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Quantum Computing: 30th September 2025

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Published 30th September 2025

🧪 Photonic and atomic hardware breakthroughs

Research highlight: single photon Skyrmions from on-chip quantum dots (elight​.springeropen​.com). On-chip quantum dot in a Gaussian Fabry–Pérot cavity yields single-photon Skyrmions via spin-polarized Laguerre–Gaussian modes and magnetic-field tuning

Caltech Team Sets Record with 6,100-Qubit Array (caltech​.edu). Caltech reports 6,100 neutral-atom qubits in a laser-trapped array, achieving long superposition and high fidelity for scalable quantum computing

This New Time Crystal is Visible (backreaction​.blogspot​.com). Visible time crystal discussed by Sabine Hossenfelder in physics video

A new approach to magnify wave functions when imaging interacting ultracold atoms (phys​.org). Magnifying ultracold fermionic wave functions with laser-shaped potentials enables real-space imaging of hidden spatial structures

🔐 Post-quantum crypto and quantum communications

Introducing (Maybe) LibOQS.NET - a post quantum cryptography library for .NET (strathweb​.com). Introducing (Maybe) LibOQS.NET: a cross-platform .NET wrapper around liboqs for ML-KEM, ML-DSA, and SLH-DSA with sample usage

Extrapolating quantum factoring (johndcook​.com). Extrapolating from two data points on quantum factoring using linear, exponential, and double-exponential models with Python curve fitting

New relay architecture based on a quantum dot single-photon source enables secure communication across 300 km (phys​.org). Quantum dot single-photon source enables 300 km secure quantum communication via a five-node relay network

Post-quantum RSA with gargantuan keys (johndcook​.com). Post-quantum RSA with gargantuan keys discusses Shor's algorithm impact and terabyte RSA keys for post-quantum security, citing Daniel Bernstein

🧠 Computational theory and quantum foundations

Applied introduction to Categorical treatment of CuTe (veitner​.bearblog​.dev). Explores categorical treatment of CuTe Layouts using morphisms, composition, projections, expansions, and coalesced maps with Python CuTe tooling

The QMA Singularity (scottaaronson​.blog). Scott Aaronson and Freek Witteveen study black-box amplification limits in QMA with a quantum oracle separation and AI-assisted proof ideas

HSBC unleashes yet another “qombie”: a zombie claim of quantum advantage that isn’t (scottaaronson​.blog). HSBC and IBM claim quantum-assisted 34% predictive gain in bond trading via quantum data transforms amid noisy hardware

Does The Weak Mixing Angle Minimize Magic? (dispatchesfromturtleisland​.blogspot​.com). Weak mixing angle near Z boson energy minimizes quantum magic, suggesting a derived constant link to Standard Model physics

In which I lose faith in quantum computing (backreaction​.blogspot​.com). Sabine Hossenfelder discusses doubts about quantum computing prospects and practical challenges

Quoting Scott Aaronson (simonwillison​.net). Freek and I could’ve solved the problem, but AI-assisted iteration helped refine a potential approach

📚 Academic Research

Not All Qubits are Utilized Equally (arxiv:cs). Analyzes qubit utilization on IBM's 27-qubit Falcon R4 with Qiskit, showing bias toward trivial mapping and potential optimizations

Average-Case Complexity of Quantum Stabilizer Decoding (arxiv:cs). Decoding random stabilizer codes is at least as hard as decoding random classical codes at constant rate, with quantum entropy and mixing-time barriers

Gate-Based and Annealing-Based Quantum Algorithms for the Maximum K-Plex Problem (arxiv:cs). Quantum gate-based and annealing-based algorithms for maximum k-plex; qTKP, qMKP, qaMKP; experiments on IBM Q simulator and D-Wave

Quantum error correction beyond $SU(2)$ spin, bosonic, and permutation-invariant codes from convex geometry (arxiv:math). Framework linking SU(q) representations to composite quantum codes across qubit, bosonic, and monolithic atomic spaces via convex geometry and Sidon-set constructions

You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models (arxiv:cs). Single-shot quantum machine learning: reduces measurements, uses probability aggregation and sharpened loss for MNIST/CIFAR-10

👋 Before you go

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