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Dominic Berry

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Dominic Berry - Professor

Macquarie University

My research is in the areas of quantum information and quantum optics. In quantum information, I developed many of the most efficient known algorithms for simulation of physical systems, which has been used as the basis for important new quantum algorithms. In the area of quantum optics, I invented the most accurate known methods to measure optical phase by using adaptive techniques, and am collaborating with experimental groups for demonstration of these methods.

My CV is available here.

PhD and Masters projects

Are you interested in doing a PhD or Masters project in quantum algorithms? PhD scholarships are available through the Sydney Quantum Academy. Applications are currently closed, but will open on 28 August. You can sign up for email updates here, or contact me at .


  • 13/07/2024: Our quantum algorithm doubling the speed of Hamiltonian simulation via quantum signal processing is now published in Physical Review A.
  • 14/06/2024: Our quantum algorithm for solving time-dependent differential equations has just been published.
  • 11/06/2024: My citation count has just passed 10,000 on Google Scholar.
  • 1/06/2024: Our new paper on quantum computing for inertial fusion target design is now published in PNAS.
  • 23/01/2024: We've shown a new quantum algorithm for Hamiltonian simulation giving a new record for speed with a factor of 2 improvement over previous methods, which were thought to be optimal for the past 8 years.
  • 19/12/2023: Our work on quantum algorithms for solving nonlinear partial differential equations is out now. We provide multiple improvements, which result in an algorithm with sublinear scaling in the number of discretisation points (so faster than classical).
  • 2/05/2023: In quantum computing, if you use a single qubit for measuring phase then the error tends to be large; we've now shown how to make the measurement optimal using just one more qubit. It is now published in AVS Quantum Science.
  • 13/01/2023: Our paper on optimal collective measurements is out today in Nature Physics.
  • 4/01/2023: We have a new arXiv paper out today. We compare our quantum algorithms to classical mean-field methods, and show that there is a significant speedup.
  • 7/10/2022: Our paper giving the optimal quantum algorithm for solving linear systems is now published. It gives a discrete adiabatic theorem that can be applied to all sorts of adiabatic algorithms.
  • 30/06/2022: Our paper on quantum algorithms for quantum field theory quantum field theory is now published. It gives an improved method for preparing states by using inequality testing, and can simulate systems that vary over space via wavelets.
  • 2/06/2022: Our work showing how to perform collective measurements is out now. This is measurements acting jointly on multiple copies of a quantum state, which provides better accuracy than measuring them individually.
  • 17/11/2021: We've now achieved the optimal quantum algorithm for solving linear equations. Our method is based on a quantum walk, and is relatively simple to perform, but the difficult part is showing that it works. To do that we proved a form of the adiabatic theorem for quantum walks and bounded the error.
  • 12/11/2021: Our work on simulation of quantum chemistry using plane waves is now published in PRX Quantum. It is a complete cost analysis of quantum algorithms adapted to first quantisation, showing that the approach is unrivaled for high accuracy simulations of solid-state materials and certain chemical compounds.
  • 13/10/2021: We've released new work on how to more efficiently simulate quantum field theory. This one is using a much faster method for preparing the Gaussians, as well as using wavelets for systems that vary over space.
  • 9/07/2021: Our work on how to perform highly efficient simulation of quantum chemistry using tensor hypercontraction is now published in PRX Quantum.
  • 28/05/2021: We have released a new analysis of quantum simulation of quantum chemistry using plane waves, qubitisation and the interaction picture. We give explicit Toffoli counts for these methods, which have the best asymptotic scaling, showing how they perform in practice with realistic numbers. We introduced a whole host of improvements, which together reduce the complexity by around a factor of 1000 over naive implementations.
  • 28/04/2021: The paper on how to perform Boson-sampling inspired QKD is now published in the journal Quantum.
  • 5/01/2021: I am now on Twitter, and will be making these announcements there as well.
  • 10/11/2020: Our work on quantum algorithms for optimisation is now published in PRX Quantum.
  • 9/11/2020: In the most exciting news regarding counts this week, we have the best Toffoli count yet for quantum chemistry, even better than the recent work of von Burg et al. We achieve the highest efficiency yet using the THC decomposition with Majorana operators.
  • 27/10/2020: We have shown that the usual limit to laser coherence is not a true limit, and it is possible to achieve coherence that is quadratically better. This work is now published in Nature Physics.
  • 16/07/2020: We have shown how to very effectively use Trotterisation for simulation of quantum systems. Unlike optimisation, this problem has an exponential speedup over classical computing, so is a realistic application for quantum computing. This work is now published in Quantum.
  • 16/07/2020: We have released new results on the arXiv showing how to efficiently perform quantum optimisation algorithms. Even using the best techniques, our results indicate that quantum computers will not be able to beat classical computing on problems with only a square root speedup.
  • 20/04/2020: Our results showing how to speed up simulation of time-dependent systems using a randomised algorithm are now published in Quantum.
  • 24/01/2020: Our result showing that there π factor in the Heisenberg limit is now published in Physical Review Letters. This shows that the usual form of the limit to phase estimation is not achievable in a single-shot scenario.
  • 3/12/2019: Our method of simulating quantum chemistry for sparse systems, with a 700 times speedup for FeMoco, is now published in Quantum.
  • 1/11/2019: Our work showing how to use the interaction picture for quantum chemistry simulations with N3.5 complexity is now published in npj Quantum Information.
  • 15/07/2019: In work with Rafal Demkowicz-Dobrzanski and others we have shown that the ultimate limit to phase measurement includes a π factor, regardless of any prior knowledge. This work is available on the arXiv.
  • 18/06/2019: We have shown how to perform simulations of time-dependent Hamiltonians with complexity scaling as the integral of the norm of the Hamiltonian, rather than the maximum value. This is useful for Hamiltonians arising from collisions where the size of the Hamiltonian can vary dramatically over time. This work is available on the arXiv.
  • 9/05/2019: We have proposed a new technique for quantum encryption using Boson sampling. This work is available on the arXiv.
  • 5/04/2019: Our paper showing how to simulate time-dependent quantum systems with exponential precision is now published in Physical Review A.
  • 4/04/2019: Our new algorithm for solving SYK models with many orders of magnitude improvement is now published in Physical Review A as a Rapid Communication.
  • 12/03/2019: Our work showing how to more accurately perform sensing with with NV centres at room temperature is now published in Physical Review B.
  • 27/02/2019: We have analysed the Trotter approach to quantum simulation, providing several improvements and showing that simulations may be performed with a surprisingly small number of quantum gates.
  • 6/02/2019: We have shown how to take advantage of the low rank nature of Hamiltonians to provide a significant speed improvement for simulating FeMoco.
  • 17/01/2019: Our work on removing arithmetic from state preparation is now published in Physical Review Letters. It is an Editors' Suggestion!

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