datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
quantum-representations
Epsilon-Transformers Belief Analysis Dataset
This dataset contains trained neural network models and their corresponding belief state regression analysis from the Epsilon-Transformers project. The models were trained on four different stochastic processes and analyzed for their ability to learn and represent belief states.
See https://github.com/adamimos/epsilon-transformers/tree/quantum-public for codebase which generated this data.
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/SimplexAI/quantum-representations.quantum-machine-learninga continuous data scrape of arxiv and google scholar papers of quantum machine learning papers particularly regarding climate.
quantum-gate-sequence-instability-v0.1
quantum-gate-sequence-instability-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in quantum gate sequences.
Each row represents a simplified quantum circuit execution scenario described through observable device and circuit proxies.
The task is to determine whether the gate sequence remains executable inside a stable coherence window or becomes unstable.
Core stability idea
Quantum gate sequences become unstable when… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/quantum-gate-sequence-instability-v0.1.quantum-error-correction-failure-v0.1
quantum-error-correction-failure-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in quantum error correction regimes.
Each row represents a simplified quantum computing scenario where logical qubits are protected using error correction.
The task is to determine whether the correction mechanism remains stable or fails due to noise and correction latency.
Core stability idea
Quantum error correction works by detecting and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/quantum-error-correction-failure-v0.1.quantum-entanglement-decay-instability-v0.1
quantum-entanglement-decay-instability-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in entangled quantum states.
Each row represents a simplified quantum system described through observable device and interaction proxies.
The task is to determine whether the entangled state remains stable or collapses due to noise and interaction instability.
Core stability idea
Entanglement stability depends on maintaining coherent… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/quantum-entanglement-decay-instability-v0.1.qna-quantum-information
Q&A Quantum Information Dataset
This dataset is created by digesting 500 different papers from the quantum information directory on arXiv,
the papers are located based on their relevance to the quantum information keyword.
Data retrieval
The data is extracted from the .pdf files using PyMuPDF package proxied from langchain.
Then the Q&A pair is generated by:
Generate N questions per page of the .pdf document based on its content.
We will feed each question to an LLM… See the full description on the dataset page: https://huggingface.co/datasets/CoAILab/qna-quantum-information.quantum-control-pulse-instability-v0.1
quantum-control-pulse-instability-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in quantum control pulse regimes.
Each row represents a simplified control scenario where quantum gates are implemented through microwave or optical pulse sequences.
The task is to determine whether the pulse regime remains stable or becomes unstable due to drift, noise, or synchronization failures.
Core stability idea
Quantum control… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/quantum-control-pulse-instability-v0.1.Quantum-Programming🧑💻 Overview
This dataset focuses on Quantum Programming and contains curated information that can be used for research, education, and model training. Quantum programming is an emerging field that leverages the principles of quantum mechanics to develop new algorithms and computational techniques. This dataset aims to provide structured information that can help both beginners and advanced users explore concepts, applications, and trends in quantum computing.
📂 Dataset Contents
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/as-krn/Quantum-Programming.Quantum_Gate_Performance_Evaluation
🧪 Quantum Gate Performance Dataset
📘 Title:
Comprehensive Quantum Gate Performance Analysis: A Comparative Study of Noise and No-Noise Effects
📂 Dataset Description:
This repository contains benchmarking results for 13 quantum gates (e.g., H, CNOT, Toffoli) tested under noisy and noise-free conditions, based on 1000 simulation runs per gate configuration. Total 26000 rows and 13 columns.
📊 Features include:
Gate Type
Execution Time
Error Rate
Fidelity… See the full description on the dataset page: https://huggingface.co/datasets/ismielabir/Quantum_Gate_Performance_Evaluation.quantum-coherence-instability-v0.1
quantum-coherence-instability-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in quantum coherence conditions.
Each row represents a simplified quantum computing stability scenario described through observable system proxies.
The task is to determine whether the system remains within a stable coherence window or is moving toward coherence collapse.
Core stability idea
Quantum computation depends on maintaining coherent… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/quantum-coherence-instability-v0.1.quantum_error_correction_telemetrycrowdsourced-robotinder-demoQuantummetrologyengine-predictive-maintenancetestABCquantum_competition