Quantum computing

Quantum computing

After decades of a heavy slog with no promise of success, quantum computing is suddenly buzzing with almost feverish excitement and activity. Nearly two years ago, IBM made a quantum computer available to the world: the 5-quantum-bit (qubit) resource they now call (a little awkwardly) the IBM Q experience. That seemed more like a toy for researchers than a way of getting any serious number crunching done. But 70,000 users worldwide have registered for it, and the qubit count in this resource has now quadrupled. In the past few months, IBM and Intel have announced that they have made quantum computers with 50 and 49 qubits, respectively, and Google is thought to have one waiting in the wings. “There is a lot of energy in the community, and the recent progress is immense”.

Quantum computing takes advantage of the strange ability of subatomic particles to exist in more than one state at any time. Due to the way the tiniest of particles behave, operations can be done much more quickly and use less energy than classical computers.

    

In classical computing, a bit is a single piece of information that can exist in two states – 1 or 0. Quantum computing uses quantum bits, or 'qubits' instead. These are quantum systems with two states. However, unlike a usual bit, they can store much more information than just 1 or 0, because they can exist in any superposition of these values.

As of 2018, the development of actual quantum computers is still in its infancy, but experiments have been carried out in which quantum computational operations were executed on a very small number of quantum bits. Both practical and theoretical research continues, and many national governments and military agencies are funding quantum computing research in additional effort to develop quantum computers for civilian, business, trade, environmental and national security purposes, such as cryptanalysis. A small 20-qubit quantum computer exists and is available for experiments via the IBM quantum experience project. D-Wave Systems has been developing their own version of a quantum computer that uses annealing.

 

How does quantum computing compare with conventional computing?

A common metaphor used to compare the two is a coin. In a conventional computer processor, a transistor is either up or down, heads or tails. But if I ask you whether that coin is heads or tails while it’s spinning, you might say the answer is both. That’s what a quantum computer builds on. Instead, a conventional bit that’s either 0 or 1, you have a quantum bit that simultaneously represents 0 and 1, until that qubit stops spinning and comes to a resting state.

The state space—or the ability to sample a large number of possible combinations—is exponential with a quantum computer. Taking the coin metaphor further, imagine I have two coins in my hand and I toss them in the air at the same time. While they’re both spinning they would represent four possible states. If I tossed three coins in the air, they would represent eight possible states. If I had 50 coins and tossed them all up in the air and asked you how many states that represents, the answer would be more states than is possible with the largest supercomputer in the world today. Three hundred coins—still a relatively small number—would represent more states than there are atoms in the universe.

Quantum computer what do we need to do

The first step is to make these quantum chips. At the same time, we’ve actually made a simulator on a supercomputer. When we run the Intel quantum simulator, it takes something like five trillion transistors to simulate 42 qubits.

             

Quantum decoherence

            

Main article: Quantum decoherence

One of the greatest challenges is controlling or removing quantum decoherence. This usually means isolating the system from its environment as interactions with the external world cause the system to decohere. However, other sources of decoherence also exist. Examples include the quantum gates, and the lattice vibrations and background thermonuclear spin of the physical system used to implement the qubits. Decoherence is irreversible, as it is effectively non-unitary, and is usually something that should be highly controlled, if not avoided. Decoherence times for candidate systems, in particular the transverse relaxation time T2 (for NMR and MRI technology, also called the dephasing time), typically range between nanoseconds and seconds at low temperature.Currently, some quantum computers require their qubits to be cooled to 20 millikelvins in order to prevent significant decoherence.

As a result, time-consuming tasks may render some quantum algorithms inoperable, as maintaining the state of qubits for a long enough duration will eventually corrupt the superpositions.

These issues are more difficult for optical approaches as the timescales are orders of magnitude shorter and an often-cited approach to overcoming them is optical pulse shaping. Error rates are typically proportional to the ratio of operating time to decoherence time, hence any operation must be completed much more quickly than the decoherence time.

     

As described in the Quantum threshold theorem, If the error rate is small enough, it is thought to be possible to use quantum error correction to suppress errors and decoherence. This allows the total calculation time to be longer than the decoherence time if the error correction scheme can correct errors faster than decoherence introduces them. An often cited figure for required error rate in each gate for fault-tolerant computation is 10−3, assuming the noise is depolarizing.

Meeting this scalability condition is possible for a wide range of systems. However, the use of error correction brings with it the cost of a greatly increased number of required qubits. The number required to factor integers using Shor's algorithm is still polynomial, and thought to be between L and L2, where L is the number of qubits in the number to be factored; error correction algorithms would inflate this figure by an additional factor of L. For a 1000-bit number, this implies a need for about 104 bits without error correction. With error correction, the figure would rise to about 107 bits. Computation time is about L2 or about 107 steps and at 1 MHz, about 10 seconds.

     

A very different approach to the stability-decoherence problem is to create a topological quantum computer with anyone, quasi-particles used as threads and relying on braid theory to form stable logic gates.