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Precision control of a quantum system requires accurate determination of the effective system Hamiltonian. We develop a method for estimating the Hamiltonian parameters for some unknown two-state system and providing uncertainty bounds on…

The objective of physics laboratory training is to develop, in students, a variety of important cognitive and psycho-motor abilities related to experimental physics. These include conceptual understanding, procedural understanding,…

Physics Education · Physics 2013-11-26 Rajesh B. Khaparde

Uncertainty quantification is a key part of astronomy and physics; scientific researchers attempt to model both statistical and systematic uncertainties in their data as best as possible, often using a Bayesian framework. Decisions might…

Instrumentation and Methods for Astrophysics · Physics 2022-07-29 Peter Hatfield

Systematic differences in experimental materials, methods, measurements, and data handling between labs, over time, and among personnel can sabotage experimental reproducibility. Uncovering such differences can be difficult and time…

Applications · Statistics 2018-07-18 Bert Gunter

Many quantum technologies rely on high-precision dynamics, which raises the question of how these are influenced by the experimental uncertainties that are always present in real-life settings. A standard approach in the literature to…

Quantum Physics · Physics 2022-04-27 Mogens Dalgaard , Carrie A. Weidner , Felix Motzoi

A small tabletop experiment for a direct measurement of the speed of light to an accuracy of few percent is described. The experiment is accessible to a wide spectrum of undergraduate students, in particular to students not majoring in…

Physics Education · Physics 2009-11-13 Kenichiro Aoki , Takahisa Mitsui

The paper deals with measures of nonlinearity. In state estimation, they are utilized i) to select a suitable state estimation algorithm by assessing the nonlinearity of a system model, ii) to adapt the estimation algorithm structure or…

Systems and Control · Electrical Eng. & Systems 2024-12-10 Ondřej Straka , Jindřich Havlík

The T2K experiment is a long-baseline neutrino oscillation experiment with the ability to measure precisely $\nu_{\mu}\rightarrow\nu_e$ and $\nu_{\mu}\rightarrow\nu_{\mu}$ oscillations. Control of systematic uncertainties-dominated by flux…

High Energy Physics - Experiment · Physics 2019-08-14 A. Kaboth

Effective software safety standards will contribute to confidence, or assurance, in the safety of the systems in which the software is used. It is infeasible to demonstrate a correlation between standards and accidents, but there is an…

Software Engineering · Computer Science 2014-04-29 John A. McDermid

Uncertainty quantification is at the core of the reliability and robustness of machine learning. In this paper, we provide a theoretical framework to dissect the uncertainty, especially the \textit{epistemic} component, in deep learning…

Machine Learning · Computer Science 2023-06-21 Ziyi Huang , Henry Lam , Haofeng Zhang

Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper…

High Energy Physics - Experiment · Physics 2022-06-20 MicroBooNE collaboration , P. Abratenko , R. An , J. Anthony , L. Arellano , J. Asaadi , A. Ashkenazi , S. Balasubramanian , B. Baller , C. Barnes , G. Barr , V. Basque , L. Bathe-Peters , O. Benevides Rodrigues , S. Berkman , A. Bhanderi , A. Bhat , M. Bishai , A. Blake , T. Bolton , J. Y. Book , L. Camilleri , D. Caratelli , I. Caro Terrazas , F. Cavanna , G. Cerati , Y. Chen , D. Cianci , J. M. Conrad , M. Convery , L. Cooper-Troendle , J. I. Crespo-Anadón , M. Del Tutto , S. R. Dennis , P. Detje , A. Devitt , R. Diurba , R. Dorrill , K. Duffy , S. Dytman , B. Eberly , A. Ereditato , J. J. Evans , R. Fine , G. A. Fiorentini Aguirre , R. S. Fitzpatrick , B. T. Fleming , N. Foppiani , D. Franco , A. P. Furmanski , D. Garcia-Gamez , S. Gardiner , G. Ge , S. Gollapinni , O. Goodwin , E. Gramellini , P. Green , H. Greenlee , W. Gu , R. Guenette , P. Guzowski , L. Hagaman , O. Hen , C. Hilgenberg , G. A. Horton-Smith , A. Hourlier , R. Itay , C. James , X. Ji , L. Jiang , J. H. Jo , R. A. Johnson , Y. -J. Jwa , D. Kalra , N. Kamp , N. Kaneshige , G. Karagiorgi , W. Ketchum , M. Kirby , T. Kobilarcik , I. Kreslo , I. Lepetic , K. Li , Y. Li , K. Lin , B. R. Littlejohn , W. C. Louis , X. Luo , K. Manivannan , C. Mariani , D. Marsden , J. Marshall , D. A. Martinez Caicedo , K. Mason , A. Mastbaum , N. McConkey , V. Meddage , T. Mettler , K. Miller , J. Mills , K. Mistry , A. Mogan , T. Mohayai , J. Moon , M. Mooney , A. F. Moor , C. D. Moore , L. Mora Lepin , J. Mousseau , M. Murphy , D. Naples , A. Navrer-Agasson , M. Nebot-Guinot , R. K. Neely , D. A. Newmark , J. Nowak , M. Nunes , O. Palamara , V. Paolone , A. Papadopoulou , V. Papavassiliou , S. F. Pate , N. Patel , A. Paudel , Z. Pavlovic , E. Piasetzky , I. D. Ponce-Pinto , S. Prince , X. Qian , J. L. Raaf , V. Radeka , A. Rafique , M. Reggiani-Guzzo , L. Ren , L. C. J. Rice , L. Rochester , J. Rodriguez Rondon , M. Rosenberg , M. Ross-Lonergan , G. Scanavini , D. W. Schmitz , A. Schukraft , W. Seligman , M. H. Shaevitz , R. Sharankova , J. Shi , J. Sinclair , A. Smith , E. L. Snider , M. Soderberg , S. Söldner-Rembold , P. Spentzouris , J. Spitz , M. Stancari , J. St. John , T. Strauss , K. Sutton , S. Sword-Fehlberg , A. M. Szelc , W. Tang , K. Terao , C. Thorpe , D. Totani , M. Toups , Y. -T. Tsai , M. A. Uchida , T. Usher , W. Van De Pontseele , B. Viren , M. Weber , H. Wei , Z. Williams , S. Wolbers , T. Wongjirad , M. Wospakrik , K. Wresilo , N. Wright , W. Wu , E. Yandel , T. Yang , G. Yarbrough , L. E. Yates , H. W. Yu , G. P. Zeller , J. Zennamo , C. Zhang

Measurement uncertainty is key to assessing, stating and improving the reliability of measurements. An understanding of measurement uncertainty is the basis for confidence in measurements and is required by many communities; among others in…

Physics Education · Physics 2024-12-30 Katy Klauenberg , Peter Harris , Philipp Möhrke , Francesca Pennecchi

Classifiers are often tested on relatively small data sets, which should lead to uncertain performance metrics. Nevertheless, these metrics are usually taken at face value. We present an approach to quantify the uncertainty of…

Machine Learning · Statistics 2021-03-05 Niklas Tötsch , Daniel Hoffmann

In Dark Matter direct detection we are facing the situation of some experiments reporting positive signals which are in conflict with limits from other experiments. Such conclusions are subject to large uncertainties introduced by the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-23 Nassim Bozorgnia , Thomas Schwetz

This paper reports the use of Tracker as a pedagogical tool in the effective learning and teaching of projectile motion in physics. When computer model building learning processes is supported and driven by video analysis data, this free…

Physics Education · Physics 2015-12-25 Loo Kang Wee , Charles Chew , Giam Hwee Goh , Samuel Tan , Tat Leong Lee

Development of conceptual multiple-choice tests related to a particular physics topic is important for designing research-based learning tools to reduce the difficulties. We explore the difficulties that the advanced undergraduate and…

Physics Education · Physics 2016-02-22 Chandralekha Singh , Guangtian Zhu

Quantifying coherence has received increasing attention, and considerable work has been directed towards finding coherence measures. While various coherence measures have been proposed in theory, an important issue following is how to…

Quantum Physics · Physics 2018-05-02 Da-Jian Zhang , C. L. Liu , Xiao-Dong Yu , D. M. Tong

The experimental evaluation of many quantum mechanical quantities requires the estimation of several directly measurable observables, such as local observables. Due to the necessity to repeat experiments on individual quantum systems in…

Quantum Physics · Physics 2024-06-10 Ruidi Zhu , Ciara Pike-Burke , Florian Mintert

Anomalies drive scientific discovery -- they are associated with the cutting edge of the research frontier, and thus typically exploit data in the low signal-to-noise regime. In astronomy, the prevalence of systematics --- both "known…

Cosmology and Nongalactic Astrophysics · Physics 2014-10-16 Hiranya V. Peiris

It has been suggested that the uncertainty in the measurement of a particle's momentum could be made arbitrarily small by observing the particle at two ends of an arbitrarily long flight path. However, consideration of the nature of the…

Quantum Physics · Physics 2007-05-23 Kirk T. McDonald