DOI: 10.5061/dryad.w3r2280zm
title: Tomography of entangling two-qubit logic operations in exchange-coupled donor electron spin qubits

description: Scalable quantum processors require high-fidelity universal quantum logic
 operations in a manufacturable physical platform. Donors in silicon
 provide atomic size, excellent quantum coherence and compatibility with
 standard semiconductor processing, but no entanglement between donor-bound
 electron spins has been demonstrated to date. Here we present the
 experimental demonstration and tomography of universal 1- and 2-qubit
 gates in a system of two weakly exchange-coupled electrons, bound to
 single phosphorus donors introduced in silicon by ion implantation. We
 surprisingly observe that the exchange interaction has no effect on the
 qubit coherence. We quantify the fidelity of the quantum
 operations using gate set tomography (GST), and we use the universal gate
 set to create entangled Bell states of the electrons spins, with fidelity
 ≈ 93%, and concurrence 0.91 ± 0.08. These results form the necessary basis
 for scaling up donor-based quantum computers.
description: # Tomography of entangling two-qubit logic operations in exchange-coupled
 donor electron spin qubits
 [https://doi.org/10.5061/dryad.w3r2280zm](https://doi.org/10.5061/dryad.w3r2280zm) This is accompanying data for the journal article 'Tomography of entangling two-qubit logic operations in exchange-coupled donor electron spin qubits' ([https://arxiv.org/abs/2309.15463](https://arxiv.org/abs/2309.15463)). **Outline of the dataset** The dataset consists of the following: * 'Main text' - folder containing the data used to produce the figures in the main text. This data is divided into subfolders according to the figure in the main text that the data is associated with. * 'Supplementary material'- folder containing the data used to produce the figures in the supplementary material. This data is divided into subfolders according to the figure in the supplementary material that the data is associated with. * 'GST' - folder containing the raw and processed data used to produce the GST figures. These folders also contain the GST report generated from the raw data, along with the jupyter notebook used to produce these reports. **Outline of the data folders** The data folders consist of the following information: * The preprocessed data files as DAT files. This preprocessed data consists of quantities such as electron spin up fraction and nuclear flip probability. * The raw SET current traces from which the preprocessed data quantities have been derived. These traces are saved in the 'traces'subfolder. Note that for some datasets, only the preprocessed data was saved and thus for these datafolders, no 'traces' folder is present. **Accessing the raw SET current traces** The raw traces are saved in HDF5 format, and can thus be accessed by a tool such as HDFview, or the python package h5py. **Replicating the data analysis** All measurements were performed and analysed using the QCoDes data framework. The jupyter notebook 'Notebook_generating_paper_figures.ipynb' contains the Python code used to analyse the data and produce the figures in the paper main text and supplementary material. This notebook can be accessed and executed by carrying out the following steps: * Download and install Anaconda ([https://www.anaconda.com/download](https://www.anaconda.com/download). This will install both Python and Jupyter Notebook. * Install the QCoDes python package. For more information on QCoDes and its installation, please see- [https://microsoft.github.io/Qcodes/](https://microsoft.github.io/Qcodes/). **GST** The GST folder consists of the following: * 'Conditional_1Q_GST_electron1_L_1024'- Contains the data for the conditional 1Q GST experiments on electron 1. This data was used in Figure 4,a of the main text. L_1024 refers to the maximum circuit depth used for this experiment, which was 1024. * 'Conditional_1Q_GST_electron2_L_1024'- Contains the data for the conditional 1Q GST experiments on electron 2. This data was used in Figure 4,b of the main text. L_1024 refers to the maximum circuit depth used for this experiment, which was 1024. * 'Unconditional_1Q_GST_L_64' - Contains the data for the unconditional 1Q GST experiments for the electrons. This data was used in Figure 3 of the main text. L_1024 refers to the maximum circuit depth used for this experiment, which was 64. * 'PyGSTi 0.9.10 Report Gen.ipynb' - Jupyter notebook containing the code to generate a GST report from the raw paper using the package pyGSTi. The specific version of pyGSTi used for these measurements was '0.9.10.1.post16'. For more information on pyGSTi and its installation, please see-[https://github.com/sandialabs/pyGSTi](https://github.com/sandialabs/pyGSTi). **GST data folder contents** Each GST dataset folder contains the following: * Raw data in timestamped data folders.This is the data from which the GST results are calculated. * GST experiment design. This folder contains: * A 'data'folder. This folder contains a txt file, with a list of the GST circuits and the corresponding results for each circuit. This txt file is created directly from the raw results. The GST report is created by reading in this txt file. * An edesign folder containing the circuits, germs and fiducials used to construct the GST experiment. These files are in .jsn format. * A html file entitled 'main' containing the analysed GST experiment results in the form of a GST report.