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Docs: Fix :alt: figure text again (#6348)
Follow up to #5386. @ax3l pointed out that the :alt: text should always provide a concise description of the image for digital accessibility, even if the caption is also always accessible.
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Docs/source/dataanalysis/picviewer.rst

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=========
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.. figure:: sample_image.png
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:alt: PICViewer GUI interface for WarpX data visualization
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PICViewer is a visualization GUI implemented on PyQt.
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The toolkit provides various easy-to-use functions for data analysis of

Docs/source/dataanalysis/visit.rst

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Your image should look similar to the one below
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.. figure:: Ez.png
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:alt: Visit visualization of Ez field component
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In 3D, you must apply the “Operators” -> “Slicing”

Docs/source/dataanalysis/visualpic.rst

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Example: ``vpic3d -Ex diags/diag1/`` could be used to visualize the transverse focusing field :math:`E_x` in a plasma wake behind a laser pulse (linearly polarized in :math:`E_y`), see below:
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.. figure:: https://user-images.githubusercontent.com/1353258/233236692-4d75b12f-de44-43dc-97bd-c96b04ee68ac.png
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:alt: 3D visualization of plasma wake fields in VisualPIC
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Example view of a 3D rendering with VisualPIC.

Docs/source/dataanalysis/workflows/tunneling.rst

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* ``Ctrl+C`` the SSH tunnel in terminal B
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.. figure:: https://user-images.githubusercontent.com/1353258/232120440-3965fa38-9ca6-4621-a100-2da74eb899cf.png
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:alt: Remote Jupyter setup with SSH tunnel and local browser connection
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Example view of remote started Jupyter service, active SSH tunnel, and local browser connecting to the service.

Docs/source/theory/amr.rst

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.. _fig_ESAMR:
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.. figure:: ICNSP_2011_Vay_fig1.png
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:alt: Mesh refinement implementation for electrostatic and electromagnetic solvers
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Sketches of the implementation of mesh refinement in WarpX with the electrostatic (left) and electromagnetic (right) solvers. In both cases, the charge/current from particles are deposited at the finest levels first, then interpolated recursively to coarser levels. In the electrostatic case, the potential is calculated first at the coarsest level :math:`L_0`, the solution interpolated to the boundaries of the refined patch :math:`r` at the next level :math:`L_{1}` and the potential calculated at :math:`L_1`. The procedure is repeated iteratively up to the highest level. In the electromagnetic case, the fields are computed independently on each grid and patch without interpolation at boundaries. Patches are terminated by absorbing layers (PML) to prevent the reflection of electromagnetic waves. Additional coarse patch :math:`c` and fine grid :math:`a` are needed so that the full solution is obtained by substitution on :math:`a` as :math:`F_{n+1}(a)=F_{n+1}(r)+I[F_n( s )-F_{n+1}( c )]` where :math:`F` is the field, and :math:`I` is a coarse-to-fine interpolation operator. In both cases, the field solution at a given level :math:`L_n` is unaffected by the solution at higher levels :math:`L_{n+1}` and up, allowing for mitigation of some spurious effects (see text) by providing a transition zone via extension of the patches by a few cells beyond the desired refined area (red & orange rectangles) in which the field is interpolated onto particles from the coarser parent level only.
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.. _fig_ESselfforce:
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.. figure:: ICNSP_2011_Vay_fig2.png
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:alt: Particle trajectory near metallic boundary with different refinement methods
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Position history of one charged particle attracted by its image induced by a nearby metallic (dirichlet) boundary. The particle is initialized at rest. Without refinement patch (reference case), the particle is accelerated by its image, is reflected specularly at the wall, then decelerates until it reaches its initial position at rest. If the particle is initialized inside a refinement patch, the particle is initially accelerated toward the wall but is spuriously reflected before it reaches the boundary of the patch whether using the method implemented in WarpX or the MC method. Providing a surrounding transition region 2 or 4 cells wide in which the potential is interpolated from the parent coarse solution reduces significantly the effect of the spurious self-force.
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.. _fig_ESselfforcemap:
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.. figure:: ICNSP_2011_Vay_fig3.png
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:alt: Maps and lineouts of spurious self-force in refinement patch
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(left) Maps of the magnitude of the spurious self-force :math:`\epsilon` in arbitrary units within one quarter of the refined patch, defined as :math:`\epsilon=\sqrt{(E_x-E_x^{ref})^2+(E_y-E_y^{ref})^2}`, where :math:`E_x` and :math:`E_y` are the electric field components within the patch experienced by one particle at a given location and :math:`E_x^{ref}` and :math:`E_y^{ref}` are the electric field from a reference solution. The map is given for the WarpX and the MC mesh refinement algorithms and for linear and quadratic interpolation at the patch refinement boundary. (right) Lineouts of the maximum (taken over neighboring cells) of the spurious self-force. Close to the interface boundary (x=0), the spurious self-force decreases at a rate close to one order of magnitude per cell (red line), then at about one order of magnitude per six cells (green line).

Docs/source/theory/boosted_frame.rst

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.. _fig_Boosted_frame:
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.. figure:: Boosted_frame.png
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:alt: Scale transformation in boosted frame simulation
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A first principle simulation of a short driver beam (laser or charged particles) propagating through a plasma that is orders of magnitude longer necessitates a very large number of time steps. Recasting the simulation in a frame of reference that is moving close to the speed of light in the direction of the driver beam leads to simulating a driver beam that appears longer propagating through a plasma that appears shorter than in the laboratory. Thus, this relativistic transformation of space and time reduces the disparity of scales, and thereby the number of time steps to complete the simulation, by orders of magnitude.
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Docs/source/theory/boosted_frame/input_output.rst

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.. _fig_inputoutput:
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.. figure:: Input_output.png
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:alt: Particle beam interactions with injection plane and diagnostic stations
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(top) Snapshot of a particle beam showing “frozen" (grey spheres) and “active" (colored spheres) macroparticles traversing the injection plane (red rectangle). (bottom) Snapshot of the beam macroparticles (colored spheres) passing through the background of electrons (dark brown streamlines) and the diagnostic stations (red rectangles). The electrons, the injection plane and the diagnostic stations are fixed in the laboratory plane, and are thus counter-propagating to the beam in a boosted frame.

Docs/source/theory/boundary_conditions.rst

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.. _fig_PEC_boundary_deposition:
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.. figure:: https://user-images.githubusercontent.com/40245517/221491318-b0a2bcbc-b04f-4b8c-8ec5-e9c92e55ee53.png
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:alt: Current deposition at absorbing and reflecting PEC boundaries
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PEC boundary current deposition along the ``x``-axis. The left boundary is absorbing while the right boundary is reflecting.

Docs/source/theory/cold_fluid_model.rst

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.. _fig_fluid_loop:
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.. figure:: https://github.com/BLAST-WarpX/warpx/assets/69021085/dcbcc0e4-7899-43e4-b580-f57eb359b457
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:alt: Fluid time step integration within PIC loop
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Fluid loop embedded within the overall PIC loop.
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Docs/source/theory/intro.rst

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.. _fig-pic:
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.. figure:: PIC.png
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:alt: Core PIC algorithm cycle showing field and particle operations
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The core Particle-In-Cell (PIC) algorithm involves four operations at each time step: 1) evolve the field equation on the grid, 2) deposit the charge and/or current densities through interpolation from the particles distributions onto the grid, 3) evolve the fields on the grid, 4) interpolate the fields from the grid onto the particles for the next particle push.
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