202 citations · 2.5k across the 68 of their papers we have counts for
60 papers · 1 filter
The computational two-way quantum capacity
Johannes Jakob Meyer, Jacopo Rizzo, Asad Raza +3
Quantum channel capacities are fundamental to quantum information theory. Their definition, however, does not limit the computational resources of sender and receiver. In this work…
Prospects for quantum advantage in machine learning from the representability of functions
Sergi Masot-Llima, Elies Gil-Fuster, Carlos Bravo-Prieto +2
Demonstrating quantum advantage in machine learning tasks requires navigating a complex landscape of proposed models and algorithms. To bring clarity to this search, we introduce a…
How hard is it to verify a classical shadow?
Georgios Karaiskos, Dorian Rudolph, Johannes Jakob Meyer +2
Classical shadows are succinct classical representations of quantum states which allow one to encode a set of properties P of a quantum state rho, while only requiring measurements…
Artificial intelligence for representing and characterizing quantum systems
Yuxuan Du, Yan Zhu, Yuan-Hang Zhang +8
Efficient characterization of large-scale quantum systems, especially those produced by quantum analog simulators and megaquop quantum computers, poses a central challenge in quant…
Computational relative entropy
Johannes Jakob Meyer, Asad Raza, Jacopo Rizzo +3
Our capacity to process information depends on the computational power at our disposal. Information theory captures our ability to distinguish states or communicate messages when i…
Quantum reinforcement learning of classical rare dynamics: Enhancement by intrinsic Fourier features
Alissa Wilms, Laura Ohff, Andrea Skolik +3
Rare events are essential for understanding the behavior of non-equilibrium and industrial systems. It is of ongoing interest to develop methods for effectively searching for rare…
A complete theory of the Clifford commutant
Lennart Bittel, Jens Eisert, Lorenzo Leone +2
The Clifford group plays a central role in quantum information science. It is the building block for many error-correcting schemes and matches the first three moments of the Haar m…
Towards efficient quantum algorithms for diffusion probabilistic models
Yunfei Wang, Ruoxi Jiang, Yingda Fan +4
A diffusion probabilistic model (DPM) is a generative model renowned for its ability to produce high-quality outputs in tasks such as image and audio generation. However, training…
Opportunities and limitations of explaining quantum machine learning
Elies Gil-Fuster, Jonas R. Naujoks, Grégoire Montavon +3
A common trait of many machine learning models is that it is often difficult to understand and explain what caused the model to produce the given output. While the explainability o…
Learning complexity gradually in quantum machine learning models
Erik Recio-Armengol, Franz J. Schreiber, Jens Eisert +1
Quantum machine learning is an emergent field that continues to draw significant interest for its potential to offer improvements over classical algorithms in certain areas. Howeve…
Simulating quantum chaos without chaos
Andi Gu, Yihui Quek, Susanne Yelin +2
Quantum chaos is a quantum many-body phenomenon that is associated with a number of intricate properties, such as level repulsion in energy spectra or distinct scalings of out-of-t…
Stability of emergent time periodicity in a few-body interacting system
Steve Campbell, Jens Eisert, Giacomo Guarnieri
We examine the onset and resilience of emergent time periodicity in a few-body all-to-all interacting Lipkin-Meshkov-Glick model, where one of the constituents is locally in contac…
Optimal trace-distance bounds for free-fermionic states: Testing and improved tomography
Lennart Bittel, Antonio Anna Mele, Jens Eisert +1
Free-fermionic states, also known as fermionic Gaussian states, represent an important class of quantum states ubiquitous in physics. They are uniquely and efficiently described by…
Artificially intelligent Maxwell's demon for optimal control of open quantum systems
Paolo Andrea Erdman, Robert Czupryniak, Bibek Bhandari +4
Feedback control of open quantum systems is of fundamental importance for practical applications in various contexts, ranging from quantum computation to quantum error correction a…
Full classification of Pauli Lie algebras
Gerard Aguilar, Simon Cichy, Jens Eisert +1
Lie groups, and therefore Lie algebras, are fundamental structures in quantum physics that determine the space of possible trajectories of evolving systems. However, classification…
Tomography of parametrized quantum states
Franz J. Schreiber, Jens Eisert, Johannes Jakob Meyer
Characterizing quantum systems is a fundamental task that enables the development of quantum technologies. Various approaches, ranging from full tomography to instances of classica…
Complexity of geometrically local stoquastic Hamiltonians
Asad Raza, Jens Eisert, Alex B. Grilo
The QMA-completeness of the local Hamiltonian problem is a landmark result of the field of Hamiltonian complexity that studies the computational complexity of problems in quantum m…
Single-shot quantum machine learning
Erik Recio-Armengol, Jens Eisert, Johannes Jakob Meyer
Quantum machine learning aims to improve learning methods through the use of quantum computers. If it is to ever realize its potential, many obstacles need to be overcome. A partic…
Online learning of quantum processes
Asad Raza, Matthias C. Caro, Jens Eisert +1
Among recent insights into learning quantum states, online learning and shadow tomography procedures are notable for their ability to accurately predict expectation values even of…
Learning quantum states of continuous variable systems
Francesco Anna Mele, Antonio Anna Mele, Lennart Bittel +5
Quantum state tomography, aimed at deriving a classical description of an unknown state from measurement data, is a fundamental task in quantum physics. In this work, we analyse th…
PAC-learning of free-fermionic states is NP-hard
Lennart Bittel, Antonio A. Mele, Jens Eisert +1
Free-fermionic states, also known as matchgates or Gaussian states, are a fundamental class of quantum states due to their efficient classical simulability and their crucial role a…
Noise-induced shallow circuits and absence of barren plateaus
Antonio Anna Mele, Armando Angrisani, Soumik Ghosh +4
Motivated by realistic hardware considerations of the pre-fault-tolerant era, we comprehensively study the impact of uncorrected noise on quantum circuits. We first show that in th…
Learning fermionic correlations by evolving with random translationally invariant Hamiltonians
Janek Denzler, Antonio Anna Mele, Ellen Derbyshire +2
Schemes of classical shadows have been developed to facilitate the read-out of digital quantum devices, but similar tools for analog quantum simulators are scarce and experimentall…
On the expressivity of embedding quantum kernels
Elies Gil-Fuster, Jens Eisert, Vedran Dunjko
One of the most natural connections between quantum and classical machine learning has been established in the context of kernel methods. Kernel methods rely on kernels, which are…