A5059788363- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Quantum chaos and dynamical systems
- Quantum-Dot Cellular Automata
- Scientific Research and Discoveries
- Advanced Memory and Neural Computing
- Plasma Diagnostics and Applications
- Quantum many-body systems
Michigan State University
2020-2024
We present a stochastic quantum computing algorithm that can prepare any eigenvector of Hamiltonian within selected energy interval $[E-\epsilon, E+\epsilon]$. In order to reduce the spectral weight all other eigenvectors by suppression factor $\delta$, required computational effort scales as $O[|\log \delta|/(p \epsilon)]$, where $p$ is squared overlap initial state with target eigenvector. The method, which we call rodeo algorithm, uses auxiliary qubits control time evolution minus some...
Quantum state preparation by adiabatic evolution is currently rendered ineffective the long implementation times of underlying quantum circuits, comparable to decoherence time present and near-term devices. These can be significantly reduced realizing these circuits with custom gates. Using classical computing, we model output a realistic two-qubit processor implementing two-spin system means This modeled then compared results simulations solving same problem on IBM (IBMQ) systems. When used...
In the current era of noisy quantum devices, there is a need for algorithms that are efficient and robust against noise. Towards this end, we introduce projected cooling algorithm computation. The able to construct localized ground state any Hamiltonian with translationally-invariant kinetic energy interactions vanish at large distances. term "localized" refers localization in position space. method can be viewed as analog evaporative cooling. We start an initial support over compact region...
This thesis investigates quantum algorithms for eigenstate preparation, with a focus on solving eigenvalue problems such as the Schrodinger equation by utilizing near-term computing devices. These are ubiquitous in several scientific fields, but more accurate solutions specifically needed prerequisite many simulation tasks. To address this, we establish three methods detail: adiabatic evolution optimal control, Rodeo Algorithm, and Variational Algorithm. The first method explored is...
The rodeo algorithm is an efficient for eigenstate preparation and eigenvalue estimation any observable on a quantum computer. This makes it promising tool studying the spectrum structure of atomic nuclei as well other fields many-body physics. only requirement that initial state has sufficient overlap probability with desired eigenstate. While exponentially faster than well-known algorithms such phase adiabatic evolution preparation, yet to be implemented actual device. In this work, we...