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Related papers: Multiple-shot labeling of quantum observables

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We study the problem of mapping an unknown mixed quantum state onto a known pure state without the use of unitary transformations. This is achieved with the help of sequential measurements of two non-commuting observables only. We show that…

Quantum Physics · Physics 2009-11-11 L. Roa , M. L. Ladron de Guevara , A. Delgado , A. Klimov

The simultaneous estimation of multiple unknown parameters is the most general scenario in quantum sensing. Quantum multi-parameter estimation theory provides fundamental bounds on the achievable precision of simultaneous estimation.…

Quantum Physics · Physics 2025-12-02 Yaoling Yang , Victor Montenegro , Abolfazl Bayat

Measuring entanglement is a demanding task that usually requires full tomography of a quantum system, involving a number of observables that grows exponentially with the number of parties. Recently, it was suggested that adding a single…

In a photonic realization of qubits the implementation of quantum logic is rather difficult due the extremely weak interaction on the few photon level. On the other hand, in these systems interference is available to process the quantum…

Quantum Physics · Physics 2015-06-26 John Calsamiglia , Norbert Lütkenhaus

Quantum information processing using linear optics is challenging due to the limited set of deterministic operations achievable without using complicated resource-intensive methods. While techniques such as the use of ancillary photons can…

Quantum Physics · Physics 2022-12-14 Dov Fields , Janos A. Bergou , Mark Hillery , Siddhartha Santra , Vladimir Malinovsky

Few-shot learning is challenging due to its very limited data and labels. Recent studies in big transfer (BiT) show that few-shot learning can greatly benefit from pretraining on large scale labeled dataset in a different domain. This paper…

Computer Vision and Pattern Recognition · Computer Science 2020-12-11 Suichan Li , Dongdong Chen , Yinpeng Chen , Lu Yuan , Lei Zhang , Qi Chu , Nenghai Yu

A quantum measurement can be described by a set of matrices, one for each possible outcome, which represents the positive operator-valued measure (POVM) of the sensor. Efficient protocols of POVM extraction for arbitrary sensors are…

We implement an all-optical setup demonstrating kernel-based quantum machine learning for two-dimensional classification problems. In this hybrid approach, kernel evaluations are outsourced to projective measurements on suitably designed…

In multi-task learning, a learner is given a collection of prediction tasks and needs to solve all of them. In contrast to previous work, which required that annotated training data is available for all tasks, we consider a new setting, in…

Machine Learning · Statistics 2017-06-09 Anastasia Pentina , Christoph H. Lampert

The advantages of using quantum states of light for object detection are often highlighted in schemes that use simultaneous and optimal measurements. Here, we describe a theoretical but experimentally realizable quantum illumination scheme…

Quantum Physics · Physics 2022-09-23 Hao Yang , Nigam Samantaray , John Jeffers

We consider the problem of correctly identifying a malfunctioning quantum device that forms part of a network of $N$ such devices, which can be considered as the quantum analogue of classical anomaly detection. In the case where the devices…

Quantum Physics · Physics 2024-10-10 M. Skotiniotis , Santiago Llorens , R. Hotz , J. Calsamiglia , R. Muñoz-Tapia

In this letter we consider the problem of certification of quantum measurements with an arbitrary number of outcomes. We propose a simple scheme for certifying any set of $d$-outcome projective measurements which do not share any common…

Quantum Physics · Physics 2022-10-26 Shubhayan Sarkar , Debashis Saha , Remigiusz Augusiak

In many a traditional physics textbook, a quantum measurement is defined as a projective measurement represented by a Hermitian operator. In quantum information theory, however, the concept of a measurement is dealt with in complete…

Quantum Physics · Physics 2015-11-06 Ravi Kunjwal , Chris Heunen , Tobias Fritz

Multi-label learning draws great interests in many real world applications. It is a highly costly task to assign many labels by the oracle for one instance. Meanwhile, it is also hard to build a good model without diagnosing discriminative…

Machine Learning · Computer Science 2019-04-16 Bo Du , Zengmao Wang , Lefei Zhang , Liangpei Zhang , Dacheng Tao

State discrimination is a useful test problem with which to clarify the power and limitations of different classes of measurement. We consider the problem of discriminating between given states of a bi-partite quantum system via sequential…

Quantum Physics · Physics 2017-09-25 Sarah Croke , Stephen M. Barnett , Graeme Weir

Quantum coherence is a fundamental resource that quantum technologies exploit to achieve performance beyond that of classical devices. A necessary prerequisite to achieve this advantage is the ability of measurement devices to detect…

Quantum measurements under realistic conditions reveal only partial information about a system. Yet, by performing sequential measurements on the same system, additional information can be accessed. We investigate this problem in the…

Quantum Physics · Physics 2025-10-23 Carles Roch I Carceller , Hanwool Lee , Jonatan Bohr Brask , Kieran Flatt , Joonwoo Bae

Entanglement is a key ingredient for quantum technologies and a fundamental signature of quantumness in a broad range of phenomena encompassing many-body physics, thermodynamics, cosmology, and life sciences. For arbitrary multiparticle…

Quantum Physics · Physics 2016-10-24 Marco Cianciaruso , Thomas R. Bromley , Gerardo Adesso

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

Large-scale multi-label classification datasets are commonly, and perhaps inevitably, partially annotated. That is, only a small subset of labels are annotated per sample. Different methods for handling the missing labels induce different…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Emanuel Ben-Baruch , Tal Ridnik , Itamar Friedman , Avi Ben-Cohen , Nadav Zamir , Asaf Noy , Lihi Zelnik-Manor