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Multi-armed bandit algorithms provide solutions for sequential decision-making where learning takes place by interacting with the environment. In this work, we model a distributed optimization problem as a multi-agent kernelized multi-armed…

Machine Learning · Computer Science 2023-12-11 Ayush Rai , Shaoshuai Mou

We experimentally study the violation of the CGLMP inequality for entangled 2-qubit and 2-qutrit states with different degrees of entanglement using numerically optimized measurement settings. The qudits are encoded and manipulated in the…

Quantum Physics · Physics 2015-08-11 Sacha Schwarz , Bänz Bessire , André Stefanov

We experimentally realize the internal and external entanglement tradeoff, which is a new kind of entanglement monogamy relation different from that usually discussed. Using a source of twin photons, we find that the external entanglement…

Duality in the entanglement of identical particles manifests that entanglement in only one variable can be revealed at a time. We demonstrate this using polarization and orbital angular momentum (OAM) variables of indistinguishable photons…

Quantum Physics · Physics 2025-11-20 Nijil Lal , Sarika Mishra , Anju Rani , Anindya Banerji , Chithrabhanu Perumangattu , R. P. Singh

We investigate optimal discrimination between two projective single-qubit measurements in a scenario where the measurement can be performed only once. We consider general setting involving a tunable fraction of inconclusive outcomes and we…

Quantum Physics · Physics 2014-12-01 M. Mikova , M. Sedlak , I. Straka , M. Micuda , M. Ziman , M. Jezek , M. Dusek , J. Fiurasek

The inability to communicate poses a major challenge to coordination in multi-agent reinforcement learning (MARL). Prior work has explored correlating local policies via shared randomness, sometimes in the form of a correlation device, as a…

Multiagent Systems · Computer Science 2026-02-12 John Gardiner , Orlando Romero , Brendan Tivnan , Nicolò Dal Fabbro , George J. Pappas

We study an important variant of the stochastic multi-armed bandit (MAB) problem, which takes penalization into consideration. Instead of directly maximizing cumulative expected reward, we need to balance between the total reward and…

Machine Learning · Statistics 2022-11-16 Guanhua Fang , Ping Li , Gennady Samorodnitsky

Many real-world problems like Social Influence Maximization face the dilemma of choosing the best $K$ out of $N$ options at a given time instant. This setup can be modeled as a combinatorial bandit which chooses $K$ out of $N$ arms at each…

Machine Learning · Computer Science 2021-10-12 Mridul Agarwal , Vaneet Aggarwal , Christopher J. Quinn , Abhishek K. Umrawal

We address the problem of the persistence of entanglement of quantum light under mode transformations, where orthogonal modes define the parties between which quantum correlations can occur. Since the representation of a fixed photonic…

Quantum Physics · Physics 2019-12-30 Jan Sperling , Armando Perez-Leija , Kurt Busch , Christine Silberhorn

When an initially entangled pair of qubits undergoes local decoherence processes, there are a number of ways in which the original entanglement can spread throughout the multipartite system consisting of the two qubits and their…

Quantum imaging is an advanced method for microscopy or investigating the optical properties of materials or bio-medical inspections with high accuracy, low noise, and extremely low photo-damage. In previous work, we proposed a quantum…

Optics · Physics 2025-05-09 Mousume Samad , Maki Shimizu , Yasuto Hijikata

We study a structured multi-agent multi-armed bandit (MAMAB) problem in a dynamic environment. A graph reflects the information-sharing structure among agents, and the arms' reward distributions are piecewise-stationary with several unknown…

Machine Learning · Computer Science 2023-06-12 Xiaotong Cheng , Setareh Maghsudi

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…

Strategic behavior against sequential learning methods, such as "click framing" in real recommendation systems, have been widely observed. Motivated by such behavior we study the problem of combinatorial multi-armed bandits (CMAB) under…

Machine Learning · Computer Science 2021-11-22 Jing Dong , Ke Li , Shuai Li , Baoxiang Wang

Conventional polarimetry, including schemes leveraging entangled light, characterizes optical samples through linear transformations of polarization states. We introduce a two-photon probing approach in which both photons of an entangled…

Coulomb interactions between confined carriers remove degeneracies in the excitation spectra of quantum dots. This provides a which path information in the cascade decay of biexcitons, thus spoiling the energy-polarization entanglement of…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 F. Troiani , C. Tejedor

We investigate duality in entanglement of a bipartite multi-photon system generated from a coherent state of light. The system can exhibit polarization entanglement if the two parts are distinguished by their parity, or parity entanglement…

Quantum Physics · Physics 2016-08-17 Su-Yong Lee , Chang-Woo Lee , Pawel Kurzynski , Dagomir Kaszlikowski , Jaewan Kim

Entangling independent photons is not only of fundamental interest but also of crucial importance for quantum information science. Two-photon interference is a major method to entangle independent identical photons. If two photons are…

Quantum Physics · Physics 2015-01-27 Tian-Ming Zhao , Han Zhang , Jian Yang , Zi-Ru Sang , Xiao Jiang , Xiao-Hui Bao , Jian-Wei Pan

In recent years, analysis methods for quantum states based on randomized measurements have been investigated extensively. Still, in the experimental implementations these methods were typically used for characterizing strongly entangled…

Decision-making problems of sequential nature, where decisions made in the past may have an impact on the future, are used to model many practically important applications. In some real-world applications, feedback about a decision is…

Machine Learning · Computer Science 2023-03-02 Ronald C. van den Broek , Rik Litjens , Tobias Sagis , Luc Siecker , Nina Verbeeke , Pratik Gajane
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