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Detailed background and inputs
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==============================
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This chapter consolidates simulation methods, external control modules, and observable analysis into one place. Use it as the deep-dive reference when selecting algorithms, driving simulations with stimuli, and interpreting outputs.
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Simulation Methods and Algorithms
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---------------------------------
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Fundamental and specialized approaches for running magnetic dynamics simulations.
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Stochastic Integration
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~~~~~~~~~~~~~~~~~~~~~~
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Numerical integration schemes (solvers) for solving the stochastic Landau-Lifshitz-Gilbert equation:
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- :doc:`input-keywords-solvers`
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Monte Carlo simulations and minimization
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Equilibrium sampling techniques for thermodynamic properties:
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- :doc:`input-keywords-montecarlo`
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Advanced Sampling and Equilibration
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Specialized methods for exploring phase space and computing thermodynamic properties:
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- :doc:`input-keywords-montecarlo`
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- :doc:`input-keywords-wanglandau`
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- :doc:`input-keywords-replicaexchange`
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Path-Finding and Optimization
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Methods for finding transitions between magnetic configurations and optimizing spin textures:
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- :doc:`input-keywords-gneb`
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- :doc:`input-keywords-spinspiral`
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Rare Event and Dynamics Methods
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Techniques for studying infrequent events and non-equilibrium dynamics:
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- :doc:`input-keywords-kmc`
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Spin-Lattice Coupling
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~~~~~~~~~~~~~~~~~~~~~
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Coupled spin and lattice evolution including magnetoelastic effects:
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- :doc:`input-keywords-sld`
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Multiscale Coupling
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~~~~~~~~~~~~~~~~~~~
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Hybrid atomistic–continuum simulations for large-scale magnetic systems:
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- :doc:`input-keywords-multiscale`
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External Stimuli and Control
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----------------------------
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Apply external driving forces and thermal control modules.
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Spatially and temporally varying magnetic fields
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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- :doc:`input-keywords-fields`
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Spin-polarized currents and torques
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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- :doc:`input-keywords-currents`
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Temperature control and three-temperature model (3TM)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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- :doc:`input-keywords-temperature-3tm`
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Temperature gradients:
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~~~~~~~~~~~~~~~~~~~~~~
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- :doc:`input-keywords-temperature-gradients`
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Observable Measurements and Analysis
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------------------------------------
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Theoretical foundations for measuring and analyzing magnetic observables and configurations.
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Magnetization Observables
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~~~~~~~~~~~~~~~~~~~~~~~~~
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Measurements of magnetization and thermodynamic moments:
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- :doc:`input-keywords-averages`
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Spin-wave Spectra (AMS/LSWT)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Adiabatic magnon spectra and linear spin-wave theory:
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- :doc:`input-keywords-ams`
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Correlations and Structure Factors
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Space and time-displaced correlation functions:
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- :doc:`input-keywords-correlations`
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- :doc:`input-keywords-autocorrelation`
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Polarization and Chirality
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~~~~~~~~~~~~~~~~~~~~~~~~~~
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Ferroelectric polarization and local chirality:
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- :doc:`input-keywords-polarization`
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Configuration Analysis and Topology
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Characterization and topological analysis of magnetic configurations:
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- :doc:`input-keywords-clusters`
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- :doc:`input-keywords-topology`
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Micromagnetic Stiffness and Parameters
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Extraction of continuum parameters from atomistic simulations:
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- :doc:`input-keywords-stiffness`
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.. toctree::
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:maxdepth: 2
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:hidden:
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dib-simulation-methods
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dib-external-stimuli
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dib-observables-analysis

content/dib-external-stimuli.rst

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External Stimuli and Control
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============================
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Apply external driving and thermal control modules.
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.. toctree::
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:maxdepth: 2
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:hidden:
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input-keywords-fields
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input-keywords-currents
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input-keywords-temperature-3tm
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input-keywords-temperature-gradients
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Observable Measurements and Analysis
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====================================
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Theory and practice for measuring and analyzing magnetic observables.
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.. toctree::
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:maxdepth: 2
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:hidden:
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input-keywords-averages
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input-keywords-ams
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input-keywords-correlations
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input-keywords-autocorrelation
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input-keywords-polarization
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input-keywords-clusters
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input-keywords-topology
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input-keywords-stiffness

content/dib-simulation-methods.rst

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Simulation Methods and Algorithms
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=================================
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Fundamental and specialized approaches for running magnetic dynamics simulations.
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.. toctree::
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:maxdepth: 2
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:hidden:
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input-keywords-solvers
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input-keywords-montecarlo
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input-keywords-wanglandau
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input-keywords-replicaexchange
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input-keywords-gneb
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input-keywords-spinspiral
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input-keywords-kmc
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input-keywords-sld
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input-keywords-multiscale

content/index.rst

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introduction
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input
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guide
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quick-reference
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output
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detailed-input-background
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tutorial
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examples
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content/input-keywords-ams.rst

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* **Magnon dispersions**: Eigenfrequencies of collective spin excitations across the Brillouin zone
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* **Density of states**: Thermodynamic and spectroscopic properties from magnon spectra
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* **Topological analysis**: Chern numbers, Berry curvature, and thermal Hall conductivity
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* **Dynamical structure factor**: :math:`S(\mathbf{q},\omega)` for comparison with inelastic neutron scattering (INS)
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The implementation follows the **Tóth-Lake formalism** [TothLake2015]_ and extensions for non-collinear magnetism, supporting:
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content/input-keywords-autocorrelation.rst

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inpsd.dat keywords: autocorrelation functions
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==============================================
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Autocorrelation functions
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=========================
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Parameters for time-resolved autocorrelation measurements
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---------------------------------------------------------
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non-equilibrium simulations. Results are written to ``autocorr.simid.out`` with
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optional spatial binning into macrocells for coarse-grained analysis.
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.. tip::
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**Input keywords:** For a complete list of all autocorrelation measurement
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parameters (``do_autocorr``, ``acfile``, ``ac_step``, etc.), see the
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comprehensive reference in :doc:`input-keywords-observables`.
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.. _autocorr-definition:
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-------------------------------------------------

content/input-keywords-averages.rst

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inpsd.dat keywords: averages and cumulants
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============================================
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Parameters for measuring averages and statistical observables
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--------------------------------------------------------------
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Averages and cumulants
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======================
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The UppASD code supports comprehensive statistical measurements of magnetization
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and thermodynamic observables during spin dynamics simulations. The averaging and
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Monte Carlo and Langevin dynamics simulations. The subsystem employs a buffered
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output strategy to minimize I/O overhead during long simulations.
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.. important::
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.. tip::
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For Monte Carlo simulations, cumulant measurements (``do_cumu``) are
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automatically enabled regardless of the input setting, as they are essential
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for characterizing equilibrium thermodynamic properties.
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**Input keywords:** For a complete list of all average and cumulant input
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parameters (``do_avrg``, ``avrg_step``, ``do_cumu``, etc.), see the
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comprehensive reference in :doc:`input-keywords-observables`.
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Canonical measurement definitions
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(seconds) instead of simulation steps in all averaging output files. This requires
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specifying the timestep ``delta_t`` in the simulation parameters.
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.. warning::
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When performing **initial phase** measurements during equilibration, ensure
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that cumulant sampling (``cumu_step``) does not begin until the system has
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thermalized. Monitor ``averages.simid.out`` to verify magnetization stability
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before analyzing cumulants.
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Notes and best practices
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**For Monte Carlo simulations:**
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- Use ``cumu_step`` comparable to or larger than system size to ensure decorrelation
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- Perform long runs (millions of sweeps) to reduce statistical noise in :math:`\langle m^4 \rangle`
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- Perform sufficiently long runs to reduce statistical noise in :math:`\langle m^4 \rangle`
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- Check convergence by monitoring running averages in ``cumulants.simid.out``
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- Use ``cumu_step`` :math:`\gg` ``avrg_step`` for reliable statistics
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- Equilibrate thoroughly before enabling cumulant measurements
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- Use projected cumulants (``do_cumu_proj Y``) to analyze sublattice ordering independently
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**Memory considerations:**
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- Buffer size ``avrg_buff`` :math:`\times` 3 :math:`\times` ``Mensemble`` determines memory per output cycle
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- For large ``Mensemble``, reduce ``avrg_buff`` to avoid memory pressure
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- Projected averages require additional memory proportional to number of types/sites
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Example inpsd.dat snippet

content/input-keywords-clusters.rst

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inpsd.dat keywords: cluster analysis
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==============================================================
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Cluster analysis keywords for grouping spins or atoms into clusters.
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--------------------------------------------------------------------------------
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The UppASD code can perform simple cluster analyses for post-processing and
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coarse-grained measurements. This page documents the input keywords used to
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control cluster detection and reporting.
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cluster_method
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Method used to define clusters. Typical values: ``distance`` (geometric cutoff), ``bond`` (bond connectivity), ``label`` (read clusters from file). Default: ``distance``.
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cluster_cutoff
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Distance cutoff (in Å) used when ``cluster_method = distance``. Two sites belong to the same cluster if their separation is less than this value. Default: **3.0**.
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cluster_file
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Path to a file containing pre-defined cluster assignments (used when ``cluster_method = label``). Format: one integer cluster id per atom, matching the system indexing used in the input files.
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Minimum number of atoms/spins for a cluster to be reported. Clusters smaller than this value are ignored. Default: **2**.
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prn_clusters
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Print cluster statistics to output (Y=yes, N=no). If enabled, the code writes cluster sizes, centroids, and a list of member indices. Default: **N**.
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save_clusters
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Save cluster assignments to disk (Y=yes, N=no). When enabled, writes ``clusters_<simid>.dat`` with one cluster id per line. Default: **N**.
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--------
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- :doc:`input-keywords-system` (system setup and atom indices)
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- :doc:`input-keywords-observables` (writing per-site outputs)
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inpsd.dat keywords: cluster embedding
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======================================
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Cluster embedding
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=================
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Parameters for embedding impurity clusters within a host system
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Input file parameters for cluster embedding
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--------------------------------------------------
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.. warning:: The original tabular grid has been replaced with a definition-style keyword list to
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avoid fragile grid-table parsing errors. See the keywords below for parameter descriptions.
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Enable cluster embedding functionality (Y=yes, N=no). When enabled, the code reads separate cluster data files and maps cluster atoms to the host system. Default: **N**.
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content/input-keywords-correlations.rst

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inpsd.dat keywords: correlation functions
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==========================================
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Correlation functions
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=====================
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--------------------------------------------------------------------------
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.. tip::
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(``do_sc``, ``do_sr``, ``sc_step``, ``qpoints``, etc.), see the comprehensive
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reference in :doc:`input-keywords-observables`.
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Sampling strategy and resolution
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--------------------------------------------------

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