Quantum computers offer great promise for cryptography and optimization problems. ZDNet explores what quantum computers will and won't be able to do, and the challenges we still face. In 1936, some 2.4 million members of the Literary Digest magazine's mailing list responded to its publisher by mail, in the broadest presidential candidates' opinion poll conducted in the United States to that time. By a margin of 57 to 43, those readers reported they favored the Republican governor of Kansas, Alf Landon, over the incumbent Democrat, Franklin D. Roosevelt. The week after the election, the magazine's cover announced in bold, black letters the message, "Is Our Face Red!" Also: Could quantum computers fix political polls? The following January, Oxford University's Public Opinion Quarterly published an essay that examined how a seemingly much smaller survey of only 50,000 participants, conducted by a fellow named George Gallup, yielded a far more accurate result than did Literary Digest. Gallup's poll was "scientific," and Oxford wanted to explain what that meant, and why opinion polling deserved that lofty moniker. For the first time, the Oxford publication explained a concept called selection bias. Specifically, if you don't ask people for enough facts about themselves, you never attain the information you need to estimate whether the people around them think and act in similar ways.
How many qubits are needed to out-perform conventional computers, how to protect a quantum computer from the effects of decoherence and how to design more than 1000 qubits fault-tolerant large scale quantum computers, these are the three basic questions we want to deal in this article. Qubit technologies, qubit quality, qubit count, qubit connectivity and qubit architectures are the five key areas of quantum computing are discussed. Earlier we have discussed 7 Core Qubit Technologies for Quantum Computing, 7 Key Requirements for Quantum Computing. Spin-orbit Coupling Qubits for Quantum Computing and AI, Quantum Computing Algorithms for Artificial Intelligence, Quantum Computing and Artificial Intelligence, Quantum Computing with Many World Interpretation Scopes and Challenges and Quantum Computer with Superconductivity at Room Temperature. Here, we will focus on practical issues related to designing large-scale quantum computers.
In the not-terribly-distant past, the goal of quantum computing research was to achieve a milestone called quantum supremacy: the point in time when a quantum computer can, in practical terms, be considered superior to a classical, semiconductor-based computer for processing any task you give it. Certainly Google already made a big enough fuss about it. This is no longer true. Engineers and scholars have since conceded that this is not possible -- that a quantum device cannot supersede a classical device. Quantum computers offer great promise for cryptography and optimization problems.
Despite the hype and hoopla surrounding the burgeoning field of quantum computing, the technology is still in its infancy. Just a few years ago, researchers were making headlines with rudimentary machines that housed less than a dozen qubits -- the quantum version of a classical computer's binary bit. At IBM's inaugural Index Developer Conference held in San Francisco this week, the company showed off its latest prototype: a quantum computing rig housing 50 qubits, one of the most advanced machines currently in existence.
After decades of research, quantum computers are approaching the scale at which they could outperform their "classical" counterparts on some problems. They will be truly practical, however, only when they implement quantum error correction, which combines many physical quantum bits, or qubits, into a logical qubit that preserves its quantum information even when its constituents are disrupted. Although this task once seemed impossible, theorists have developed multiple techniques for doing so, including "surface codes" that could be implemented in an integrated-circuit-like planar geometry. For ordinary binary data, errors can be corrected, for example, using the majority rule: A desired bit, whether 1 or 0, is first triplicated as 111 or 000. Later, even if one of the three bits has been corrupted, the other two "outvote" it and allow recovery of the original data.