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arXiv 2023年

作者： Gambardella, Giosuè Biagetti, Matteo Moretti, Chiara Sefusatti, Emiliano Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34151 Italy Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain Area Science Park Località Padriciano 99 Trieste34149 Italy Scuola Internazionale di Studi Superiori Avanzati via Bonomea 265 Trieste34136 Italy Istituto Nazionale di Astrofisica Osservatorio Astronomico di Trieste via Tiepolo 11 Trieste34143 Italy Istituto Nazionale di Fisica Nucleare Sezione di Trieste via Valerio 2 Trieste34127 Italy Centro Nazionale "High Performance Computer Big Data and Quantum Computing" Italy

We explore the reach of an analytical model at one-loop in Perturbation Theory (PT) to accurately describe measurements of the galaxy power spectrum from numerical simulations in redshift space. We consider the validity range in terms of three different diagnostics: 1) the goodness of fit;2) a figure-of-bias quantifying the error in recovering the fiducial value of a cosmological parameter;3) an internal consistency check of the theoretical model quantifying the running of the model parameters with the scale cut. We consider different sets of measurements corresponding to an increasing cumulative simulation volume in redshift space. For each volume we define a median value and the associated scatter for the largest wavenumber where the model is valid (the k-reach of the model). We find, as a rather general result, that the median value of the reach decreases with the simulation volume, as expected since the smaller statistical errors provide a more stringent test for the model. This is true for all the three definitions considered, with the one given in terms of the figure-of-bias providing the most stringent scale cut. More interestingly, we also find that the error associated with the k-reach value is quite large, with a significant probability of being as low as 0.1 ℎMpc−1 (or, more generally, up to 40% smaller than the median) for all the simulation volumes considered. We explore as well the additional information on the growth rate parameter encoded in the power spectrum hexadecapole, compared to the analysis of monopole and quadrupole, as a function of simulation volume. While our analysis is, in many ways, rather simplified, we find that the gain in the determination of the growth rate is quite small in absolute value and well within the statistical error on the corresponding figure of merit. Copyright © 2023, The Authors. All rights reserved.

关键词： Power spectrum

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Neural posterior estimation with guaranteed exact coverage: The ringdown of GW150914

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Physical Review D 2023年第4期108卷 044029-044029页

作者： Marco Crisostomi Kallol Dey Enrico Barausse Roberto Trotta SISSA Via Bonomea 265 34136 Trieste Italy and INFN Sezione di Trieste 34127 Trieste Italy IFPU—Institute for Fundamental Physics of the Universe Via Beirut 2 34014 Trieste Italy School of Physics Indian Institute of Science Education and Research Thiruvananthapuram Maruthamala PO Vithura Thiruvananthapuram 695551 Kerala India Physics Department Imperial College London Prince Consort Road SW7 2AZ London United Kingdom Centro Nazionale “High Performance Computer Big Data and Quantum Computing” Via Magnanelli 2 40033 Casalecchio di Reno (BO) Italy

We analyze the ringdown phase of the first detected black-hole merger, GW150914, using a simulation-based inference pipeline based on masked autoregressive flows. We obtain approximate marginal posterior distributions for the ringdown parameters, namely the mass, spin, and the amplitude and phases of the dominant mode and its first overtone. Thanks to the locally amortized nature of our method, we are able to calibrate our posteriors with injected simulations, producing posterior regions with guaranteed (i.e., exact) frequentist coverage of the true values. For GW150914, our calibrated posteriors provide only mild evidence (∼2σ) for the presence of an overtone, even if the ringdown is assumed to start at the peak of the amplitude.

关键词： Classical black holes General relativity Gravitational waves

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Online Job Scheduler for Fault-tolerant quantum Multiprogramming

arXiv

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arXiv 2025年

作者： Nishio, Shin Wakizaka, Ryo Sakuma, Daisuke Ueno, Yosuke Suzuki, Yasunari Graduate School of Science and Technology Keio University Kanagawa Yokohama Japan Department of Physics and Astronomy University College London Gower Street London United Kingdom Graduate School of Informatics Kyoto University Sakyo-ku Kyoto Japan Graduate School of Media and Governance Keio University Kanagawa Fujisawa Japan Center for Quantum Computing RIKEN Saitama Wako Japan Computer & Data Science Laboratories NTT Corporation Musashino Tokyo Japan

Fault-tolerant quantum computers are expected to be offered as cloud services due to their significant resource and infrastructure requirements. quantum multiprogramming, which runs multiple quantum jobs in parallel, is a promising approach to maximize the utilization of such systems. A key challenge in this setting is the need for an online scheduler capable of handling jobs submitted dynamically while other programs are already running. In this study, we formulate the online job scheduling problem for fault-tolerant quantum computing systems based on lattice surgery and propose an efficient scheduler to address it. To meet the responsiveness required in an online environment, our scheduler approximates lattice surgery programs, originally represented as polycubes, by using simpler cuboid representations. This approximation enables efficient scheduling while improving overall throughput. In addition, we incorporate a defragmentation mechanism into the scheduling process, demonstrating that it can further enhance QPU utilization. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

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Perturbative quantum simulation

arXiv

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arXiv 2021年

作者： Sun, Jinzhao Endo, Suguru Lin, Huiping Hayden, Patrick Vedral, Vlatko Yuan, Xiao Center on Frontiers of Computing Studies Peking University Beijing100871 China Clarendon Laboratory University of Oxford Parks Road OxfordOX1 3PU United Kingdom Quantum Advantage Research Beijing100080 China NTT Computer & Data Science Laboratories NTT Corporation Musashino Tokyo180-8585 Japan School of Computer Science Peking University Beijing100871 China Stanford Institute for Theoretical Physics Stanford University StanfordCA94305 United States Centre for Quantum Technologies National University of Singapore Singapore117543 Singapore

Approximation based on perturbation theory is the foundation for most of the quantitative predictions of quantum mechanics, whether in quantum many-body physics, chemistry, quantum field theory or other domains. quantum computing provides an alternative to the perturbation paradigm, yet state-of-the-art quantum processors with tens of noisy qubits are of limited practical utility. Here, we introduce perturbative quantum simulation, which combines the complementary strengths of the two approaches, enabling the solution of large practical quantum problems using limited noisy intermediate-scale quantum hardware. The use of a quantum processor eliminates the need to identify a solvable unperturbed Hamiltonian, while the introduction of perturbative coupling permits the quantum processor to simulate systems larger than the available number of physical qubits. We present an explicit perturbative expansion that mimics the Dyson series expansion and involves only local unitary operations, and show its optimality over other expansions under certain conditions. We numerically benchmark the method for interacting bosons, fermions, and quantum spins in different topologies, and study different physical phenomena, such as information propagation, charge-spin separation, and magnetism, on systems of up to 48 qubits only using an 8 + 1 qubit quantum hardware. We experimentally demonstrate our scheme on the IBM quantum cloud, verifying its noise robustness and illustrating its potential for benchmarking large quantum processors with smaller ones. Copyright © 2021, The Authors. All rights reserved.

关键词： Hamiltonians

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Optimizing Scene Classification: A Robust Approach with Transfer Learning and Automated Machine Learning Integration

Journal of Engineering Research

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Journal of Engineering Research 2025年

作者： Mohamed Hammad Samia A. Chelloug Samah AlShathri Ahmed A. Abd El-Latif Department of Information Technology Faculty of Computers and Information Menoufia University Shibin El Kom 32511 Egypt EIAS Data Science Lab College of Computer and Information Sciences and Center of Excellence in Quantum and Intelligent Computing Prince Sultan University Riyadh 11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom 32511 Egypt

Scene classification is a fundamental challenge in computer vision. Recognizing the complexity of this task is the aim of our study that addresses the need for accurate and robust scene classification by leveraging the capabilities of two widely recognized databases. The motivation behind this research lies in enhancing the accuracy and efficiency of scene classification systems. Therefore, our primary goal is to explore and implement a comprehensive methodology that combines transfer learning and automated machine learning techniques to achieve superior classification results. Our approach commences with a meticulous data loading process, followed by preprocessing steps to ensure the optimal representation of information. We have conducted class distribution analysis to understand the dataset's nuances. Subsequently, we have employed two key models: MobileNetV2 for transfer learning and a custom convolutional neural network (CNN) model featuring batch normalization. This diverse methodology aims to capture intricate patterns within the data. An innovative step of our approach involves employing Tree-based Pipeline Optimization Tool (TPOT), an automated machine learning tool, for model selection and hyperparameter tuning. The results underscore the effectiveness of our methodology, achieving impressive classification accuracy across diverse scenes. This research contributes valuable insights into the integration of transfer learning and automated machine learning for robust and accurate scene recognition, offering a comprehensive approach to address the complexities of scene classification.

关键词： CNN Scene Recognition TPOT MobileNetV2 Transfer Learning Machine Learning

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quantum error mitigation for rotation-symmetric bosonic codes with symmetry expansion

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Physical Review A 2025年第6期111卷 062402-062402页

作者： Suguru Endo Yasunari Suzuki Kento Tsubouchi Rui Asaoka Kaoru Yamamoto Yuichiro Matsuzaki Yuuki Tokunaga NTT Computer and Data Science Laboratories NTT Corporation Musashino 180-8585 Tokyo Japan Department of Applied Physics University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Research Center for Emerging Computing Technologies National Institute of Advanced Industrial Science and Technology (AIST) Central2 1-1-1 Umezono Tsukuba Ibaraki 305-8568 Japan NEC-AIST Quantum Technology Cooperative Research Laboratory National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki 305-8568 Japan

The rotation symmetric bosonic code (RSBC) is a unified framework of practical bosonic codes that have rotation symmetries, such as cat codes and binomial codes. While cat and binomial codes achieve the breakeven point in which the coherence time of the encoded qubits exceeds that of unencoded qubits, the state preparation fidelity needs to be improved for practical quantum computing. Concerning this problem, we investigate the framework of symmetry expansion, a class of quantum error mitigation that virtually projects the state onto the noise-free symmetric subspace by exploiting the system's intrinsic symmetries and postprocessing of measurement outcomes. Although symmetry expansion has been limited to error mitigation of quantum states immediately before measurement, we successfully generalize symmetry expansion for state preparation. Then, we consider two types of stabilization: photon number and phase stabilization. Photon number stabilization can be performed by leveraging the rotation operators. On the other hand, the phase errors can be suppressed via the extension towards phase direction by leveraging the recently proposed projective squeezing method. To implement our method, we use an ancilla qubit and a randomly generated controlled gate between the bosonic code states and the ancilla qubit. Our novel error mitigation method will significantly enhance computation accuracy in the near-term bosonic quantum computing.

关键词： Qubits

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Optimizing Multi-Hop quantum Communication using Bidirectional quantum Teleportation Protocol

arXiv

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arXiv 2025年

作者： Ikken, N. Kumar, P. Slaoui, A. Kar, B. Laamara, R. Ahl Almousa, M. El-Latif, A.A. Abd LPHE-Modeling and Simulation Faculty of Sciences Mohammed V University Rabat Morocco Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Centre of Physics and Mathematics CPM Faculty of Sciences Mohammed V University in Rabat Rabat Morocco EIAS Data Science Lab College of Computer and Information Sciences Center of Excellence in Quantum and Intelligent Computing Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom32511 Egypt

In this paper, we introduce a new method for Bidirectional quantum Teleportation called Bidirectional quantum Teleportation using the Modified Dijkstra Algorithm and quantum Walk (BQT-MDQW). This method uses different types of entangled states, such as the GHZ-Bell state, W-Bell state, and Cluster-Bell state, to improve quantum communication in multi-hop quantum wireless networks. We focus on the W-Bell state and compare the quantum Dijkstra algorithm with the classical Dijkstra method to see which one works better. We apply both versions to quantum and classical simulators, measuring their performance through fidelity, memory utilization, and throughput calculations. Our results show that the shortest path problem may be solved with significantly reduced computer complexity using the quantum Dijkstra algorithm based on quantum walks. The introduction of a quantum walk, which permits dynamic transitions between quantum channels and the effective exploration of quantum network states, is an important part of the protocol. Using the capacity of the quantum walk to adjust to changing quantum states, we also introduce a method for successfully identifying unitary matrices under varying quantum channels. The bidirectional teleportation structure of the protocol is designed to solve the multi-hop teleportation problem in quantum wireless networks. In addition, we present quantum Dijkstra’s algorithm, which uses quantum gates to significantly decrease computational complexity and solve the networking problem by building on the quantum walk framework. This method shows how quantum computing may be used to solve arbitrary optimization issues such as the shortest path problem. Finally, we present a novel multi-hop quantum teleportation system encompassing both unidirectional and bidirectional communication, as introduced in the quantum Dijkstra algorithm system. This system significantly enhances communication in quantum networks by enabling efficient and reliable information

关键词： quantum channel

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An implementation of nDGP gravity in Pinocchio

arXiv

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arXiv 2023年

作者： Song, Yanling Hu, Bin Ruan, Cheng-Zong Moretti, Chiara Monaco, Pierluigi Center for Gravitation and Cosmology College of Physical Science and Technology Yangzhou University Yangzhou225009 China Institute for Frontier in Astronomy and Astrophysics Beijing Normal University Beijing102206 China Department of Astronomy Beijing Normal University Beijing100875 China Institute of Theoretical Astrophysics University of Oslo Oslo0315 Norway SISSA - International School for Advanced Studies Via Bonomea 265 Trieste34136 Italy Centro Nazionale "High Performance Computer Big Data and Quantum Computing" Italy INAF Osservatorio Astronomico di Trieste Via Tiepolo 11 TriesteI-34143 Italy IFPU Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34014 Italy Dipartimento di Fisica Universitá di Trieste Sezione di Astronomia via Tiepolo 11 TriesteI-34143 Italy INFN Sezione di Trieste Italy

In this paper we investigate dark matter structure formation in the normal branch of the Dvali-Gabadadze-Porrati (nDGP) model using the PINOCCHIO algorithm. We first present 2nd order Lagrangian perturbation theory for the nDGP model, which shows that the 1st- and 2nd-order growth functions in nDGP are larger than those in ΛCDM. We then examine the dynamics of ellipsoidal collapse in nDGP, which is accelerated compared to ΛCDM due to enhanced gravitational interactions. Running the nDGP-PINOCCHIO code with a box size of 512 Mpc h−1 and 10243 particles, we analyze the statistical properties of the output halo catalogs, including the halo power spectrum and halo mass function. The calibrated PINOCCHIO halo power spectrum agrees with N-body simulations within 5% in the comoving wavenumber range k −1) at redshift z = 0. The agreement is extended to smaller scales for higher redshifts. For the cumulative halo mass function, the agreement between N-body and PINOCCHIO is also within the simulation scatter. Copyright © 2023, The Authors. All rights reserved.

关键词： Power spectrum

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A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem

A Decomposition Algorithm for the Sparse Generalized Eigenva...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Ganzhao Yuan Li Shen Wei-Shi Zheng Center for Quantum Computing Peng Cheng Laboratory Tencent AI Lab School of Data and Computer Science Sun Yat-sen University

ISBN: (纸本)9781728132945

The sparse generalized eigenvalue problem arises in a number of standard and modern statistical learning models, including sparse principal component analysis, sparse Fisher discriminant analysis, and sparse canonical correlation analysis. However, this problem is difficult to solve s-ince it is NP-hard. In this paper, we consider a new effective decomposition method to tackle this problem. Specifically, we use random or/and swapping strategies to find a working set and perform global combinatorial search over the small subset of variables. We consider a bisection search method and a coordinate descent method for solving the quadratic fractional programming subproblem. In addition, we provide some theoretical analysis for the proposed method. Our experiments on synthetic data and real-world data have shown that our method significantly and consistently outperforms existing solutions in term of accuracy.

关键词： descent method working set eigenvalues Search methods synthetic data Nondeterministic polynomial-time hard decomposition Binary search Theoretical analysis discriminant analysis mathematical programming

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Anharmonic Effects on the Squeezing of Axion Perturbations

arXiv

引用

arXiv 2023年

作者： Danieli, Valentina Kobayashi, Takeshi Bartolo, Nicola Matarrese, Sabino Viel, Matteo SISSA International School for Advanced Studies Via Bonomea 265 Trieste34136 Italy INFN - Sezione di Trieste via Valerio 2 Trieste34127 Italy IFPU Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34014 Italy Kobayashi-Maskawa Institute for the Origin of Particles the Universe Nagoya University Nagoya464-8602 Japan Dipartimento di Fisica e Astronomia "G. Galilei" Università degl Studi di Padova Via Francesco Marzolo 8 Padova35131 Italy INFN - Sezione di Padova Via Francesco Marzolo 8 Padova35131 Italy INAF - Osservatorio Astronomico di Padova Vicolo dell’Osservatorio 5 Padova35122 Italy Gran Sasso Science Institute Viale F. Crispi 7 L’AquilaI-67100 Italy INAF - Osservatorio Astronomico di Trieste Via G.B. Tiepolo 11 TriesteI-34131 Italy ICSC - Italian Research Center on High Performance Computing Big Data and Quantum Computing Italy

It is assumed in standard cosmology that the Universe underwent a period of inflation in its earliest phase, providing the seeds for structure formation through vacuum fluctuations of the inflaton scalar field. These fluctuations get stretched by the quasi-exponential expansion of the Universe and become squeezed. The aim of this paper is to deepen the understanding of the squeezing process, considering the effect of self-interactions. Axion-like particles can provide a useful setup to study this effect. Specifically we focus on the consequences that a non-trivial evolution of the background axion field has on the squeezing of the perturbations. We follow the evolution of the axion’s fluctuation modes from the horizon exit during inflation to the radiation-dominated epoch. We compute Bogoliubov coefficients and squeezing parameters, which are linked to the axion particle number and isocurvature perturbation. We find that the quantum mechanical particle production and the squeezing of the perturbations are enhanced, if one accounts for anharmonic effects, i.e., the effect of higher order terms in the potential. This effect becomes particularly strong towards the hilltop of the potential. Copyright © 2023, The Authors. All rights reserved.

关键词： quantum theory

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