Quantum Complexity Science Initiative

Department of Physics – University of Malta

ADIABATIC COMPUTING

Universal adiabatic quantum computing and quantum algorithms simulating chemical physics

QUANTUM COMPLEX SYSTEMS

A ‘Quantum Theory’ of Networked and Complex Systems

TENSOR NETWORK STATES

Graphical calculus representing quantum states, algorithms and invariants

TIME-REVERSAL SYMMETRY

Time-reversal symmetry breaking in modern quantum information science by ‘chiral quantum walks

A theory uniting disciplines

We are a vibrant and focused research group happily based in the Department of Physics at the University of Malta. We study the fundamental implications physics has on information and computation, typically viewed through the lens of quantum theory. Quantum theory has provided uninterrupted insights both in the fundamental laws governing our world and in the novel mathematics developed in its description.
Quantum theory first provided a predictive mechanism explaining how atoms are formed. Applications widened yet the theory seemed riddled with an 'inherent complexity' and laced with the prediction of several peculiar non-intuitive features, first thought to be mathematical (not physically meaningful) artifacts.
These 'oddities' turned out to be experimentally relevant, physically testable predictions. And a new quantum theory of information and computation put these 'paradoxes' to work as fundamental new features to be harnessed in the way matter and information behave and interact.
Understanding the inherent complexity of the quantum world, the ramifications the laws physics place on information and computation and adapting the mathematical machinery developed in quantum theory such that it can tackle similar problems in related fields broadly defines our research commitment.

Jacob Biamonte

Lead of the Quantum Complexity Science Initiative
Jacob-Biamonte
  • Short Biography

    My interdisciplinary research group is known as the, Quantum Complexity Science Initiative, which is comprised of students and research staff with backgrounds in physics, mathematics and computer science. Our work aims to understand what fundamentally separates quantum and stochastic systems and applies this knowledge to develop applications of quantum effects to technology, such as e.g. quantum enhanced computer algorithms to accelerate machine learning. In this regard, our research is increasingly focused on the emerging field that unites quantum information with complex network theory and machine learning.

    My early work established the computational universality of specific quantum many-body ground states used in adiabatic quantum computing, and developed aspects of the theory of tensor network states. I have recently received several international awards for my work, including the Shapiro Fellowship in Mathematical Physics and I am an invited 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

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JACOB BIAMONTE

Principal Investigator
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JACOB TURNER

Research Scientist

Postdoctoral and Research Scientist Alumni

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MAURO FACCIN

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VILLE BERGHOLM

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TOMI JOHNSON

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JAMES WHITFIELD

Now Assistant Professor, Dartmouth
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ZOLTÁN ZIMBORÁS

Assistant Professor, Wigner Research Centre for Physics, Hungarian Academy of Sciences

PhD and Long-Term Visiting Student Alumni

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DAVID YUDONG CAO

Graduated 2016
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JACOB TURNER

Graduated 2015
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PIOTR MIGDAŁ

Graduated 2014
Institut de Ciències Fotòniques, Barcelona

Administrative Staff

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EDWARD DUCA

media officer
Dr Edward Duca B.Sc.(Hons.)(Melit.),M.Sc.(Leics.),Ph.D.(Edin.) Communications & Alumni Relations Office Room 127 Administration Building University of Malta Msida contact+356 2340 3451
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LUSA ZEGLOVA

webpage design and scientific illustration
scientific illustrator

External and Collaborative Research Council

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JOHN C. BAEZ

mathematical network theory
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MIKE MOSCA

quantum computing
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SETH LLOYD

quantum information

Research Highlights

uniting the fields of quantum information and complexity science

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