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Quasiminimal structures play an important role in non-elementary categoricity. In this paper we explore possibilities of constructing quasiminimal models of a given first-order theory. We present several constructions with increasing…

Logic · Mathematics 2015-10-21 Levon Haykazyan

Quantum self-interference enables the counterfactual transmission of information, whereby the transmitted bits involve no particles traveling through the channel. In this work, we show how counterfactuality can be realized even when the…

Quantum Physics · Physics 2023-10-18 Vinod N. Rao , Anindita Banerjee , R. Srikanth

In this paper, we discuss content and context for quantum properties. We give some examples of why quantum properties are problematic: they depend on the context in a non-trivial way. We then connect this difficulty with properties to the…

Quantum Physics · Physics 2021-09-01 J. Acacio de Barros , Federico Holik , Décio Krause

The coherence of an individual quantum state can be meaningfully discussed only when referring to a preferred basis. This arbitrariness can however be lifted when considering sets of quantum states. Here we introduce the concept of set…

Quantum Physics · Physics 2021-06-08 Sébastien Designolle , Roope Uola , Kimmo Luoma , Nicolas Brunner

Information theory has its particles, bits and qubits, just as physics has electrons and photons. However, in physics we have a special category of objects with no clear counterparts in information theory: quasiparticles. They are…

Quantum Physics · Physics 2024-05-24 M. Pawlowski , A. Winter

Quantum state discrimination depicts the general progress of extracting classical information from quantum systems. We show that quantum state discrimination can be realized in a device-independent scenario using tools of self-testing…

Quantum Physics · Physics 2024-01-25 Xinyu Qiu , Lin Chen

The quasiprobability representation of quantum states addresses two main concerns, the identification of nonclassical features and the decomposition of the density operator. While the former aspect is a main focus of current research, the…

Quantum Physics · Physics 2018-10-26 J. Sperling , I. A. Walmsley

Unravelling hidden patterns in datasets is a classical problem with many potential applications. In this paper, we present a challenge whose objective is to discover nonlinear relationships in noisy cloud of points. If a set of point…

Machine Learning · Statistics 2018-05-31 Terry Lyons , Imanol Perez Arribas

To address semi-supervised learning from both labeled and unlabeled data, we present a novel meta-learning scheme. We particularly consider that labeled and unlabeled data share disjoint ground truth label sets, which can be seen tasks like…

Computer Vision and Pattern Recognition · Computer Science 2020-08-26 Yun-Chun Chen , Chao-Te Chou , Yu-Chiang Frank Wang

We point out an earlier unnoticed implication of quantum indistinguishability, namely, a property which we call `dualism' that characterizes the entanglement of two identical particles (say, two ions of the same species) -- a feature which…

Quantum Physics · Physics 2013-04-05 S. Bose , D. Home

Self-training is an effective approach to semi-supervised learning. The key idea is to let the learner itself iteratively generate "pseudo-supervision" for unlabeled instances based on its current hypothesis. In combination with consistency…

Machine Learning · Statistics 2021-11-05 Julian Lienen , Eyke Hüllermeier

It is shown that quantum systems of identical particles can be treated as if they were different when they are in well differentiated states. This simplifying assumption allows the consideration of quantum systems isolated from the rest of…

Quantum Physics · Physics 2009-03-12 Alberto C. de la Torre , Hector O. Martin

Let $G$ be an additive group of order $v$. A $k$-element subset $D$ of $G$ is called a $(v, k, \lambda, t)$-almost difference set if the expressions $gh^{-1}$, for $g$ and $h$ in $D$, represent $t$ of the non-identity elements in $G$…

Combinatorics · Mathematics 2014-09-02 Kathleen Nowak

Partial-label learning is a kind of weakly-supervised learning with inexact labels, where for each training example, we are given a set of candidate labels instead of only one true label. Recently, various approaches on partial-label…

Machine Learning · Computer Science 2022-08-30 Zhenguo Wu , Jiaqi Lv , Masashi Sugiyama

Pairs of states, or "boxes" are the basic objects in the resource theory of asymmetric distinguishability (Wang and Wilde, 2019), where free operations are arbitrary quantum channels that are applied to both states. From this point of view,…

Quantum Physics · Physics 2021-07-28 Gergely Bunth , Péter Vrana

Quantum mechanics provides a statistical description about nature, and thus would be incomplete if its statistical predictions could not be accounted for by some realistic models with hidden variables. There are, however, two powerful…

Quantum Physics · Physics 2012-10-04 Xi Kong , Mingjun Shi , Fazhan Shi , Pengfei Wang , Pu Huang , Qi Zhang , Chenyong Ju , Changkui Duan , Sixia Yu , Jiangfeng Du

The formulation of quantum theory does not comply with the notion of objective existence of elementary particles. Objective existence independent of observation implies the distinguishability of elementary particles. In other words: If…

Quantum Physics · Physics 2007-11-26 Bilha Nissenson

Standard quantum mechanics undeniably violates the notion of separability that classical physics accustomed us to consider as valid. By relating the phenomenon of quantum nonseparability to the all-important concept of potentiality, we…

Quantum Physics · Physics 2008-11-25 Vassilios Karakostas

The relational approach to quantum states asserts that the physical description of quantum systems is always relative to something or someone. In relational quantum mechanics (RQM) it is relative to other quantum systems, in the…

Quantum Physics · Physics 2021-07-09 Časlav Brukner

The cost and scarcity of fully supervised labels in statistical machine learning encourage using partially labeled data for model validation as a cheaper and more accessible alternative. Effectively collecting and leveraging weakly…

Machine Learning · Statistics 2022-06-16 Maxime Cauchois , John Duchi