Consider the task of verifying that a given quantum device, designed to produce a particular entangled state, does indeed produce that state. One natural approach would be to characterize the output state by quantum state tomography, or alternatively, to perform some kind of Bell test, tailored to the state of interest. We show here that neither approach is optimal among local verification strategies for 2-qubit states. We find the optimal strategy in this case and show that quadratically fewer total measurements are needed to verify to within a given fidelity than in published results for quantum state tomography, Bell test, or fidelity estimation protocols. We also give efficient verification protocols for any stabilizer state. Additionally, we show that requiring that the strategy be constructed from local, nonadaptive, and noncollective measurements only incurs a constant-factor penalty over a strategy without these restrictions.

The finite element method is used to approximately solve boundary value problems for differential equations. The method discretises the parameter space and finds an approximate solution by solving a large system of linear equations. Here we investigate the extent to which the finite element method can be accelerated using an efficient quantum algorithm for solving linear equations. We consider the representative general question of approximately computing a linear functional of the solution to a boundary value problem, and compare the quantum algorithm's theoretical performance with that of a standard classical algorithm -the conjugate gradient method. Prior work had claimed that the quantum algorithm could be exponentially faster, but did not determine the overall classical and quantum runtimes required to achieve a predetermined solution accuracy. Taking this into account, we find that the quantum algorithm can achieve a polynomial speedup, the extent of which grows with the dimension of the partial differential equation. In addition, we give evidence that no improvement of the quantum algorithm could lead to a super-polynomial speedup when the dimension is fixed and the solution satisfies certain smoothness properties.

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In this article, we estimate the cost of simulating electrolyte molecules in Li-ion batteries on a fault-tolerant quantum computer, focusing on the molecules that can provide practical solutions to industrially relevant problems. Our resource estimate is based on the fusion-based quantum computing scheme using photons, but can be modified easily to the more conventional gate-based model as well. We find the cost of the magic state factory to constitute no more than ∼ 2% of the total footprint of the quantum computer, which suggests that it is more advantageous to use algorithms that consume many magic states at the same time. We suggest architectural and algorithmic changes that can accommodate such a capability. On the architecture side, we propose a method to consume multiple magic states at the same time, which can potentially lead to an order of magnitude reduction in the overall computation time without incurring additional expense in the footprint. This is based on a fault-tolerant measurement of a Pauli product operator in constant time, which may be useful in other contexts as well. We also introduce a method to implement an arbitrary fermionic basis change in logarithmic depth, which may be of independent interest. * IK's contribution was carried out while he was affiliated with PsiQuantum. IK's current affiliation is the