asinh — Element-wise inverse hyperbolic sine in MATLAB and RunMat.

Y = asinh(X) evaluates the inverse hyperbolic sine of each element in X. Real and complex inputs are handled element-wise, with branch behavior matching MATLAB semantics.

Syntax

Y = asinh(X)

Inputs

Returns

Errors

How asinh works

• Accepts scalars, vectors, matrices, and N-D tensors and applies the operation element-wise using MATLAB's broadcasting rules.
• Logical inputs are promoted to doubles (true → 1.0, false → 0.0) before the inverse hyperbolic sine is applied.
• Character arrays are interpreted as numeric code points and return dense double arrays with the same shape.
• Real inputs produce real outputs for all finite values. Complex inputs follow MATLAB's principal branch definition asinh(z) = log(z + sqrt(z^2 + 1)).
• NaNs and infinities propagate according to IEEE arithmetic and match MATLAB's special-case tables.

Does RunMat run asinh on the GPU?

RunMat Accelerate keeps tensors on the GPU when:

1. A provider is registered and implements the unary_asinh hook. 2. The inputs do not require complex promotion that the provider cannot represent.

If either condition is not met, RunMat gathers the data to the host, evaluates asinh with the CPU reference implementation, and returns the correct MATLAB result. This guarantees correctness without forcing users to manually call gpuArray or gather.

GPU memory and residency

You usually do not need to call gpuArray explicitly. The fusion planner keeps tensors on the GPU whenever the active provider exposes the necessary hooks (unary_asinh) and the runtime can keep the data in real form. When the GPU path is incomplete, RunMat gathers to the host automatically and still returns MATLAB-compatible results. Manual gpuArray / gather remains available for workflows that require explicit residency control.

Examples

Inverse hyperbolic sine of a scalar

y = asinh(0.5)

Expected output:

y = 0.4812

Applying asinh to every element of a vector

x = linspace(-2, 2, 5);
y = asinh(x)

Expected output:

y = [-1.4436 -0.8814 0 0.8814 1.4436]

Evaluating asinh on a matrix

A = [0 -0.5 1.0; 1.5 -2.0 3.0];
B = asinh(A)

Expected output:

B =
         0   -0.4812    0.8814
    1.1948   -1.4436    1.8184

Computing asinh on GPU data

G = gpuArray([0.25 0.5; 0.75 1.0]);
result_gpu = asinh(G);
result = gather(result_gpu)

Expected output:

result = [0.2475 0.4812; 0.6931 0.8814]

Handling complex arguments with asinh

z = [1 + 2i, -0.5 + 0.75i];
w = asinh(z)

Expected output:

w =
   1.4694 + 1.0634i
  -0.6063 + 0.6822i

Using asinh inside fused GPU expressions

G = gpuArray(rand(1024, 1));
Y = sinh(G) + asinh(G)

Using asinh with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how asinh changes the result.

FAQ

Related Math functions

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how asinh is executed, line by line, in Rust.

• View the source for asinh in Rust on GitHub
• Learn how the RunMat runtime works
• Found a bug? Open an issue with a minimal reproduction.

About RunMat

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