By Bobby Corpus, President, OneQuantum Philippines

In 2012, an article appeared in the Harvard Business Review that says data scientists are the sexiest job of the 21st century. That’s about to change.

Looking at LinkedIn, you can say that data science roles are now commonplace in big organizations. Data science tools in machine learning are now commoditized so that anyone can, for example, create their own service to extract text from images just by using cloud-based services. However advanced the algorithms may be in data science, they are still based on classical bits, that is, bits that have a definite value of either 0 or 1.

We are at the dawn of a new era of computing, a paradigm shift from our everyday knowledge of computing. In this era, a different kind of computer is being built. And with it, a different way of thinking about algorithms and a different skill set is involved. We are at the dawn of Quantum Computing.

IDC forecasts worldwide quantum computing market to grow to $8.6 billion in 2027
IBM unveils 127-Qubit quantum processor

What’s all the excitement in Quantum Computing?

There are at least two very important algorithms that got the world very excited about Quantum Computing. They are Shor’s algorithm and Grover’s algorithm.

It has been demonstrated theoretically that Shor’s algorithm can decrypt encryptions based on RSA and elliptic curves. These cryptosystems are currently used to secure our online shopping or when we transact with our bank online. So far, the number of logical qubits of existing quantum computers is less than 100 so we have nothing to worry about for now. But what is important to realize is that these cryptosystems are based on mathematical properties that make it extremely hard to decrypt them. For example, the RSA encryption is based on the hardness to factor a very large number. It would take about 300 trillion years to decrypt a 2048-bit RSA encryption. If a quantum computer can solve this, what other problems can it solve?

Grover’s algorithm is a quantum search algorithm. Searching is something we do daily. Can you imagine life without Google?

Suppose you’re given a set of data containing an alphabetical list of names and their corresponding phone numbers. Finding the phone number given a name is very fast. If you have a million rows on this list, it will take you about 20 tries in the worst case to realize that the name you are looking for is not in the list. Now given the same data, what if we try to find the name given a phone number? Without an index, you will need to examine every entry in the list of 1 million rows if the phone number you’re looking for turns out to be at the end of the list. Grover’s algorithm can find your number in only 1,000 tries, that’s a quadratic speed up. Because of this, Grover’s algorithm is extensively used in machine learning algorithms like k-medians, neural networks, support vector machines, etc.

That’s the excitement in Quantum Computing.

A different kind of machine

All information in this world can be encoded as a series of 1’s and 0’s. This is called binary encoding. Each 1 or 0 is called a bit. When you examine it a bit, it has a definite value. It’s either 0 or 1. In quantum computing, the bit is now replaced by a qubit. What’s special about a qubit is that it not only represents a value of 0 or 1, but it can also have both values at the same time. This special property allows the quantum computer to perform mathematical operations on all values the qubits can assume at once. This quantum parallelism is also known as the superposition of states.

With this feature of quantum computing, how do we harness this to compute hard problems?

A different way of thinking

Unlike classical computing where you get a definite answer, quantum computing depends on the probability of the answer occurring. This means you don’t get the same answer the next time you execute the algorithm. This might be confusing. That’s quantum mechanics rearing its head for you. As physicist extraordinaire Richard Feynman (who proposed the quantum computer in the 1980s) famously says “nobody understands quantum mechanics.”

So, how do you get the answer to your computation if you don’t get the same answer in the next run? In quantum computing, you apply what is known as gates that will drive the computation so that the correct answer will result in high probability. You can make the probability as close as possible to 1 to give you the confidence that you got the correct answer.

Different algorithms

Having to perform mathematical computation for all possible inputs at once and driving the computation to increase the probability of getting the answer means that the computation needs a different kind of algorithm than what we are used to.

Shor’s algorithm is a good example. It is the algorithm that can crack the RSA and elliptic curve encryption, given we have sufficient logical qubits. The algorithm starts with enumerating at once all possible numbers the qubits can assume (this is not possible with a classical computer) and applying quantum gates that will allow you to compute what is known as the period. From there, you can crack the encryption.

These algorithms are only applicable if you have a quantum computer since you need that superposition of states.

Different skill set

To come up with algorithms to solve hard problems using a quantum computer needs a different kind of skill set that is at the moment extremely rare. Every gate that you see in a quantum circuit can be translated into mathematics. When in mathematical form, you can prove if your algorithm can give you the correct answer and with what probability and how many times you need to execute the algorithm to get the answer. Since quantum computing is still in its infancy, to design algorithms, you would need people who have mathematical maturity. For example, to realize that RSA and Elliptic Curve Cryptography, two entirely different cryptosystems, have the same abstract mathematical structure and can therefore be decrypted using the same algorithm (Shor’s algorithm) is mathematical maturity. They need to be able to formulate the problem as a set of equations and map them into a form that can be run on a quantum computer. They would also need to be creative since designing quantum algorithms is not that obvious due to a different kind of thinking required.

In the future, these algorithms will be available as components that you just use out of the box like what’s happening right now in machine learning. However, for now, we need those skill sets to design novel quantum algorithms that will one day be packaged as reusable components.

So what’s the sexiest skill in the future? It’s the quantum computing skill.

There is a lot to Quantum Computing but we can only cover a small portion of it in the hope of getting you curious and excited to dig deeper into it. We, the OneQuantum community, are here to help you in that journey.

OneQuantum Philippines is a local chapter of the OneQuantum global community. It aims to make the Philippines a quantum-ready nation by educating students at an early age so it would be easy for them to acquire quantum computing skills.