Multi Terminal Probabilistic Compressed Sensing

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Realand imaginary -time quantum state evolutions are crucial in physics and chemistry for exploring quantum dynamics, preparing ground states, and computing thermodynamic observables. On near -term devices, variational quantum time evolution is a promising ...

We study the drainage of a viscous liquid film coating the outside of a solid horizontal cylinder, where gravity acts vertically. We focus on the limit of large Ohnesorge numbers Oh, where inertia is negligible compared to viscous effects. We first study t ...

Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identificat ...

Approximate message passing (AMP) algorithms have become an important element of high-dimensional statistical inference, mostly due to their adaptability and concentration properties, the state evolution (SE) equations. This is demonstrated by the growing ...

Barocaloric (BC) materials provide cheaper and more energy efficient alternatives to traditional refrigerants. Some liquid alkanes were recently shown to exhibit a colossal BC effect, matching the entropy changes in commercial vapour-liquid refrigerants. D ...

Displaced communication, whereby individuals communicate regarding a subject that is not immediately present (spatially or temporally), is one of the key features of human language. It also occurs in a few animal species, most notably the honeybee, where t ...

The complex mechanics of porous and granular media play a significant role in various industrial processes and natural phenomena. As an example, understanding the mechanics of how failure occurs, localizes and propagates in porous brittle solids under vari ...

In this paper we study a fully connected planted spin glass named the planted XY model. Motivation for studying this system comes both from the spin glass field and the one of statistical inference where it models the angular synchronization problem. We de ...

Signal recovery under generative neural network priors has emerged as a promising direction in statistical inference and computational imaging. Theoretical analysis of reconstruction algorithms under generative priors is, however, challenging. For generati ...

A simple model to study subspace clustering is the high-dimensional k -Gaussian mixture model where the cluster means are sparse vectors. Here we provide an exact asymptotic characterization of the statistically optimal reconstruction error in this model i ...

The conditional mean is a fundamental and important quantity whose applications include the theories of estimation and rate-distortion. It is also notoriously difficult to work with. This paper establishes novel bounds on the differential entropy of the co ...

We photoexcite high-energy holon-doublon pairs as a way to alter the magnetic free energy landscape and resulting phase diagram of the frustrated honeycomb magnet ??-RuCl3. The pair recombination through multimagnon emission is tracked through the time evo ...

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

The accurate investigation of many geophysical phenomena via direct numerical simulations is computationally not possible nowadays due to the huge range of spatial and temporal scales to be resolved. Therefore advances in this field rely on the development ...

This thesis presents the first cavity quantum electrodynamics experiments performed with a degenerate gas of

^6

Li with strong atom-atom interactions. The first part of this manuscript describes the design and the building of the apparatus that has been e ...

Near-term quantum devices can be used to build quantum machine learning models, such as quantum kernel methods and quantum neural networks (QNN), to perform classification tasks. There have been many proposals on how to use variational quantum circuits as ...

Understanding how proteins fold into their native structure is a fundamental problem in biophysics, crucial for protein design. It has been hypothesized that the formation of a molten globule intermediate precedes folding to the native conformation of glob ...

Magnetic skyrmions are nanometric and non-trivial spin textures with non-zero topological charge. Their robustness against perturbations and the possibility to control them using external stimuli make them ideal candidates for future spintronic application ...

Quantum many-body dynamics generically result in increasing entanglement that eventually leads to thermalization of local observables. This makes the exact description of the dynamics complex despite the apparent simplicity of (high-temperature) thermal st ...

We introduce a novel hybrid algorithm to simulate the real-time evolution of quantum systems using parameterized quantum circuits. The method, named "projected - Variational Quantum Dynamics" (p-VQD) realizes an iterative, global projection of the exact ti ...

Multi Terminal Probabilistic Compressed Sensing

Chattez avec Graph Search

Variational quantum time evolution without the quantum geometric tensor

Stability of a liquid layer draining around a horizontal cylinder: Interplay of capillary and gravity forces

Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models

Graph-based approximate message passing iterations

Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

The evolution of behavioral cues and signaling in displaced communication

Modeling the mechanics and rheology of porous and granular media: an elastoplastic continuum approach

Planted XY model: Thermodynamics and inference

Multi-layer State Evolution Under Random Convolutional Design

Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap

Differential Entropy of the Conditional Expectation Under Additive Gaussian Noise

Nonequilibrium quasistationary spin disordered state in ?-RuCl3

A Functional Perspective on Information Measures

Exploiting Marginal Stability in Slow-Fast Quasilinear Dynamical Systems

Cavity Quantum Electrodynamics with strongly correlated fermions

Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

Molten globule-like transition state of protein barnase measured with calorimetric force spectroscopy

Skyrmion Control and Phase Transitions in Cu2OSeO3

Time-evolution of local information: Thermalization dynamics of local observables

An efficient quantum algorithm for the time evolution of parameterized circuits