Zobrazeno 1 - 10
of 1 660
pro vyhledávání: '"Araújo, A. F."'
Constrained multiobjective optimization problems (CMOPs) are commonly found in real-world applications. CMOP is a complex problem that needs to satisfy a set of equality or inequality constraints. This paper proposes a variant of the bidirectional co
Externí odkaz:
http://arxiv.org/abs/2410.19439
This paper introduces the inverse modeling constrained multi-objective evolutionary algorithm based on decomposition (IM-C-MOEA/D) for addressing constrained real-world optimization problems. Our research builds upon the advancements made in evolutio
Externí odkaz:
http://arxiv.org/abs/2410.19203
Autor:
de Carvalho, José A., Batista, Carlos A., de Veras, Tiago M. L., Araujo, Israel F., da Silva, Adenilton J.
The initialization of quantum states or Quantum State Preparation (QSP) is a basic subroutine in quantum algorithms. In the worst case, general QSP algorithms are expensive due to the application of multi-controlled gates required to build them. Here
Externí odkaz:
http://arxiv.org/abs/2409.05618
The potential role of a cosmic vacuum dark component in the properties of neutron stars is investigated. It is assumed that the static, spherically symmetric distribution of matter within neutron stars is supported by two distinct components: ordinar
Externí odkaz:
http://arxiv.org/abs/2408.01006
Autor:
Lee, Changwon, Araujo, Israel F., Kim, Dongha, Lee, Junghan, Park, Siheon, Ryu, Ju-Young, Park, Daniel K.
Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This approach is particularly attractive due to the absence of the barren pl
Externí odkaz:
http://arxiv.org/abs/2403.19099
The Helstrom measurement (HM) is known to be the optimal strategy for distinguishing non-orthogonal quantum states with minimum error. Previously, a binary classifier based on classical simulation of the HM has been proposed. It was observed that usi
Externí odkaz:
http://arxiv.org/abs/2403.15308
Publikováno v:
Phys. Rev. A 110, 022411 (2024)
Quantum embedding is a fundamental prerequisite for applying quantum machine learning techniques to classical data, and has substantial impacts on performance outcomes. In this study, we present Neural Quantum Embedding (NQE), a method that efficient
Externí odkaz:
http://arxiv.org/abs/2311.11412
We provide a method for compiling approximate multi-controlled single qubit gates into quantum circuits without ancilla qubits. The total number of elementary gates to decompose an n-qubit multi-controlled gate is proportional to 32n, and the previou
Externí odkaz:
http://arxiv.org/abs/2310.14974
Autor:
Vale, Rafaella, Azevedo, Thiago Melo D., Araújo, Ismael C. S., Araujo, Israel F., da Silva, Adenilton J.
Multi-controlled unitary gates have been a subject of interest in quantum computing since its inception, and are widely used in quantum algorithms. The current state-of-the-art approach to implementing n-qubit multi-controlled gates involves the use
Externí odkaz:
http://arxiv.org/abs/2302.06377
Publikováno v:
In Marine Pollution Bulletin November 2024 208
