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Probability - The Science of Uncertainty and Data
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Explore circuit simulation with CedarEDA: import circuits, perform simulations, compute performance measures, set up automated verification, and tune parameters for optimal results.
Explore automated theorem proving for hybrid systems using Elenchos, a Julia package simplifying verification of ModelingToolkit.jl models with differential dynamic logic and KeYmaera X.
Explore BinaryBuilder 2's redesign, addressing pain points and unlocking new capabilities for complex software projects, multiple compilers, and platforms in Julia package development.
Explore FUSE.jl, a unified framework for fusion device design using Julia. Learn how it integrates models, enhances efficiency, and optimizes fusion power plant designs through multi-objective approaches.
Explore Unitary Fund's initiatives in quantum open-source: microgrants, community activities, and research projects. Gain insights into fostering innovation and collaboration in quantum technology.
Build reusable components for scientific modeling and engineering using ModelingToolkit.jl in Julia, focusing on acausal modeling and digital twin creation.
Explore efficient sea ice modeling with Subzero.jl, leveraging Julia's speed for advanced climate simulations. Learn about discrete-element modeling and performance improvements in sea ice dynamics research.
Explore Layout.jl for CAD of quantum hardware, featuring 2D layouts, 3D models, and schematic-driven workflows. Learn geometric operations, automated placement, and integration with other tools.
Explore UnROOT.jl, a Julia package for high-performance data I/O in high-energy physics. Learn about its optimizations, type stability challenges, and performance comparisons with popular alternatives.
Explore AI's computational impact, from theoretical understanding to efficient hardware design. Gain insights on optimizing AI models for real-world applications across various computational scales.
Explore DistributedWorkflow.jl, a Julia interface for task-based workflow management. Learn to build domain-specific workflows, leverage dynamic scheduling, and simplify parallel distributed application development for HPC and domain scientists.
Learn to define and test strict interfaces in Julia using Interfaces.jl. Explore run-time and compile-time constraints, optional components, and traits for improved package interoperability and robust object behavior.
Explore RandomizedDiagonalEstimation.jl, a toolkit for implicit diagonal estimation in large matrices, featuring established algorithms and novel extensions for matrix functions.
Explore QSS algorithms for solving large sparse stiff discontinuous systems, outperforming classic solvers in specific scenarios like switched power converter circuits.
Explore quantum computing's hardware, algorithms, and challenges, with insights on Julia's role and potential in this emerging field.
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