arXiv:2608. 11733v1 Announce Type: cross Abstract: Effective implementation of high-level quantum gates is essential for practical quantum computing.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2508. 10807v2 Announce Type: replace-cross Abstract: We present a native three-qubit entangling gate that exploits engineered interactions to realize control-control-target and control-target-target operations in a single coherent step.
arXiv:2510. 12430v2 Announce Type: replace-cross Abstract: Translating a general quantum circuit on a specific hardware topology with a reduced set of available gates, also known as transpilation, comes with a substantial increase in the length of the equivalent circuit.
arXiv:2602. 16018v2 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) are a powerful framework for learning representations from graph-structured data, but their direct implementation on near-term quantum hardware remains challenging due to circuit depth, multi-qubit interactions, and qubit scalability constraints.
arXiv:2607. 29134v1 Announce Type: cross Abstract: Recent work suggests that relational database management systems (RDBMSs) can execute quantum circuit simulation by compiling the simulation into SQL workloads (primarily join-and-aggregate tensor contractions).
arXiv:2607. 21121v1 Announce Type: cross Abstract: In this work, a quantum architecture search framework for approximate quantum state preparation (QSP) is proposed.
arXiv:2602. 22241v2 Announce Type: replace-cross Abstract: This work presents a formulation to express and optimize stochastic neural networks as quantum circuits in gate-based quantum computing.