Variational benchmarks for quantum many-body problems.

The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this work, we introduce a metric of variational accuracy, the V-score, obtained from the variational energy and its variance. We provide an extensive curated dataset of variational calculations of many-body quantum systems, identifying cases where state-of-the-art numerical approaches show limited accuracy and future algorithms or computational platforms, such as quantum computing, could provide improved accuracy.

Language models for quantum simulation.

A key challenge in the effort to simulate today's quantum computing devices is the ability to learn and encode the complex correlations that occur between qubits. Emerging technologies based on language models adopted from machine learning have shown unique abilities to learn quantum states. We highlight the contributions that language models are making in the effort to build quantum computers and discuss their future role in the race to quantum advantage.

Quantum process tomography with unsupervised learning and tensor networks.

The impressive pace of advance of quantum technology calls for robust and scalable techniques for the characterization and validation of quantum hardware. Quantum process tomography, the reconstruction of an unknown quantum channel from measurement data, remains the quintessential primitive to completely characterize quantum devices. However, due to the exponential scaling of the required data and classical post-processing, its range of applicability is typically restricted to one- and two-qubit gates.

Synthetic dataset of speckle images for fiber optic temperature sensor.

The published data correspond to images of simulated specklegrams, which result from the calculation of the modal interference that occurs in a multimode optical fiber. These have a characteristic pattern due to the constructive or destructive interference between the light modes depending on their phase differences. The specklegram contains valuable information since the propagation of the modes varies according to the influence of some external disturbances, and therefore, the speckle pattern changes.

Kagome qubit ice.

Topological phases of spin liquids with constrained disorder can host a kinetics of fractionalized excitations. However, spin-liquid phases with distinct kinetic regimes have proven difficult to observe experimentally. Here we present a realization of kagome spin ice in the superconducting qubits of a quantum annealer, and use it to demonstrate a field-induced kinetic crossover between spin-liquid phases.

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation.

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics.

Observation of topological phenomena in a programmable lattice of 1,800 qubits.

The work of Berezinskii, Kosterlitz and Thouless in the 1970s revealed exotic phases of matter governed by the topological properties of low-dimensional materials such as thin films of superfluids and superconductors. A hallmark of this phenomenon is the appearance and interaction of vortices and antivortices in an angular degree of freedom-typified by the classical XY model-owing to thermal fluctuations. In the two-dimensional Ising model this angular degree of freedom is absent in the classical case, but with the addition of a transverse field it can emerge from the interplay between frustration and quantum fluctuations.

Machine learning quantum phases of matter beyond the fermion sign problem.

State-of-the-art machine learning techniques promise to become a powerful tool in statistical mechanics via their capacity to distinguish different phases of matter in an automated way. Here we demonstrate that convolutional neural networks (CNN) can be optimized for quantum many-fermion systems such that they correctly identify and locate quantum phase transitions in such systems. Using auxiliary-field quantum Monte Carlo (QMC) simulations to sample the many-fermion system, we show that the Green's function holds sufficient information to allow for the distinction of different fermionic phases via a CNN.

Spinon Walk in Quantum Spin Ice.

We study a minimal model for the dynamics of spinons in quantum spin ice. The model captures the essential strong coupling between the spinon and the disordered background spins. We demonstrate that the spinon motion can be mapped to a random walk with an entropy-induced memory in imaginary time.

A two-dimensional spin liquid in quantum kagome ice.

Actively sought since the turn of the century, two-dimensional quantum spin liquids (QSLs) are exotic phases of matter where magnetic moments remain disordered even at zero temperature. Despite ongoing searches, QSLs remain elusive, due to a lack of concrete knowledge of the microscopic mechanisms that inhibit magnetic order in materials. Here we study a model for a broad class of frustrated magnetic rare-earth pyrochlore materials called quantum spin ices.

Definition and invariance properties of the complex degree of spatial coherence.

Within the framework of the phase-space representation of random electromagnetic fields provided by electromagnetic spatial coherence wavelets, and by using the Fresnel-Arago laws for interference and polarization as an analysis tool, the meaning of the spatial coherence-polarization tensor and its invariance under transformations is studied. The results give new insight into the definition and properties of the complex degree of spatial coherence by showing that its invariance is not required for properly describing the behavior of random electromagnetic fields within the scope of physically measurable quantities.

Spatial coherence wavelets and phase-space representation of diffraction.

The phase-space representation of the Fresnel-Fraunhofer diffraction of optical fields in any state of spatial coherence is based on the marginal power spectrum carried by the spatial coherence wavelets. Its structure is analyzed in terms of the classes of source pairs and the spot of the field, which is treated as the hologram of the map of classes. Negative values of the marginal power spectrum are interpreted as negative energies.

Phase-space representation and polarization domains of random electromagnetic fields.

The phase-space representation of stationary random electromagnetic fields is developed by using electromagnetic spatial coherence wavelets. The propagation of the field's power and states of spatial coherence and polarization results from correlations between the components of the field vectors at pairs of points in space. Polarization domains are theoretically predicted as the structure of the field polarization at the observation plane.

Young's experiment with electromagnetic spatial coherence wavelets.

We discuss Young's experiment with electromagnetic random fields at arbitrary states of coherence and polarization within the framework of the electric spatial coherence wavelets. The use of this approach for the electromagnetic spatial coherence theory allows us to envisage the existence of polarization domains inside the observation plane. We show that it is possible to locally control those polarization domains by means of the correlation properties of the electromagnetic wave.

Wavemeter based on moiré effect.

A moiré-effect-based procedure used to measure the wavelength of coherent sources is shown. Two plane waves, individually coherent but mutually incoherent and located at the entrance pupil of a Michelson interferometer with slightly tilted mirrors, generate a moiré pattern at the output plane. The spatial period of that moiré pattern is determined by the spatial frequencies of the interferograms superimposed on intensity.