Alex Kamenev
University of Minnesota, MN·Physics
Quantum computers are still noisy and error-prone, but they can already perform nontrivial tasks. This raises a practical question: which useful problems can today's machines solve?
- Fields
Physics
Computer Science
- Topics
quantum computing
quantum computation
quantum optimization
- Grants
- 1 known grant, through Jan 2027
What they work on
- Extend non-equilibrium quantum field theory to include Lindbladian dynamics, which describe driven qubit arrays that lose energy to their surroundings.
- Determine whether a many-body localization transition, where a quantum system becomes stuck instead of spreading out, exists in the qubit array's state space, and characterize its properties.
- Develop theory for cooling cycles that melt glassy states through a first-order transition and refreeze them through a second-order transition, as a route to approximate quantum optimization.
- Implement these cooling protocols on the D-Wave 5000-qubit platform and develop tools to compare the experimental data with theoretical predictions.
More about the research
One candidate is optimization, which means finding the best sequence of bits under a complicated set of criteria called a cost function. To a physicist, this is the same as finding the low-energy states of a disordered material, or glass. In other words, the task is to cool the glass.
Why it matters
Many practical problems, from scheduling to design, amount to finding the best option under a complex set of criteria. Cooling protocols that work on real, noisy quantum hardware could show how present-day quantum computers can tackle these optimization problems. The theory could guide better use of commercial devices.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Christopher Baldwin
Michigan State University, MI·Physics
Test whether catalysts proposed to improve adiabatic quantum computation retain their advantage on spin-glass models, the statistical-physics analogues of hard optimization problems, and identify the mechanisms behind each success or failure.
Yizhi You
Northeastern University, MA·Physics·Early-career
Construct microscopic models and hybrid fracton field theories to describe the collective behavior of fractons, particle-like excitations with restricted mobility, and the phases and phase transitions they form.
Daniel Boyanovsky
University of Pittsburgh, PA·Physics
Calculate how axion dark matter candidates were produced, decayed, and thermalized in the early universe, using non-equilibrium effective field theory, a simplified particle-physics description for changing conditions, to predict dark matter abundance.
The school
University of Minnesota: 88 labs on PI Pages, $1.4B a year on research, 722 research doctorates a year.
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