256 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Southern CaliforniaUS18 papers
- California Institute of TechnologyUS5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Infrared Processing and Analysis CenterUS4 papers
- ETH ZurichCH3 papers
- Flatiron Institute3 papers
- Technical University of MunichDE3 papers
- Université Grenoble AlpesFR3 papers
- Université Paris CitéFR3 papers
- Université Paris Sciences et LettresFR3 papers
- University of British ColumbiaCA3 papers
- University of CambridgeGB3 papers
8 papers · 1 filter
Quantum Fourier Transform using Dynamic Circuits
Elisa Bäumer, Vinay Tripathi, Alireza Seif +2
In dynamic quantum circuits, classical information from mid-circuit measurements is fed forward during circuit execution. This emerging capability of quantum computers confers nume…
A Post-Training Approach for Mitigating Overfitting in Quantum Convolutional Neural Networks
Aakash Ravindra Shinde, Charu Jain, Amir Kalev
Quantum convolutional neural network (QCNN), an early application for quantum computers in the NISQ era, has been consistently proven successful as a machine learning (ML) algorith…
Localization transition induced by programmable disorder
Jaime L. C. da C. Filho, Zoe Gonzalez Izquierdo, Andreia Saguia +3
We investigate the occurrence of many-body localization (MBL) on a spin-1/2 transverse-field Ising model defined on a Chimera connectivity graph with random exchange interactions a…
Quantum algorithm for time-dependent Hamiltonian simulation by permutation expansion
Yi-Hsiang Chen, Amir Kalev, Itay Hen
We present a quantum algorithm for the dynamical simulation of time-dependent Hamiltonians. Our method involves expanding the interaction-picture Hamiltonian as a sum of generalize…
NetKet: A Machine Learning Toolkit for Many-Body Quantum Systems
Giuseppe Carleo, Kenny Choo, Damian Hofmann +15
We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and…
Noise suppression via generalized-Markovian processes
Jeffrey Marshall, Lorenzo Campos Venuti, Paolo Zanardi
It is by now well established that noise itself can be useful for performing quantum information processing tasks. We present results which show how one can effectively reduce the…
Quantum coherence generating power, maximally abelian subalgebras, and Grassmannian Geometry
Paolo Zanardi, Lorenzo Campos Venuti
We establish a direct connection between the power of a unitary map in -dimensions () to generate quantum coherence and the geometry of the set of maximal…
Modular Quantum Information Processing by Dissipation
Jeffrey Marshall, Lorenzo Campos Venuti, Paolo Zanardi
Dissipation can be used as a resource to control and simulate quantum systems. We discuss a modular model based on fast dissipation capable of performing universal quantum computat…