| --- |
| license: apache-2.0 |
| pipeline_tag: tabular-regression |
| datasets: |
| - Allanatrix/QST |
| tags: |
| - Physics |
| --- |
| # NexaQST: Quantum State Tomography with Physics-Informed Neural Networks |
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| **NexaQST** is a Quantum State Tomography model built using a Physics-Informed Neural Network (PINN) trained on synthetic 2-qubit experiments. This model leverages quantum mechanical priors such as positivity, Hermiticity, and trace constraints to ensure physically plausible reconstructions of quantum states. |
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| --- |
|
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| ## Model Overview |
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| - **Task**: Reconstruct quantum states (density matrices) from tomographic measurement traces |
| - **System**: Simulated 2-qubit experiments |
| - **Architecture**: Physics-Informed Neural Network (PINN) |
| - **Constraints Embedded**: |
| - Positivity |
| - Hermiticity |
| - Trace normalization (Tr(Ο) = 1) |
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| --- |
|
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| ## Dataset Generation |
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| - **Simulation Toolkit**: [`QuTiP`](https://qutip.org/) |
| - **Process**: |
| 1. Generated full 2-qubit tomography experiments via simulation |
| 2. Extracted and structured measurement traces |
| 3. Derived backward synthetic traces from known density matrices |
| 4. Created supervised training pairs: `(trace β density matrix)` |
| 5. Enforced physical constraints directly inside the model during training |
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| --- |
|
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| ## Model Input/Output |
|
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| - **Input**: Vector of tomographic measurement traces |
| - **Output**: Reconstructed density matrix (complex-valued 4x4 for 2 qubits) |
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| --- |
|
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| ## Example Usage |
|
|
| ```python |
| # Pseudocode for usage |
| |
| from model import NexaQSTModel |
| import torch |
| |
| model = NexaQSTModel() |
| model.load_state_dict(torch.load("nexaqst_model.pt")) |
| model.eval() |
| |
| traces = load_measurement_vector("qst_trace.npy") # shape: (N,) |
| rho_pred = model.predict_density_matrix(traces) |
| |
| # rho_pred is a 4x4 complex-valued matrix satisfying physical constraints |
| ```` |
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| --- |
|
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| ## Applications |
|
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| * Quantum error correction diagnostics |
| * Quantum system identification |
| * Educational simulation of QST techniques |
| * Physically consistent state estimation for quantum simulations |
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| --- |
|
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| ## Licensing & Citation |
|
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| * If used in publications or products, please credit the Nexa Scientific Suite. |
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| --- |
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| ## π Related Tools |
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| * [π Nexa Data Studio](https://huggingface.co/spaces/Allanatrix/NexaDataStudio) |
| * [π¬ Nexa R\&D Hub](https://huggingface.co/spaces/Allanatrix/NexaR&D) |
| * [π§ Nexa MOE Models](https://huggingface.co/collections/Allanatrix/nexa-models) |
| * [π Nexa Hub (Main Portal)](https://huggingface.co/spaces/Allanatrix/NexaHub) |
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| --- |
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| *Created by [Allan](https://huggingface.co/Allanatrix), independent quantum systems architect and ML researcher. Part of the Nexa scientific computing ecosystem.* |
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