Our endeavor on variational benchmarks for quantum many-body problems is now published in
@ScienceMagazine!
In this large collaborative work (~30 institutions) led by
@cqs_lab @EPFL_en, we established a practical, agreed-upon metric to quantify the hardness of quantum problems involving many particles (e.g. in materials).
The resulting metric, called v-score, is handy to compute and intrinsically suited for variational methods on both classical and quantum devices (e.g. Matrix Product States, Neural Quantum States, Variational Auxiliary Field Monte Carlo, Variational Quantum Eigensolver, DMFT solvers, and many others).
One surprising outcome is that this metric almost universally correlates with the error on ground state energies, for problems seemingly unrelated and for the tens of different techniques we have benchmarked.
This allows us to identify those problems and regions of interactions and parameters that are factually hard for existing many-body methods (e.g. spin liquids in some 3D geometries, Hubbard models for specific values of the coupling U etc.).
The v-score can assess progress of novel computational methods, both classical and quantum-based.
It will help shape criteria for measuring quantum computing performance, transitioning from generic, average-hardness qualifiers of computational complexity theory to physics-chemistry based hardness quantifiers for problems central to computational quantum science. In this domain, well-established heuristics exist, making any quantum-driven improvement both significant and highly valued.
Read the article here:
science.org/doi/10.1126/scie…