13 Facts About Quantum algorithm

In quantum computing, a quantum algorithm is an algorithm which runs on a realistic model of quantum computation, the most commonly used model being the quantum circuit model of computation.

Similarly, a quantum algorithm is a step-by-step procedure, where each of the steps can be performed on a quantum computer.

Deutsch–Jozsa algorithm solves a black-box problem which probably requires exponentially many queries to the black box for any deterministic classical computer, but can be done with one query by a quantum computer.

The Quantum algorithm determines whether a function f is either constant or balanced.

Bernstein–Vazirani algorithm is the first quantum algorithm that solves a problem more efficiently than the best known classical algorithm.

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Quantum phase estimation algorithm is used to determine the eigenphase of an eigenvector of a unitary gate given a quantum state proportional to the eigenvector and access to the gate.

Since the discrete logarithm problem reduces to Gauss sum estimation, an efficient classical Quantum algorithm for estimating Gauss sums would imply an efficient classical Quantum algorithm for computing discrete logarithms, which is considered unlikely.

Quantum algorithm walk is the quantum analogue of a classical random walk, which can be described by a probability distribution over some states.

Quantum algorithm walks are known to give exponential speedups for some black-box problems.

The Quantum algorithm estimates the result of a scalar measurement on the solution vector to a given linear system of equations.

Quantum approximate optimization algorithm is a toy model of quantum annealing which can be used to solve problems in graph theory.

The algorithm makes use of classical optimization of quantum operations to maximize an objective function.

Variational quantum eigensolver algorithm applies classical optimization to minimize the energy expectation of an ansatz state to find the ground state energy of a molecule.