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Quantum error mitigation and correction mediated by Yang-Baxter equation and artificial neural network
The manuscript introduces the basics of quantum error sources and explores the potential of using classical computation for error mitigation.
QArchSearch: A Scalable Quantum Architecture Search Package
The current era of quantum computing has yielded several algorithms that promise high computational efficiency.
Fundamental causal bounds of quantum random access memories
Quantum random access memory (QRAM), a fundamental component of many essential quantum algorithms for tasks such as linear algebra, data search, and machine learning, is often proposed to offer $\mathcal{O}(\log N)$ circuit depth for $\mathcal{O}(N)$ data size, given $N$ qubits.
Towards provably efficient quantum algorithms for large-scale machine-learning models
Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process.
Estimating the randomness of quantum circuit ensembles up to 50 qubits
Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information.
Ab Initio Molecular Dynamics on Quantum Computers
Ab initio molecular dynamics (AIMD) is a valuable technique for studying molecules and materials at finite temperatures where the nuclei evolve on potential energy surfaces obtained from accurate electronic structure calculations.
Chemical Physics
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
Proposed recently, the Quantum Approximate Optimization Algorithm (QAOA) is considered as one of the leading candidates for demonstrating quantum advantage in the near term.
Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems
The Quantum Approximate Optimization Algorithm (QAOA) is arguably one of the leading quantum algorithms that can outperform classical state-of-the-art methods in the near term.
Evaluating Quantum Approximate Optimization Algorithm: A Case Study
We perform a large-scale numerical study of the approximation ratios attainable by QAOA is the low- to medium-depth regime.
Quantum Physics Data Structures and Algorithms
