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Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Uwe Aickelin , Steve Cayzer

A simple model is proposed for the direct correlation function (DCF) for simple fluids consisting of a hard-core contribution, a simple parametrized core correction, and a mean-field tail. The model requires as input only the free energy of…

Statistical Mechanics · Physics 2007-10-08 James F. Lutsko

The means to obtain the rate constants of a chemical reaction is a fundamental open problem in both science and the industry. Traditional techniques for finding rate constants require either chemical modifications of the reactants or…

Statistics Theory · Mathematics 2019-07-09 Y. Zhang , Z. Yao , P. Forssen , T. Fornstedt

We state a quantum version of Bayes's rule for statistical inference and give a simple general derivation within the framework of generalized measurements. The rule can be applied to measurements on N copies of a system if the initial state…

Quantum Physics · Physics 2009-11-06 Ruediger Schack , Todd A. Brun , Carlton M. Caves

We propose a scheme to measure the quantum state of photons in a cavity. The proposal is based on the concept of quantum weak values and applies equally well to both the solid-state circuit and atomic cavity quantum electrodynamics (QED)…

Quantum Physics · Physics 2019-04-24 Lupei Qin , Zhong Wang , Cheng Zhang , Xin-Qi Li

Continuous-variable quantum cryptographic systems, including random number generation and key distribution, are often based on coherent detection. The essence of the security analysis lies in the randomness quantification. Previous analyses…

Quantum Physics · Physics 2018-10-24 Hongyi Zhou , Pei Zeng , Mohsen Razavi , Xiongfeng Ma

Within the framework of weighted integrable Hamiltonian systems, we study the long-time behavior of the associated statistical ensembles. We construct an action-dependent angular conjugacy that rectifies the nonuniform angular flow into a…

Dynamical Systems · Mathematics 2025-09-29 Xinyu Liu , Yong Li

We study distributed output feedback control for a heterogeneous multi-agent system (MAS), consisting of N different continuous-time linear dynamical systems. For achieving output consensus, a virtual reference model is assumed to generate…

Optimization and Control · Mathematics 2016-10-31 Luis D. Alvergue , Abhishek Pandey , Guoxiang Gu , Xiang Chen

Grouped data are commonly encountered in applications. The Bernstein polynomial model is proposed as an approximate model in this paper for estimating a univariate density function based on grouped data. The coefficients of the Bernstein…

Methodology · Statistics 2015-07-21 Zhong Guan

The immune system is a real-time example of an evolving system that navigates the essentially infinite complexity of protein sequence space. How this system responds to disease and vaccination is discussed. Of particular focus is the case…

Cell Behavior · Quantitative Biology 2007-05-23 Michael W. Deem

Ab initio instanton rate theory is a computational method for rigorously including tunnelling effects into calculations of chemical reaction rates based on a potential-energy surface computed on the fly from electronic-structure theory.…

Chemical Physics · Physics 2018-05-08 Gabriel Laude , Danilo Calderini , David P. Tew , Jeremy O. Richardson

Most present applications of time-dependent density functional theory use adiabatic functionals, i.e. the effective potential at time t is determined solely by the density at the same time. This paper discusses a method that aims to go…

Strongly Correlated Electrons · Physics 2009-11-10 Yair Kurzweil , Roi Baer

We study a dynamical system model of an idiotypic immune network with a small number of degrees of freedom, mainly focusing on the effect of a threshold above which antibodies can recognise antibodies. The response of the system to…

Condensed Matter · Physics 2009-11-07 Satoko Itaya , Tatsuya Uezu

We introduce a direct Boltzmann inversion method to infer the interaction potential in particle systems using as input particle configurations generated at an arbitrary state point of the system. Unlike iterative Boltzmann inversion, the…

Statistical Mechanics · Physics 2026-05-25 Olivier Coquand , Davide Paolino , Ludovic Berthier

We present a new analysis on the quantum control for a quantum system coupled to a quantum probe. This analysis is based on the coherent control for the quantum system and a hyperthesis that the probe can be prepared in specified initial…

Quantum Physics · Physics 2009-11-01 J. Nie , H. C. Fu , X. X. Yi

Quantile matching is a strictly monotone transformation that sends the observed response values $\{y_1, . . . , y_n\}$ to the quantiles of a given target distribution. A likelihood based criterion is developed for comparing one target…

Methodology · Statistics 2020-01-14 Peter McCullagh , Micol Federica Tresoldi

We describe the development of a new toolkit for data analysis. The analysis package is based on Bayes' Theorem, and is realized with the use of Markov Chain Monte Carlo. This gives access to the full posterior probability distribution.…

Data Analysis, Statistics and Probability · Physics 2015-05-13 Allen Caldwell , Daniel Kollar , Kevin Kroeninger

We present a unified picture of dispersive readout of quantum systems in and out of equilibrium. A cornerstone of the approach is the backaction of the measured system to the cavity obtained with non-equilibrium linear-response theory. It…

Mesoscale and Nanoscale Physics · Physics 2018-08-29 Sigmund Kohler

The characterization of quantum critical phenomena is pivotal for the understanding and harnessing of quantum many-body physics. However, their complexity makes the inference of such fundamental processes difficult. Thus, efficient and…

Quantum Physics · Physics 2022-04-27 Ricardo Puebla , Alessio Belenchia , Giulio Gasbarri , Eric Lutz , Mauro Paternostro

Flexible and scalable decentralized learning solutions are fundamentally important in the application of multi-agent systems. While several recent approaches introduce (ensembles of) kernel machines in the distributed setting, Bayesian…

Machine Learning · Computer Science 2025-02-11 Fernando Llorente , Daniel Waxman , Petar M. Djurić
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