• Corpus ID: 246063477

Lecture Notes on Quantum Algorithms for Scientific Computation

  title={Lecture Notes on Quantum Algorithms for Scientific Computation},
  author={Lin Lin},
  • Lin Lin
  • Published 20 January 2022
  • Computer Science, Physics
  • ArXiv
This is a set of lecture notes used in a graduate topic class in applied mathematics called ``Quantum Algorithms for Scientific Computation'' at the Department of Mathematics, UC Berkeley during the fall semester of 2021. These lecture notes focus only on quantum algorithms closely related to scientific computation, and in particular, matrix computation. The main purpose of the lecture notes is to introduce quantum phase estimation (QPE) and ``post-QPE'' methods such as block encoding, quantum… 
FABLE: Fast Approximate Quantum Circuits for Block-Encodings
This paper proposes FABLE, a method to generate approximate quantum circuits for block-encodings of matrices in a fast manner, and benchmarks the method for Heisenberg and Hubbard Hamiltonians, and Laplacian operators to illustrate that they can be implemented with a reduced gate complexity without approximation error.
Double-bracket flow quantum algorithm for diagonalization
A quantum algorithm for preparing eigenstates of quantum systems is presented which makes use of only forward and backward evolutions under a prescribed Hamiltonian and phase flips. It is based on the
A Gauss-Newton based Quantum Algorithm for Combinatorial Optimization
A Gauss-Newton based quantum algorithm (GNQA) for combinatorial optimization problems that, under optimal conditions, rapidly converges towards one of the optimal solutions without being trapped in local minima or plateaus is presented.
Gravitational wave matched filtering by quantum Monte Carlo integration and quantum amplitude amplification
An exponential reduction of the qubit number is achieved compared with Gao et al.