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qxmt 0.5.4 documentation

  • QXMT reference
    • qxmt.ansatze package
      • qxmt.ansatze.pennylane package
        • qxmt.ansatze.pennylane.uccsd module
      • qxmt.ansatze.base module
      • qxmt.ansatze.builder module
    • qxmt.datasets package
      • qxmt.datasets.openml package
        • qxmt.datasets.openml.loader module
      • qxmt.datasets.generate package
        • qxmt.datasets.generate.linear module
        • qxmt.datasets.generate.loader module
      • qxmt.datasets.file package
        • qxmt.datasets.file.loader module
      • qxmt.datasets.raw_preprocess package
        • qxmt.datasets.raw_preprocess.sampling module
        • qxmt.datasets.raw_preprocess.filter module
      • qxmt.datasets.transform package
        • qxmt.datasets.transform.normalizer module
        • qxmt.datasets.transform.reducer module
      • qxmt.datasets.builder module
      • qxmt.datasets.schema module
    • qxmt.devices package
      • qxmt.devices.base module
      • qxmt.devices.amazon module
      • qxmt.devices.amazon_device module
      • qxmt.devices.ibmq module
      • qxmt.devices.ibmq_device module
      • qxmt.devices.pennylane_device module
      • qxmt.devices.builder module
      • qxmt.devices.device_info module
    • qxmt.evaluation package
      • qxmt.evaluation.metrics package
        • qxmt.evaluation.metrics.base module
        • qxmt.evaluation.metrics.defaults_classification module
        • qxmt.evaluation.metrics.defaults_regression module
        • qxmt.evaluation.metrics.defaults_vqe module
      • qxmt.evaluation.evaluation module
    • qxmt.experiment package
      • qxmt.experiment.evaluation_factory module
      • qxmt.experiment.executor module
      • qxmt.experiment.experiment module
      • qxmt.experiment.repository module
      • qxmt.experiment.reproducer module
      • qxmt.experiment.schema module
    • qxmt.feature_maps package
      • qxmt.feature_maps.pennylane package
        • qxmt.feature_maps.pennylane.rotation module
        • qxmt.feature_maps.pennylane.ising module
        • qxmt.feature_maps.pennylane.npqc module
        • qxmt.feature_maps.pennylane.yzcx module
      • qxmt.feature_maps.base module
    • qxmt.generators package
      • qxmt.generators.description module
      • qxmt.generators.prompts module
    • qxmt.hamiltonians package
      • qxmt.hamiltonians.pennylane package
        • qxmt.hamiltonians.pennylane.molecular module
      • qxmt.hamiltonians.base module
      • qxmt.hamiltonians.builder module
    • qxmt.kernels package
      • qxmt.kernels.pennylane package
        • qxmt.kernels.pennylane.fidelity_kernel module
        • qxmt.kernels.pennylane.projected_kernel module
      • qxmt.kernels.base module
      • qxmt.kernels.sampling module
    • qxmt.models package
      • qxmt.models.hyperparameter_search package
        • qxmt.models.hyperparameter_search.search module
      • qxmt.models.qkernels package
        • qxmt.models.qkernels.base module
        • qxmt.models.qkernels.builder module
        • qxmt.models.qkernels.qrigge module
        • qxmt.models.qkernels.qsvc module
        • qxmt.models.qkernels.qsvr module
      • qxmt.models.vqe package
        • qxmt.models.vqe.base module
        • qxmt.models.vqe.basic module
        • qxmt.models.vqe.builder module
      • qxmt.models.builder module
    • qxmt.utils package
      • qxmt.utils.git module
      • qxmt.utils.yaml module
    • qxmt.visualization package
      • qxmt.visualization.plot_classification_performance module
      • qxmt.visualization.plot_dataset module
      • qxmt.visualization.plot_metrics module
      • qxmt.visualization.plot_optimization_performance module
      • qxmt.visualization.plot_regression_performance module
      • qxmt.visualization.plot_vqe_performance module
    • qxmt.configs module
    • qxmt.constants module
    • qxmt.decorators module
    • qxmt.exceptions module
    • qxmt.logger module
    • qxmt.types module
  • Tutorial: Applying QXMT to Your Own Experiments
    • Simple Case Using Only the Default Dataset and Quantum Kernel Model
    • Practical Case with Custom Functions and the MNIST Dataset for Quantum Kernel Models
    • Using the VQE Module for Quantum Chemistry Calculations
    • Tool Reference

Python Module Index

q
 
q
- qxmt
    qxmt.ansatze.pennylane
    qxmt.evaluation.metrics.defaults_vqe

By kenya-sk

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