3 citations · 9 across the 10 of their papers we have counts for
10 papers
Eigenstate Preparation Through Near-Optimal Eigenprobability Filtering
Po-Wei Huang, Bence Bakó, Bálint Koczor
Quantum simulation is expected to be a main application of quantum computers with realistic utility in quantum chemistry, materials science and beyond. However, preparing excited o…
Quantum enhanced rare event discovery and sampling
Naixu Guo, Po-Wei Huang, Qisheng Wang +4
Financial crashes, cascading failures in infrastructure, and critical errors in AI systems are frequently triggered by events that occur with extremely small probability. Efficient…
Low-depth amplitude estimation via statistical eigengap estimation
Po-Wei Huang, Bálint Koczor
Amplitude estimation, in its original form, is formulated as phase estimation upon the Grover iterate. Subsequent improvements to the algorithm have eliminated the need for phase e…
Accelerating Inference for Multilayer Neural Networks with Quantum Computers
Arthur G. Rattew, Po-Wei Huang, Naixu Guo +2
Fault-tolerant Quantum Processing Units (QPUs) promise to deliver exponential speed-ups in select computational tasks, yet their integration into modern deep learning pipelines rem…
Fullqubit alchemist: Quantum algorithm for alchemical free energy calculations
Po-Wei Huang, Gregory Boyd, Gian-Luca R. Anselmetti +11
Accurately computing the free energies of biological processes is a cornerstone of computer-aided drug design, but it is a daunting task. The need to sample vast conformational spa…
QKAN: quantum Kolmogorov-Arnold networks with applications in machine learning and multivariate state preparation
Petr Ivashkov, Po-Wei Huang, Kelvin Koor +2
We introduce quantum Kolmogorov-Arnold networks (QKAN), a quantum algorithmic framework inspired by the recently proposed Kolmogorov-Arnold Networks (KAN). QKAN inherits the compos…
Concept learning of parameterized quantum models from limited measurements
Beng Yee Gan, Po-Wei Huang, Elies Gil-Fuster +1
Classical learning of the expectation values of observables for quantum states is a natural variant of learning quantum states or channels. While learning-theoretic frameworks esta…
Quantum algorithm for large-scale market equilibrium computation
Po-Wei Huang, Patrick Rebentrost
Classical algorithms for market equilibrium computation such as proportional response dynamics face scalability issues with Internet-based applications such as auctions, recommende…
Classical combinations of quantum states for solving banded circulant linear systems
Po-Wei Huang, Xiufan Li, Kelvin Koor +1
Solving linear systems is of great importance in numerous fields. Proposed quantum algorithms for preparing solutions for linear systems include the HHL algorithm with subsequent r…
Post-variational quantum neural networks
Po-Wei Huang, Patrick Rebentrost
Hybrid quantum-classical computing in the noisy intermediate-scale quantum (NISQ) era with variational algorithms can exhibit barren plateau issues, causing difficult convergence o…