A glance at quantum computing

As the common saying goes, “if you keep doing what you’ve been doing, you’ll keep getting what you’ve been getting,” in the absence of external influences, of course. Expecting a different outcome for the same input is insanity, as Albert Einstein has been quoted to say. So, if we keep crunching numbers the way we’ve […]

As the common saying goes, “if you keep doing what you’ve been doing, you’ll keep getting what you’ve been getting,” in the absence of external influences, of course. Expecting a different outcome for the same input is insanity, as Albert Einstein has been quoted to say. So, if we keep crunching numbers the way we’ve been doing for the past sixty years, we’ll keep shying away from attacking the biggest computational challenges of our time. By “the way we’ve been doing for the past sixty years,” I don’t mean we haven’t made strides in speeding up computation, for the reality of Moore’s law will quickly invalidate such a suggestion. Moreover, I have written extensively on supercomputing in this column in Daily Trust.
What I am saying is that we have not achieved much improvement in the basic manner in which computers work – the framework of binary operations, that is. Quantum computing (QC) might just foot the bill and bring to us the much needed novelty to solve our humongous computing problems. Last week’s issue of The Economist, the British business magazine, carries an article on the topic, focusing on recent accelerated business interests.
So, how is QC different from the traditional way that we compute? The traditional computer does everything in terms of ones and zeroes. Thus, we have two, or binary, states: 0 and 1 (or logically “off” and “on”). Thus, instructions and the data they operate on, must eventually be converted to strings of 0’s and 1’s. The conversion of data to the binary system is a secondary school exercise – i.e., straight forward.
Quantum computing uses the laws of quantum mechanics in physics to process information. A quantum computer uses quantum bits, abbreviated “qubits,” which is a system that encodes the one and the two into two distinguishable quantum states. However, quantum particles behave “randomly” (stochastically or probabilistically, in grown-up’s terminologies). Therefore, we can exploit the fact that a quantum system can be in multiple states at the same time. In other words, something can be “here” and “there,” or “up” and “down” at the same time, in the words of the Institute of Quantum Computing (IQC) at the University of Waterloo in Canada. The ability of a quantum system to be in multiple states at the same time is referred to as superposition.
The existence of an extremely strong correlation between quantum particles is also exploited in QC. That is, two quantum particles remember each other’s locations in space and time, no matter the distance of separation – even when placed at opposite sides of the universe! This connection which, by the way, boggles the mind, is referred to as entanglement. Thus, the superposition and entanglement phenomena enable a quantum computer to process an inordinately huge number of calculations simultaneously, compared to just one at a time for traditional computers. However, coming up with the algorithms that exploit these features is a challenge.
The list of possibilities with quantum computers relative to traditional computers is fairly long. The use in cryptography is particularly noteworthy. While any computer can multiply two fairly large numbers, breaking a large number (say with 500 digits) into its factors is presently only in the (potential) purview of quantum computers. Thus, encryption technologies exploit the difficulty of using traditional computers to factor large numbers. According to IQC, “In fact, the difficulty of factoring big numbers is the basis for much of our present day cryptography. It’s based on math problems that are too tough to solve. RSA encryption, the method used to encrypt your credit/ATM card number when you’re shopping online, relies completely on the factoring problem.” (Encryption has to do with “scrambling” data so that only those who know the code can decrypt it. The most popular encryption algorithm is called RSA algorithm; which is named after the initials of the last names of its inventors. It was first described in 1977 by Ron Rivest, Adi Shamir and Leonard Adleman, then students at the Massachusetts Institute of Technology.)
Amongst other advantages of QC is the ability to accurately simulate physics at the atomic level, which could speed up the rate at which drugs are developed and provide better ways of removing carbon dioxide from the atmosphere. Image and face recognition technologies, as well as the ability to handle BIG DATA, are other highly attractive promises of QC. However, QC is not cure-all! As pointed out by The Economist, compared to traditional computing, downloading web pages will not go faster with QC, nor will QC enhance graphics processing in computer games.
Who’s funding QC research? Well, try Google, IBM, Hewlett-Packard (HP), and Microsoft, from the commercial side. As expected, the United States government is funding QC projects, via The National Aeronautics and Space Administration (NASA). The crypto side of QC appeals to the United States’ National Security Agency (NSA), where the development of robust, error-free qubits is of interest.
A precise answer to what should constitute the qubits in QC seems to be the biggest issue confronting the technology. Various groups scattered all over the world are working hard to solve this problem. Nitrogen atoms embedded in diamonds are being studied, as are photon particles – which make up light, and the use of a semiconductor. The semiconductor route will be attractive if the semiconductor can be laid on semiconductor chips already in use in traditional computers. This will shorten the time-to-market relative to that for the contending approaches.
Bottom line Commercial quantum computers, with all their promises, might surface in the near future.