Understanding Quantum Computing

One suggested approach to the stability-decoherence problem is to create a topological quantum computer with anyons, quasi-particles used as threads and relying on braid theory to form stable logic gates (images: Wikipedia).

Quantum computing although still in its infancy is a quantum bits that uses a very different form of data handling to perform calculations. In short, it’s a quantum-mechanical phenomena computing. The emergence of quantum computing is based on a new kind of data unit that is non-binary, as it has more than two definite states (0 or 1). Quantum computation uses quantum bits or qubits that can be in superpositions and entanglements states.

Unlike classical computer that works on bits of data that are binary, quantum computer, maintains a sequence of qubits, which can represent a one, a zero, or any quantum superposition of those two qubit states. A pair of qubits can be in any quantum superposition of 4 states, and three qubits in any superposition of 8 states. According to scientists, qubits are based on physical atoms and molecular structures. However, many find it helpful to theorize a qubit as a binary data unit with superposition.

To bring to light the importance of quantum computing, many national governments and military agencies are funding quantum computing research on top of effort to develop quantum computers for civilian, business, trade, environmental and national security purposes, such as cryptanalysis. John Preskill introduced the term quantum supremacy to refer to the hypothetical speedup advantage that a quantum computer would have over a classical computer in a certain field. Roger Schlafly pointed out that the claimed theoretical benefits of quantum computing go beyond the proven theory of quantum mechanics and imply non-standard interpretations, such as multiple worlds and negative probabilities. Schlafly on the other hand maintains that the Born rule is just “metaphysical fluff” and that quantum mechanics doesn’t rely on probability any more than other branches of science but simply calculates the expected observation values.

One of the greatest challenges of quantum computing is controlling or removing quantum decoherence; that is, loss of quantum coherence or means of isolating the system from its environment as interactions with the external world causes the system to decohere. Right now, some quantum computers require their qubits to be cooled to 20 millikelvins in order to prevent significant decoherence.  Meaning 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.

One suggested approach to the stability-decoherence problem is to create a topological quantum computer with anyons, quasi-particles used as threads and relying on braid theory to form stable logic gates. Here are four of several quantum computing models in development:

In February 2018, scientists reported, for the first time, the discovery of a new form of light, which may involve polaritons, that could be useful in the development of quantum computers. while in March 2018, Google Quantum AI Lab announced a 72 qubit processor called Bristlecone. IBM Research announced eight quantum computing startups joined the IBM Q Network, including: Zapata Computing, Strangeworks, QxBranch, Quantum Benchmark, QC Ware, Q-CTRL, Cambridge Quantum Computing, and 1QBit in April 2018.

Quantum computers are really good at solving those problems where you’ve got an exponential number of permutations to try out, said Stanford Clark. However, quantum computers will never be able to run the type of logic that we’re familiar with in the classical computer architecture, said Andy Stanford Clark. Although, quantum computers may be faster than classical computers for some problem types, A Turing machine can simulate these quantum computers, so such a quantum computer could never solve an undecidable problem like the halting problem.