18 citations · 22 across the 18 of their papers we have counts for
22 papers
A provable quantum advantage for approximate optimization via decoded quantum interferometry
Maximilian J. Kramer, Elies Gil-Fuster, Benjamin D. M. Jones +2
Decoded quantum interferometry (DQI) is a novel paradigm for tackling approximate optimization problems on quantum computers. This framework comes with strong performance guarantee…
Adaptivity is all you need: Optimal stabilizer learning using just single-copy measurements
L. Bittel, J. Eisert, W. Gong +2
Stabilizer states are central to quantum computing, underlying quantum error correction, benchmarking, and efficient classical simulation. Yet their learnability exhibits a strikin…
Testing quantum Gaussianity with constant sample complexity
Mahtab Yaghubi Rad, Ricard Puig, Saksham Hassanandani +4
Efficiently testing whether a quantum state possesses a given structure is both a fundamental and a practical task in quantum information. Among the most important structured famil…
The power of oracle access: Optimal sample and query complexity of the abelian state hidden subgroup problem
Yuhan Liu, Jose Carrasco, Jens Eisert +1
In the quest to identify further quantum algorithms exhibiting superpolynomial speed-ups, a recurring theme is that the complexity of a problem is largely shaped by the input acces…
Efficient learning of Clifford disentanglers and typical -doped unitaries with exponentially more gates
Gerard Aguilar, Sofiene Jerbi, Jens Eisert +1
Highly entangled and highly non-stabilizer quantum states need not be hard to learn. We give efficient algorithms for testing and recovering hidden tensor-product structure in unkn…
Cautious optimism for deep parameterized quantum circuits
Marie Kempkes, Elies Gil-Fuster, Carlos Bravo-Prieto +5
A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it remains unclear how their performa…
Approximate sampling from decoded quantum interferometry via Markov chain Monte Carlo methods
Elies Gil-Fuster, Matan Ninio, Lennart Bittel +4
Optimization problems are among the leading candidates for industrially relevant quantum advantage. Decoded quantum interferometry (DQI) has been proposed to tackle approximate opt…
Provable learning separation for predicting time-evolution of quantum many-body systems
Rahul Bandyopadhyay, Riccardo Molteni, Jens Eisert +2
Given that quantum computers are naturally suited to simulate the behavior of quantum many-body systems, an immediate question arises: can one formulate physically motivated quantu…
Optimal stellar rank approximation of squeezed cat states with photon catalysis
Julian K. Nauth, Nathan Walk, Ananga M. Datta +4
Non-Gaussian quantum states and operations constitute essential resources for achieving quantum computational advantage and enabling quantum error correction in bosonic platforms.…
Optimal algorithmic complexity of inference in quantum kernel methods
Elies Gil-Fuster, Seongwook Shin, Sofiene Jerbi +2
Quantum kernel methods are among the leading candidates for achieving quantum advantage in supervised learning. A key bottleneck is the cost of inference: evaluating a trained mode…
A PAC-Bayesian approach to generalization for quantum models
Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert +3
Generalization is a central concept in machine learning theory, yet for quantum models, it is predominantly analyzed through uniform bounds that depend on a model's overall capacit…
Simulation of noisy quantum circuits using frame representations
Janek Denzler, Jose Carrasco, Jens Eisert +1
One of the core research questions in the theory of quantum computing is to find out to what precise extent the classical simulation of a noisy quantum circuits is possible and whe…
Reinforcement learning of quantum circuit architectures for molecular potential energy curves
Maureen Krumtünger, Alissa Wilms, Paul K. Faehrmann +4
Quantum chemistry and optimization are two of the most prominent applications of quantum computers. Variational quantum algorithms have been proposed for solving problems in these…
Stability of digital and analog quantum simulations under noise
Jayant Rao, Jens Eisert, Tommaso Guaita
Quantum simulation is a central application of near-term quantum devices, pursued in both analog and digital architectures. A key challenge for both paradigms is the effect of impe…
No Universal Purification in Quantum Mechanics
Zhenhuan Liu, Zhenyu Du, Jens Eisert +2
Many central tasks in fundamental physics and quantum information processing are possible only insofar as mixed quantum states can be made purer. In this work, we prove that the li…
Energy-independent tomography of Gaussian states
Lennart Bittel, Francesco Anna Mele, Francesco A. Mele +3
The exploration of tomography of bosonic Gaussian states is presumably as old as quantum optics, but only recently, their precise and rigorous study have been moving into the focus…
Quantum circuit simulation with a local time-dependent variational principle
Aaron Sander, Maximilian Fröhlich, Mazen Ali +6
Classical simulations of quantum circuits are vital for assessing potential quantum advantage and benchmarking devices, yet they require sophisticated methods to avoid the exponent…
Classical simulation of noisy quantum circuits via locally entanglement-optimal unravelings
Simon Cichy, Paul K. Faehrmann, Lennart Bittel +2
Classical simulations of noisy quantum circuits are instrumental to our understanding of the behavior of real-world quantum systems and the identification of regimes where one expe…
Non-Clifford Cost of Random Unitaries
Lorenzo Leone, Salvatore F. E. Oliviero, Alioscia Hamma +2
Recent years have enjoyed a strong interest in exploring properties and applications of random quantum circuits. In this work, we explore the ensemble of -doped Clifford circuit…
An unconditional distribution learning advantage with shallow quantum circuits
N. Pirnay, S. Jerbi, J. -P. Seifert +1
One of the core challenges of research in quantum computing is concerned with the question whether quantum advantages can be found for near-term quantum circuits that have implicat…
More global randomness from less-random local gates
Ryotaro Suzuki, Hosho Katsura, Yosuke Mitsuhashi +3
Random circuits giving rise to unitary designs are key tools in quantum information science and many-body physics. In this work, we investigate a class of random quantum circuits w…
Entangled inputs cannot make imperfect quantum channels perfect
Fernando G. S. L. Brandao, Jens Eisert, Michal Horodecki +1
Entangled inputs can enhance the capacity of quantum channels, this being one of the consequences of the celebrated result showing the non-additivity of several quantities relevant…