Principle supervision and address all contact to: Dr. Mohammad Rowshan
Co-supervision: Prof. Simon Devitt
A physical qubit whose noise is engineered to be biased toward a dominant, more easily correctable error channel, rather than left as generic depolarizing noise, can sharply reduce the physical qubit overhead needed for fault tolerance. Recent experimental results across several platforms, including metastable neutral-atom qubits and superconducting dual-rail qubits, have shown that strong erasure bias is achievable in practice, where the location of an error is known even before decoding begins. Similar bias-toward-erasure or bias-toward-a-preferred-Pauli behaviour is emerging or anticipated on other platforms as well. What hasn’t kept pace is the code and decoder side: most quantum LDPC codes and their decoders are still designed and benchmarked against generic noise models, so the gains available from a genuinely bias-matched code-decoder pair remain largely untapped.
This project will develop QEC codes and matched decoders co-designed around erasure and bias structure, built to generalise across hardware noise profiles rather than being tied to one platform. A code that only survives well as a memory is of limited use, so candidate constructions will also be assessed for their compatibility with native Clifford transversal gates, and where feasible, non-Clifford logic, so that noise-tailoring doesn’t come at the cost of losing cheap logical operations. Alongside new constructions, the project will also study deformation and diagnosis of known code families, characterising how existing codes respond to erasure- and bias-structured noise and identifying what deformations improve their performance under realistic, non-generic noise conditions, rather than treating new-family construction as the only route forward. The student will characterise the threshold and overhead gains achievable over platform-agnostic codes as a function of bias strength and erasure fraction, and connect the results to QSI’s fault-tolerant compilation pipeline so that platform-specific noise parameters can be fed directly into compiler-level resource estimates.
Expected outputs: new code constructions and/or deformations of known families tailored to erasure- and bias-structured noise, an assessment of native gate compatibility (transversal Clifford, and non-Clifford where achievable) for the resulting codes, matched decoders, a general framework relating bias/erasure parameters to code and decoder performance, and simulation benchmarks (Stim/PyMatching-class tooling).
Target venues:
- Journals: Physical Review A, Physical Review Letters, Quantum, PRX Quantum, IEEE TIT
- Conferences: IEEE QCE, IEEE ISIT
2. What I’m looking for in an HDR student
- A strong quantitative background in one of: applied mathematics, computer science, electrical engineering, or theoretical physics, with prior exposure to coding theory (classical or quantum) or quantum information
- Comfort with abstract algebra, linear algebra, probability theory, and/or graph theory, or a demonstrated ability to pick these up quickly
- Solid numerical simulation skills in Python; prior exposure to tools like Stim or PyMatching is a bonus, not a requirement
- A motivated and self-directed working style.
- Clear written and spoken communication, since the field publishes fast and the student needs to keep pace
This is a theory- and simulation-driven project.
3. New or current HDR student
This is for a new HDR student, not yet enrolled at UTS, to be recruited and funded by the project. However, if there are candidates currently enrolled who have relevant background and interest, I am open to that as well.
4. Stipend and fees
Domestic students will be encouraged to apply for the Australian RTP award. Stipends is approximately $40,000AUD per year (tax free). International students can apply and may be subject to international tuition fees by UTS.
Quantum Technology at Scale 