David Jihoon Kim

on the atlas — 26

• nLab8 savers
• What Every Programmer Should Know About Memory7 savers
• [2511.17460] Improved error correction with leakage reduction units built into qubit measurement in a superconducting quantum processor1 savers
• Practical Guide for Building Superconducting Quantum Devices1 savers
• [2110.00557] The QICK (Quantum Instrumentation Control Kit): Readout and control for qubits and detectors1 savers
• DGoettlich/history-llms: Information hub for our project training the largest possible historical LLMs. ·1 savers
• [2402.17764] The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits1 savers
• An Elementary Introduction to Information Geometry1 savers
• Statistical Mechanics of Deep Learning2 savers
• [2304.03408] Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks1 savers
• [2404.07200] Toward a Better Understanding of Fourier Neural Operators from a Spectral Perspective1 savers
• Benchmarking the noise sensitivity of different parametric two-qubit gates in a single superconducting quantum computing platform | Phys. Rev. Research1 savers
• Quantum computing with trapped ions - ScienceDirect1 savers
• 3D-printed micro ion trap technology for quantum information applications | Nature1 savers
• [2507.20100] Circuit simulation of readout process toward large-scale superconducting quantum circuits1 savers
• Erasure Qubits: Overcoming the Limit in Superconducting Circuits | Phys. Rev. X1 savers
• PhysRevApplied.10.0540621 savers
• [1610.03438] Introduction to Quantum Electromagnetic Circuits1 savers
• [2503.10935] Bias-preserving and error-detectable entangling operations in a superconducting dual-rail system1 savers
• [2601.20927] Entangling logical qubits without physical operations1 savers
• [2510.01346] Aristotle: IMO-level Automated Theorem Proving2 savers
• Beyond Linear Response: Equivalence between Thermodynamic Geometry and Optimal Transport | Phys. Rev. Lett.1 savers
• [2110.03922] The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks1 savers
• Why We Think | Lil'Log25 savers
• The last six months in LLMs, illustrated by pelicans on bicycles1 savers
• microgpt1 savers