Aglais Xqvm Quantum Vm

If you're encoding binary optimization problems for quantum annealers, this gives you a proper IR layer instead of wrestling with vendor-specific formats. It's a stack-based VM written in Rust with four crates: bytecode, assembler, disassembler, and interpreter. You write QUBO or Ising models in XQASM assembly (or build them programmatically), compile to bytecode, and run anywhere the VM supports, including no_std environments like WASM. The TSP example in the repo shows the real pattern: generate coefficients in Rust, emit parameterized assembly, then assemble and execute. Think of it as LLVM for quantum annealing problems, though you're still responsible for the actual annealing solver on the backend.

skills.sh installs: 266
GitHub stars: 26
last updated: Jun 3, 2026

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Install

$ npx -y skills add aradotso/trending-skills --skill aglais-xqvm-quantum-vm --agent claude-code

Installs into .claude/skills of the current project.

Files

Aglais XQVM Skill

Skill by ara.so — Daily 2026 Skills collection.

Aglais XQVM is a hardware-agnostic virtual machine for quantum computing written in Rust. It provides a unified bytecode intermediate representation for binary optimization problems (QUBO/Ising formulations) targeting quantum annealers — think LLVM for quantum computing. The VM is stack-based with a 256-slot register file, supports no_std + alloc for WASM/bare-metal deployment, and ships four crates: bytecode, assembler, disassembler, and interpreter.

Installation & Setup

Prerequisites

# Install Rust stable
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Install dev tools (cargo-nextest, clippy, etc.)
make deps

Build from source

git clone https://github.com/QuipNetwork/xq-rs
cd xq-rs
cargo build --release
# Binaries: target/release/xqasm, target/release/xqdism, target/release/xqvm

Add as a library dependency

# Cargo.toml
[dependencies]
aglais-xqvm-bytecode = { path = "crates/bytecode" }
aglais-xqvm-vm       = { path = "crates/vm" }

For no_std environments (WASM, bare-metal):

SKILL.md on GitHub

Details

Repository: github.com/aradotso/trending-skills
First seen: Jun 3, 2026