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The axion anti-quark nugget (A$\bar{\mathrm{Q}}$N) model was developed to explain in a natural way the asymmetry between matter and antimatter in Universe. In this hypothesis, a similitude between the dark and the visible components exists.…

High Energy Physics - Phenomenology · Physics 2024-07-10 Ionel Lazanu , Mihaela Parvu

In this paper, we consider non-coherent detection for molecular communication systems in the presence of inter-symbol-interference. In particular, we study non-coherent detectors based on memory-bits-based thresholds in order to achieve low…

Information Theory · Computer Science 2021-04-20 Xuewen Qian , Marco Di Renzo , Andrew W. Eckford

A sensitivity of the collider FCC-hh to anomalous quartic gauge couplings (aQGCs) of neutral bosons in lead-lead collisions is studied. Examining diphoton production, the bounds on aQGCs at $5\sigma$ and 95\% C.L. are obtained depending on…

High Energy Physics - Phenomenology · Physics 2025-08-12 S. C. İnan , A. V. Kisselev

World Health Organization (WHO) provides the guideline for managing the Particulate Matter (PM) level because when the PM level is higher, it threats the human health. For managing PM level, the procedure for measuring PM value is needed…

Machine Learning · Computer Science 2020-02-17 YeongHyeon Park , Won Seok Park , Yeong Beom Kim

The Compressed Baryonic Matter (CBM) experiment at the future Facility for Antiproton and Ion Research (FAIR) in Darmstadt is designed to investigate the properties of high-density QCD matter with multi-differential measurements of hadrons…

Nuclear Experiment · Physics 2021-06-01 Anna Senger , Peter Senger

Physical implementations of quantum information processing devices are generally not unique, and we are faced with the problem of choosing the best implementation. Here, we consider the sensitivity of quantum devices to variations in their…

Quantum Physics · Physics 2018-06-06 Mark J. Kandula , Pieter Kok

We employ so-called quantum kernel estimation to exploit complex quantum dynamics of solid-state nuclear magnetic resonance for machine learning. We propose to map an input to a feature space by input-dependent Hamiltonian evolution, and…

Quantum Physics · Physics 2022-03-14 Takeru Kusumoto , Kosuke Mitarai , Keisuke Fujii , Masahiro Kitagawa , Makoto Negoro

The pursuit of discovery in particle physics has always required study at the highest possible energies. Multi-TeV muon colliders, which have important advantages, offer unprecedented potential for investigating new physics beyond the…

High Energy Physics - Phenomenology · Physics 2023-07-26 S. Spor , M. Köksal

Quantum extreme learning machines (QELMs) are unconventional computing architectures that bear remarkable promise in both classical and quantum machine-learning tasks, such as the estimate of quantum state properties. However, the…

We propose here a proposal to connect neutrino and energy frontiers, by exploiting collimated muon beams for neutrino oscillations, which generate symmetric neutrino and antineutrino sources: $\mu^+\rightarrow e^+\,\bar{\nu}_{\mu}\,…

High Energy Physics - Phenomenology · Physics 2023-10-31 Alim Ruzi , Tianyi Yang , Dawei Fu , Sitian Qian , Leyun Gao , Qiang Li

The rapid advancements in quantum computing (QC) and machine learning (ML) have sparked significant interest, driving extensive exploration of quantum machine learning (QML) algorithms to address a wide range of complex challenges. The…

Quantum Physics · Physics 2025-05-27 Samuel Yen-Chi Chen , Huan-Hsin Tseng , Hsin-Yi Lin , Shinjae Yoo

Quantum Monte Carlo (QMC) is a family of powerful tools for addressing quantum many-body problems. However, its applications are often plagued by the fermionic sign problem. A promising strategy is to simulate an interaction without sign…

Nuclear Theory · Physics 2025-05-01 Jun Liu , Teng Wang , Bing-Nan Lu

The use of kernel functions is a common technique to extract important features from data sets. A quantum computer can be used to estimate kernel entries as transition amplitudes of unitary circuits. Quantum kernels exist that, subject to…

Network traffic anomaly detection is a critical cybersecurity challenge requiring robust solutions for complex Internet of Things (IoT) environments. We present a novel hybrid quantum-classical framework integrating an enhanced Quantum…

The development of edge computing places critical demands on energy-efficient model deployment for multiple-input multiple-output (MIMO) detection tasks. Deploying deep unfolding models such as PGD-Nets and ADMM-Nets into…

Machine Learning · Computer Science 2025-05-20 Zeyi Ren , Jingreng Lei , Yichen Jin , Ermo Hua , Qingfeng Lin , Chen Zhang , Bowen Zhou , Yik-Chung Wu

Quantum computing promises to speed up some of the most challenging problems in science and engineering. Quantum algorithms have been proposed showing theoretical advantages in applications ranging from chemistry to logistics optimization.…

Quantum Physics · Physics 2021-11-12 Niklas Heim , Atiyo Ghosh , Oleksandr Kyriienko , Vincent E. Elfving

The increasing number of cyber threats and rapidly evolving tactics, as well as the high volume of data in recent years, have caused classical machine learning, rules, and signature-based defence strategies to fail, rendering them unable to…

Machine Learning · Computer Science 2025-12-18 Siva Sai , Ishika Goyal , Shubham Sharma , Sri Harshita Manuri , Vinay Chamola , Rajkumar Buyya

Advances in astronomy are often driven by serendipitous discoveries. As survey astronomy continues to grow, the size and complexity of astronomical databases will increase, and the ability of astronomers to manually scour data and make such…

Instrumentation and Methods for Astrophysics · Physics 2019-01-09 Daniel Giles , Lucianne Walkowicz

We show that assuming fermion generations to be given by a gauge symmetry plus a certain Higgs mechanism for its breaking, the known empirical features of quark and lepton mixing can be largely explained, including in particular the fact…

High Energy Physics - Phenomenology · Physics 2011-09-13 J Bordes , HM Chan , ST Tsou

Dark matter (DM) remains one of the most compelling unresolved problems in fundamental physics, motivating the search for new detection approaches. We propose a network-based quantum sensor architecture to enhance sensitivity to ultralight…

Quantum Physics · Physics 2025-09-17 Adriel I. Santoso , Le Bin Ho
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