Light, trapped atoms and ions, and solid-state devices based on semiconductors or superconductors. Researchers are experimenting with many different physical systems to hold and process quantum information, including Superposition of information is a central resource used in quantum processing and, along with other quantum rules, enables powerful new ways to compute. These superpositions provide a vast range of possible states for a quantum computer to work with, albeit with limitations on how they can be manipulated and accessed. N bits or qubits: n bits can represent any one of 2 n possible values at any moment, while n qubits can include components corresponding to all 2 n classical states simultaneously in superposition. Indeed, one way to represent a qubit is by the polarization of a single photon of light. You could use horizontally polarized light to represent 0 and vertically polarized light to represent 1, but light can also be polarized on an angle and then has both horizontal and vertical components at once. A qubit, however, can occupy a superposition of these two information states, taking on characteristics of both. Noise can make the qubit state wander continuously from its correct location.Ī classical bit has only two possible values: 0 or 1. Other possible superpositions of 0 and 1 (described by complex numbers a and b) cover the rest of the surface. The states 0 and 1 sit at the north and south poles, and the polarization states D, A, R, and L lie on the equator. The possible states of a single isolated qubit are neatly represented on a sphere, known as a Bloch sphere. These states become fully fledged quantum bits (qubits) when they consist of pulses that each contain a single photon. Examples include the diagonal ( D) polarization at 45°, the antidiagonal ( A) at –45°, as well as right ( R) and left ( L) circularly polarized light (the imaginary number i represents a difference in phase). Light polarized at other angles has components of both H and V, representing 0 and 1 simultaneously. A classical binary digit could be represented by encoding 0 as horizontally ( H) polarized light, and 1 as vertically ( V) polarized light. Polarized light is an example of superposition. Abstract though it may seem, information always involves a physical representation, and the physics matters. This was the mantra of the distinguished IBM researcher Rolf Landauer. But before describing how we think such error correction can be made practical, we need to first review what makes a quantum computer tick. The two of us, along with many other researchers involved in quantum computing, are trying to move definitively beyond these preliminary demos of QEC so that it can be employed to build useful, large-scale quantum computers. But these experiments still have not reached the level of quality and sophistication needed to reduce the overall error rate in a system. A mature body of theory built up over the past quarter century now provides a solid theoretical foundation, and experimentalists have demonstrated dozens of proof-of-principleĮxamples of QEC. This tremendous susceptibility to errors is the single biggest problem holding back quantum computing from realizing its great promise.įortunately, an approach known as quantum error correction (QEC) can remedy this problem, at least in principle. The situation inside a quantum computer is far different: The information itself has its own idiosyncratic properties, and compared with standard digital microelectronics, state-of-the-art quantum-computer hardware is more than a billion trillion times as likely to suffer a fault. They both involve conventional, classical information, carried by hardware that is relatively immune to errors. Dates chiseled into an ancient tombstone have more in common with the data in your phone or laptop than you may realize.
0 kommentar(er)
