Fast Forward Method On Landau-Majorana-Zener System

Quantum computers have data in the form of quantum bits (qubits), which are 0 and 1 simultaneously. This 0 and 1 state is the electron spin state on the quantum computer, namely spin up and spin down. Qubits are very sensitive to environmental disturbances, so it is necessary to accelerate the adiabatic dynamics so that the system's coherence is not disturbed by environmental interactions. These spin dynamics can be accelerated using the fast forward method, which uses an additional phase to drive the spin adiabatically. The adiabatic state is a state where the dynamics of a system have the same characteristics as the initial state after the dynamics take place. This research was conducted by qualitatively reviewing physical theory and conducting literature studies on previous research on the fast-forward method and the Landau-Majorana-Zener system. The results of this study obtained wave function solutions, regularization terms, and additional Hamiltonians in the Landau-Majorana-Zener system to accelerate adiabatic spin dynamics so that spin dynamics on quantum computers are not disturbed by the environment. After adding additional Hamiltonian adiabatic dynamics in the Landau-Majorana Zener system can be maintained but requires considerable energy. The magnetic field needed to create the same graph as the wave function graph before adding Hamiltonian, B0 = 100 Tesla. The energy required to accelerate the adiabatic spin dynamics is large, so the cost is also quite large. Therefore, efforts are needed to minimize the energy required to accelerate the adiabatic spin dynamics.

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Journal
Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Published
2024-12-30
DOI
https://doi.org/10.24042/jipfalbiruni.v13i2.24576
Primary Topic
Numerical methods for differential equations
Type
article
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article

Fast Forward Method On Landau-Majorana-Zener System

Dedy Hamdani, Iwan Setiawan, Albet Karuniawan
Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Numerical methods for differential equations
article

Fast Forward Method On Landau-Majorana-Zener System

Dedy Hamdani, Iwan Setiawan, Albet Karuniawan
article en

Abstract

Quantum computers have data in the form of quantum bits (qubits), which are 0 and 1 simultaneously. This 0 and 1 state is the electron spin state on the quantum computer, namely spin up and spin down. Qubits are very sensitive to environmental disturbances, so it is necessary to accelerate the adiabatic dynamics so that the system's coherence is not disturbed by environmental interactions. These spin dynamics can be accelerated using the fast forward method, which uses an additional phase to drive the spin adiabatically. The adiabatic state is a state where the dynamics of a system have the same characteristics as the initial state after the dynamics take place. This research was conducted by qualitatively reviewing physical theory and conducting literature studies on previous research on the fast-forward method and the Landau-Majorana-Zener system. The results of this study obtained wave function solutions, regularization terms, and additional Hamiltonians in the Landau-Majorana-Zener system to accelerate adiabatic spin dynamics so that spin dynamics on quantum computers are not disturbed by the environment. After adding additional Hamiltonian adiabatic dynamics in the Landau-Majorana Zener system can be maintained but requires considerable energy. The magnetic field needed to create the same graph as the wave function graph before adding Hamiltonian, B0 = 100 Tesla. The energy required to accelerate the adiabatic spin dynamics is large, so the cost is also quite large. Therefore, efforts are needed to minimize the energy required to accelerate the adiabatic spin dynamics.

Jurnal Ilmiah Pendidikan Fisika Al-BiruniVol. 13(2)
University of Bengkulu (ID)
Openalex Percentile: Top 60%
Numerical methods for differential equations
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Fast Forward Method On Landau-Majorana-Zener System — Dedy Hamdani, Iwan Setiawan, et al. · Jurnal Ilmiah Pendidikan Fisika Al-Biruni (2024) | TGRS Research Map | TGRS