By Le Bellac M., de Forcrand-Millard P.

Quantum details and computation is a speedily increasing and cross-disciplinary topic. This booklet offers a self-contained creation to the sphere for physicists, mathematicians and desktop scientists who need to know extra approximately this interesting topic. After a step by step creation to the quantum bit (qubit) and its major homes, the writer offers the mandatory heritage in quantum mechanics. The center of the topic, quantum computation, is illustrated by way of an in depth remedy of 3 quantum algorithms: Deutsch, Grover and Shor. the ultimate chapters are dedicated to the actual implementation of quantum desktops, together with the newest points, comparable to superconducting qubits and quantum dots, and to a quick account of quantum info. Written at a degree appropriate for undergraduates in actual sciences, no prior wisdom of quantum mechanics is thought, and basically simple notions of physics are required.

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**Extra resources for A Short Introduction to Quantum Information and Quantum Computation**

**Example text**

It begins with the assumption that round-off errors are independent. This assumption is, of course, not valid, because if the same problem is run on the same machine several times, the answers will always be the same. We can, however, adopt a stochastic model of the propagation of round-off errors in which the local errors are treated as if they were random variables. Thus we can assume that the local round-off errors are either uniformly or normally distributed between their extreme values. Using statistical methods, we can then obtain the standard deviation, the variance of distribution, and estimates of the accumulated roundoff error.

We will make good use of this method in Chap. 4. 6 SOME COMMENTS ON CONVERGENCE OF SEQUENCES Calculus, and more generally analysis, is based on the notion of convergence. Basic concepts such as derivative, integral, and continuity are defined in terms of convergent sequences, and elementary functions such as ln x or sin x are defined by convergent series, At the same time, numerical answers to engineering and scientific problems are never needed exactly. Rather, an approximation to the answer is required which is accurate “to a certain number of decimal places,” or accurate to within a given tolerance It is therefore not surprising that many numerical methods for finding the answer of a given problem merely produce (the first few terms of) a sequence which is shown to converge to the desired answer.

In other words, it is difficult to get hold of the function mentioned in the definition of convergence. (2) Even when some knowledge about is available, it may turn out that the required n is too large to make the calculation of feasible. Example The number is the value of the infinite series Hence, with the sequence is monotone-decreasing to its limit Moreover, To calculate correct to within 10-6 using this sequence, we would need 106 < 4 n + 3, or roughly, n = 250,000. On a computer using eight-decimal-digit floating-point arithmetic, round-off in the calculation of is probably much larger than 10-6.