Tag: quantum-computing
All the articles with the tag "quantum-computing".
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On Quantum Algorithms for Neural-Network Training: A Conjecture on Fault-Tolerant Speedups
The Suhubdy Conjecture — a three-form mathematical conjecture for a fault-tolerant quantum algorithm that accelerates — or replaces — backpropagation for empirical-risk minimisation in neural networks. Positioned against the Baur–Strassen cheap-gradient bound, Jordan and Gilyén–Arunachalam–Wiebe gradient-estimation algorithms, Abbas et al. (NeurIPS 2023) impossibility, quantum SDP and interior-point solvers, the Zhang–Leng–Li and Garg–Kothari–Netrapalli–Sherif lower bounds, and the 2024–2026 line on quantum non-logconcave sampling. Companion arXiv-style preprint (.tex source and .pdf) provided.
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The 1,000-Qubit Ceiling That Probably Isn't
Oxford physicist Tim Palmer claims quantum computers face a hard 1,000-qubit ceiling that would protect RSA and ECC forever. A careful reading of the physics and the math says otherwise---and your migration timeline should not wait to find out.
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On Quantum Backpropagation, Information Reuse, and Cheating Measurement Collapse
Can quantum models train as efficiently as classical neural networks? Abbas et al. prove backpropagation scaling is impossible without multiple copies of a quantum state, then show how shadow tomography gets you most of the way there. A deep dive into the paper that defines the trainability frontier for quantum machine learning.
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Google Just Cut the Quantum Resources to Break Bitcoin's Cryptography by 20x
Google Quantum AI, the Ethereum Foundation, and Stanford published a 57-page whitepaper showing <500,000 physical qubits and ~9 minutes suffice to break Bitcoin and Ethereum's elliptic curve cryptography---a 20x reduction over prior estimates. This is not FUD. It is an engineering specification.