November 2025: Check out our latest work now on the arXiv by group members Spyros and Muhammad. We focus on circuits relevant to variational quantum algorithms and demonstrate that their depth can be reduced by introducing additional qubits, mid-circuit measurements, and classically controlled operations. Using fluid dynamics as an illustrative example, we show that our proposed circuits are efficient and advantageous in noisy regimes!

November 2025: We recently submitted a paper onto arXiv where we demonstrate a new approach to qubit-efficient optimization by framing it as a geometrical problem, aligning the quantum representation with the inherent structure of the problem itself. This work establishes a direct link between a mathematical concept called the Sherali-Adams polytope and the consistency required for accurate quantum computation, resulting in a streamlined process that requires significantly fewer qubits. This method achieves impressive results on challenging optimization tasks, surpassing existing approaches and paving the way for more powerful and efficient quantum algorithms by leveraging the underlying geometry of the problem – congrats to Gordon!

July 2025: Check out our latest work now on the arXiv by group members Eleftherios, Muhammad, and collaborators (arXiv link will be available from 29/7/25). This paper presents a resource-efficient, low-depth Hadamard test circuit and tailored variational ansatz for NISQ devices, significantly reducing gate counts. The approach accurately simulates nonlinear Burgers’ dynamics and remains resilient to hardware noise, showing strong agreement with classical benchmarks. Please reach out if you have any questions or are interested to find out more!

May 2025: Our work by Muhammad and collaborators on a qubit- and shot-efficient method for optimizing cost functions in variational quantum algorithms has recently been published. This innovative study introduces the Sequential Grid-Based Explicit Optimization (SGEO) protocol, redefining optimization in variational quantum algorithms. By expressing parameterized quantum circuits as weighted sums of unitary operators, SGEO enables efficient computation of cost functions and their derivatives, enhancing both speed and accuracy. Read the full paper here!

March 2025: Our team recently presented at APS March Meeting 2025, with an invited talk on utility-scale quantum optimization and posters on quantum CFD and drone path planning – special thanks to Gordon Ma and Muhammad Umer for representing our work, and to all collaborators including SGX, ExxonMobil, and Thales!

Jan 2025: Our recently published work by Muhammad and collaborators investigates a recently proposed variational quantum algorithm’s ability to find ground states of the nonlinear Schrödinger equation using real superconducting quantum hardware. Despite noise affecting energy evaluations, the algorithm reliably converges for small instances, offering practical insights for solving nonlinear problems with quantum devices. Great work team!