Optimization of Measurement Scheme for Neutral Atom Quantum Computers
Session Number
Project ID: CMPS 30
Advisor(s)
Dr. Tirthak Patel, Rice University
Discipline
Computer Science
Start Date
17-4-2024 8:35 AM
End Date
17-4-2024 8:50 AM
Abstract
With the introduction of Quantum Computers, multiple methods have arisen that focus on simulating Quantum Computers. The most common and popular way many of the largest Quantum Computers are built is with superconducting qubits, similar to those built at places such as Google and IBM. Neutral Atom Technology is a quantum computer that utilizes neutral atoms as qubits. By shining lasers at the atom, the energy level of an atom can be increased, allowing the atom to enter a state of excitement. Since each atom has a wide range of excited states, this is a great medium to store and process quantum information. However, this method isn’t popular due to the computational costs it brings. To address this computational challenge, 5 policies were created to help assess which method allowed for the most accurate results while costing the least computational power. By running simulations of each of these policies and comparing the statistical data with the results, we are able to assess and find the best heuristics for running simulations on Neutral Atom Quantum Computers.
Optimization of Measurement Scheme for Neutral Atom Quantum Computers
With the introduction of Quantum Computers, multiple methods have arisen that focus on simulating Quantum Computers. The most common and popular way many of the largest Quantum Computers are built is with superconducting qubits, similar to those built at places such as Google and IBM. Neutral Atom Technology is a quantum computer that utilizes neutral atoms as qubits. By shining lasers at the atom, the energy level of an atom can be increased, allowing the atom to enter a state of excitement. Since each atom has a wide range of excited states, this is a great medium to store and process quantum information. However, this method isn’t popular due to the computational costs it brings. To address this computational challenge, 5 policies were created to help assess which method allowed for the most accurate results while costing the least computational power. By running simulations of each of these policies and comparing the statistical data with the results, we are able to assess and find the best heuristics for running simulations on Neutral Atom Quantum Computers.