5 citations · 7 across the 7 of their papers we have counts for
7 papers
Noise structuring in fixed-depth Trotter simulation: stationary channels and observable-level depolarization
G. L. Stavisskii, W. V. Pogosov, L. E. Fedichkin +1
We analyze fixed-depth Trotter simulation as a method for structuring hardware noise in digital many-body dynamics. The number of layers is chosen using the largest endpoint time a…
Spectral theory of energy-selective quantum search with Ising Hamiltonian phase oracles
A. S. Plyashechnik, A. A. Zhukov, A. V. Lebedev +1
We develop an exact spectral-response theory for the Grover-type iterate \(W_T=D_ξ\exp(-\mathrm{i} T H)\), in which the evolution generated by a diagonal Ising Hamiltonian is used…
Sideband fingerprints of antibunched light in cascaded quantum wave mixing
R. D. Ivanovskikh, W. V. Pogosov, A. A. Elistratov +5
Quantum wave mixing on a single superconducting qubit produces a hierarchy of coherent side peaks associated with elastic multiphoton scattering pathways. In a cascaded source--pro…
Photon pairs, squeezed light and the quantum wave mixing effect in a cascaded qubit system
R. D. Ivanovskikh, W. V. Pogosov, A. A. Elistratov +6
We develop a theoretical description of quantum wave mixing (QWM) in a cascaded waveguide-QED system of two superconducting qubits, where the probe is driven by an external coheren…
Hybrid physical/logical zero-noise extrapolation with limited logical executions
D. V. Babukhin, W. V. Pogosov
Partially error-corrected logical executions are expected to become available before fully fault-tolerant quantum computation, but such executions usually take much longer runtime…
Grover's search meets Ising models: a quantum algorithm for finding low-energy states
Andrey Zhukov, Andrey Lebedev, Walter Pogosov
We propose a methodology for implementing Grover's algorithm in the digital quantum simulation of disordered Ising models. The core concept revolves around using the evolution oper…
Quantum error mitigation in the regime of high noise using deep neural network: Trotterized dynamics
A. A. Zhukov, W. V. Pogosov
We address a learning-based quantum error mitigation method, which utilizes deep neural network applied at the postprocessing stage, and study its performance in presence of differ…