Polfed.jl provides an efficient implementation of polynomially filtered Lanczos diagonalization for mid-spectrum eigenpairs in quantum many-body systems, supporting larger sizes via on-the-fly polynomial transformations and GPU acceleration.
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A qualitative study of mixed-ability teams identifies four types of interrelated failures and workarounds in information representation use, influenced by stigmas and social dynamics.
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Computing eigenpairs of quantum many-body systems with Polfed.jl
Polfed.jl provides an efficient implementation of polynomially filtered Lanczos diagonalization for mid-spectrum eigenpairs in quantum many-body systems, supporting larger sizes via on-the-fly polynomial transformations and GPU acceleration.
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"If We Had the Information That We Need to Interpret the World Around Us, We Wouldn't Be Disabled:" Barriers and Opportunities in Information Work among Blind and Sighted Colleagues
A qualitative study of mixed-ability teams identifies four types of interrelated failures and workarounds in information representation use, influenced by stigmas and social dynamics.