Update archived news (#13)

* Update

* Update

* Update archived news (#12)

Author: huiyuxie

index.md

@@ -15,15 +15,15 @@ TrixiCUDA.jl offers CUDA acceleration for solving hyperbolic PDEs on GPUs. It is
 
 ### Recent Update
 
+*Update on Jun 6, 2025*:
+- The scalar indexing issue on GPU arrays has been fixed for most common examples, but for more complicated cases you can run them error‐free by doing `using CUDA; CUDA.allowscalar(true)`, and a permanent fix will be available soon.
+
 *Update on Mar 19, 2025*:
 - The issue between the latest version of CUDA.jl and Trixi.jl has been resolved. The package is now compatible with CUDA.jl v5.7.0 and Trixi.jl v0.10 (see [TrixiCUDA.jl PR #141](https://github.com/trixi-gpu/TrixiCUDA.jl/pull/141)).
 
 *Update on Jan 28, 2025*:
 - It is recommended to update your Julia version to 1.10.8 (the latest LTS release) to avoid the issue of circular dependencies during package precompilation, which is present in Julia 1.10.7 (see [issue](https://discourse.julialang.org/t/circular-dependency-warning/123388)).
 
-*Update on Dec 31, 2024*:
-- The initial round of kernel optimization starts with the volume integral kernels (see [TrixiCUDA.jl PR #102](https://github.com/trixi-gpu/TrixiCUDA.jl/pull/102)) and will later extend to all existing kernels used in the semidiscretization process.
-
 [*Archived Update*](/update)
 
 ## Acceleration Overview