Article
Astronomy & Astrophysics
Samuel Goldman, Nima Lashkari, Robert G. Leigh, Mudassir Moosa
Summary: The exact renormalization group is a powerful tool for studying field theories, and by applying it to the flow of wave functionals, a large class of continuous unitary networks can be obtained, including a class of Gaussian continuous multiscale renormalization Ansatze. These generalized wave functional ERG schemes allow for modifications of the dispersion relation, significantly altering the entanglement structure of the ultraviolet states. This construction demonstrates that cMERA can be derived from a more fundamental microscopic principle, opening up avenues for exploring cMERA beyond the free field regime.
Article
Astronomy & Astrophysics
Ivan Kukuljan
Summary: A truncated Hamiltonian method is used to study nonequilibrium real time dynamics in the Schwinger model, revealing novel phenomena such as dynamical horizon violation and correlated meson pairs. These results provide insights into the nonequilibrium behavior in (1+1)D quantum electrodynamics.
Article
Astronomy & Astrophysics
M. Costa, G. Panagopoulos, H. Panagopoulos, G. Spanoudes
Summary: The study focuses on the Gluino-Glue operator in the context of Supersymmetric N = 1 Yang-Mills theory. It utilizes a Gauge-Invariant Renormalization Scheme to calculate Green's functions and conversion factors, allowing for analysis of low-lying bound states via numerical simulations.
Article
Physics, Multidisciplinary
Doruk Efe Goekmen, Zohar Ringel, Sebastian D. Huber, Maciej Koch-Janusz
Summary: This research introduces an algorithm utilizing state-of-the-art machine-learning results to identify the most relevant operators describing properties of complex physical systems, advancing the field of interpretable applications of machine learning. By demonstrating its effectiveness on an interacting model, the study shows the potential of this algorithm in automated theory building.
PHYSICAL REVIEW LETTERS
(2021)
Article
Physics, Fluids & Plasmas
Doruk Efe Gokmen, Zohar Ringel, Sebastian D. Huber, Maciej Koch-Janusz
Summary: Real-space mutual information (RSMI) is an important quantity for finding coarse-grained descriptions of physical systems, and a breakthrough in machine learning has introduced variational lower bounds parametrized by neural networks. The combination of these techniques allows for the unsupervised extraction of relevant degrees of freedom efficiently. The study also demonstrates the recovery of information from partial input data and the identification of emergent symmetries, with applications to both equilibrium and nonequilibrium systems.
Article
Physics, Multidisciplinary
Xun Gao, Eric R. Anschuetz, Sheng-Tao Wang, J. Ignacio Cirac, Mikhail D. Lukin
Summary: This research demonstrates the powerful resource of generative modeling derived from quantum correlations. It provides an unconditional proof that quantum-inspired models surpass conventional Bayesian networks in expressive power and verifies their applicability through numerical tests. This has significant implications for designing quantum machine learning protocols and improving classical algorithms using ideas from quantum foundations.
Article
Materials Science, Multidisciplinary
Anas Abdelwahab, Goekmen Polat, Eric Jeckelmann
Summary: The study investigates asymmetric two-leg Hubbard ladders with different on-site interactions Uy and hoppings ty on each leg using the density-matrix renormalization group method and exact diagonalizations. It is found that the pairing effect observed in symmetric ladders is still present even after introducing the leg asymmetry. When studying the pairing effect, one-band Hubbard ladder models are better described as one-dimensional correlated two-band models rather than sublattices of higher-dimensional systems. The asymmetric Hubbard ladder serves as a simple model to study pairing in the crossover regime between charge-transfer and Mott insulators.
Article
Astronomy & Astrophysics
Mudit Rai, Lisong Chen, Daniel Boyanovsky
Summary: In this study, a dynamical resummation method (DRM) was implemented to investigate the time evolution of infrared dressing in nongauge theories. The analysis revealed that the anomalous dimension Delta is solely determined by the slope of the spectral density at threshold, independent of ultraviolet behavior. The time evolution of entanglement entropy, obtained through tracing over unobserved massless quanta, was shown to be infrared finite and described the flow of information from single particles to multiparticle dressed states.
Article
Quantum Science & Technology
Irene Lopez Gutierrez, Christian B. Mend
Summary: A promising application of neural-network quantum states is to describe the time dynamics of many-body quantum systems. In this study, we employ neural-network quantum states to approximate the implicit midpoint rule method, which preserves the symplectic form of Hamiltonian dynamics. The results show that this approach achieves comparable accuracy to the stochastic configuration method without the need to compute the (pseudo-)inverse of a matrix.
Article
Physics, Multidisciplinary
Dariusz Prorok
Summary: A statistical (thermal) model was used to analyze the hadron yields in central nucleus-nucleus collisions at top RHIC and LHC energies, incorporating a more general form of least squares test statistic and including light nuclei data. Due to limited data, a toy model was constructed with correlation coefficients as free parameters, leading to speculative conclusions within the limitations.
CHINESE JOURNAL OF PHYSICS
(2021)
Article
Physics, Multidisciplinary
Shuping Li, Xinsheng Lu, Jianfeng Li
Summary: Using MFCCA method, this paper examines the cross-correlations between market interest rate, treasury yields and policy interest rate, revealing the presence of multifractal properties and sensitivity to external shocks. In the long term, small fluctuations are persistent while large fluctuations are generally antipersistent. The results suggest that cross-correlation scaling exponents are sensitive to external shocks.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Materials Science, Multidisciplinary
Ravi Teja Ponnaganti, Matthieu Mambrini, Didier Poilblanc
Summary: The implementation of the hard-core-dimer Hilbert space in cold-Rydberg-atom simulators provides a route for investigating the real-time dynamics of dimer liquids. By considering an initial resonating valence bond state on the square lattice, the researchers were able to study the critical Coulomb phase with algebraic and dipolar correlations. They used the representation of this state as a special point in a broader manifold of SU(2)-symmetric, translationally invariant, projected entangled pair states (PEPS) to compute its nonequilibrium dynamics. The results show that projecting the time evolution onto the PEPS manifold remains accurate at small timescales, and the state evolves within a PEPS submanifold characterized by a U(1) gauge symmetry, indicating the stability of the Coulomb phase under this unitary evolution.
Article
Materials Science, Multidisciplinary
Diego L. B. Ferreira, Thiago O. Maciel, Reinaldo O. Vianna, Fernando Iemini
Summary: We studied the ground state properties of the one-dimensional extended Hubbard model at half filling from the perspective of its particle reduced density matrix. Our analysis of quantum correlations and coherence showed that different properties exhibit complementary behaviors and provide a qualitative view of the model's phase diagram. In particular, we found a transition in the entanglement spectrum signaling a change in the pairing ordering in the superconducting region.
Article
Physics, Fluids & Plasmas
Anastasiia Gorbunova, Carlo Pagani, Guillaume Balarac, Leonie Canet, Vincent Rossetto
Summary: We conducted numerical simulations to study the spatiotemporal two-point correlation function of passively advected scalar fields in three-dimensional homogeneous isotropic turbulence. Our aim was to test analytical results obtained using functional renormalization group (FRG). The simulations showed decay of Eulerian correlations of the scalar as a Gaussian at small time delays and a predicted crossover to exponential decay at large time delays, which could not be observed due to numerical noise. We accurately confirmed FRG results by introducing finite time correlations in the synthetic velocity field and studying the crossover between two regimes.
PHYSICAL REVIEW FLUIDS
(2021)
Article
Astronomy & Astrophysics
Damiano Anselmi
Summary: This paper reconsiders the Lee-Wick (LW) models and compares them to models with purely virtual particles. The paper argues against the LW premise and presents a method to partially remove LW ghosts while preserving physical particles. However, the method has issues with general covariance and may not be applicable to quantum gravity.
Article
Physics, Multidisciplinary
Marek Gluza, Thomas Schweigler, Mohammadamin Tajik, Joao Sabino, Federica Cataldini, Frederik S. Moller, Si-Cong Ji, Bernhard Rauer, Joerg Schmiedmayer, Jens Eisert, Spyros Sotiriadis
Summary: We investigate two mechanisms leading to memory loss of non-Gaussian correlations in an isolated quantum system. One mechanism is based on spatial scrambling, resulting in locally Gaussian steady states. The other mechanism, called 'canonical transmutation', is based on the mixing of canonically conjugate fields, resulting in relative Gaussianity even at finite system sizes and times. Through analyzing experimental data, we find that canonical transmutation, rather than spatial scrambling, is responsible for Gaussification in the experiment. The study shows that both mechanisms reveal Gaussian correlations that are already present at the initial time, but practically inaccessible.
Article
Physics, Multidisciplinary
Julius Wallnoefer, Frederik Hahn, Mustafa Guendogan, Jasminder S. Sidhu, Fabian Wiesner, Nathan Walk, Jens Eisert, Janik Wolters
Summary: This manuscript simulates the performance of memory-assisted quantum key distribution (MA-QKD) schemes using satellite-based orbiting quantum memories. The results suggest that implementing global quantum networks with near-term devices is feasible. A global quantum repeater network using satellite-based links is advantageous for long-distance communication compared to fiber-based networks. The simulation toolbox used in this work allows for exploring various strategies and parameters, providing insights into achievable quantum key distribution rates for different satellite and ground station geometries.
COMMUNICATIONS PHYSICS
(2022)
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.
Article
Optics
Nicole Yunger Halpern, Naga B. T. Kothakonda, Jonas Haferkamp, Anthony Munson, Jens Eisert, Philippe Faist
Summary: This research explores the application of quantum complexity and resource theory in many-body systems, confirming the definition of a resource theory of uncomplexity. The study introduces two operational tasks and two monotones that decrease complexity.
