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Sentient artificial intelligence, computers accurately predicting financial market trends, impossible to hack cybersecurity systems, new medicines, and more efficient solar cells. These all represent the potential impact quantum computers could have on everyday life. Imagine the most powerful computer in the universe. Now imagine building a trillion identical copies, each operating in a different parallel dimension. These analogies demonstrate the kind of processing power quantum computing can bring to our lives.
Financial trading remains one of the most volatile and unpredictable sectors in the world. Quantum computing has the potential to aid a trader in mapping out the complete lifecycle of a market, accurately predicting the highest yielding trades and any market crashes. How is this possible? The answer lies in looking at two quantum algorithms – Grover and Shaw.
Let’s apply the Grover algorithm first. When asked to find a specific data set within an unsorted list, a classical computer would take much longer to find it then a quantum computer would. For example, if we gave a classical computer an unsorted list of ‘K’ items (‘K’ representing all the items), to search for a specific item in this list, the computer would take on average K/2 searches.If it still couldn’t find the item, the computer would take K searches.
Now let’s apply Grover’s algorithm (GA). Instead of K/2 searches, the quantum computer takes only the square root of K searches. Therefore, if a K list has 1 billion items, then a GA search would only require the square root of 1 billion searches. This means only 31,623 searches compared to the 500,000,000 searches a classical computer would perform. If you apply this to financial modeling where a trader is examining a large data set and identify a specific trade to buy or sell, using quantum computing would enable them to find that trade far quicker then classical computing would. Financial trends instantly become easier to see and more accurate to predict.
Shor’s algorithm is slightly different but has an equally useful application in finance. We know that any integer number can be broken down into a product of prime numbers, but finding the prime factors is always believed to be an almost insurmountable problem using conventional computing. If we apply this to banking, our current cyber security systems and online transactions assume that factoring integers of 1,000 or more digits is impossible.
However, quantum computing makes it possible. Shor’s algorithm posits a polynomial-time quantum algorithm where you can factor integers beyond 1,000 or more digits. This is a radically challenging assumption for the security of online transactions, as it means a quantum computer would be able to bypass banking security incredibly quickly.
Chemical reactions are essentially quantum in nature. They form super-positioned states meaning a classical computer that deals only in 1s and 0s would take days or even weeks to work out the energy of a molecule. Illustrating this in binary terms, a quantum computer would calculate the energy of a propane molecule in seconds simply because it can see the states that are 1s, 0s, both 1s and 0s, and the states in between. For example, proteins consist of long strains of molecules that may or may not become important biological components of an existing or new disease.
A quantum calculation could potentially read all the permeations of a protein. Imagine the impact this could have on medical research and drug creation? Instead of waiting years whilst new drugs are tested – each test being laboriously performed and documented before the correct chemical reaction is found – a quantum test could enable an exponential amount of molecule simulations leading us to find the right chemical reactions in as little as minutes. The challenge lies in building a quantum computer capable of performing these calculations. Fortunately, scientists at Los Alamos National Laboratory believe they are close.
The quantum-to-classical transition occurs when you add more and more particles to a quantum system, such that the weird quantum effects go away and the system starts to behave more classically. For these systems, it's essentially impossible to use a classical computer to study the quantum-to-classical transition. We could study this with our algorithm, and a quantum computer consisting of several hundred qubits, which we anticipate will be available in the next few years based on the current progress in the field.
Patrick Coles of the Physics of Condensed Matter and Complex Systems Group at Los Alamos National Laboratory
Our understanding of the laws of physics no longer applies in quantum methodology (a reason many scientists remain irritated and baffled by quantum physics), allowing us to open our minds to possibilities we would never have considered and perhaps enabling us to find better and more effective cures for things like cancer. Simply put, quantum processors would outstrip classical processors by a factor of 1 million or more, leading to speedier and more effective drug research.
The current challenge in quantum computing is in storing and holding onto quantum information (QI). Qubits remain tricky to make because of their superposition state. The wall that scientists continually run into is in getting qubits to react in the specific ways we want them to, enabling us to do things like cure cancer. Superconducting materials, trapped ions, and even individual neutral atoms just cannot hold on to QI long enough for it to be of any use. MIT scientists devised a new approach by using a cluster of simple molecules made of just two atoms. This method allowed quantum information to be stored for 1 second. Whilst this sounds ridiculously short, it is still much longer thanprevious attempts were able to achieve.
The potential impact a quantum computer could have on our lives remains exciting and fascinating. With quantum computing experiments taking place almost every day now by companies, including Google and IBM, we might be on the cusp of a new technological evolution.