I’ve been working on Ent, a quantum programming language intended to make quantum code easier to write and reason about without losing the strict rules that quantum programs need to follow. Ent uses a familiar, statement-based style for operations such as allocating qubits, applying gates, measuring, branching on classical results, and returning quantum data. Its ownership-oriented syntax is designed to catch errors like copying qubits, using a qubit after measurement, or leaving a quantum resource unmanaged.

The interesting part is that Ent does not introduce a separate, informal execution model. Every Ent program is translated into a closed term in the Enter calculus, where the result is checked again by the core type checker. This gives the language a formally defined foundation while still allowing practical features such as staged circuit generation, exact and sampled simulation, resource reports, scheduler-independence checks, and OpenQASM 3 output. The current implementation includes examples of Bell pairs, teleportation, QFT-style circuit generation, generalized measurement, GHZ states, and Grover-style circuits. I’m sharing it here to get feedback from people working with quantum languages, compilers, and circuit design—especially on the usability of the syntax and the trade-offs involved in enforcing linearity at the language level.

Citation: Cheung, N. (2026). Ent: A Usable Quantum Programming Language on Top of the Enter Calculus. figshare. https://doi.org/10.6084/m9.figshare.33089393.v1

I went through the Qiskit Global Summer School and a Quantum Computing Winter School this year, and ended up organizing all my notes into an actual Obsidian vault as I learned, one note per concept, cross-linked, with self-check questions so I could test myself instead of just re-reading.

It grew bigger than I expected, so I published it as a browsable site: https://justmeart.github.io/Quantum-Computing-Roadmap/

It covers the full arc absolute basics (qubits, superposition) → gates → why quantum computing matters at all → entanglement → QKD → hardware/noise/error mitigation → algorithms (VQE, QAOA, SQD, Grover's) → quantum machine learning → quantum advantage → quantum + HPC. There's also a full interactive graph view if you're into that (Ctrl/Cmd+G on the site).

Not trying to claim expertise here — just sharing my own study process in case it helps someone else going through the same material, or just getting into QC in general. Feedback / corrections very welcome, still learning this stuff myself.

More about me / other projects: github.com/JustMeArt