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Optimal experiment design for parameter estimation is a research topic that has been in the interest of various studies. A key problem in optimal input design is that the optimal input depends on some unknown system parameters that are to…

Systems and Control · Computer Science 2019-04-17 Lirong Huang , Håkan Hjalmarsson , László Gerencsér

Structural reliability analysis is concerned with estimation of the probability of a critical event taking place, described by $P(g(\textbf{X}) \leq 0)$ for some $n$-dimensional random variable $\textbf{X}$ and some real-valued function…

Computation · Statistics 2021-04-13 Christian Agrell , Kristina Rognlien Dahl

Causal effect estimation often succeeds cost-constrained sequential data collection. This work considers multivariate linear front-door models with arbitrary unobserved confounding on treatment and response. We optimize the experimental…

Methodology · Statistics 2026-03-24 Leopold Mareis , Mathias Drton

The unknown parameters of simulation models often need to be calibrated using observed data. When simulation models are expensive, calibration is usually carried out with an emulator. The effectiveness of the calibration process can be…

Computation · Statistics 2024-12-03 Özge Sürer , Stefan M. Wild

Optimization via simulation has been well established to find optimal solutions and designs in complex systems. However, it still faces modeling and computational challenges when extended to the multi-stage setting. This survey reviews the…

Optimization and Control · Mathematics 2023-12-08 Zhuo Zhang , Dan Wang , Haoxiang Yang , Shubin Si

Computer experiments with both qualitative and quantitative factors are widely used in many applications. Motivated by the emerging need of optimal configuration in the high-performance computing (HPC) system, this work proposes a…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-08 Xia Cai , Li Xu , C. Devon Lin , Yili Hong , Xinwei Deng

In an era where scientific experiments can be very costly, multi-fidelity emulators provide a useful tool for cost-efficient predictive scientific computing. For scientific applications, the experimenter is often limited by a tight…

Methodology · Statistics 2023-10-30 Chih-Li Sung , Yi Ji , Simon Mak , Wenjia Wang , Tao Tang

Bayesian experimental design involves the optimal allocation of resources in an experiment, with the aim of optimising cost and performance. For implicit models, where the likelihood is intractable but sampling from the model is possible,…

Machine Learning · Statistics 2019-02-26 Steven Kleinegesse , Michael Gutmann

In a Josephson phase qubit the coherent manipulations of the computational states are achieved by modulating an applied ac current, typically in the microwave range. In this work we show that it is possible to find optimal modulations of…

Mesoscale and Nanoscale Physics · Physics 2010-09-08 Shabnam Safaei , Simone Montangero , Fabio Taddei , Rosario Fazio

Building more powerful quantum computers requires manufacturing processes with tight tolerances. To improve the tolerances on Josephson junctions, techniques to fine tune their properties after fabrication have been developed. Understanding…

Quantum Physics · Physics 2025-11-17 Oscar W. Kennedy , Jared H. Cole , Connor D. Shelly

Establishment of phase-coherence and a non-dissipative (super)current between two weakly coupled superconductors, known as the Josephson effect, plays a foundational role in basic physics and applications to metrology, precision sensing,…

The construction of decision-theoretic Bayesian designs for realistically-complex nonlinear models is computationally challenging, as it requires the optimization of analytically intractable expected utility functions over high-dimensional…

Methodology · Statistics 2016-07-01 Antony Overstall , David Woods

Clinical decision-making often involves selecting tests that are costly, invasive, or time-consuming, motivating individualized, sequential strategies for what to measure and when to stop ascertaining. We study the problem of learning…

Machine Learning · Statistics 2026-04-16 Doudou Zhou , Yiran Zhang , Dian Jin , Yingye Zheng , Lu Tian , Tianxi Cai

The theory of time-dependent quantum transport addresses the question: How do electrons flow through a junction under the influence of an external perturbation as time goes by? In this paper, we invert this question and search for a…

Mesoscale and Nanoscale Physics · Physics 2014-07-10 K. J. Pototzky , E. K. U. Gross

The quantum character of Josephson junctions is ordinarily revealed through the analysis of the switching currents, i.e. the current at which a finite voltage appears: A sharp rise of the voltage signals the passage (tunnel) from a trapped…

Quantum Physics · Physics 2016-10-24 Vincenzo Pierro , Giovanni Filatrella

Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain. Recent developments in deep neural networks and normalizing flows…

Quantum Physics · Physics 2023-06-27 Leopoldo Sarra , Florian Marquardt

Josephson Junctions are important components in superconducting qubits. It introduces anharmonicity to the energy level spacings of the qubit which allow us to identify two unique quantum energy states for computing. It is difficult to…

Quantum Physics · Physics 2023-10-03 Haochen Li , Soe Gon Yee Thant , Rainer Dumke

We consider an experiment with at least two stages or batches and $O(N)$ subjects per batch. First, we propose a semiparametric treatment effect estimator that efficiently pools information across the batches, and show it asymptotically…

Methodology · Statistics 2023-09-28 Harrison H. Li , Art B. Owen

We investigate by theory and experiment, the Josephson junction switching current detector in an environment with frequency dependent damping. Analysis of the circuit's phase space show that a favorable topology for switching can be…

Superconductivity · Physics 2013-05-29 Jochen Walter , Erik Tholen , Joachim Sjostrand , David B. Haviland

We consider the problem of making a quick decision in favor of one of two possible physical signal models while the numerical measurements are acquired by sensing devices featuring minimal digitization complexity. Therefore, the digital…

Signal Processing · Electrical Eng. & Systems 2019-10-29 Manuel S. Stein , Michael Fauß
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