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A collection of pre-optimized QV64, 128, 256, 512 and 1024 to be mapped to a line graph.
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创建时间：
2025-01-24
相关数据集
Scalable Randomized Benchmarking of Quantum Computers using Mirror Circuits
This is supplemental data and code for: T. Proctor et al., Scalable randomized benchmarking of quantum computers using mirror circuits, arXiv 2112.09853 (2021). This folder contains all the data and
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Data underlying the publication: Reinforcement learning in compilers for DQC
It becomes increasingly difficult to scale the number of qubits in a single quantum processor. In order to scale to more computational capability, distributed quantum computing (DQC) offers an alterna
DataCite Commons2026-03-25 更新60
Code and Data for "Anticoncentration in Clifford Circuits and Beyond: From Random Tensor Networks to Pseudo-Magic States"
Anticoncentration describes how an ensemble of quantum states spreads over the allowed Hilbert space, leading to statistically uniform output probability distributions. In this work, we investigate th
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Quantum benchmark results: XENet.
Results of Core Redesign on the quantum computer with CrystalConv. σ denotes standard deviation. (CSV)
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Measurement and classical optimization strategies for quantum variational problems
This dataset contains results obtained from simulations of the non-linear Schrödinger equation using quantum networks, alongside a measurement benchmark conducted for a 2-qubit test system. The data w
DataCite Commons2024-04-29 更新40
