Modified parallel code-phase search for acquisition in presence of sign transition

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A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Michaël Unser, Pakshal Narendra Bohra, Pol del Aguila Pla

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

2023

How to Find Molecules with Long-lasting Charge Migration?

Jiri Vanicek, Nikolay Golubev, Alan Scheidegger

Under certain conditions, the ionization of a molecule may create a superposition of electronic states, leading to ultrafast electron dynamics. If controlled, this motion could be used in attochemistry applications, but it has been shown that the decoheren ...

SWISS CHEMICAL SOC2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Optimizing Quantum Compilers: Efficient and Effective Algorithms

Fereshte Mozafari Ghoraba

Quantum computing has made significant progress in recent years, with Google and IBM releasing quantum computers with 72 and 50 qubits, respectively. Google has also achieved quantum supremacy with its 54-qubit device, and IBM has announced the release of ...

EPFL2023

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Ali Garjani

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

IEEE COMPUTER SOC2023

A low-temperature prismatic slip instability in Mg understood using machine learning potentials

William Curtin, Xin Liu, Binglun Yin

Prismatic slip in magnesium at temperatures T

PERGAMON-ELSEVIER SCIENCE LTD2023

Fast correlation function calculator A high-performance pair-counting toolkit

Cheng Zhao

Context. A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented.Aims. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simula ...

EDP SCIENCES S A2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

arXiv2023

Dissipative Solitons and Switching Waves in Dispersion-Modulated Kerr Cavities

Tobias Kippenberg, Rui Ning Wang, Johann Emmeram Riemensberger, Miles Henry Anderson, Alexey Tikan, Aleksandr Tusnin, Alisa Davydova

We theoretically and experimentally investigate the formation of dissipative coherent structures in Kerr nonlinear optical microresonators, whose spectrum encompasses an integrated dispersion that exceeds the cavity free-spectral range. We are able to acce ...

American Physical Society2023

Programmable frequency-bin quantum states in a nano-engineered silicon device

Matteo Galli, Marco Clementi

Frequency-bin qubits get the best of time-bin and dual-rail encodings, but require external modulators and pulse shapers to build arbitrary states. Here, instead, the authors work directly on-chip by controlling the interference of biphoton amplitudes gene ...

Nature Portfolio2023

Fully solvable finite simplex lattices with open boundaries in arbitrary dimensions

Fabrizio Minganti

Finite simplex lattice models are used in different branches of science, e.g., in condensed-matter physics, when studying frustrated magnetic systems and non-Hermitian localization phenomena; or in chemistry, when describing experiments with mixtures. An n ...

Amer Physical Soc2023