There has been a lot of news about how quantum computers will change computing as we know it. That said, a general-purpose quantum computer that will have the capability of replacing the classical computers we use every day may perpetually be out of reach. At Fidelity, we do not need to wait for a general-purpose quantum computer. There are a few specific types of problems that quantum computers will likely be able to tackle in the near term and optimization problems just so happen to be one of those types of problems. FCAT is positioning Fidelity to be able to leverage this new technology the moment it becomes viable by exploring the optimization algorithms and implementations that have the most potential to deliver value to Fidelity and our customers.
Optimization problems find the best solution out of the universe of possible options. That’s something our classical computers can certainly do, but there are limits such as the number of variables or the number and types of constraints we put on a problem so that the problem can be solved in a reasonable amount of time. A classic example would be running a Monte Carlo simulation to determine if an investor’s portfolio will likely be large enough to last through retirement. A Monte Carlo simulation estimates the likelihood of a particular outcome — in this case, financial security in retirement — by taking the variables that are uncertain (for example, future market performance), assigning them to random values, and then repeatedly running that process many times to show a distribution of likely outcomes. This distribution provides confidence in the likelihood of the desired outcome — in this example, that the portfolio is likely large enough for retirement. This method requires many iterations to be reliable and therefore, a lot of time.
Quantum computing has the potential to change that. With a quantum computer, quantum bits (or qubits) have a partial chance of being a 0 AND a partial chance of 1 (unlike their binary counterparts in standard computers, which can only be one OR the other). That means the qubits can essentially be split in the Monte Carlo simulation, settling the distribution curve and resulting in an answer much faster. To bring this to life, FCAT created the video below illustrating why Monte Carlo simulations run faster on a quantum computer.
Quantum computers are still early in their life cycle, but have already shown potential to positively disrupt the technology that we use today. FCAT is exploring the many ways that this new technology has the potential to impact the financial services industry. Quantum computing has the potential to impact everything from AI and machine learning to random number generation. Keep an eye out for updates from FCAT as we share our journey through the space.
FCAT - How Quantum Computing Will Change How We Solve Optimization Problems
“What’s a Qubit?” is a virtual reality experience designed to teach fundamental building blocks of quantum computing through a virtual reality immersive experience. The experience allows you to fly through a quantum computer at the size of a single...
This Quantum-to-Quantum PoC showcases the ability to optimize the use of different quantum technologies, and also features a hardware-agnostic approach which enables Fidelity to easily switch to new quantum systems as they become available.
