47 citations · 94 across the 14 of their papers we have counts for
15 papers
A variational quantum algorithm for entanglement quantification
Lucas Friedrich, Marcos L. W. Basso, Alberto B. P. Junior +4
Quantum entanglement is a foundational resource in quantum information science, underpinning applications across physics. However, detecting and quantifying entanglement remains a…
A short review on qudit quantum machine learning
Tiago de Souza Farias, Lucas Friedrich, Jonas Maziero
As quantum devices scale toward practical machine learning applications, the binary qubit paradigm faces expressivity and resource efficiency limitations. Multi-level quantum syste…
QuForge: A Library for Qudits Simulation
Tiago de Souza Farias, Lucas Friedrich, Jonas Maziero
Quantum computing with qudits, an extension of qubits to multiple levels, is a research field less mature than qubit-based quantum computing. However, qudits can offer some advanta…
Barren plateaus are amplified by the dimension of qudits
Lucas Friedrich, Tiago de Souza Farias, Jonas Maziero
Variational Quantum Algorithms (VQAs) have emerged as pivotal strategies for attaining quantum advantage in diverse scientific and technological domains, notably within Quantum Neu…
Quantum neural network with ensemble learning to mitigate barren plateaus and cost function concentration
Lucas Friedrich, Jonas Maziero
The rapid development of quantum computers promises transformative impacts across diverse fields of science and technology. Quantum neural networks (QNNs), as a forefront applicati…
Preparing general mixed quantum states on quantum computers
Lucas Friedrich, Douglas F. Pinto, Diego S. Starke +1
The preparation of quantum states is a fundamental subroutine for a broad class of quantum information protocols and is critical for both quantum communication and quantum computat…
Learning to learn with an evolutionary strategy applied to variational quantum algorithms
Lucas Friedrich, Jonas Maziero
Variational Quantum Algorithms (VQAs) employ parameterized quantum circuits optimized using classical methods to minimize a cost function. While VQAs have found broad applications,…
The quantum cost function concentration dependency on the parametrization expressivity
Lucas Friedrich, Jonas Maziero
Although we are currently in the era of noisy intermediate scale quantum devices, several studies are being conducted with the aim of bringing machine learning to the quantum domai…
Restricting to the chip architecture maintains the quantum neural network accuracy
Lucas Friedrich, Jonas Maziero
In the era of noisy intermediate-scale quantum devices, variational quantum algorithms (VQAs) stand as a prominent strategy for constructing quantum machine learning models. These…
Avoiding Barren Plateaus with Classical Deep Neural Networks
Lucas Friedrich, Jonas Maziero
Variational quantum algorithms (VQAs) are among the most promising algorithms in the era of Noisy Intermediate Scale Quantum Devices. Such algorithms are constructed using a parame…
Evolution strategies: Application in hybrid quantum-classical neural networks
Lucas Friedrich, Jonas Maziero
With the rapid development of quantum computers, several applications are being proposed for them. Quantum simulations, simulation of chemical reactions, solution of optimization p…
Entropy Stable p-Nonconforming Discretizations with the Summation-by-Parts Property for the Compressible Navier-Stokes Equations
David C. Del Rey Fernandez, Mark H. Carpenter, Lisandro Dalcin +4
The entropy conservative, curvilinear, nonconforming, p-refinement algorithm for hyperbolic conservation laws of Del Rey Fernandez et al. (2019), is extended from the compressible…
Entropy Stable Space-Time Discontinuous Galerkin Schemes with Summation-by-Parts Property for Hyperbolic Conservation Laws
Lucas Friedrich, Gero Schnücke, Andrew R. Winters +3
This work examines the development of an entropy conservative (for smooth solutions) or entropy stable (for discontinuous solutions) space-time discontinuous Galerkin (DG) method f…
An Entropy Stable h/p Non-Conforming Discontinuous Galerkin Method with the Summation-by-Parts Property
Lucas Friedrich, Andrew R. Winters, David C. Del Rey Fernández +3
This work presents an entropy stable discontinuous Galerkin (DG) spectral element approximation for systems of non-linear conservation laws with general geometric (h) and polynomia…
Conservative and Stable Degree Preserving SBP Operators for Non-Conforming Meshes
Lucas Friedrich, David C. Del Rey Fernandez, Andrew R. Winters +3
Non-conforming numerical approximations offer increased flexibility for applications that require high resolution in a localized area of the computational domain or near complex ge…