Quantum algorithms offer significant speedup for specific problems, such as factoring large numbers, searching unsorted databases, and simulating quantum systems.

Shor's Algorithm is a quantum algorithm that can factor large integers in polynomial time, providing a significant advantage over classical algorithms.

Grover's Algorithm leverages superposition to search an unsorted database with a time complexity of sqrt(N), providing a quadratic speedup over classical search algorithms.

The Deutsch-Jozsa Algorithm is designed to distinguish between constant and balanced functions by employing a single query to the function.

Simon's Algorithm is used to find hidden periodicities in a sequence with a time complexity of O(N), providing an exponential speedup over classical algorithms.

The Quantum Phase Estimation Algorithm is used to efficiently estimate the phase of a quantum state, enabling the simulation of quantum systems and providing insights into quantum phenomena.

The main hurdle in implementing quantum algorithms is the lack of scalable and reliable quantum computers that can handle the large number of qubits required for practical applications.

QAOA is a quantum algorithm designed to tackle optimization problems by employing a parameterized quantum circuit to approximate the optimal solution.

Quantum machine learning algorithms aim to harness the unique features of quantum mechanics, such as superposition and entanglement, to develop novel machine learning approaches with enhanced capabilities.

Grover's Algorithm is specifically designed to efficiently search for a marked item in an unsorted database, providing a quadratic speedup over classical search algorithms.

One of the significant applications of quantum algorithms in cryptography is their potential to break existing encryption algorithms, such as RSA and ECC, which are widely used for secure communication.

The HHL Algorithm (Harrow-Hassidim-Lloyd Algorithm) is designed to efficiently solve linear systems of equations, providing a significant speedup over classical algorithms for certain problem instances.

Quantum algorithms offer the potential to efficiently find the global optimum for optimization problems, which is often challenging for classical algorithms, especially in high-dimensional search spaces.

The VQE Algorithm (Variational Quantum Eigensolver Algorithm) is designed to efficiently find the ground state energy of a quantum system by employing a parameterized quantum circuit and optimizing its parameters.

The main obstacle in developing quantum algorithms for practical use is the lack of scalable and reliable quantum computers that can handle the large number of qubits required for meaningful applications.