Results 51 to 60 of about 2,420 (204)
A new class of biohybrid spheroids is engineered through the self‐assembly of adherent cells and extracellular matrix‐mimetic hydrogel microparticles (microgels). By mimicking a snowballing effect, this approach enables scalable formation of porous, millimeter‐scale spheroids with enhanced cell viability and molecular diffusion.
Zaman Ataie +7 more
wiley +1 more source
A probabilistic framework based on random time‐space coding metasurfaces enables control of the spatial distribution of electromagnetic fields temporal statistics. By tailoring the marginal and joint distributions of random codes, electromagnetic fields with desired mean and variance patterns are realized, enabling simultaneous transmission and jamming.
Jia Cheng Li +3 more
wiley +1 more source
Qubit Reduction and Quantum Speedup for Wireless Channel Assignment Problem
In this article, we propose a novel method of formulating an NP-hard wireless channel assignment problem as a higher-order unconstrained binary optimization (HUBO), where the Grover adaptive search (GAS) is used to provide a quadratic speedup for solving
Yuki Sano +2 more
doaj +1 more source
An Algorithm for Unconstrained Quadratically Penalized Convex Optimization [PDF]
A descent algorithm, "Quasi-Quadratic Minimization with Memory" (QQMM), is proposed for unconstrained minimization of the sum, $F$, of a non-negative convex function, $V$, and a quadratic form. Such problems come up in regularized estimation in machine learning and statistics. In addition to values of $F$, QQMM requires the (sub)gradient of $V$.
openaire +2 more sources
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
An important and difficult problem in optimization is the high-order unconstrained binary optimization, which can represent many optimization problems more efficiently than quadratic unconstrained binary optimization, but how to quickly solve it has ...
Bi-Ying Wang +5 more
doaj +1 more source
Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
wiley +1 more source
Digital Annealer for quadratic unconstrained binary optimization: A comparative performance analysis
Digital Annealer (DA) is a computer architecture designed for tackling combinatorial optimization problems formulated as quadratic unconstrained binary optimization (QUBO) models. In this paper, we present the results of an extensive computational study to evaluate the performance of DA in a systematic way in comparison to multiple state-of-the-art ...
Oylum Şeker +2 more
openaire +2 more sources
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
Quadratic unconstrained binary optimization formulation for rectified-linear-unit-type functions [PDF]
5 pages, 2 ...
Sato, Go +4 more
openaire +3 more sources

