Clustered‑Cyclic qLDPC Codes Spotlighted at Growing QEC2026
The accepted talks at #QEC2026 on #QuantumErrorCorrection are out. This conference has grown from a small fringe event into a major conference, mirroring the rapid development of the field. https://t.co/A7laIEyznK I am glad to see our work on clustered-cyclic codes on the list of accepted talks, as a means to do resource-economical, relatively simple and highly parallelizable quantum computing with qLDPC codes https://t.co/LhqZfibd24. Warm thanks to Boren Gu, Andy Liu, @armanda_oq, Qian Xu, and @Joschka_Roffe for the wonderful collaboration.
QCTiP2026 Launches in Oxford with Five Quantum Talks
#QCTiP2026 is about to begin in Oxford. Given the rapid progress in the field, this conference on quantum computing theory in practice could hardly be more timely: https://t.co/FCb3yhGhgD was a real pleasure to host #QCTiP2025 in Berlin last year, and...
Tight Bounds Reveal Optimal Inference Complexity for Quantum Kernels
Optimal algorithmic complexity of inference in quantum kernel methods for classical data. Quantum kernel methods are among the leading candidates for achieving quantum advantage in supervised machine learning. A key bottleneck is the cost of inference: evaluating a trained model on...
Bridging Gaps: Navigating Roadblocks to Quantum Advantage
The challenges in and possibilities of achieving quantum advantage. It has been a great pleasure to discuss with @science_eye where we stand in quantum computing, what the remaining road blocks or "gaps" are and how we can overcome them. Recent months...
Quantum 2025 Trends: Error Correction Dominates, Simulation Lags
On his blog https://t.co/OV89KJngtS, the friend and colleague @quantum_minhsiu presents the 2025 "trends in quantum research". He offers the results of a comprehensive analysis of quantum papers and their ranking on SciRate, having run sophisticated scripts. Some trends do not surprise...
Logarithmic-Depth Quantum Circuits Possible Without Error Correction
In the absence of quantum error correction, and under fairly general—possibly even non-unital—noise models, one can still hope to achieve quantum circuits of logarithmic depth. While these can still be quite deep in practice, this insight is important when planning...
Just-in-Time Decoding Enables High‑Threshold 2D Non‑Pauli Quantum Gates
Recent weeks have brought a range of new ideas in quantum error correction for fault tolerant-quantum computing, along with deeper exploration of their implications. We introduce a new approach: a method for achieving high-threshold decoding of non-Pauli codes aimed at...
Mid‑circuit Measurements Add Magic, Making Adaptive FLO Classically Hard
Measurement-induced non-commutativity in adaptive fermionic linear optics We show that mid-circuit measurements of fermions with internal degrees of freedom can induce the equivalent of "magic" to free fermionic circuits and render them classically hard to sample. https://t.co/r7rZBcyLHL Fermionic linear optics (FLO) with Gaussian...
New Randomized Measurement Protocol Estimates Arbitrary Nonlinear Quantum Observables Optimally
Optimal randomized measurements for a family of nonlinear quantum properties: We answer how non-linear quantities can be estimated with the same standards as expectation values in classical shadows. https://t.co/6e3fWUyL0p Quantum learning encounters fundamental challenges when estimating nonlinear properties, owing to the inherent linearity...
Quantum-Centric Supercomputing Accelerates Future Computing Frontier
It was a great pleasure—and truly exciting—to moderate the “Key Dialogue Quantum Technologies” and to listen to the great and impressive talk “Transforming Computing with Quantum-Centric Supercomputing” by @jmchow. His talk at the #GCConference was a wonderful showcase of cutting-edge technology and the...
First PAC‑Bayesian Data‑Dependent Generalization Bounds for Quantum Models
A PAC-Bayesian approach to generalization for quantum models. We take steps towards non-uniform and data-dependent bounds for generalization of quantum machine learning models. https://t.co/czcmNpnD0q In detail, #generalization is a central concept in machine learning theory, yet for quantum models, it is predominantly analyzed...
Quantum Simulations Target Real-World Industrial and Societal Challenges
The third session of the #QuantumTechnologies track at the #GCConference of the @BerlinUAlliance is dedicated to exploring how quantum simulation can address industrial and societal challenges. Stefan Kühn opens the session with perspectives on using quantum computers to tackle problems in...
Advancing Quantum Networks: Optical Experiments and Hybrid Photonics
The second #quantumtechnologies session at the #GCConference focused on experimental quantum optical implementations of quantum communication concepts. Eleni Diamanti opened the session with an inspiring talk on the Paris-based efforts toward quantum networks. She was followed by Matheus Ribeiro-Sen, who spoke...
Quantum Computing Meets AI at GCConference Kickoff
We had a great start to the #quantumtechnologies theme at the #GCConference, with two sessions. Christian Gogolin delivered an inspiring and insightful keynote on the use of quantum computers in quantum chemistry. This was followed by three eminent researchers who explored...
Compact Zero Modes Cap Entanglement Growth in Bosonic Systems
How compactness curbs entanglement growth in bosonic systems This work addresses a puzzling phenomenon in the study of entanglement in continuous quantum field descriptions. https://t.co/IxMegFdqnj #Zeromodes, understood here as degrees of freedom with vanishing confining frequency, play a central role in the #nonequilibrium...