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Quantum Bayesian Inference with Renormalization for Gravitational Waves

3 points by westurner 2y ago

westurner 2y ago
ScholarlyArticle: "Quantum Bayesian Inference with Renormalization for Gravitational Waves" (2025) https://iopscience.iop.org/article/10.3847/2041-8213/ada6ae https://iopscience.iop.org/article/10.3847/2041-8213/ada6ae NewsArticle: "Black Holes Speak in Gravitational Waves, Heard Through Quantum Walks" (2025) https://thequantuminsider.com/2025/01/29/black-holes-speak-in-gravitational-waves-heard-through-quantum-walks/ https://thequantuminsider.com/2025/01/29/black-holes-speak-i... : > Unlike classical MCMC, which requires a large number of iterative steps to converge on a solution, QBIRD uses a quantum-enhanced Metropolis algorithm that incorporates quantum walks to explore the parameter space more efficiently. Instead of sequentially evaluating probability distributions one step at a time, QBIRD encodes the likelihood landscape into a quantum Hilbert space, allowing it to assess multiple transitions between parameter states simultaneously. This is achieved through a set of quantum registers that track state evolution, transition probabilities, and acceptance criteria using a modified Metropolis-Hastings rule. > Additionally, QBIRD incorporates renormalization and downsampling, which progressively refine the search space by eliminating less probable regions and concentrating computational resources on the most likely solutions. These techniques enable QBIRD to achieve accuracy comparable to classical MCMC while reducing the number of required samples and computational overhead, making it a more promising approach for gravitational wave parameter estimation as quantum hardware matures.
- westurner 2y ago
  Parameter estimation algorithms: "Learning quantum Hamiltonians at any temperature in polynomial time" (2024) https://arxiv.org/abs/2310.02243 https://arxiv.org/abs/2310.02243 .. https://news.ycombinator.com/item?id=40396171 https://news.ycombinator.com/item?id=40396171 "Robustly learning Hamiltonian dynamics of a superconducting quantum processor" (2024) https://www.nature.com/articles/s41467-024-52629-3 https://www.nature.com/articles/s41467-024-52629-3 .. https://news.ycombinator.com/item?id=42086445 https://news.ycombinator.com/item?id=42086445

3 points by westurner 2y ago

ScholarlyArticle: "Quantum Bayesian Inference with Renormalization for Gravitational Waves" (2025) https://iopscience.iop.org/article/10.3847/2041-8213/ada6ae https://iopscience.iop.org/article/10.3847/2041-8213/ada6ae NewsArticle: "Black Holes Speak in Gravitational Waves, Heard Through Quantum Walks" (2025) https://thequantuminsider.com/2025/01/29/black-holes-speak-in-gravitational-waves-heard-through-quantum-walks/ https://thequantuminsider.com/2025/01/29/black-holes-speak-i... : > Unlike classical MCMC, which requires a large number of iterative steps to converge on a solution, QBIRD uses a quantum-enhanced Metropolis algorithm that incorporates quantum walks to explore the parameter space more efficiently. Instead of sequentially evaluating probability distributions one step at a time, QBIRD encodes the likelihood landscape into a quantum Hilbert space, allowing it to assess multiple transitions between parameter states simultaneously. This is achieved through a set of quantum registers that track state evolution, transition probabilities, and acceptance criteria using a modified Metropolis-Hastings rule. > Additionally, QBIRD incorporates renormalization and downsampling, which progressively refine the search space by eliminating less probable regions and concentrating computational resources on the most likely solutions. These techniques enable QBIRD to achieve accuracy comparable to classical MCMC while reducing the number of required samples and computational overhead, making it a more promising approach for gravitational wave parameter estimation as quantum hardware matures.

westurner 2y ago
Parameter estimation algorithms: "Learning quantum Hamiltonians at any temperature in polynomial time" (2024) https://arxiv.org/abs/2310.02243 https://arxiv.org/abs/2310.02243 .. https://news.ycombinator.com/item?id=40396171 https://news.ycombinator.com/item?id=40396171 "Robustly learning Hamiltonian dynamics of a superconducting quantum processor" (2024) https://www.nature.com/articles/s41467-024-52629-3 https://www.nature.com/articles/s41467-024-52629-3 .. https://news.ycombinator.com/item?id=42086445 https://news.ycombinator.com/item?id=42086445