activity
20222026
most citedQuantum Channel Learning

8 citations · 16 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Semidefinite Programming for Quantum Channel Learning

Mikhail Gennadievich Belov, Victor Victorovich Dubov, Vadim Konstantinovich Ivanov +3

The problem of reconstructing a quantum channel from a sample of classical data is considered. When the total fidelity can be represented as a ratio of two quadratic forms (e.g., i…

q-fin.CP2025

Trade Execution Flow as the Underlying Source of Market Dynamics

Mikhail Gennadievich Belov, Victor Victorovich Dubov, Vadim Konstantinovich Ivanov +3

In this work, we demonstrate experimentally that the execution flow, , is the fundamental driving force of market dynamics. We develop a numerical framework to calculate…

quant-ph2025

Superstate Quantum Mechanics

Mikhail Gennadievich Belov, Victor Victorovich Dubov, Vadim Konstantinovich Ivanov +3

We introduce Superstate Quantum Mechanics (SQM), a theory that considers states in Hilbert space subject to multiple quadratic constraints, with ``energy'' also expressed as a quad…

cs.LG2024★ 8 cited

Quantum Channel Learning

Mikhail Gennadievich Belov, Victor Victorovich Dubov, Alexey Vladimirovich Filimonov +1

The problem of an optimal mapping between Hilbert spaces and , based on a series of density matrix mapping measurements , , is form…

cs.LG2024★ 8 cited

Partially Unitary Learning

Mikhail Gennadievich Belov, Vladislav Gennadievich Malyshkin

The problem of an optimal mapping between Hilbert spaces of and of based on a set of wavefunction measurements (within a ph…

q-fin.CP2022

Market Directional Information Derived From (Time, Execution Price, Shares Traded) Sequence of Transactions. On The Impact From The Future

Vladislav Gennadievich Malyshkin, Mikhail Gennadievich Belov

An attempt to obtain market directional information from non-stationary solution of the dynamic equation: "future price tends to the value maximizing the number of shares traded pe…