{"id":145472,"date":"2026-07-01T08:58:46","date_gmt":"2026-07-01T00:58:46","guid":{"rendered":"https:\/\/www.curtin.edu.au\/research\/?post_type=hdr-r-projects&p=145472"},"modified":"2026-07-01T08:58:46","modified_gmt":"2026-07-01T00:58:46","slug":"quantum-simulation-using-fault-tolerant-quantum-algorithms","status":"publish","type":"hdr-r-projects","link":"https:\/\/www.curtin.edu.au\/research\/hdr-r-projects\/quantum-simulation-using-fault-tolerant-quantum-algorithms\/","title":{"rendered":"Quantum simulation using fault-tolerant quantum algorithms"},"content":{"rendered":"\n
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Quantum computing since its conception in the mid-1980s by Physics Nobel Laureate Richard P. Feynman has gained significant attention in areas such as simulating physical systems, optimisation, and machine learning. Quantum processing units operate according to the laws of quantum mechanics. In particular, two intrinsic properties of the quantum realm, namely quantum superposition and entanglement, play a central role in offering computational advantage.
Simulating phenomena governed by the laws of quantum physics is one of the most important long-term applications of quantum computers. Quantum computing devices were originally envisaged for this purpose, and over the past few years early demonstrations of quantum simulation have been performed in chemistry, material science, many-body physics, and condensed matter systems.
While early and near-term devices are limited by noise and hardware constraints, fault-tolerant quantum computing (FTQC) provides a pathway toward accurate and scalable quantum simulations. In this regime, algorithms such as Quantum Phase Estimation (QPE), block-encoding methods, linear combination of unitaries (LCU), and qubitization enable systematically improvable and high-precision simulation of physical systems, including electronic structure problems and real-time quantum dynamics. These approaches remove the reliance on heuristic approximations and instead exploit error-corrected logical qubits for controlled, high-depth computations.
This project investigates fault-tolerant quantum algorithms to simulate physical systems on future quantum processors. A key focus is on mapping physical Hamiltonians into efficient quantum representations and designing simulation workflows that minimise resource overheads such as logical qubit counts, T-gate complexity, and circuit depth.
Some physical phenomena are naturally encoded more efficiently on certain quantum architectures. Therefore, classifying problem structure and matching it with optimal FTQC algorithmic primitives is an important aspect of this research, particularly for large-scale quantum chemistry and many-body physics problems.<\/p>\n\n\n\n

Aim  <\/p>\n\n\n\n

This research work will develop fault-tolerant quantum algorithms for encoding, evolving, and extracting physical observables from quantum systems such as molecular electronic structure and strongly correlated materials. Each of these steps will require algorithmic optimisation to ensure scalability in the fault-tolerant regime. The proposed methods will focus on reducing asymptotic resource costs while maintaining numerical accuracy for physically relevant observables such as ground-state energies and dynamical correlation functions.<\/p>\n\n\n\n

Objectives <\/p>\n\n\n\n

It is expected the outcomes will address key challenges in fault-tolerant quantum simulation, including:<\/p>\n\n\n\n

    \n
  1. efficient Hamiltonian representation using block-encoding and sparse or structured decompositions,<\/li>\n\n\n\n
  2. development and optimisation of Quantum Phase Estimation and related eigenvalue estimation techniques for many-body systems, and<\/li>\n\n\n\n
  3. reduction of fault-tolerant resource overheads, including T-gate counts, magic state costs, and logical circuit depth through improved algorithmic constructions such as qubitization and optimized signal processing techniques.
    The project results will include publications in peer-reviewed journals in quantum information science and quantum physics, including leading venues in the field.<\/li>\n<\/ol>\n\n\n\n

    Significance <\/p>\n\n\n\n

    Quantum information science has undergone at least three decades of intensive scientific research. Quantum technologies are now one of the most strategically important technological areas, with quantum computing representing a major subdiscipline across the global research and development ecosystem.
    The simulation of physical systems composed of many interacting particles (electrons, atoms, spins) is known to be computationally intractable for classical computers in general settings. Fault-tolerant quantum computers are expected to overcome these limitations by enabling scalable and accurate simulation of quantum dynamics and electronic structure without uncontrolled approximations.
    While practical fault-tolerant quantum computers are not yet available, the development of algorithms that explicitly target this regime is essential for guiding hardware design and resource estimation. This project is therefore timely in establishing foundational methods for future large-scale quantum simulation.
    Fault-tolerant quantum algorithms such as Quantum Phase Estimation and qubitization-based simulation frameworks will enable high-precision electronic structure calculations, potentially accelerating discovery in chemistry and materials science. On a broader scale, these capabilities will support applications in energy systems, catalysis, and quantum-enabled materials design.<\/p>\n\n\n\n

    Ideal Candidate <\/p>\n\n\n\n

    We are looking for a self-motivated PhD candidate with excellent organisation, problem-solving and project management skills. It is expected that the candidate participates in seminars, group meetings, and other activities of scientific exchange. Candidates with strong quantitative skills, including familiarity with the following items are desired for this project:
    1) background in theoretical physics, in particular, quantum information theory
    2) keen interest in study of few- and many-body physical systems
    3) programming skills with Python and managing projects in cloud-based systems such as Github<\/p>\n\n\n\n

    Additionally, the applicants should meet the eligibility criteria for entry into a PhD program at Curtin University. <\/p>\n\n\n\n

    This project is open to International and Domestic applicants. <\/p>\n\n\n\n

    Scholarship  <\/p>\n\n\n\n

    If you are identified as the preferred candidate for this project, you may be considered for an RTP scholarship<\/a>. <\/p>\n\n\n\n

    Enquires and How to Apply <\/p>\n\n\n\n

    For enquires about this opportunity contact Dr Shak Daryanoosh at\u00a0Shakib.Daryanoosh@curtin.edu.au<\/a><\/p>\n\n\n\n

    To formally apply submit an\u00a0Expression of Interest<\/a>\u00a0to Dr Shak Daryanoosh during the Central Scholarship round (July 1st – July 31st 2026)\u00a0<\/p>\n","protected":false},"author":125,"featured_media":0,"template":"","faculties":[51],"hdr_types":[5487],"research_areas":[5298],"class_list":["post-145472","hdr-r-projects","type-hdr-r-projects","status-publish","hentry","faculties-science-and-engineering","hdr_types-rtp-scholarship","research_areas-data-science-machine-learning-and-ai"],"acf":false,"featured_image":false,"_links":{"self":[{"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/hdr-r-projects\/145472","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/hdr-r-projects"}],"about":[{"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/types\/hdr-r-projects"}],"author":[{"embeddable":true,"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/users\/125"}],"version-history":[{"count":0,"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/hdr-r-projects\/145472\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/media?parent=145472"}],"wp:term":[{"taxonomy":"faculties","embeddable":true,"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/faculties?post=145472"},{"taxonomy":"hdr_types","embeddable":true,"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/hdr_types?post=145472"},{"taxonomy":"research_areas","embeddable":true,"href":"https:\/\/www.curtin.edu.au\/research\/wp-json\/wp\/v2\/research_areas?post=145472"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}