English
Related papers

Related papers: Extreme Spin Squeezing from Deep Reinforcement Lea…

200 papers

In this paper, we investigate spin squeezing in a hybrid quantum system consisting of a Silicon-Vacancy (SiV) center ensemble coupled to a diamond acoustic waveguide via the strain interaction. Two sets of non-overlapping driving fields,…

Quantum Physics · Physics 2023-08-11 Zhen-Qiang Ren , Xian-Liang Lu , Ze-Liang Xiang

Entanglement can improve the measurement precision of quantum sensors beyond the shot noise limit. Neutral atoms, the basis of some of the most precise and accurate optical clocks and interferometers, do not naturally exhibit all-to-all…

Reinforcement learning (RL) has emerged as a promising paradigm for training reasoning-oriented models by leveraging rule-based reward signals. However, RL training typically tends to improve single-sample success rates (i.e., Pass@1) while…

Computation and Language · Computer Science 2026-04-21 Yifu Huo , Chenglong Wang , Ziming Zhu , Shunjie Xing , Peinan Feng , Tongran Liu , Qiaozhi He , Tianhua Zhou , Xiaojia Chang , Jingbo Zhu , Zhengtao Yu , Tong Xiao

Precise control of quantum systems is of fundamental importance for quantum device engineering, such as is needed in the fields of quantum information processing, high-resolution spectroscopy and quantum metrology. When scaling up the…

Squeezed spin states have important applications in quantum metrology and sensing. It has been shown by S{\o}rensen and M{\o}lmer [Phys. Rev. A 66, 022314(2002)] that an effective one-axis-twisting interaction can be realized in a cavity…

Quantum Physics · Physics 2019-05-08 Gang Liu , Ya-Ni Wang , Li-Fen Yan , Nian-Quan Jiang , Wei Xiong , Ming-Feng Wang

Nuclear magnetic resonance (NMR) experiments can reveal local properties in materials, but are often limited by the low signal-to-noise ratio. Spin squeezed states have an improved resolution below the Heisenberg limit in one of the spin…

Squeezing of collective atomic spins has been shown to improve the sensitivity of atomic clocks and magnetometers to levels significantly below the standard quantum limit. In most cases the requisite atom-atom entanglement has been…

Ultracold atoms in an ultrahigh-finesse optical cavity are a powerful platform to produce spin squeezing since photon of cavity mode can induce nonlinear spin-spin interaction and thus generate a one-axis twisting Hamiltonian…

Quantum Physics · Physics 2015-02-03 Caifeng Li , Jingtao Fan , Lixuan Yu , Gang Chen , Tian-Cai Zhang , Suotang Jia

In this work we study One Axis Twisting (OAT) spin squeezing for metrology in the presence of decoherence. We study Linbladian evolution in the presence of both T_1 and T_2 (longitudinal and transverse relaxation processes). We show that…

Quantum Physics · Physics 2024-03-22 Garry Goldstein

Quantum optimal control in the presence of decoherence is difficult, particularly when not all Hamiltonian parameters are known precisely, as in quantum sensing applications. In this context, maximizing the sensitivity of the system is the…

Quantum Physics · Physics 2026-01-19 Logan W. Cooke , Stefanie Czischek

We demonstrate the creation of entangled, spin-squeezed states using a collective, or joint, measurement and real-time feedback. The pseudospin state of an ensemble of $N= 5\times 10^4$ laser-cooled $^{87}$Rb atoms is deterministically…

Atomic Physics · Physics 2016-03-09 Kevin C. Cox , Graham P. Greve , Joshua M. Weiner , James K. Thompson

Quantum metrology experiments in atomic physics and quantum optics have demonstrated measurement accuracy beyond the shot-noise limit via multi-particle entanglement. At the same time, electron microscopy, an essential tool for…

Spin squeezing has been explored in atomic systems as a tool for quantum sensing, improving experimental sensitivity beyond the spin standard quantum limit for certain measurements. To optimize absolute metrological sensitivity, it is…

High Energy Physics - Phenomenology · Physics 2025-02-21 Eric Boyers , Garry Goldstein , Alexander O. Sushkov

Deep Reinforcement Learning (DRL) is applied to control a nonlinear, chaotic system governed by the one-dimensional Kuramoto-Sivashinsky (KS) equation. DRL uses reinforcement learning principles for the determination of optimal control…

We show that the two-axis counter twisting interaction squeezes a coherent spin state into three states of interest in quantum information, namely, the twin-Fock state, the equally-weighted superposition state, and the state that achieves…

Quantum Physics · Physics 2015-01-07 Emi Yukawa , Gerard Milburn , Masahito Ueda , Kae Nemoto

We predict that exploiting spin-orbit coupling in a harmonically trapped spinor quantum gas can lead to scaling of the optimal measurement precision beyond the Heisenberg scaling. We show that quadratic scaling with the number of atoms can…

Quantum Physics · Physics 2023-03-15 Karol Gietka , Helmut Ritsch

Building robust instruments capable of making interferometric measurements with precision beyond the standard quantum limit remains an important goal in many metrology laboratories. We describe here the basic concepts underlying spin…

Quantum Physics · Physics 2015-06-03 Hermann Uys , Michael J. Biercuk , Joe Britton , John J. Bollinger

Entanglement generation and detection are two of the most sought-after goals in the field of quantum control. Besides offering a means to probe some of the most peculiar and fundamental aspects of quantum mechanics, entanglement in…

Mesoscale and Nanoscale Physics · Physics 2011-11-29 M. S. Rudner , L. M. K. Vandersypen , V. Vuletic , L. S. Levitov

We demonstrate control of the electron number down to the last electron in tunable few-electron quantum dots defined in catalytically grown InAs nanowires. Using low temperature transport spectroscopy in the Coulomb blockade regime we…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 C. Fasth , A. Fuhrer , L. Samuelson , Vitaly N. Golovach , Daniel Loss

Deep reinforcement learning (DRL) has significantly advanced the field of combinatorial optimization (CO). However, its practicality is hindered by the necessity for a large number of reward evaluations, especially in scenarios involving…

Machine Learning · Computer Science 2024-07-18 Hyeonah Kim , Minsu Kim , Sungsoo Ahn , Jinkyoo Park