Quantum Complexity Science Initiative
Jacob Biamonte
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Short Biography
I hold a permanent senior faculty position in 'Theoretical Quantum Physics' at the University of Malta and an appointment at the Institute of Quantum Computing, at the University of Waterloo. I was appointed the 'Shapiro Fellow' in Mathematical Physics at Pennsylvania State University and gave the accompanied lecture series on uniting the fields of quantum information with complexity science. I worked as an early research scientist at D-Wave Systems Inc. 'the quantum computing company' in Vancouver B.C. and completed an award winning doctoral thesis from the University of Oxford. My postdoctoral research was done mainly at Harvard University and at the University of Oxford. I am an elected member of the Foundational Questions Institute (FQXi). In terms of community service, I'm on the editorial boards for several journals, including New Journal of Physics.
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Working Team
Research Highlights
uniting the fields of quantum information and complexity science
Explore our topics
Quantum Theory and Complex Networks
By correctly studying information as an entity fundamentally governed by the laws of physics, development of an emerging common language is already binding certain ideas and mapping some techniques between the fields of quantum physics and complexity science. What’s more, the ubiquitous use of various network and graph theories inside of both disciplines, creates a stage for an abstracted comparison of networked systems, recovering both fields as special cases of more general mathematical entities. Work along these lines is really only just getting started. And even with these similarities, and other bridges still being built, there seems to be an even vaster host of differences. Pinpointing these similarities and reconciling[…]
Adiabatic Quantum Computing
Our work has been to develop a universal adiabatic quantum computer. Adiabatic quantum computing generally relies on the idea of embedding a problem instance into a physical system, such that the systems lowest energy configuration stores the problem instance solution. While any quantum algorithm can be run on a universal adiabatic quantum computer in principle, combinatorial optimisation problems appear to be the most suitable choice for near-term devices. Recent experimental progress has resulted in annealers with hundreds of spins and studying the quantum properties of these devices has sparked dramatic interest and debate in this rapidly growing area. More generally, several notable results have emerged on the topic of ground[…]
Quantum Walks
Chiral quantum walks offer a means to control quantum evolutions on graphs by controlling time-reversal symmetry breaking and the interplay of this effect with the global topological structure of the underlying network. The theory is part of a larger idea to merge time-symmetry theory with quantum information science and to address the quantum challenges of control on complex networks. For a readable introduction to quantum walks see these Azimuth Blog posts as well as the review articles on walks listed at the end of this page. Introduction to quantum walks on complex networks, Quantum Network Theory Part 1 The relation between quantum walks on complex networks and node degree, Quantum[…]
Experimental Collaborations
Experimental quantum physics is where the rubber meets the road. There’s been incredible progress in demonstrating various quantum algorithms and other building blocks for a future device to surpass the best conceivable classical computer. The most interesting aspect of quantum information science is the fact that these ideas and concepts await a physical realization, which offer new practical relms in information processing. Mapping our ideas and merging them with the ideas and realizations of top experimental groups is something we place of great value on. This includes our long-term collaboration with D-wave Systems Inc., the NMR group of IQC Canada as well as the NV-center group of Stuttgart Germany not[…]
Ising Hamiltonian Formulation of Boolean Operations and Gates
D-Wave Systems Inc. builds annealing devices that exhibit quantum effects. These devices as well as other physical systems implement a programmable Ising model of the form. \begin{equation} H = \sum_i c_i Z_i+\sum_{ ij} c_{ij}Z_iZ_j \end{equation} Where zed is the familiar Pauli matrix. The approach I took program D-Wave’s computer was to encode universal computation into its ground state by relying on specific Hamiltonians that embed logical Boolean operations. This is what I’m going to briefly tell you about here. Different methods also exist to emulate many-body interactions with two-body Hamiltonians, see the section on many-body to two-body decomposition gadget Hamiltonians. We have sometimes called the Ising formulation of logical functions:[…]
Quantum Simulation
In his famous 1981 talk, Feynman proposed that unlike classical computers, which would presumably experience an exponential slowdown when simulating quantum phenomena, a universal quantum simulator would not. An ideal quantum simulator would be controllable, and built using existing technology. In some cases, moving away from gate-model-based implementations of quantum computing may offer a more feasible solution for particular experimental implementations. We’ve considered both gate-model as well as adiabatic quantum simulation, together with experimental realizations. In short. Quantum effects are a feature, not a bug and quantum effects are inherently good at simulating themselves. The area of quantum simulation considers dedicated quantum systems as well as quantum computer algorithms which[…]
Tensor Networks
Tensor networks gave rise to efficiently compact representations for certain classes of quantum states, and provide a graphical language to reason about quantum processes. The methods reach outside of physics to large areas of computer science and even more recently have found applications in complex networks. In quantum physics, these methods are widely considered to form the backbone of tensor network contraction algorithms to model physical systems and are used in the abstract tensor languages to represent e.g. channels, maps, states and processes appearing in quantum theory. In particular, tensor networks provide a graphical language — the expressiveness of this language has fostered its growing popularity. As a modeling language,[…]