On September 29, IBM reported on a survey conducted with Vanguard Financial Asset Management Company, a quantum computing company that optimizes the construction of its investment portfolio.
The experiment pointed out one of the most demanding issues in the financial sector. They achieve real profitability and risk goals Follow multiple restrictions.
To do this, they applied a technique called the “Sampling-based Variational Quantum Algorithm” (VQA). Combine quantum and classic resources The announcement shows that we find rough solutions to complex problems.
How did these quantum “VQA” algorithms work and how were they applied in this experiment?
Quantum computers are not “perfect” or errors yet. But there are already ways to use them Combine them with a classic computer.
One of these forms is the quantum mutation algorithm (VQA). They act as “mixed teams”: The quantum part explores lands with very large potential, while the classic part improves and corrects the results.
These algorithms are trained in stages using simple, flexible quantum circuits with error-reducing techniques.
That’s why they are suitable for this early stage of quantum computing. It appears that Rookie Explorer uses a drone (quantum part) to view the entire map from above, and with the help of a guide (classic part), selecting the best route.
The idea, led by the scope of IBM and Vanguard’s experiments, was implemented as follows:
- This study used 109 out of the 133 qubits of the IBM Quantum Heron R1 processor (basic quantum computing units such as bits on traditional computers).
- Additionally, up to 4,200 “logic doors” (basic quantum operation) circuits were executed.
- After collecting a sample of the possible solution for the quantum part, We applied classic methods to hone and improve these results.
What were the results of the experiment?
Hybrid quantum classical computing method has been applied Wallet construction on bond stock exchanges (ETFs)and use a classic solution called Cplex, using as a reference. This best solves such problems on a reduced scale.
The results revealed “promising indicators” and “flows.” Quantum classical work has consistently surpassed its To a purely classic local search approach, especially when the size of the problem increases.
This advantage is the integration of quantum and classical resources. It can bring great benefits to complex financial tasksIBM’s statement said noise-related challenges still need to be aware of, but are open midway to future applications in asset management.
These tests with quantum and trading were not the first of its kind. As Cryptonotics explained on September 25th, IBM was already working with HSBC Bank in quantum trading trials applied to bonds.
bank Improvements to traditional methods have been reportedindicating the growing interest in the financial sector in these technologies.
As quantum computers grow and these algorithms mature, this hybrid combination can overcome classical methods with complex problems and many limitations.
