Improving soft magnetic properties in FINEMET-like alloys with Ga addition

Zhu, Qianke; Chen, Zhe; Zhang, Shuling; Li, Qiushu; Jiang, Yong; Wu, Peixuan; Zhang, Kewei

doi:10.1016/j.jmmm.2019.165297

Cited by 12 publications

(4 citation statements)

References 24 publications

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“…typical in these phases [10,[17][18][19]. QMC algorithm, on the other hand, runs into the infamous fermionic sign problem [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Simulations of Frustrated Ising Hamiltonians with Quantum Approximate Optimization

Lotshaw,

Xu,

Khalid

et al. 2022

Preprint

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Novel magnetic materials are important for future technological advances. Theoretical and numerical calculations of ground state properties are essential in understanding these materials, however, computational complexity limits conventional methods for studying these states. Here we investigate an alternative approach to preparing materials ground states using the quantum approximate optimization algorithm (QAOA) on near-term quantum computers. We study Ising spin models on unit cells of square, Shastry-Sutherland, and triangular lattices, with varying field amplitudes and couplings in the material Hamiltonian. We find relationships between the theoretical QAOA success probability and the structure of the ground state, indicating that only a modest number of measurements ( < ∼ 100) are needed to find the ground state of our nine-spin Hamiltonians, even for parameters leading to frustrated magnetism. We further demonstrate the approach in calculations on a trapped-ion quantum computer and succeed in recovering each ground state of the Shastry-Sutherland unit cell with probabilities close to ideal theoretical values. The results demonstrate the viability of QAOA for materials ground state preparation in the frustrated Ising limit, giving important first steps towards larger sizes and more complex Hamiltonians where quantum computational advantage may prove essential in developing a systematic understanding of novel materials.

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“…typical in these phases [10,[17][18][19]. QMC algorithm, on the other hand, runs into the infamous fermionic sign problem [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Simulations of Frustrated Ising Hamiltonians with Quantum Approximate Optimization

Lotshaw,

Xu,

Khalid

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Quantum material properties are intrinsically related to the structure of the ground states. However, exact ground states are notoriously challenging to calculate classically, requiring the field to resort to using semi-classical limits [2][3][4][5] or fully quantum approaches with restricted applicability [6][7][8][9][10][11][12]. New, fully quantum computational tools are required to understand current problems including frustrated two-dimensional quantum magnets currently explored by bulk neutron scattering and thin film susceptibility [13,14].…”

Section: Introductionmentioning

confidence: 99%

Simulations of frustrated Ising Hamiltonians using quantum approximate optimization

Lotshaw

Khalid

et al. 2022

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

Novel magnetic materials are important for future technological advances. Theoretical and numerical calculations of ground-state properties are essential in understanding these materials, however, computational complexity limits conventional methods for studying these states. Here we investigate an alternative approach to preparing materials ground states using the quantum approximate optimization algorithm (QAOA) on near-term quantum computers. We study classical Ising spin models on unit cells of square, Shastry-Sutherland and triangular lattices, with varying field amplitudes and couplings in the material Hamiltonian. We find relationships between the theoretical QAOA success probability and the structure of the ground state, indicating that only a modest number of measurements ( ≲ 100 ) are needed to find the ground state of our nine-spin Hamiltonians, even for parameters leading to frustrated magnetism. We further demonstrate the approach in calculations on a trapped-ion quantum computer and succeed in recovering each ground state of the Shastry-Sutherland unit cell with probabilities close to ideal theoretical values. The results demonstrate the viability of QAOA for materials ground state preparation in the frustrated Ising limit, giving important first steps towards larger sizes and more complex Hamiltonians where quantum computational advantage may prove essential in developing a systematic understanding of novel materials. This article is part of the theme issue ‘Quantum annealing and computation: challenges and perspectives’.

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“…Under laboratory conditions, annealing is most often performed in vacuum or in an inert environment (e.g., in He, Ar, N 2 , H 2 , and others), whereas this is carried out in air in industrial production. To improve the soft magnetic properties, it was attempted to vary the concentration of elements in the Finemet alloy [8][9][10][11][12][13][14][15][16], to substitute them with other elements [17][18][19][20][21][22][23][24], to perform annealing of the initial quasi-amorphous alloy for various times [25] and at various temperatures [8], in a magnetic field or without it [26][27][28][29][30][31], as well as under a pressure [32] or a tensile load [33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Effect of Temperature of Long Annealing on the Structure and Magnetic Properties of Nanocrystalline FeSiNbCuB Alloy

et al. 2021

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The dependence of soft magnetic properties of the Fe 73.5 Si 13.5 Nb 3 Cu 1 B 9 alloy on the 2-hour air annealing temperature T an at temperatures from 520 to 620°C is studied. It is shown that the magnetic hysteresis loop is significantly broadens and becomes more inclined, and the Curie temperature of the amorphous matrix surrounding α-FeSi nanocrystals decreases with increasing T an . The atomic structure and phase composition of alloy samples are studied by transmission X-ray diffraction. After annealing at temperatures to 580°C, nanocrystals contain mostly D0 3 phase (Fe 3 Si stoichiometry) and are ~7 nm in average size. Their relative fraction in the alloy increases with temperature due to additional iron diffusion from the matrix to nanocrystals. After annealings at T an > 600°C, the average nanocrystal size increases, and iron boride crystal reflections appear in X-ray diffraction patterns. Degradation of soft magnetic properties of nanocrystalline Fe 73.5 Si 13.5 Nb 3 Cu 1 B 9 alloy with annealing temperature from 520 to 580°C is explained by a decrease in the silicon concentration in FeSi nanocrystals, which results in an increase in the magnetocrystalline anisotropy.

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Improving soft magnetic properties in FINEMET-like alloys with Ga addition

Cited by 12 publications

References 24 publications

Simulations of Frustrated Ising Hamiltonians with Quantum Approximate Optimization

Simulations of Frustrated Ising Hamiltonians with Quantum Approximate Optimization

Simulations of frustrated Ising Hamiltonians using quantum approximate optimization

Effect of Temperature of Long Annealing on the Structure and Magnetic Properties of Nanocrystalline FeSiNbCuB Alloy

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