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Hilbert Space is a category for books that develop and apply the mathematics of Hilbert spaces—the infinite-dimensional analogue of Euclidean space where inner products, length, and orthogonality make rigorous analysis possible. It includes accessible introductions to functional analysis and linear operators; advanced monographs on spectral theory, partial differential equations, and operator algebras; and application-driven works in quantum mechanics, signal processing, statistics, and machine learning. Readers will find problem collections, conceptual overviews, and research treatises featuring tools like Fourier and wavelet analysis, reproducing kernels, projections, and eigenvalue methods. This category serves mathematicians, physicists, engineers, and scientifically curious readers seeking the geometric and analytic backbone underlying much of modern theory and technology.

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