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For combinatorial optimization, the quantum approximate optimization algorithm (QAOA) [6] briefly had a better approximation ratio than any known polynomial time classical algorithm (for a certain problem), [7] until a more effective classical algorithm was proposed. [8] The relative speed-up of the quantum algorithm is an open research question.
In quantum computing, the variational quantum eigensolver (VQE) is a quantum algorithm for quantum chemistry, quantum simulations and optimization problems.It is a hybrid algorithm that uses both classical computers and quantum computers to find the ground state of a given physical system.
Qiskit Optimization is an open-source framework that covers the whole range from high-level modeling of optimization problems, with automatic conversion of problems to different required representations, to a suite of easy-to-use quantum optimization algorithms that are ready to run on classical simulators, as well as on real quantum devices ...
Portfolio optimization is the process of selecting an optimal portfolio (asset distribution), out of a set of considered portfolios, according to some objective. The objective typically maximizes factors such as expected return , and minimizes costs like financial risk , resulting in a multi-objective optimization problem.
Quantum computing stocks have emerged as one of 2024's hottest investment themes, with the Defiance Quantum ETF (NASDAQ: QTUM) soaring 49.4% year to date, nearly doubling the S&P 500's robust 24.3 ...
Quantum computers are capable of manipulating high-dimensional vectors using tensor product spaces and thus are well-suited platforms for machine learning algorithms. [21] The quantum algorithm for linear systems of equations has been applied to a support vector machine, which is an optimized linear or non-linear binary classifier.
In quantum computing, a quantum algorithm is an algorithm that runs on a realistic model of quantum computation, the most commonly used model being the quantum circuit model of computation. [ 1 ] [ 2 ] A classical (or non-quantum) algorithm is a finite sequence of instructions, or a step-by-step procedure for solving a problem, where each step ...
Quantinuum's full Quantum Monte Carlo Integration engine is designed to use quantum algorithms to perform estimations more efficiently and accurately than equivalent classical tools, inferring an early-stage quantum advantage in areas such as derivative pricing, portfolio risk calculations and regulatory reporting.