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The uncertainty principle restricts potential information one gains about physical properties of the measured particle. However, if the particle is prepared in entanglement with a quantum memory, the corresponding entropic uncertainty…

Quantum Physics · Physics 2017-03-10 Yunlong Xiao , Naihuan Jing , Xianqing Li-Jost

The uncertainty principle brings out intrinsic quantum bounds on the precision of measuring non-commuting observables. Statistical outcomes in the measurement of incompatible observables reveal a trade-off on the sum of corresponding…

Quantum Physics · Physics 2013-11-11 H. S. Karthik , A. R. Usha Devi , J. Prabhu Tej , A. K. Rajagopal

Uncertainty relations lie at the very core of quantum mechanics, and form the cornerstone of essentially all quantum cryptographic applications. In particular, they play an important role in cryptographic protocols in the…

Quantum Physics · Physics 2008-08-27 Stephanie Wehner , Andreas Winter

A prominent formulation of the uncertainty principle identifies the fundamental quantum feature that no particle may be prepared with certain outcomes for both position and momentum measurements. Often the statistical uncertainties are…

Quantum Physics · Physics 2015-01-08 Fabian Furrer , Mario Berta , Marco Tomamichel , Volkher B. Scholz , Matthias Christandl

We introduce quantum parameter estimation with the encoding being via a quantum measurement. We quantify the precision for estimating parameters characterizing a general two-outcome qubit measurement, considering two cases: when the…

Quantum Physics · Physics 2025-12-12 Shuva Mondal , Priya Ghosh , Ujjwal Sen

Recently, an entropic uncertainty relation for multiple measurements has been proposed by Liu et al. in [Phys. Rev. A 91, 042133 (2015)]. However, the lower bound of the relation is not always tight with respect to different measurements.…

Quantum Physics · Physics 2021-12-22 Bo-Fu Xie , Fei Ming , Dong Wang , Liu Ye , Jing-Ling Chen

The performance of ensemble-based data assimilation techniques that estimate the state of a dynamical system from partial observations depends crucially on the prescribed uncertainty of the model dynamics and of the observations. These are…

Computation · Statistics 2021-02-24 Tadeo Javier Cocucci , Manuel Pulido , Magdalena Lucini , Pierre Tandeo

The uncertainty principle is one of the key concepts in quantum theory. This principle states that it is not possible to measure two incompatible observables simultaneously and accurately. In quantum information theory, the uncertainty…

Quantum Physics · Physics 2020-06-25 Soroush Haseli , Saeed Haddadi , Mohammad Reza Pourkarimi

This thesis applies entropy as a model independent measure to address three research questions concerning financial time series. In the first study we apply transfer entropy to drawdowns and drawups in foreign exchange rates, to study their…

Statistical Finance · Quantitative Finance 2018-07-26 Stephan Schwill

We present a generic study on the information-theoretic security of multi-setting device-independent quantum key distribution protocols, i.e., ones that involve more than two measurements (or inputs) for each party to perform, and yield…

Quantum Physics · Physics 2023-12-12 Hong-Yi Su

The ability of many powerful machine learning algorithms to deal with large data sets without compromise is often hampered by computationally expensive linear algebra tasks, of which calculating the log determinant is a canonical example.…

Machine Learning · Statistics 2017-09-11 Diego Granziol , Stephen Roberts

Analyses in high energy physics aim to put the Standard Model---the commonly accepted theory---to test. For convincing conclusions, analysis methods are needed which offer an unambiguous comparison between data and theory while allowing…

High Energy Physics - Phenomenology · Physics 2018-07-19 Till Martini

In a ubiquitous $SU(2)$ dynamics, achieving the simultaneous optimal estimation of multiple parameters is significant but difficult. Using quantum control to optimize this $SU(2)$ coding unitary evolution is one of solutions. We propose a…

Quantum Physics · Physics 2022-02-09 Yu Yang , Shihao Ru , Min An , Yunlong Wang , Feiran Wang , Pei Zhang , Fuli Li

Problems of probabilistic inference and decision making under uncertainty commonly involve continuous random variables. Often these are discretized to a few points, to simplify assessments and computations. An alternative approximation is…

Artificial Intelligence · Computer Science 2013-03-08 William B. Poland , Ross D. Shachter

The Principle of Maximum Entropy is a rigorous technique for estimating an unknown distribution given partial information while simultaneously minimizing bias. However, an important requirement for applying the principle is that the…

Information Theory · Computer Science 2026-02-03 Kenneth Bogert , Matthew Kothe

Variations of phase-matching measurement-device-independent quantum key distribution (PM-MDI QKD) protocols have been investigated before, but it was recently discovered that this type of protocol (under the name of twin-field QKD) can beat…

Quantum Physics · Physics 2018-10-30 Jie Lin , Norbert Lütkenhaus

In classical and quantum information theory, operational quantities such as the amount of randomness that can be extracted from a given source or the amount of space needed to store given data are normally characterized by one of two…

Quantum Physics · Physics 2011-03-18 Marco Tomamichel , Roger Colbeck , Renato Renner

Security of practical continuous-variable quantum key distribution is addressed and a security analysis framework, which does not rely on phase-space symmetries of signal states and correlations, is developed. In a general…

Quantum Physics · Physics 2019-08-06 Vladyslav C. Usenko

For a closed-loop control system with a digital channel between the sensor and the controller, the notion of invariance entropy quantifies the smallest average rate of information above which a given compact subset of the state space can be…

Optimization and Control · Mathematics 2021-11-19 Mahendra Singh Tomar , Christoph Kawan , Majid Zamani

The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible constrained to match empirical data, for instance, feature expectations. We seek to generalize…

Information Theory · Computer Science 2022-05-30 Kenneth Bogert