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21 results for “Quantum Circuits”
Dataset for "Quantum bath suppression in a superconducting circuit by immersion cooling"
<p>Dataset supporting the findings in the manuscript "Quantum bath suppression in a superconducting circuit by immersion cooling" by M Lucas et al. (<em>Nature Communications</em> <strong>14</strong>, 3522 (2023), arxiv:2210.03816) Containing: description of files & figures, raw datasets obtained from superconducting resonator noise and quality factor measurements, electron spin resonance measurements.</p>
Data and code for "Niobium Quantum Interference Microwave Circuits with Monolithic Three-Dimensional (3D) Nanobridge Junctions"
<p>Data and measurements scripts for the paper "Niobium Quantum Interference Microwave Circuits with Monolithic Three-Dimensional (3D) Nanobridge Junctions"</p> <p>The package "stuelab" used in the scripts is also included. <br><br>Funding by the Deutsche Forschungsgemeinschaft (DFG) via Grants No. BO 6068/1-1, No. BO 6068/2-1, and No. KO 1303/13-2, and support from the COST actions NANOCOHYBRI (CA16218) and SUPERQUMAP (CA21144)</p>
Quantum Volume circuits optimized with CPLEX on a line of qubits
<p>We provide BIP optimized circuits for QV64, 128 and 256 for qubits in a line topology. An Notebook is provided for loading the circuits.</p> <p>For more details see https://arxiv.org/abs/2106.06446</p>
Datasets, figures and simulation scripts for "Quantum circuit compilation with quantum computers"
<p>The files contain the datasets and figures with the results of the manuscript "<a title="Quantum circuit compilation with quantum computers" href="https://doi.org/10.48550/arXiv.2408.00077" target="_blank" rel="noopener">Quantum circuit compilation with quantum computers</a>".</p> <p>The repository URL links to the repository with the simulation scripts used to produce the datasets and figures.</p>
Data for "Entanglement Dynamics in Monitored Kitaev Circuits: Loop Models, Symmetry Classification, and Quantum Lifshitz Scaling"
<p>We provide the data and scripts used to produce the figures shown in our publication "Entanglement Dynamics in Monitored Kitaev Circuits:<br>Loop Models, Symmetry Classification, and Quantum Lifshitz Scaling".</p>
Depth and Number of added SWAPs for newly developed routing code for QAOA quantum circuits
<p>We developed a qubit routing algorithm with polynomial classical run time for the Quantum Approximate Optimization Algorithm (QAOA). The algorithm follows a two step process. First, it obtains a near-optimal solution, based on Vizing's theorem for the edge coloring problem, consisting of subsets of the interaction gates that can be executed in parallel on a fully parallelized all-to-all connected QPU. Second, it proceeds with greedy application of SWAP gates based on their net effect on the distance of remaining interaction gates on a specific hardware connectivity graph. Our algorithm strikes a balance between optimizing for both the circuit depth and total SWAP gate count. We show that it improves upon existing state-of-the-art routing algorithms for QAOA circuits defined on <span><span><span><span>k</span></span></span></span>-regular as well as Erdös-Renyi problem graphs of sizes up to <span><span><span><span>N</span><span>≤</span><span>400</span></span></span></span>. This repository contains data and a ipython notebook used for plotting the results presented in the paper</p>
Simulation of free fermion transport on 2D lattice using constant-depth quantum circuits
<p>In these simulations, we consider a fermion initialized on a reference lattice site, and observe how it evolves freely through a two-dimensional (2D) lattice. The lattice comprises 16 sites with closed boundary conditions, and lattice site '0' is considered our reference site, where the fermion is initialized. We examine transport of a fermion on this 16-site lattice both with and without disorder. To do this, we track the occupation number at varying distances $M$ from the reference site as the fermion evolves freely through time. When there is no disorder in the system, we expect the fermion to behave ballistically and oscillate back and forth within the lattice. The file '4x4_2DFF_mu=0.0_nsteps=900_t=90.0_backend=ibm_washington_shot=50000_nis_ps_DD_M3.txt' has the results from simulating a free fermion on a 2D lattice with no disorder on the ibmq_washington QPU, while '4x4_2DFF_mu=0.0_nsteps=900_t=90.0_backend=qasm_sim_shot=100000_nis.txt' has the results from the noise-free quantum simulator. </p> <p>When there is large random disorder in the system, we expect the fermion to exhibit Anderson localization. '4x4_2DFF_mu=10.0_nsteps=900_t=90.0_backend=ibm_washington_shot=50000_nis_ps_DD_M3_Anderson_loc.txt' shows results from simulating a free fermion on a 2D lattice with large random disorder on the ibmq\_washington QPU, while '4x4_2DFF_mu=10.0_nsteps=900_t=90.0_backend=qasm_sim_shot=100000_nis.txt' shows results from the noise-free quantum simulator. </p> <p>Simulations on the the noise-free quantum simulator were performed with 100,000 shots. Simulations on the QPU were performed with 50,000 shots and any shot that did not conserve particle number was discarded. Two straightforward error mitigation techniques were also used to reduce noise in the results from the QPU. The first was a scalable readout error mitigation method implemented with the mthree package, which reduces errors in quantum measurement via calibration. The second was dynamical decoupling, a method that can suppress qubit decoherence via the application of a set of pulses (which together amount to application of the identity operator) to idling qubits which cancels the system-environment interaction.</p>
Data for Bolometer operating at the threshold for circuit quantum electrodynamics
<p>Data in figures of publication "Bolometer operating at the threshold for circuit quantum electrodynamics" published in Nature.</p>
Supporting data for 'CMOS-based cryogenic control of silicon quantum circuits'
<p>Data supporting for paper 'CMOS-based cryogenic control of silicon quantum circuits'.</p> <p>Loading data requires using 'pickle' function.</p> <p>An example:</p> <p>import pickle<br> data = 'J_calibration_3'<br> f = open('/.../data', 'rb')<br> ds = pickle.load(f)<br> f.close()</p>
Quantum Software Design Patterns Detection for Qiskit and QASM circuits
Open the record for dataset details and reuse information.
Quantum circuits used in the "Multi-qubit Lattice Surgery Scheduling" paper
<div> <div>This contains the circuit sets used for the experiments in the paper "Multi-qubit lattice surgery scheduling" (DOI https://doi.org/10.4230/LIPIcs.TQC.2024.1). For the description of the dataset, please see the readme file included in the compressed file.</div> </div>
Dataset for: Phonon engineering of atomic-scale defects in superconducting quantum circuits
<p>Dataset for manuscript [Phonon engineering of atomic-scale defects in superconducting quantum circuits]<br>After unzipping, this folder contains all data necessary to evaluate the conclusions presented in the paper. A detailed description can be found in the README.md file after unzipping.</p>
Data and code for "A flux-tunable YBa2Cu3O7 quantum interference microwave circuit"
<p>Data and measurements scripts for the paper "A flux-tunable YBa2Cu3O7 quantum interference microwave circuit".<br><br>Funding by the Deutsche Forschungsgemeinschaft (DFG) via Grant Nos. BO 6068/1-1 and BO 6068/2-1.</p>
Learning to rank quantum circuits for hardware-optimized performance enhancement
<p>These data were used in the work described in the manuscript <em>Learning to rank quantum circuits for hardware-optimized performance enhancement</em>, <a href="https://arxiv.org/abs/2411.03302">https://arxiv.org/abs/2411.03302</a>. </p> <p>Data was collected throughout a 9 month period. The data for each individual collection run is stored in a separate directory, for example <code>ibmq_guadalupe_2022_11_22_14_49_51</code>.</p> <p>The <code>jobs.pkl</code> file is a pickled dictionary that contains essentially all of the relevant data. Note that the dictionary includes Qiskit <code>QuantumCircuit</code> objects created with an older version of Qiskit, and as such an older Qiskit version must be used to load these files (version 0.43.0 works).</p> <ul> <li>The keys are integers indexing the circuit (0, 1, ..., n-1)</li> <li>The values are themselves dictionaries containing various data fields:</li> <li>'initial_circuit': the initial circuit, before transpilation or layout selection</li> <li>'num_qubits': the number of qubits used in the circuit</li> <li>'circuit_type': a string denoting the type of circuit (qaoa, bv, inv_qft, or clifford)</li> <li>'seed_compiler': the compiler PRNG seed</li> <li>'target_state': the target state for so-called one-hot or deterministic circuits</li> <li>'target_state_bin': the target state represented in binary</li> <li>'transpiled circuit': the transpiled circuit</li> <li>'deflated circuit': the deflated transpiled circuit (unused qubits are dropped)</li> <li>'layouts': a list of layouts (each represented by a list), determining the subgraph isomorphism</li> <li>'mm transpiled circuits (no dd)': the set of transpiled layouts (without dynamical decoupling)</li> <li>'mm transpiled circuits (dd)': the set of transpiled layouts (with dynamical decoupling)</li> <li>'job success': whether the job succeeded (True or False)</li> <li>'success fraction': the Hellinger fidelity, which equals success probability for one-hot circuits</li> <li>'mm fidelity': the Mapomatic score</li> <li>'T1 times': the single-qubit idle times</li> <li>'T1 fidelity': the T1 score</li> <li>'zz phases': the set of ZZ phase accumulations for two-qubit mutually-idle periods</li> <li>'zz fidelity': the ZZ fidelity</li> </ul>
Scalable Randomized Benchmarking of Quantum Computers using Mirror Circuits
<p>This is supplemental data and code for: T. Proctor et al., <em><a href="http://https://doi.org/10.48550/arXiv.2112.09853">Scalable randomized benchmarking of quantum computers using mirror circuits</a>, </em>arXiv 2112.09853 (2021).</p> <p>This folder contains all the data and the analysis code to generate the results presented in that paper. The core data analysis routines use PyGSTi, which can be found at <a href="https://github.com/pyGSTio/pyGSTi">https://github.com/pyGSTio/pyGSTi</a>.</p> <p>Please direct any questions to Timothy Proctor (tjproct@sandia.gov).</p>
Cooling photon-pressure circuits into the quantum regime
<p>This contains the data and processing scripts used for the figures of the manuscript and supplementary material of "Cooling photon-pressure circuits into the quantum regime".</p>
Data and code for "Multimode microwave circuit optomechanics as a platform to study coupled quantum harmonic oscillators"
<p>Components design files, code used to produce figures and measurement scripts for the results in "Multimode microwave circuit optomechanics as a platform to study coupled quantum harmonic oscillators".</p>
Data from: Stationary quantum entanglement between a massive mechanical membrane and a low frequency LC circuit
<p>Source data for figures.</p>
Observation of quantum many-body effects due to zero point fluctuations in superconducting circuits
<p>Scripts used for the data treatment of sample A</p>
Quantum circuits reproduce the experimental two-dimensional many-body localization transition point
<p>abstract: While many studies point towards the existence of many-body localization (MBL) in one dimension, the fate of higher-dimensional strongly disordered systems is a topic of current debate. The latest experiments as well as several recent numerical studies indicate that such systems behave many-body localized—at least on practically relevant timescales. However, thus far, theoretical approaches have been unable to quantitatively reproduce experimentally measured MBL features—an important requirement to demonstrate their validity. In this Letter, we use fermionic quantum circuits as a variational method to approximate the full set of eigenstates of two-dimensional MBL systems realized in fermionic optical lattice experiments. Using entanglement-based features, we obtain a phase transition point in excellent agreement with the experimentally measured value. Moreover, we calculate the filling-fraction-dependent MBL phase diagram. We argue that our approach best captures the underlying charge-density-wave experiments and compute the mean localization lengths, which can be compared to future experiments.</p> <p>Access will be granted upon reasonable request.</p>
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