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Much of uncertainty quantification to date has focused on determining the effect of variables modeled probabilistically, and with a known distribution, on some physical or engineering system. We develop methods to obtain information on the…

Numerical Analysis · Mathematics 2015-03-19 Kamaljit Chowdhary , Paul Dupuis

We survey and investigate some computational aspects of the Fourier-Mukai transform.

High Energy Physics - Theory · Physics 2008-11-26 Nikolaj M. Glazunov

We uncover an inconsistency in the uniform WKB quantization of deformed quantum mechanics.

High Energy Physics - Theory · Physics 2026-04-01 Dharmesh Jain

As Large Language Models (LLMs) are increasingly deployed in real-world applications, reliable uncertainty quantification (UQ) becomes critical for safe and effective use. Most existing UQ approaches for language models aim to produce a…

Computation and Language · Computer Science 2026-04-14 Maiya Goloburda , Roman Vashurin , Fedor Chernogorsky , Nurkhan Laiyk , Daniil Orel , Preslav Nakov , Maxim Panov

The uncertainty relation is a distinctive characteristic of quantum theory. The uncertainty is essentially rooted in quantum states. In this work we regard the uncertainty as an intrinsic property of quantum state and characterize it…

Quantum Physics · Physics 2024-05-31 Ming-Jing Zhao , Yuanhong Tao

To assess the durability of structures, heat and moisture transport need to be analyzed. To provide a reliable estimation of heat and moisture distribution in a certain structure, one needs to include all available information about the…

Numerical Analysis · Computer Science 2013-03-19 Anna Kucerova , Jan Sykora

Uncertainty quantification for complex deep learning models is increasingly important as these techniques see growing use in high-stakes, real-world settings. Currently, the quality of a model's uncertainty is evaluated using…

Machine Learning · Computer Science 2021-12-15 Benjamin Kompa , Jasper Snoek , Andrew Beam

We review the alternative proposals introduced recently in the literature to update the standard formula to estimate the uncertainty on the mean of repeated measurements, and we compare their performances on synthetic examples with normal…

Data Analysis, Statistics and Probability · Physics 2022-09-13 Pascal Pernot , Jean-Paul Berthet

A calculator program has been written to give confidence intervals on branching ratios for rare decay modes (or similar quantities) calculated from the number of events observed, the acceptance factor, the background estimate and the…

High Energy Physics - Experiment · Physics 2011-07-19 Roger Barlow

Although gauge invariance preserves the values of physical observables, a gauge transformation can introduce important alterations of physical interpretations. To understand this, it is first shown that a gauge transformation is not, in…

Quantum Physics · Physics 2013-02-07 H. R. Reiss

It is difficult to evaluate the precision of quantum measurements because it is not possible to conduct a second reference measurement on the same physical system to compare the measurement outcome with a more accurate value of the measured…

Quantum Physics · Physics 2021-02-10 Holger F. Hofmann

A pedagogical and reasonably self-contained introduction to the measurement problems in quantum mechanics and their partial solution by environment-induced decoherence (plus some other important aspects of dcoherence) is given. The point…

Quantum Physics · Physics 2007-05-23 Tulsi Dass

Some aspects of application of the Uncertainty Principle in the range of interaction radiation with matter surveyed. The procedure of adjustment is proposed at calculation of values of an electromagnetic energy in a quantum theory of a…

Quantum Physics · Physics 2007-05-23 N. V. Brazovskaja , V. Ye Brazovsky

I use an instrumental approach to investigate some commonly made claims about interpretations of quantum mechanics, especially those that pertain questions of locality. The here presented investigation builds on a recently proposed taxonomy…

Quantum Physics · Physics 2024-10-08 Sabine Hossenfelder

Uncertainty estimation is important for ensuring safety and robustness of AI systems. While most research in the area has focused on un-structured prediction tasks, limited work has investigated general uncertainty estimation approaches for…

Machine Learning · Statistics 2021-02-12 Andrey Malinin , Mark Gales

The effects of the theoretical uncertainties in the description of neutrino-nucleus cross sections for supernova neutrino energies are investigated.

Nuclear Theory · Physics 2009-04-17 Giampaolo Co' , Viviana De Donno , Chiara Maieron

We study the stability of holonomic quantum computations with respect to errors in assignment of control parameters. The general expression for fidelity is obtaned. In the small errors limit the simple formulae for the fidelity decrease…

Quantum Physics · Physics 2007-05-23 V. I. Kuvshinov , A. V. Kuzmin

In the context of Monte Carlo (MC) simulation of particle transport Uncertainty Quantification (UQ) addresses the issue of predicting non statistical errors affecting the physical results, i.e. errors deriving mainly from uncertainties in…

Computational Physics · Physics 2015-06-18 Paolo Saracco , Maria Grazia Pia

A short critical review of the concept of decoherence, its consequences, and its possible implications for the interpretation of quantum theory is given.

Quantum Physics · Physics 2007-05-23 H. D. Zeh

In computational materials science, mechanical properties are typically extracted from simulations by means of analysis routines that seek to mimic their experimental counterparts. However, simulated data often exhibit uncertainties that…

Data Analysis, Statistics and Probability · Physics 2017-12-07 Paul N. Patrone , Anthony J. Kearsley , Andrew M. Dienstfrey