jhwilson/ControlMap.jl: ControlMap.jl v1.0.0: Control-Basis and Kraus-Channel Core for Stochastic Quantum Control

This first release packages the reusable finite-dimensional control-map components used by the ControlCAT simulation repository and the stochastic quantum-control calculations behind: Andrew A. Allocca, Devesh K. Verma, Sriram Ganeshan, and Justin H. Wilson, "Universality of stochastic control of quantum chaos with measurement and feedback," arXiv:2506.10067. ControlMap.jl is intended to be the lightweight Julia base layer for constructing the paper's control basis, applying the measurement-feedback Kraus channel, and sharing those pieces across higher-level simulation workflows. Highlights Added deterministic construction of the tight-binding control basis for the operator 2 - cos(2*pi*x) - cos(2*pi*p), including reproducible phase conventions and midpoint degeneracy handling. Added a compact KrausFamily representation for the measurement-feedback Kraus operators, with allocation-conscious in-place application routines for trajectory simulations. Added probability and sampling APIs for Born-rule Kraus outcomes, including kraus_probabilities, sample_kraus_index, and apply_sample_kraus. Added the paper-default active control block convention, N_ctrl = N / 2, while also supporting full_dim=true for workflows where the channel should act on the full basis. Added operator utilities for centered grid indices, unitary DFT construction, X^2 + P^2 in position and control bases, and harmonic-oscillator ladder operators. Added lightweight visualization helpers under ControlMap.Examples, including torus coherent states and Husimi-Q diagnostics. Added runnable examples and benchmark scripts for Kraus-channel application, Husimi visualizations, eigenfunction comparisons, and X^2 + P^2 diagnostics. Added tests for basis unitarity, Kraus completeness, closed-form coefficient agreement, probability normalization, sampling behavior, and basic Husimi-Q sanity checks. Notes For ControlCAT ControlCAT can use this package as the shared base for the control-basis and Kraus-channel pieces while keeping cat-map dynamics, trajectory orchestration, and paper-scale data generation in the ControlCAT repository. The default build_kraus_family(theta, N) behavior follows the paper's N_ctrl = N / 2 convention; use build_kraus_family(theta, N; full_dim = true) only for non-cat-map workflows that intentionally apply the channel to the full Hilbert space. Install directly from GitHub with: using Pkg Pkg.add(url = "https://github.com/jhwilson/ControlMap.jl") Validation The package test suite can be run from the repository root with: julia --project=. -e 'using Pkg; Pkg.test()' The included tests cover the core numerical invariants expected from this base package: control-basis unitarity, Kraus-channel completeness, probability normalization, and agreement with the closed-form Kraus matrix elements.