced semiconductor manufacturing process.…
A coherent state representation for the electrons of ordered antiferromagnets is used to derive effective Hamiltonians for the dynamics of holes in such systems. By an appropriate choice of these states, the constraint of forbidden double…
Model order reduction provides low-complexity high-fidelity surrogate models that allow rapid and accurate solutions of parametric differential equations. The development of reduced order models for parametric \emph{nonlinear} Hamiltonian…
A physics-based compact model for silicon gate-all-around (GAA) nanowire tunneling FETs (NW-tFETs) with good accuracy has been developed by considering Phonon-Assisted Tunneling (PAT) and transition from Quantum Capacitance Limit (QCL) to…
This work proposes an adaptive structure-preserving model order reduction method for finite-dimensional parametrized Hamiltonian systems modeling non-dissipative phenomena. To overcome the slowly decaying Kolmogorov width typical of…
Nanoscale semiconductor materials have been extensively investigated as the channel materials of transistors for energy-efficient low-power logic switches to enable scaling to smaller dimensions. On the opposite end of transistor…
We propose a novel approach to optimize the design of heterogeneous materials, with the goal of enhancing their effective fracture toughness under mode-I loading. The method employs a Gaussian processes-based Bayesian optimization framework…
Characterizing long-range electric fields and built-in potentials in functional materials at nano- to micrometer scales is of supreme importance for optimizing devices. E.g., the functionality of semiconductor heterostructures or battery…