Quantum Computing Today

From how an enzyme works in a biological reaction to how our brain potentially works in metaphysical realms, quantum mechanics may just provide us the answers we have been fumbling in the darkness for so long. Through the quantum superposition and entanglement, nature has its own way to create miracles which may previously seem unfathomable in the classical scale before our eyes.

In theory, because of the superposition possibility of the quantum bits (called Qubits, explained by an earlier blog article on new chip designs), if we can use the qubits to represent computational mechanisms, it should deliver exponentially increased computing power, by an order of millions of times faster than traditional computers. Researchers at World Economic Forum held in Davos, Switzerland in January 2016 expressed great enthusiasms that such technologies will become available and be the disruptive force to the traditional computing and communication technologies by year 2020. It comes with high hopes that quantum computers may bring a giant leap forward in complex computations such as in machine learning and optimization. We may also expect that the future machines can become a lot smarter in a “humanly” way.

Quantum computers are hard to produce because the difficulties to detect the quantum particles or control the quantum state. Some current pioneers of these quantum machine initiatives, either the quantum chips made by IBM or D-Wave machines that Google has invested in, may require special algorithms to operate. Traditional algorithms are not suitable on these quantum designs. Because algorithms can definitely make a significant difference on the performance of the problem-solving of any machine, heated debates and competitions on these new quantum computers are common. The light-year promises in computational power from these quantum machines compared to the classical supercomputers or algorithms have yet been demonstrated, but by theory, that stage is achievable.

New ideas are coming out these years to make these machines capable of handling all conventional computational jobs. We may need it for many current AI algorithms to work faster and better. However the economical or practical judgment of whether we need a sickle to shave the beard is another question. From pure computational standpoints, software simulations of quantum computations are possible and in progress in the technology world today. These simulations can offer significant cost advantage over the hardware solutions before we truly can harness the quantum particles in measurable ways.

The future scenarios will likely be that hardware and software go hand in hand as the evolution of traditional computation has indicated. We hope that not just machines, but all common people will benefit from the fruits of these breakthroughs. By then, advancements in science and technology, and expanded understanding of our universe may well lead us into another period of explorations and new questions on just about everything.