2021
DOI: 10.48550/arxiv.2110.12354
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Analytical solution for nonadiabatic quantum annealing to arbitrary Ising spin Hamiltonian

Bin Yan,
Nikolai A. Sinitsyn

Abstract: We point to the existence of an analytical solution to a general quantum annealing (QA) problem of finding low energy states of an arbitrary Ising spin Hamiltonian HI by implementing time evolution with a Hamiltonian H(t) = HI + g(t)Ht. We will assume that the nonadiabatic annealing protocol is defined by a specific decaying coupling g(t) and a specific mixing Hamiltonian Ht that make the model analytically solvable arbitrarily far from the adiabatic regime. In specific cases of HI, the solution shows the poss… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(4 citation statements)
references
References 28 publications
(47 reference statements)
0
4
0
Order By: Relevance
“…where C i• is the i th row of matrix C. For all weights, the derivative can be written as ∂L ∂|w = 2C|w + µ|P + λ|R . Setting all derivatives equal to zero leads to the linear system (46). Note: In the first step, Hadamard gates are applied to t qubits (t depends on the desired precision of the representation of the eigenvalues λ i ).…”
Section: Calculating Risk Measures On a Quantum Computermentioning
confidence: 99%
See 3 more Smart Citations
“…where C i• is the i th row of matrix C. For all weights, the derivative can be written as ∂L ∂|w = 2C|w + µ|P + λ|R . Setting all derivatives equal to zero leads to the linear system (46). Note: In the first step, Hadamard gates are applied to t qubits (t depends on the desired precision of the representation of the eigenvalues λ i ).…”
Section: Calculating Risk Measures On a Quantum Computermentioning
confidence: 99%
“…Unfortunately, using the solution described above does not recover the whole speed-up. A quick check of system (46) reveals that its main component is a covariance matrix which is hardly sparse. As a result, s = N and the complexity of the HHL algorithm for portfolio optimization increases to O[N log(N )κ/ ].…”
Section: Calculating Risk Measures On a Quantum Computermentioning
confidence: 99%
See 2 more Smart Citations