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>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0