The first quantum computers are expected to perform well on quadratic optimisation problems. In this paper a quadratic problem in finance is taken, the Portfolio Optimisation problem. Here, a set of assets is chosen for investment, such that the total risk is minimised, a minimum return is realised and a budget constraint is met. This problem is solved for several instances in two main indices, the Nikkei225 and the S&P500 index, using the state-of-the-art implementation of D-Wave’s quantum annealer and its hybrid solvers. The results are benchmarked against conventional, state-of-the-art, commercially available tooling. Results show that for problems of the size of the used instances, the D-Wave solution, in its current, still limited size...
We report the Atos Q-score for D-Wave's quantum devices, classical algorithms and hybrid quantum-cla...
We benchmark the quantum processing units of the largest quantum annealers to date, the 5000+ qubit ...
We briefly review various computational methods for the solution of optimization problems. First, se...
The first quantum computers are expected to perform well on quadratic optimisation problems. In this...
In this work, we introduce a new workflow to solve portfolio optimization problems on annealing plat...
We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We de...
This paper proposes a highly efficient quantum algorithm for portfolio optimisation targeted at near...
The prediction of financial crashes in a complex financial network is known to be an NP-hard problem...
49 pages, 4 figuresQuantum computers are expected to have substantial impact on the finance industry...
Matching electricity demand and supply by decentralised generators will be very important in the nea...
An approach to solve combinatorial optimization problems on a D-Wave Quantum Annealer while using a ...
The exploitation of quantum mechanical principles seems to provide a decisive advantage over classic...
Quantum computing has the potential to revolutionize the way hard computational problems are solved ...
The D-Wave machine is a powerful annealer based on superconducting qubits to attack complex optimiza...
Quantum annealing is getting increasing attention in combinatorial optimization. The quantum process...
We report the Atos Q-score for D-Wave's quantum devices, classical algorithms and hybrid quantum-cla...
We benchmark the quantum processing units of the largest quantum annealers to date, the 5000+ qubit ...
We briefly review various computational methods for the solution of optimization problems. First, se...
The first quantum computers are expected to perform well on quadratic optimisation problems. In this...
In this work, we introduce a new workflow to solve portfolio optimization problems on annealing plat...
We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We de...
This paper proposes a highly efficient quantum algorithm for portfolio optimisation targeted at near...
The prediction of financial crashes in a complex financial network is known to be an NP-hard problem...
49 pages, 4 figuresQuantum computers are expected to have substantial impact on the finance industry...
Matching electricity demand and supply by decentralised generators will be very important in the nea...
An approach to solve combinatorial optimization problems on a D-Wave Quantum Annealer while using a ...
The exploitation of quantum mechanical principles seems to provide a decisive advantage over classic...
Quantum computing has the potential to revolutionize the way hard computational problems are solved ...
The D-Wave machine is a powerful annealer based on superconducting qubits to attack complex optimiza...
Quantum annealing is getting increasing attention in combinatorial optimization. The quantum process...
We report the Atos Q-score for D-Wave's quantum devices, classical algorithms and hybrid quantum-cla...
We benchmark the quantum processing units of the largest quantum annealers to date, the 5000+ qubit ...
We briefly review various computational methods for the solution of optimization problems. First, se...