Universal quantum algorithms that prepare arbitrary n-qubit quantum states require${O\left(2^{n}\right)}$gate complexity. The complexity can be reduced by considering specific families of quantum states depending on the task at hand. In particular, multipartite quantum states that are invariant under permutations, e.g. Dicke states, have intriguing properties. In this paper, we consider states invariant under cyclic permutations, which we call cyclic states. We present a quantum algorithm that deterministically prepares cyclic states with gate complexity${O\left(n\right)}$without requiring any ancillary qubit. Through both analytical and numerical analyses, we show that our algorithm is more efficient than existing ones.

We propose a flow for automated quantum compilation. Our flow takes a Boolean function implemented in Python as input and translates it into a format appropriate for reversible logic synthesis. We focus on two quantum compilation tasks: uniform state preparation and oracle synthesis. To illustrate the use of our flow, we solve IBM's virtual hackathon challenge of 2019, called the Zed city problem, an instance of vertex coloring, by using quantum search algorithms. The expressiveness of Python in combination with automated compilation algorithms allows us to express quantum algorithms at a high level of abstraction, which reduces the effort to implement them, and leads to better and more flexible implementations. We show that our proposed flow generates a lower-cost circuit implementation of the oracle needed to solve IBM's challenge when compared to the winning submission.

In this paper we consider the compilation of quantum state permutations into quantum gates for physical quantum computers. A sequence of generic single-target gates, which realize the input permutation, are extracted using a decomposition based reversible logic synthesis algorithm. We present a compilation algorithm that translates single-target gates into a quantum circuit composed of the elementary quantum gate sets that are supported by IBM's 5-qubit and 16-qubit, and Rigetti's 8-qubit and 19-qubit superconducting transmon QPUs. Compared to generic state-of-the-art compilation techniques, our technique improves gate volume and gate depth by up to 59% and 53%, respectively.

Tag array in on-chip caches is one of the most vulnerable components to radiation-induced soft errors. Protecting the tag array in some processors is limited to error detection using the parity check, since the overheads of error correcting codes are not affordable in this component. State-of-the-art tag protection schemes combine the parity check with replication to provide error correction capability. Classifying these replication-based schemes into partial-replication and full-replication, the former offers a low overhead protection in which a large fraction of detectable errors remain uncorrectable, whereas the latter imposes a significant overhead to correct all of the errors. This paper proposes a low overhead full-replication scheme, so called Replicating in Altered Ways of Tag (RAW-Tag), to correct all detectable errors. RAW-Tag manipulates the cache replacement algorithm and keeps track of the incoming/evicting cache lines to not only provide a replica for all tags, but also eliminate the simultaneous susceptibility of both a tag and its replica to a single Multiple-Bit Upset (MBU). The simulation results show that RAW-Tag imposes no performance overhead and increases the energy consumption of L1 and L2 caches by only 6.6 and 0.3 percent, respectively, as compared with the baseline.