202 citations · 2.5k across the 68 of their papers we have counts for
10 papers · 2 filters
An in-principle super-polynomial quantum advantage for approximating combinatorial optimization problems via computational learning theory
Niklas Pirnay, Vincent Ulitzsch, Frederik Wilde +2
Combinatorial optimization - a field of research addressing problems that feature strongly in a wealth of scientific and industrial contexts - has been identified as one of the cor…
Exponentially tighter bounds on limitations of quantum error mitigation
Yihui Quek, Daniel Stilck França, Sumeet Khatri +2
Quantum error mitigation has been proposed as a means to combat unwanted and unavoidable errors in near-term quantum computing without the heavy resource overheads required by faul…
Stochastic noise can be helpful for variational quantum algorithms
Junyu Liu, Frederik Wilde, Antonio Anna Mele +3
Saddle points constitute a crucial challenge for first-order gradient descent algorithms. In notions of classical machine learning, they are avoided for example by means of stochas…
Perturbative gadgets for gate-based quantum computing: Non-recursive constructions without subspace restrictions
Simon Cichy, Paul K. Faehrmann, Sumeet Khatri +1
Perturbative gadgets are a tool to encode part of a Hamiltonian, usually the low-energy subspace, into a different Hamiltonian with favorable properties, for instance, reduced loca…
Probing coherent quantum thermodynamics using a trapped ion
O. Onishchenko, G. Guarnieri, P. Rosillo-Rodes +6
Quantum thermodynamics is aimed at grasping thermodynamic laws as they apply to thermal machines operating in the deep quantum regime, a regime in which coherences and entanglement…
Classical surrogates for quantum learning models
Franz J. Schreiber, Jens Eisert, Johannes Jakob Meyer
The advent of noisy intermediate-scale quantum computers has put the search for possible applications to the forefront of quantum information science. One area where hopes for an a…