Rafael Macêdo
@rafammacedo.bsky.social
Quantum information theory PhD candidate @ IIP, Natal
Reposted by Rafael Macêdo
In predicting properties of electronic structure or deciphering signals produced by Nature, will classical artificial intelligence eat quantum's lunch? Here @robbieking1000.bsky.social considers the issue from the perspective of complexity theory.
quantumfrontiers.com/2025/12/11/c...
quantumfrontiers.com/2025/12/11/c...
Can AI Predict the Quantum Universe?
AI promises to revolutionize the way we do science, which raises a central technological question of our time: Can classical AI understand all natural phenomena, or are some fundamentally beyond it…
quantumfrontiers.com
December 14, 2025 at 6:16 PM
In predicting properties of electronic structure or deciphering signals produced by Nature, will classical artificial intelligence eat quantum's lunch? Here @robbieking1000.bsky.social considers the issue from the perspective of complexity theory.
quantumfrontiers.com/2025/12/11/c...
quantumfrontiers.com/2025/12/11/c...
Reposted by Rafael Macêdo
Did anyone notice that a quantum algorithms book dropped this year?
doi.org/10.1017/9781...
It's based on this paper:
arxiv.org/abs/2310.03011
doi.org/10.1017/9781...
It's based on this paper:
arxiv.org/abs/2310.03011
Quantum Algorithms
Cambridge Core - Algorithmics, Complexity, Computer Algebra, Computational Geometry - Quantum Algorithms
doi.org
November 21, 2025 at 1:24 PM
Did anyone notice that a quantum algorithms book dropped this year?
doi.org/10.1017/9781...
It's based on this paper:
arxiv.org/abs/2310.03011
doi.org/10.1017/9781...
It's based on this paper:
arxiv.org/abs/2310.03011
Reposted by Rafael Macêdo
I am extremely proud of this review article to Quantum Machine Learning 🌟🌟
arxiv.org/abs/2511.15969
Our goal was to give a bird's eye view of QML, from quantum PAC, to Linear Algebraic approaches and variational methods.
Huge thanks to my co author Su Yeon Chang@
arxiv.org/abs/2511.15969
Our goal was to give a bird's eye view of QML, from quantum PAC, to Linear Algebraic approaches and variational methods.
Huge thanks to my co author Su Yeon Chang@
A Primer on Quantum Machine Learning
Quantum machine learning (QML) is a computational paradigm that seeks to apply quantum-mechanical resources to solve learning problems. As such, the goal of this framework is to leverage quantum proce...
arxiv.org
November 21, 2025 at 2:38 AM
I am extremely proud of this review article to Quantum Machine Learning 🌟🌟
arxiv.org/abs/2511.15969
Our goal was to give a bird's eye view of QML, from quantum PAC, to Linear Algebraic approaches and variational methods.
Huge thanks to my co author Su Yeon Chang@
arxiv.org/abs/2511.15969
Our goal was to give a bird's eye view of QML, from quantum PAC, to Linear Algebraic approaches and variational methods.
Huge thanks to my co author Su Yeon Chang@