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Classical Surrogates for Quantum Learning Models
Physical Review Letters, 2023 The advent of noisy intermediate-scale quantum computers has put the search for possible applications to the forefront of quantum information science. One area where hopes for an advantage through near-term quantum computers are high is quantum machine learning, where variational quantum learning models based on parametrized quantum circuits are ...
Franz J. Schreiber +2 more
openaire +3 more sources
Sequential optimization of strip bending process using multiquadric radial basis function surrogate models [PDF]
, 2013 Surrogate models are used within the sequential optimization strategy for forming processes. A sequential improvement (SI) scheme is used to refine the surrogate model in the optimal region. One of the popular surrogate modeling methods for SI is Kriging.
Boogaard, A.H. van den +2 more
core +6 more sources
Surrogate modeling of RF circuit blocks [PDF]
, 2010 Surrogate models are a cost-effective replacement for expensive computer simulations in design space exploration. Literature has already demonstrated the feasibility of accurate surrogate models for single radio frequency (RF) and microwave devices ...
Croon, Jeroen A +3 more
core +1 more source
Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy [PDF]
, 2012 This paper presents a novel mechanism to adapt surrogate-assisted population-based algorithms. This mechanism is applied to ACM-ES, a recently proposed surrogate-assisted variant of CMA-ES. The resulting algorithm, saACM-ES, adjusts online the lifelength
Loshchilov, Ilya +2 more
core +4 more sources
Efficient simulation-driven design optimization of antennas using co-kriging [PDF]
, 2012 We present an efficient technique for design optimization of antenna structures. Our approach exploits coarse-discretization electromagnetic (EM) simulations of the antenna of interest that are used to create its fast initial model (a surrogate) through ...
Couckuyt, Ivo +3 more
core +1 more source
Response surface methodology using a prior knowledge and its application to pin fin heat sink design
Nihon Kikai Gakkai ronbunshu, 2019 Large number of simulations or experiments is needed for optimization and uncertainty quantification of a mechanical system. Therefore, if simulations or experiments are numerically expensive and time consuming, it is difficult to execute optimization ...
Kazuo MUTO, Makoto ONODERA
doaj +1 more source
A Surrogate Model of Gravitational Waveforms from Numerical Relativity Simulations of Precessing Binary Black Hole Mergers [PDF]
, 2017 We present the first surrogate model for gravitational waveforms from the coalescence of precessing binary black holes. We call this surrogate model NRSur4d2s. Our methodology significantly extends recently introduced reduced-order and surrogate modeling
Blackman, Jonathan +6 more
core +3 more sources
Energies, 2022 Integrated optimization of well placement and hydraulic fracture parameters in naturally fractured shale gas reservoirs is of significance to enhance unconventional hydrocarbon energy resources in the oil and gas industry.
Jun Zhou +3 more
doaj +1 more source
Virtual and Physical Prototyping, 2021 Additive manufacturing enables the fabrication of parts with complex geometries, thereby opening up the design space from part scale to microarchitecture scale.
Guo Yilin +2 more
doaj +1 more source
Applied Sciences, 2020 To find the optimal design for an engineering object, thousands of (or even more) simulations should be implemented to obtain the outcome data for the variously designed objects.
Sahuck Oh
doaj +1 more source