Average-Case Complexity Versus Approximate Simulation of Commuting Quantum Computations.

We use the class of commuting quantum computations known as IQP (instantaneous quantum polynomial time) to strengthen the conjecture that quantum computers are hard to simulate classically. We show that, if either of two plausible average-case hardness conjectures holds, then IQP computations are hard to simulate classically up to constant additive error. One conjecture relates to the hardness of estimating the complex-temperature partition function for random instances of the Ising model; the other concerns approximating the number of zeroes of random low-degree polynomials.

Are random pure States useful for quantum computation?

We show the following: a randomly chosen pure state as a resource for measurement-based quantum computation is-with overwhelming probability-of no greater help to a polynomially bounded classical control computer, than a string of random bits. Thus, unlike the familiar "cluster states," the computing power of a classical control device is not increased from P to BQP (bounded-error, quantum polynomial time), but only to BPP (bounded-error, probabilistic polynomial time). The same holds if the task is to sample from a distribution rather than to perform a bounded-error computation.

Practical scheme for quantum computation with any two-qubit entangling gate.

Which gates are universal for quantum computation? Although it is well known that certain gates on two-level quantum systems (qubits), such as the controlled-not, are universal when assisted by arbitrary one-qubit gates, it has only recently become clear precisely what class of two-qubit gates is universal in this sense. We present an elementary proof that any entangling two-qubit gate is universal for quantum computation, when assisted by one-qubit gates. A proof of this result for systems of arbitrary finite dimension has been provided by Brylinski and Brylinski; however, their proof relies on a long argument using advanced mathematics.