News of the group on Computational and Statistical Physics

Here you can follow up on (parts of) what is happening in terms of the group's and their member's development.


< HPC day
30/07/2019 - Age: 5 yrs

Quantum sampling

Technique for benchmarking quantum computers

In a recent new paper in collaboration with Jeffrey Marshall and Itay Hen from the University of Southern California (USC) and Lev Barash from Landau Institute for Theoretical Physics in Chernogolovka, we have adapted population annealing to the problem of sampling the density of states of frustrated spin systems. A prominent example are the Ising spin-glass configurations that represent the states of the D-Wave series of quantum computers. Our new approach allows to assess to which extent these machines sample states thermodynamically acurately.

Estimating the density of states (DOS) of systems with rugged free energy landscapes is a notoriously difficult task of the utmost importance in many areas of physics ranging from spin glasses to biopolymers. DOS estimation has also recently become an indispensable tool for the benchmarking of quantum annealers when these function as samplers. Some of the standard approaches suffer from a spurious convergence of the estimates to metastable minima, and these cases are particularly hard to detect. Here, we introduce a sampling technique based on population annealing enhanced with a multi-histogram analysis and report on its performance for spin glasses. We demonstrate its ability to overcome the pitfalls of other entropic samplers, resulting in some cases in large scaling advantages that can lead to the uncovering of new physics. The new technique avoids some inherent difficulties in established approaches and can be applied to a wide range of systems without relevant tailoring requirements. Benchmarking of the studied techniques is facilitated by the introduction of several schemes that allow us to achieve exact counts of the degeneracies of the tested instances.