Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,186 @@
+---
+language:
+- en
+license: mit
+size_categories:
+- n<1K
+task_categories:
+- other
+tags:
+- quantum-computing
+- quantum-noise
+- error-mitigation
+- NISQ
+- IBM-Quantum
+- transfer-learning
+- few-shot-learning
+- physics
+pretty_name: "Quantum Noise Transfer: Cross-Device Few-Shot Adaptation"
+dataset_info:
+  features:
+    - name: circuit_id
+      dtype: string
+    - name: backend
+      dtype: string
+    - name: circuit_type
+      dtype: string
+    - name: n_qubits
+      dtype: int32
+    - name: T1_mean
+      dtype: float64
+    - name: T2_mean
+      dtype: float64
+    - name: readout_error_mean
+      dtype: float64
+    - name: cx_error_mean
+      dtype: float64
+    - name: noisy_distribution
+      dtype: string
+    - name: ideal_distribution
+      dtype: string
+    - name: x
+      sequence: float64
+    - name: y
+      sequence: float64
+  splits:
+    - name: train
+      num_examples: 170
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/train-00000-of-00001.parquet
+---
+
+# Quantum Noise Transfer: Cross-Device Few-Shot Adaptation Dataset
+
+[![arXiv](https://img.shields.io/badge/arXiv-2604.24397-b31b1b.svg)](https://arxiv.org/abs/2604.24397)
+
+> **Paper:** [Few-Shot Cross-Device Transfer for Quantum Noise Modeling on Real Hardware](https://arxiv.org/abs/2604.24397)
+>
+> **Authors:** Sahil Al Farib, Sheikh Redwanul Islam, Azizur Rahman Anik
+
+## Dataset Description
+
+A real-hardware quantum noise dataset collected from two IBM Quantum devices for studying cross-device transfer learning in quantum error mitigation. Each sample pairs a **noisy output distribution** (measured on real hardware) with the corresponding **ideal output distribution** (from noiseless simulation), augmented with device calibration features.
+
+### Source Devices
+
+| Device | Role | Samples |
+|:---|:---|:---:|
+| `ibm_fez` | Source (Backend A) | 85 |
+| `ibm_marrakesh` | Target (Backend B) | 85 |
+| **Total** | | **170** |
+
+### Circuit Composition
+
+| Circuit Type | Count | Purpose |
+|:---|:---:|:---|
+| Random | 40 | Structural diversity; generalization |
+| Bell state | 15 | Two-qubit entanglement; CX error sensitivity |
+| GHZ state | 15 | Multi-qubit entanglement; error accumulation |
+| QFT | 15 | Layered gate accumulation; coherent errors |
+
+All circuits use **2-5 qubits**, **depth 2-8**, and **8,192 shots** per execution.
+
+### Device Calibration Comparison
+
+| Property | ibm_fez (A) | ibm_marrakesh (B) | Delta |
+|:---|:---:|:---:|:---:|
+| T1 (us) | 142.4 | 192.8 | +35.4% |
+| T2 (us) | 104.1 | 114.0 | +9.6% |
+| Readout error | 0.0285 | 0.0335 | +17.5% |
+| CX gate error | 0.0328 | 0.0560 | **+70.7%** |
+
+## Dataset Fields
+
+| Field | Type | Description |
+|:---|:---|:---|
+| `circuit_id` | string | Unique circuit identifier (UUID) |
+| `backend` | string | IBM Quantum backend name (`ibm_fez` or `ibm_marrakesh`) |
+| `circuit_type` | string | Circuit family: `random`, `bell`, `ghz`, or `qft` |
+| `n_qubits` | int | Number of qubits (2-5) |
+| `T1_mean` | float | Mean qubit relaxation time (seconds) |
+| `T2_mean` | float | Mean qubit dephasing time (seconds) |
+| `readout_error_mean` | float | Mean readout error rate |
+| `cx_error_mean` | float | Mean CX (CNOT) gate error rate |
+| `noisy_distribution` | string (JSON) | Measured probability distribution from real hardware |
+| `ideal_distribution` | string (JSON) | Ground-truth distribution from noiseless simulation |
+| `x` | list[float] | 41-dim input feature vector (circuit + calibration + noisy dist) |
+| `y` | list[float] | 32-dim target vector (ideal distribution, zero-padded) |
+
+### Feature Vector (`x`) Layout (41 dimensions)
+
+| Index | Feature |
+|:---|:---|
+| 0 | Number of qubits |
+| 1 | Circuit depth |
+| 2 | CX gate count |
+| 3 | H gate count |
+| 4 | X gate count |
+| 5 | Mean T1 (standardized) |
+| 6 | Mean T2 (standardized) |
+| 7 | Mean readout error (standardized) |
+| 8 | Mean CX gate error (standardized) |
+| 9-40 | Noisy output distribution (32-dim, zero-padded) |
+
+## Additional Files
+
+```
+figures/              # All paper figures (PNG + PDF)
+data/raw/             # Raw data from IBM Quantum hardware
+  calibration_A.json  # ibm_fez calibration snapshot
+  calibration_B.json  # ibm_marrakesh calibration snapshot
+  circuit_meta.json   # Circuit structure metadata
+  ideal.json          # Ideal (simulated) distributions
+  noisy_A.json        # Noisy measurements from ibm_fez
+  noisy_B.json        # Noisy measurements from ibm_marrakesh
+data/processed/       # Preprocessed datasets
+  dataset.json        # Full dataset (JSON format)
+  dataset_standardized.json  # Standardized features
+results/              # Experiment results
+  experiment_results_fixed.json
+  ablation_results_fixed.json
+  training_history.json
+  example_prediction.json
+```
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("sahilfarib/quantum-noise-transfer")
+
+# Filter by backend
+source = ds["train"].filter(lambda x: x["backend"] == "ibm_fez")
+target = ds["train"].filter(lambda x: x["backend"] == "ibm_marrakesh")
+
+print(f"Source samples: {len(source)}")  # 85
+print(f"Target samples: {len(target)}")  # 85
+```
+
+## Key Results
+
+Using this dataset, a Residual Noise Adapter trained on `ibm_fez` achieves:
+
+| Condition | KL Divergence | Improvement |
+|:---|:---:|:---:|
+| In-domain (A->A) | 0.3014 | -- |
+| Zero-shot (A->B) | 1.6706 | baseline |
+| Few-shot K=20 | **1.1924** | **-28.6%** |
+
+## Citation
+
+```bibtex
+@article{farib2026fewshot,
+  title={Few-Shot Cross-Device Transfer for Quantum Noise Modeling on Real Hardware},
+  author={Farib, Sahil Al and Islam, Sheikh Redwanul and Anik, Azizur Rahman},
+  journal={arXiv preprint arXiv:2604.24397},
+  year={2026}
+}
+```
+
+## License
+
+MIT