Solving combinatorial optimization problems efficiently is a major stake in the industry. Thanks to the power of quantum computing, it is nowadays possible to prepare, with implementation on small datasets, the quantum machine learning algorithms that will solve these problems for the next generations of quantum computers.

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The Quantum Prince in the Kingdom of Finance

                Figure 1 : Simulations                                                       Figure 2: Simulation Selected


                   Figure 3: Real Data

This blog has been authored by Aditya Bothra and Vijayaraghavan V from Infosys Ltd.

References:

1.       A.I. Adekitan, Monte Carlo Simulation

https://www.researchgate.net/publication/326803384_MONTE_CARLO_SIMULATION

2.       Pooja Rao, Kwangmin Yu, Hyunkyung Lim, Dasol Jin, Deokkyu Choi, 

Quantum amplitude estimation algorithms on IBM quantum devices, https://arxiv.org/abs/2008.02102

3.       Ashley Montanaro, Quantum speedup of Monte Carlo methods, https://arxiv.org/abs/1504.06987

4.       X.Fu, L.Riesebos, L.Lao, C.G.Almudever, F.Sebastiano, R.Versluis, E.Charbon, K.Bertels, 

        The engineering challenges in quantum computing  

        https://www.researchgate.net/publication/316948252_The_engineering_challenges_in_quantum_computing

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