Editorial Material
Physics, Multidisciplinary
Lothar Wondraczek
Summary: Two-dimensional model glasses exhibit low-frequency vibrational density of states related to the quasilocalized dynamics of string-like objects, providing an explanation for the universal boson peak feature in glasses.
Article
Chemistry, Physical
Wenbo Dong, Vahideh Alizadeh, Jan Blasius, Luke Wylie, Leonard Dick, Zhijie Fan, Barbara Kirchner
Summary: Several amino-acid based imidazolium ILs were investigated using ab initio molecular dynamics (AIMD) with full polarization. Different charge scheme methods were analyzed to predict dipole moments, highlighting the importance of anion and cation separately. The local interactions of monopole-dipole electrostatic interactions were measured, showing no preferential alignment. IR and Raman spectra were analyzed to differentiate between anion and cation components.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Computer Science, Artificial Intelligence
Joey Tianyi Zhou, Le Zhang, Du Jiawei, Xi Peng, Zhiwen Fang, Zhe Xiao, Hongyuan Zhu
Summary: This paper proposes a method to address the issue of imbalanced data distribution in crowd counting datasets by introducing locality-aware data partition and augmentation. The proposed method demonstrates its effectiveness and superiority through extensive experiments.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Astronomy & Astrophysics
Nuha Chreim, Christian Hoelbling, Christian Zielinski
Summary: This article provides an explicit proof for the locality of staggered overlap operators, covering both Adams' original two flavor construction and a single flavor version. Similar to Neuberger's operator, an admissibility condition for the gauge fields is required.
Article
Multidisciplinary Sciences
Till Jonas Frederick Johann, Ugo Marzolino
Summary: Entanglement, a strong quantum correlation, has five inequivalent approaches for indistinguishable particles, with three of them proven to be incompatible with any locality notion defined by identifying subsystems through local operators and requiring entanglement to represent correlations between subsets of operators.
SCIENTIFIC REPORTS
(2021)
Article
Computer Science, Artificial Intelligence
Huawen Liu, Wenhua Zhou, Hong Zhang, Gang Li, Shichao Zhang, Xuelong Li
Summary: This research introduces a novel hash bit reduction schema to derive shorter binary codes, effectively reducing the number of hash bits and improving the retrieval performance of LSH.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Quantum Science & Technology
Xiaoyun He, Anqi Zhang, Shengmei Zhao
Summary: A quantum algorithm named QLPP is proposed for efficient dimensionality reduction through locality preserving projection. Compared to the classical LPP algorithm, QLPP shows a polynomial speedup when dealing with large-scale data sets.
QUANTUM INFORMATION PROCESSING
(2022)
Article
Mechanics
Andre N. Souza, Tyler Lutz, Glenn R. Flierl
Summary: We analyze a class of stochastic advection problems by conditionally averaging the passive tracer equation with respect to a given flow state. We obtain expressions for the turbulent diffusivity as a function of the flow statistics spectrum. The ensemble average turbulent flux is expressed as a linear operator that acts on the ensemble average of the tracer.
JOURNAL OF FLUID MECHANICS
(2023)
Article
Mechanics
Xingyu Guo, Chen-Te Ma
Summary: This study extends the measure of entanglement in pure states to three qubits and discovers the difference between entanglement measure and non-locality. A new diagnosis method for quantum entanglement, the generalized R-matrix or correlation matrix, is proposed and supported by experimental evidence showing the discrepancy between the numerical results and expectations.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Multidisciplinary Sciences
C. A. Bedard
Summary: The paper discusses various approaches to locally describing quantum systems and their formal equivalence, as well as quantifying the cost of such descriptions through the number of qubits involved. The study shows that the exponential growth of degrees of freedom in describing a small system within a large Universe is expected. Additionally, the investigation also includes structures that supplement the universal wave function.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2021)
Article
Automation & Control Systems
A. K. Devika, Rakesh Kumar Sanodiya, Babita Roslind Jose, Jimson Mathew
Summary: Traditional machine learning methods only focus on learning tasks. This research proposes a novel strategy for unsupervised visual domain adaptation, which uses knowledge gained from one domain to adapt to another. The proposed approach utilizes input data features to induce information transfer between different domains.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Astronomy & Astrophysics
Abhijit B. Bendre, Kandaswamy Subramanian
Summary: In this study, we use singular value decomposition to directly fit the time-series data of the mean turbulent electromotive force (E) versus the large-scale magnetic field (B) from a galactic dynamo simulation. By finding the non-local dependence of (E) on (B) through the convolution kernel K-ij, we calculate the turbulent transport coefficients and show the significance of including non-locality for capturing their amplitudes. We also find that the higher order corrections to the standard transport coefficients are small in this case.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2022)
Article
Engineering, Mechanical
Emma Lejeune, Peerasait Prachaseree
Summary: Living systems have an amazing ability to sense, store, and respond to mechanical stimuli, and there is increasing interest in designing engineered systems to replicate this functionality. This work focuses on the question of whether mechanical systems can transform mechanical information into sensor readouts to meet the requirements for a locality sensitive hash function. The findings suggest that different mechanical systems vary in their effectiveness in performing this task, and this research serves as a starting point for future investigation into designing and optimizing mechanical systems for conveying mechanical information for downstream computing.
EXTREME MECHANICS LETTERS
(2023)
Article
Biochemical Research Methods
Giulio Ermanno Pibiri, Yoshihiro Shibuya, Antoine Limasset
Summary: Minimal perfect hashing is the problem of mapping a static set of distinct keys into an address space bijectively. In practice, the intrinsic relationships between input keys can lower the complexity of the hash function. This study introduces a new type of locality-preserving minimal perfect hash function designed for consecutively extracted k-mers from a collection of strings. Experimental results demonstrate that the functions built with this method can be smaller and faster to query than the most efficient ones in the literature.
Article
Automation & Control Systems
Xuelong Li, Qi Wang, Feiping Nie, Mulin Chen
Summary: Linear discriminant analysis (LDA) is a well-known technique for supervised dimensionality reduction, but real-world data seldom satisfy its assumptions. To handle data with complex distributions, a new method called locality adaptive discriminant analysis (LADA) is proposed, which finds principal projection directions without imposing assumptions on data distribution and explores data relationships while minimizing noise.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Multidisciplinary Sciences
Abhinav Deshpande, Arthur Mehta, Trevor Vincent, Nicolas Quesada, Marcel Hinsche, Marios Ioannou, Lars Madsen, Jonathan Lavoie, Haoyu Qi, Jens Eisert, Dominik Hangleiter, Bill Fefferman, Ish Dhand
Summary: This research work makes progress in improving both the theoretical evidence and experimental prospects for demonstrating a quantum computational advantage in photonics. They propose a programmable QCA architecture called high-dimensional GBS and show that high-dimensional GBS experiments outperform particular algorithms for simulating GBS.
Article
Quantum Science & Technology
Alexander Jahn, Zoltan Zimboras, Jens Eisert
Summary: The study of critical quantum many-body systems through conformal field theory is an important field in modern quantum physics. Certain conformal field theory models have a duality with gravity theories in higher dimensions. In order to reproduce this duality, many discrete models based on tensor networks have been proposed. This study shows that the symmetries of these models are suitable for approximating conformal field theory states, introducing the concept of quasi-periodic conformal field theory.
Article
Physics, Multidisciplinary
Zahra Baghali Khanian, Manabendra Nath Bera, Arnau Riera, Maciej Lewenstein, Andreas Winter
Summary: We extend the previous results on quantum thermodynamics to the case of multiple non-commuting charges and develop a resource theory of thermodynamics for asymptotically many non-interacting systems. The phase diagram of the system is formed by associating the vector of expected charge values and entropy with every state. Our key result is the Asymptotic Equivalence Theorem, which connects the equivalence classes of states under asymptotic charge-conserving unitaries with the points on the phase diagram. Using the phase diagram, we analyze the first and second laws of thermodynamics and provide insights into the storage of different charges in physically separate batteries.
ANNALES HENRI POINCARE
(2023)
Article
Physics, Mathematical
J. Haferkamp, F. Montealegre-Mora, M. Heinrich, J. Eisert, D. Gross, I Roth
Summary: Many quantum information protocols require the use of random unitaries, and unitary t-designs are often used as an alternative to Haar-random unitaries. In this work, we explore the non-Clifford resources needed to break the limitation of only being able to implement up to 3-designs with Clifford operations. We find that injecting a certain number of non-Clifford gates into a random Clifford circuit can produce an epsilon-approximate t-design, regardless of the system size. We also derive new bounds on the convergence time of random Clifford circuits to the t-th moment of the uniform distribution on the Clifford group.
COMMUNICATIONS IN MATHEMATICAL PHYSICS
(2023)
Article
Physics, Multidisciplinary
M. Hinsche, M. Ioannou, A. Nietner, J. Haferkamp, Y. Quek, D. Hangleiter, J. -P. Seifert, J. Eisert, R. Sweke
Summary: The task of learning a probability distribution from samples is common in the natural sciences. This study extensively characterizes the learnability of output distributions from local quantum circuits. The results show that Clifford circuit output distributions are efficiently learnable, but the injection of a single T gate makes density modeling task difficult. Additionally, generative modeling of universal quantum circuits is hard for any learning algorithm, classical or quantum, indicating no quantum advantage for probabilistic modeling tasks.
PHYSICAL REVIEW LETTERS
(2023)
Article
Multidisciplinary Sciences
Mohammadamin Tajik, Marek Gluza, Nicolas Sebe, Philipp Schuettelkopf, Federica Cataldini, Joao Sabino, Frederik Moller, Si-Cong Ji, Sebastian Erne, Giacomo Guarnieri, Spyros Sotiriadis, Jens Eisert, Jorg Schmiedmayer
Summary: We investigate signal propagation in a quantum field simulator of the Klein-Gordon model using two strongly coupled parallel one-dimensional quasi-condensates. We observe the propagation of correlations along sharp light-cone fronts by measuring local phononic fields after a quench. The curved propagation fronts and reflection at sharp edges are observed when the local atomic density is inhomogeneous. By comparing the data with theoretical predictions, we find agreement with curved geodesics of an inhomogeneous metric.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Quantum Science & Technology
Johannes Jakob Meyer, Marian Mularski, Elies Gil-Fuster, Antonio Anna Mele, Francesco Arzani, Alissa Wilms, Jens Eisert
Summary: Variational quantum machine learning is a widely studied application of near-term quantum computers. This work explores how symmetries of the learning problem can be used to construct quantum learning models with symmetrical outcomes. By utilizing tools from representation theory, a standard gateset can be transformed into an equivariant gateset that respects the symmetries of the problem. The proposed methods are benchmarked on toy problems and show a substantial increase in generalization performance.
Review
Physics, Multidisciplinary
Dominik Hangleiter, Jens Eisert
Summary: Quantum random sampling is the main proposal to demonstrate the computational advantage of quantum computers over classical computers. Recent large-scale implementations of quantum random sampling have possibly surpassed the capabilities of existing classical hardware for simulation. This review comprehensively discusses the theoretical basis and practical implementation of quantum random sampling, as well as its classical simulation, and explores open questions and potential applications in the field.
REVIEWS OF MODERN PHYSICS
(2023)
Article
Multidisciplinary Sciences
J. Helsen, M. Ioannou, J. Kitzinger, E. Onorati, A. H. Werner, J. Eisert, I. Roth
Summary: With quantum computing devices becoming more complex, there is a need for tools that can provide precise diagnostic information about quantum operations. The authors propose a new approach that uses random gate sequences and native measurements followed by classical post-processing to estimate various gate set properties. They also discuss applications for optimizing quantum gates and diagnosing cross-talk. This research is important for the development and improvement of quantum computing devices.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
F. H. B. Somhorst, R. van der Meer, M. Correa Anguita, R. Schadow, H. J. Snijders, M. de Goede, B. Kassenberg, P. Venderbosch, C. Taballione, J. P. Epping, H. H. van den Vlekkert, J. Timmerhuis, J. F. F. Bulmer, J. Lugani, I. A. Walmsley, P. W. H. Pinkse, J. Eisert, N. Walk, J. J. Renema
Summary: This study demonstrates that in a unitarily evolving system, single-mode measurements can converge to a thermal state using photons in an integrated optical interferometer. The resolution to the paradox between unitary evolution and the second law of thermodynamics is the recognition that the global unitary evolution of a multi-partite quantum state causes local subsystems to evolve towards maximum-entropy states. The experiment utilizes a programmable integrated quantum photonic processor to manipulate quantum states and shows the potential of photonic devices for simulating non-Gaussian states.
NATURE COMMUNICATIONS
(2023)
Article
Quantum Science & Technology
Ingo Roth, Jadwiga Wilkens, Dominik Hangleiter, Jens Eisert
Summary: Extracting tomographic information about quantum states is crucial in developing high-precision quantum devices. This study shows that by exploiting the low-rank structure of quantum states, a scalable 'blind' tomography scheme can be achieved with a computationally efficient post-processing algorithm. The efficiency of the scheme is further improved by utilizing the sparse structure of the calibrations.
Article
Optics
Niklas Pirnay, Ryan Sweke, Jens Eisert, Jean-Pierre Seifert
Summary: Density modeling is the task of learning an unknown probability density function from samples, and it is a central problem in unsupervised machine learning. This research demonstrates that fault-tolerant quantum computers can offer a superpolynomial advantage over classical learning algorithms in a specific density modeling problem, assuming standard cryptographic assumptions. The results also provide insights for future distribution learning separations between quantum and classical learning algorithms, including the relationship between hardness results in supervised learning and distribution learning.
Article
Materials Science, Multidisciplinary
Philipp Schmoll, Augustine Kshetrimayum, Jan Naumann, Jens Eisert, Yasir Iqbal
Summary: We investigate the ground state of the spin S = 1/2 Heisenberg antiferromagnet on the shuriken lattice, and found that a valence bond crystal with resonances over length six loops emerges as the ground state, yielding the lowest reported estimate of the ground state energy for this model. We also study the model in the presence of an external magnetic field and find the emergence of 0, 1/3, and 2/3 magnetization plateaus, with the 1/3 and 2/3 plateau states respecting translation and point group symmetries and featuring loop-four plaquette resonances.
Article
Quantum Science & Technology
Konstantin Tiurev, Peter-Jan H. S. Derks, Joschka Roffe, Jens Eisert, Jan-Michael Reiner
Summary: This study develops topological surface codes adapted to known noise structures and investigates their performance with specific decoders. Experimental results show that this approach significantly improves error thresholds and reduces failure rates. Furthermore, the study reveals the importance of tailored surface codes in correcting local noise.
Article
Quantum Science & Technology
Jarn de Jong, Frederik Hahn, Jens Eisert, Nathan Walk, Anna Pappa
Summary: Sharing multi-partite quantum entanglement allows for diverse secure communication tasks. In this work, an anonymous CKA protocol for three parties is proposed, implemented in a highly practical network setting using a linear cluster state among quantum nodes. The protocol protects the identities of the participants and contributes to identifying feasible quantum communication tasks for network architectures beyond point-to-point.
