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Found 11 papers, 6 papers with code
RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training
Arbitrary state preparation algorithms can be broadly categorized into arithmetic decomposition (AD) and variational quantum state preparation (VQSP).
Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers
Quantum Error Correction (QEC) mitigates this by employing redundancy, distributing quantum information across multiple data qubits and utilizing syndrome qubits to monitor their states for errors.
QuEst: Graph Transformer for Quantum Circuit Reliability Estimation
Specifically, the TorchQuantum library also supports using data-driven ML models to solve problems in quantum system research, such as predicting the impact of quantum noise on circuit fidelity and improving the quantum circuit compilation efficiency.
NAPA: Intermediate-level Variational Native-pulse Ansatz for Variational Quantum Algorithms
Therefore, we propose NAPA, a native-pulse ansatz generator framework for VQAs.
QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning
Nevertheless, we find that due to the significant quantum errors (noises) on real machines, gradients obtained from naive parameter shift have low fidelity and thus degrading the training accuracy.
QuantumNAT: Quantum Noise-Aware Training with Noise Injection, Quantization and Normalization
Furthermore, to improve the robustness against noise, we propose noise injection to the training process by inserting quantum error gates to PQC according to realistic noise models of quantum hardware.
Towards Efficient On-Chip Training of Quantum Neural Networks
The results demonstrate that our on-chip training achieves over 90% and 60% accuracy for 2-class and 4-class image classification tasks.
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits
Extensively evaluated with 12 QML and VQE benchmarks on 14 quantum computers, QuantumNAS significantly outperforms baselines.
Systematic Crosstalk Mitigation for Superconducting Qubits via Frequency-Aware Compilation
One of the key challenges in current Noisy Intermediate-Scale Quantum (NISQ) computers is to control a quantum system with high-fidelity quantum gates.
Quantum Physics
SQUARE: Strategic Quantum Ancilla Reuse for Modular Quantum Programs via Cost-Effective Uncomputation
Compiling high-level quantum programs to machines that are size constrained (i. e. limited number of quantum bits) and time constrained (i. e. limited number of quantum operations) is challenging.
Quantum Physics
Minimizing State Preparations in Variational Quantum Eigensolver by Partitioning into Commuting Families
Variational quantum eigensolver (VQE) is a promising algorithm suitable for near-term quantum machines.
Quantum Physics
