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Asian Option Dataset
The dataset used in the paper is the Asian option dataset, which consists of 32 intervals (5 qubits) and a minimum value of 17. and a maximum value of 300. -
Scalably learning quantum many-body Hamiltonians from dynamical data
The dataset used in the paper is a collection of measurement outcomes from dynamical data, used to learn families of interacting many-body Hamiltonians. -
Traveling Salesman Problem (TSP) instances
The dataset used in the paper is the Traveling Salesman Problem (TSP) instances, specifically the Burma'7 instance, and six additional instances with 5 to 14 nodes. -
Modelling Dynamic Interactions Between Relevance Dimensions
The dataset used in the paper is a user study dataset, where participants are shown query-document pairs and asked questions about different relevance dimensions. -
Quantum Adiabatic Algorithm Design using Reinforcement Learning
The dataset used in the paper is a reinforcement learning-based approach for automated quantum adiabatic algorithm design. The dataset consists of Grover search and 3-SAT problems. -
Faster Stochastic First-Order Method for Maximum-Likelihood Quantum State Tom...
Maximum-likelihood quantum state tomography dataset -
Lattice QCD datasets
The dataset used in this paper is a collection of lattice QCD simulations, specifically the three-point correlation function data of nucleon vector and axial-vector charges. -
Quantum CNN Dataset
The dataset used in this paper is a dataset for training quantum convolutional neural networks. -
Quantum CNN
The dataset used in this paper is a quantum convolutional neural network (QCNN) dataset. -
Quantum Neural Network
The dataset used in this paper is not explicitly described, but it is mentioned that the authors used a dataset for regression/classification problems in the quantum setting. -
Unitary Compilation Dataset
The dataset used for unitary compilation task. -
Entanglement Generation Dataset
The dataset used for entanglement generation and unitary compilation tasks. -
Reservoir Computing via Quantum Recurrent Neural Networks
The dataset used in this paper is a function approximation and time-series prediction framework. -
SARS-CoV-2 Complete Genomes
The dataset used for training and testing the quantum style-based GAN model for predicting spike protein variation structure of COVID-19 epidemic strains. -
SARS-CoV-2 RNA sequences
The dataset used for training and testing the quantum style-based GAN model for predicting spike protein variation structure of COVID-19 epidemic strains. -
Quantum State Generation with Structure-Preserving Diffusion Model
The dataset consists of quantum states of a 4-qubit system with three different levels of entanglements.
