realsqrt — Compute real square roots element-wise and reject values that require complex results.

Y = realsqrt(X) computes sqrt(X) for real nonnegative inputs. Unlike sqrt, it rejects negative real values and complex inputs instead of producing complex results.

Syntax

Y = realsqrt(X)

Inputs

Returns

Errors

How realsqrt works

• realsqrt(X) applies the operation element-wise and preserves the input shape.
• Logical values convert to doubles (true -> 1.0, false -> 0.0) before the square root is taken.
• Character arrays are interpreted as their numeric code points and return dense double tensors.
• Sparse inputs preserve sparsity: stored values are square-rooted and unstored zeros remain zero.
• Negative real values raise a domain error because the result would be complex.
• Complex scalar and complex tensor inputs are rejected, even if their imaginary parts are zero.
• NaNs and positive infinities propagate according to IEEE real square-root arithmetic.

Does RunMat run realsqrt on the GPU?

realsqrt is GPU-aware but not fused. Provider execution is used only after a nonnegative-domain check. This preserves MATLAB-compatible error behavior for negative inputs while still allowing nonnegative gpuArray inputs to remain device-resident.

GPU memory and residency

RunMat keeps real gpuArray inputs on the active provider when it can prove the values are nonnegative and the provider exposes the required reduce_min and unary square-root hooks. Complex gpuArray inputs are rejected before provider execution. If the nonnegative proof is unavailable, if NaNs prevent a reduction proof, or if the provider lacks the hook, RunMat gathers to host and applies the same real-domain validation as CPU inputs.

Examples

Taking the real square root of a scalar

y = realsqrt(9)

Expected output:

y = 3

Square roots of a matrix

A = [1 4 9; 16 25 36];
R = realsqrt(A)

Expected output:

R = [1 2 3; 4 5 6]

Rejecting negative values

realsqrt([-1 4])

Expected output:

Error using realsqrt
Input must be nonnegative.

Preserving sparse storage

S = sparse([1 3], [1 2], [4 9], 3, 2);
R = realsqrt(S)

Expected output:

R = sparse([1 3], [1 2], [2 3], 3, 2)

Running on GPU data

G = gpuArray([0 1; 4 9]);
out = realsqrt(G);
result = gather(out)

Expected output:

result = [0 1; 2 3]

Using realsqrt with coding agents

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

FAQ

Related Math functions

Open-source implementation

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

• View the source for realsqrt 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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