activity
20192026
most citedScaling advantage in quantum simulation of geometrically frustrated magnets

153 citations · 232 across the 5 of their papers we have counts for

collaborators

5 papers

math.OC2026

Wall-Clock Complexity for Zeroth-Order Optimization with Tunable Oracle Fidelity

Alexandra Suvorikova, Igor Pavlov, Artem Vasin +4

Zeroth-order (black-box) optimization is applied when gradients are unavailable and objective evaluations rely on expensive simulations. In many such applications, the oracle fidel…

math.OC2023

Information-Theoretic Upper Bounds for Deterministic Noise in Zeroth-Order Convex Optimization

Dmitry Pasechnyuk-Vilensky, Igor Pavlov, Martin Takáč +1

We study zeroth-order convex optimization on Euclidean balls with function values corrupted by a fixed, uniformly bounded deterministic perturbation. For a query budget , the ma…

quant-ph2023★ 13 cited

Transmission of vortex electrons through a solenoid

G. K. Sizykh, A. D. Chaikovskaia, D. V. Grosman +2

We argue that it is generally nonstationary Laguerre-Gaussian states (NSLG) rather than the Landau ones that appropriately describe electrons with orbital angular momentum both in…

quant-ph2019★ 153 cited

Scaling advantage in quantum simulation of geometrically frustrated magnets

Andrew D. King, Jack Raymond, Trevor Lanting +51

The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter s…

quant-ph2019★ 66 cited

Demonstration of nonstoquastic Hamiltonian in coupled superconducting flux qubits

I. Ozfidan, C. Deng, A. Y. Smirnov +45

Quantum annealing (QA) is a heuristic algorithm for finding low-energy configurations of a system, with applications in optimization, machine learning, and quantum simulation. Up t…