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Bayesian approaches developed to solve the optimal design of sequential experiments are mathematically elegant but computationally challenging. Recently, techniques using amortization have been proposed to make these Bayesian approaches…

机器学习 · 计算机科学 2022-06-20 Tom Blau , Edwin V. Bonilla , Iadine Chades , Amir Dezfouli

Quantum channels enable the implementation of communication tasks inaccessible to their classical counterparts. The most famous example is the distribution of secret key. However, in the absence of quantum repeaters, the rate at which these…

As the number of qubits in a sensor increases, the complexity of designing and controlling the quantum circuits grows exponentially. Manually optimizing these circuits becomes infeasible. Optimizing entanglement distribution in large-scale…

量子物理 · 物理学 2025-09-01 Laxmisha Ashok Attisara , Sathish Kumar

The derivation of ultimate limits to communication over certain quantum repeater networks have provided extremely valuable benchmarks for assessing near-term quantum communication protocols. However, these bounds are usually derived in the…

量子物理 · 物理学 2022-06-02 Riccardo Laurenza , Nathan Walk , Jens Eisert , Stefano Pirandola

Feasible distribution of quantum entanglement over long distances remains a fundamental step towards quantum secure communication and quantum network implementations. Quantum repeater nodes based on quantum memories promise to overcome…

量子物理 · 物理学 2021-05-17 Michał Lipka , Mateusz Mazelanik , Michał Parniak

We propose a distributed deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is based on the deep Q-network, a convolutional neural network trained…

机器学习 · 计算机科学 2015-10-16 Hao Yi Ong , Kevin Chavez , Augustus Hong

We study the estimation of risk-sensitive policies in reinforcement learning problems defined by a Markov Decision Process (MDPs) whose state and action spaces are countably finite. Prior efforts are predominately afflicted by computational…

机器学习 · 统计学 2020-03-02 Junyu Zhang , Amrit Singh Bedi , Mengdi Wang , Alec Koppel

Learning probability distribution is an essential framework in classical learning theory. As a counterpart, quantum state learning has spurred the exploration of quantum machine learning theory. However, as dimensionality increases,…

量子物理 · 物理学 2023-10-13 Mingrui Jing , Geng Liu , Hongbin Ren , Xin Wang

The ability to distribute secret keys between two parties with information-theoretic security, that is, regardless of the capacities of a malevolent eavesdropper, is one of the most celebrated results in the field of quantum information…

量子物理 · 物理学 2015-09-01 Eleni Diamanti , Anthony Leverrier

Realization of a globe-spanning quantum network is a current worldwide goal, where near and long term implementations will benefit from connectivity between platforms optimized for specific tasks. Towards this goal, a quantum network…

Reformulating the history matching problem from a least-square mathematical optimization problem into a Markov Decision Process introduces a method in which reinforcement learning can be utilized to solve the problem. This method provides a…

机器学习 · 计算机科学 2022-12-26 Omar S. Alolayan , Abdullah O. Alomar , John R. Williams

We present numerical simulations of deep reinforcement learning on a measurement-based quantum processor--a time-multiplexed optical circuit sampled by photon-number-resolving detection--and find it generates squeezed cat states with an…

量子物理 · 物理学 2026-05-13 Amanuel Anteneh , Olivier Pfister

Deep reinforcement learning has been recognized as an efficient technique to design optimal strategies for different complex systems without prior knowledge of the control landscape. To achieve a fast and precise control for quantum…

量子物理 · 物理学 2021-01-05 Hailan Ma , Daoyi Dong , Steven X. Ding , Chunlin Chen

The stabilization of quantum states is a fundamental problem for realizing various quantum technologies. Measurement-based-feedback strategies have demonstrated powerful performance, and the construction of quantum control signals using…

系统与控制 · 电气工程与系统科学 2026-04-10 Chunxiang Song , Yanan Liu , Daoyi Dong , Hidehiro Yonezawa

For secure practical systems, quantum key distribution (QKD) must provide high key rates over long distances. Time-entanglement-based QKD promises to increase the secret key rate and distribution distances compared to other QKD…

信息论 · 计算机科学 2023-03-06 Lara Dolecek , Emina Soljanin

We study reinforcement learning from human feedback in general Markov decision processes, where agents learn from trajectory-level preference comparisons. A central challenge in this setting is to design algorithms that select informative…

机器学习 · 计算机科学 2025-12-05 Andreas Schlaginhaufen , Reda Ouhamma , Maryam Kamgarpour

Quantum Machine Learning (QML) is considered to be one of the most promising applications of near term quantum devices. However, the optimization of quantum machine learning models presents numerous challenges arising from the imperfections…

机器学习 · 计算机科学 2022-05-17 Owen Lockwood

Long-distance quantum communication via distant pairs of entangled quantum bits (qubits) is the first step towards more secure message transmission and distributed quantum computing. To date, the most promising proposals require quantum…

量子物理 · 物理学 2009-11-13 O. A. Collins , S. D. Jenkins , A. Kuzmich , T. A. B. Kennedy

We study quantum repeater chains in which entangled links between neighbouring nodes are created through heralded entanglement generation and adjacent links are swapped as soon as possible. Since heralded entanglement generation attempts…

量子物理 · 物理学 2026-02-17 Jeroen Grimbergen , Stav Haldar , Alvaro Gomez Inesta , Stephanie Wehner

The use of quantum scissors, as candidates for non-deterministic amplifiers, in continuous-variable quantum key distribution systems is investigated. Such devices rely on single-photon sources for their operation and as such, they do not…

量子物理 · 物理学 2020-07-16 Masoud Ghalaii , Carlo Ottaviani , Rupesh Kumar , Stefano Pirandola , Mohsen Razavi