Advent Of Quantum Computers Blurring The Line Between Man And Machine

Quantum mechanics is a subject that has the strange property of simultaneously being logically rigorous and yet completely counter-intuitive. So much so, that even a towering intellect like Einstein could never bring himself to accept its principles even though products based on the same exist all around us.

The earliest oddity, identified by Schrodinger, one of the founders of quantum mechanics, is about a hypothetical cat that is neither dead nor alive until someone actually observes it. A similar oddity is that of quantum entanglement, where the behaviour of one particle is instantly affected by the behaviour of another particle, however distant it may be – an example of “spooky” action-at-a-distance. Explaining these phenomena is beyond the scope and temerity of this article and so the reader would have to accept them here in good, almost religious, faith and carry on with the belief that such phenomena have been observed and explained by scientists under the most rigorous experimental circumstances.

Any programmable digital computer that we use – the desktop, the smartphone or the ones at Google – is based on a finite state machine (FSM). It can, at any instant of time, be in one of a large, but finite, number of well-defined states. The state of an FSM is defined by the value stored in each of its memory locations and we know that these can either be 0 or 1. So an FSM with, say, 16 bits of memory could in principle be in any one of 216 states. Any instruction to the FSM changes the value of one or more bits and the FSM moves to a different state. An FSM along with the ability to read binary input, from an infinite tape, and write back on the same tape, is the Turing machine, which is the theoretical basis for any modern computer.

The fundamental principle of computer science is that the world is computable, meaning that any logically decidable problem can be represented and solved on a Turing machine and hence, by extension, on some possibly very powerful, digital computer. This is the basis of our immense belief in computer technology that powers everything from smartphones to artificial intelligence. But even as long back as 1982, Nobel Prize-winning physicist Richard Feynman had questioned this principle because he realised that Turing/FSM-based computers could not solve the problem of simulating the movement of multiple particles, whereas nature was doing it all the time.

Did the quantum mechanical behaviour of nature mean that nature had a computing device that was inherently superior to the Turing machines built by classical computer technology? This is where the concept of a quantum computer was born.

A computer is a state-machine where its state is defined by the collective states of each of its memory locations. In a classical computer, each memory location, or bit, can either be 0 or 1 and certainly not both, but in a quantum computer it can be both 0 and 1 simultaneously – very much like Schrodinger’s cat that was dead and alive at the same time. This is where the going gets really rough for anyone who has spent a lifetime in classical computer science because this is something that is completely counter-intuitive. A memory location, a bit, is a transistor, or switch, made of silicon that is either ON or OFF. How can it be both? Turns out, if you keep aside computer science and open your books on quantum mechanics, it is indeed possible that a body can be in two states at the same time based on the well-established principle of quantum superposition. Now, if we go back to our 16-bit classical computer with its 216 states and replace it with a quantum computer with 16 quantum bits, or qubits, of memory, we have a machine that can be in 216 states simultaneously. If that is not mind-bending enough, all these 216 states will collapse into any one of the states as soon as we try to observe it. It is almost as if nature is playing a game with us, pretending to be classical whereas it is actually quantum.

But why are we obsessed with this counter-intuitive phenomenon? Will it have a drastic improvement on existing digital computer technology? Not really. Your spreadsheet, email, YouTube, eCommerce, smartphone will hardly change, but two things could. First, current cybersecurity systems, which are based on our inability to decompose integers into their prime factors in a reasonable amount of time, could be ripped apart by quantum computers, leaving all passwords vulnerable to hackers. Second, artificial intelligence could be taken to altogether unbelievable levels of sophistication. So quantum computers will soon have a very important role to play – but how far away are we from real, practical systems?

The biggest challenge is the construction of the physical memory locations, and the complexity of the engineering problem is evident from the following: A modern IBM classical computer chip has anything between two and seven billion transistors, each of which can be ON or OFF. The corresponding IBM quantum computer chip, which powers the IBM Quantum Experience machine, has only five, yes just five, qubits of memory that can be in quantum superposition of ON and OFF. Why so? First, the memory locations have to be cooled to near zero Kelvin (minus 273 degrees Celsius, when atoms would stop moving) to exhibit their quantum superposition behaviour. If the cryogenic challenge was not enough, the second challenge is even bigger. Unlike the memory locations of classical computers whose states can be determined by sensing the presence or absence of an electrical voltage, the multiple, superimposed quantum states collapse as soon as any effort is made to observe them. This is as if a room has a house of cards that collapse as soon as the door is opened by the observer, and the observer has to figure out what the house looked like by observing the disposition of the cards on the floor! Since the qubits can never be accessed directly, as in a classical computer with read-and-write statements, they can only be “influenced” indirectly.

To put things in perspective, ENIAC, one of the world’s first first-generation vacuum tube-based classical computers, had 20 memory units, or accumulators in 1945, and a second-generation, transistor-based computer from the University of Manchester had only 200 transistors in 1955. Since then, we have moved through third-generation integrated chips and the current fourth generation of microprocessors have scaled up to billions of transistors, thanks to the inexorable pressure of Moore’s Law. If we remember that even with its 20 memory units, ENIAC was used to solve problems in weather forecasting, atomic energy calculations, wind tunnel design, the current five-qubit IBM machine does not look as hopeless, or helpless, as it seems to be.

Actually, things are a little better off. D-Wave, a Canadian company that has been building quantum computers since 1999, came out with a 128-qubit machine in 2010, a 512-qubit machine in 2012 and a 1000 qubit-machine in 2015. Initially there were some doubts about whether these were quantum machines at all, but after these machines were actually installed and used first by Lockheed Martin at the University of Southern California and later at the Quantum AI Lab of NASA Ames Research Centre by a team from Google, these doubts have receded to a large extent. Even though some doubts persist, there is enough evidence of quantum behaviour or at least great promise that these doubts will be resolved soon. In early 2017, D-Wave announced the sale of its first commercially available $15 million 2000-qubit machine to cybersecurity firm Temporal Defence Systems.

IBM’s five-qubit Quantum Experience is positioned as a general-purpose computer. It could be used for any computational task but would be efficient only if the programme was designed to use quantum properties – a colour TV is useful only if the broadcast is in colour. Very few programmes can do this today, but Shor’s Algorithm, used to crack passwords, is definitely one such. D-Wave systems on the other hand, are designed to solve one class of problems that minimise the weighted sum of a large number of interrelated, or entangled, variables. This may sound restrictive, but the reason why everyone from Google to Temporal is interested is because this class of problems is similar to the ones that occur in artificial neural networks that lie at the heart of systems based on machine learning.

Spectacular progress in machine learning with artificial neural networks using classical computers itself, is rapidly closing the gap between biological and non-biological intelligence or even between carbon and silicon “life forms”. With the advent of quantum computers, one more crucial barrier between the natural world and its man-made, artificial model could break down – as could the increasingly thin line that delineates man from machine. Will this drag man down to the level of machines? Or will these machines push man up towards his eventual union, or Yoga, with the transcendent omniscience that some refer to as God or Brahman?

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