10 citations · 17 across the 5 of their papers we have counts for
6 papers
Entanglement of superpositions in zero-energy subspace: insights from stabilizer theory
Konstantin Antipin, Richik Sengupta
Exact zero-energy eigenstates built from entangled dimers have recently been found in a large class of spin Hamiltonians. While the individual states have a simple structure, their…
Parametrized-circuit-free quantum regression with variance regularization
Yerassyl Balkybek, Andrey Kardashin, Vladimir V. Palyulin +1
Quantum regression tasks for predicting properties of quantum states are commonly addressed using variational quantum algorithms. While variational quantum circuits are highly expr…
On measurement-dependent variance in quantum neural networks
Andrey Kardashin, Konstantin Antipin
Variational quantum circuits have become a widely used tool for performing quantum machine learning (QML) tasks on labeled quantum states. In some specific tasks or for specific va…
Predicting properties of quantum systems by regression on a quantum computer
Andrey Kardashin, Yerassyl Balkybek, Vladimir V. Palyulin +1
Quantum computers can be considered as a natural means for performing machine learning tasks for inherently quantum labeled data. Many quantum machine learning techniques have been…
Construction of genuinely entangled multipartite subspaces from bipartite ones by reducing the total number of separated parties
K. V. Antipin
Construction of genuinely entangled multipartite subspaces with certain characteristics has become a relevant task in various branches of quantum information. Here we show that suc…
Construction of genuinely multipartite entangled subspaces and the associated bounds on entanglement measures for mixed states
K. V. Antipin
Genuine entanglement is the strongest form of multipartite entanglement. Genuinely entangled pure states contain entanglement in every bipartition and as such can be regarded as a…