From the 1 of 6 linked papers with an AI index.
6 papers
Resource-efficient linear-optical generation of GHZ-like states
Suren A. Fldzhyan, Stanislav S. Straupe, Mikhail Yu. Saygin
The paper presents a linear‑optical scheme for generating GHZ‑like multi‑photon entangled states that uses tunable, non‑maximally entangled intermediate states to reduce the photon…
Perturbative photonic matrix-vector multiplication with reduced phase-shift range
S. A. Fldzhyan, S. S. Straupe, M. Yu. Saygin
Programmable photonic meshes provide a promising platform for analog matrix-vector multiplication, but their scalability is often limited by the large phase-shift ranges required i…
Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers
Andrei Chertkov, Artem Basharin, Mikhail Saygin +3
The growing demand for energy-efficient, high-performance AI systems has led to increased attention on alternative computing platforms (e.g., photonic, neuromorphic) due to their p…
Single-photon-boosted type-I fusion gates
A. A. Melkozerov, S. S. Straupe, M. Yu. Saygin
Fusion measurements are a key primitive for linear-optical quantum computing and quantum networks. Type-I and type-II fusion gates are widely used to combine small entangled resour…
Native QR Factorization on Programmable Photonic Meshes
S. A. Fldzhyan, S. S. Straupe, M. Yu. Saygin
We propose a photonic native procedure for computing the QR factorization of a matrix using a programmable unitary interferometer mesh. The method configures the mesh through a seq…
LLM-Guided Evolutionary Search for Algebraic T-Count Optimization
Daniil Fisher, Valentin Khrulkov, Mikhail Saygin +2
T-count minimization is an NP-hard problem that arises in fault-tolerant quantum compilation. In the parity-matrix representation, which captures the non-Clifford part of a quantum…