no code implementations • 22 Feb 2024 • Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli
A key challenge in realizing fault-tolerant quantum computers is circuit optimization.
no code implementations • 9 Oct 2023 • Johannes Bausch, Andrew W Senior, Francisco J H Heras, Thomas Edlich, Alex Davies, Michael Newman, Cody Jones, Kevin Satzinger, Murphy Yuezhen Niu, Sam Blackwell, George Holland, Dvir Kafri, Juan Atalaya, Craig Gidney, Demis Hassabis, Sergio Boixo, Hartmut Neven, Pushmeet Kohli
Quantum error-correction is a prerequisite for reliable quantum computation.
no code implementations • 28 Jan 2021 • Tamara Kohler, Stephen Piddock, Johannes Bausch, Toby Cubitt
Recent work has demonstrated the existence of universal Hamiltonians - simple spin lattice models that can simulate any other quantum many body system to any desired level of accuracy.
Quantum Physics
no code implementations • 23 Dec 2020 • James D. Watson, Johannes Bausch, Sevag Gharibian
It is known that three fundamental questions regarding local Hamiltonians -- approximating the ground state energy (the Local Hamiltonian problem), simulating local measurements on the ground space (APX-SIM), and deciding if the low energy space has an energy barrier (GSCON) -- are $\mathsf{QMA}$-hard, $\mathsf{P}^{\mathsf{QMA}[log]}$-hard and $\mathsf{QCMA}$-hard, respectively, meaning they are likely intractable even on a quantum computer.
Quantum Physics Strongly Correlated Electrons Mathematical Physics Mathematical Physics
1 code implementation • NeurIPS 2020 • Johannes Bausch
In this work we construct a quantum recurrent neural network (QRNN) with demonstrable performance on non-trivial tasks such as sequence learning and integer digit classification.
no code implementations • 15 Mar 2020 • Laura Clinton, Johannes Bausch, Toby Cubitt
In this work, we develop quantum algorithms for Hamiltonian simulation "one level below" the circuit model, exploiting the underlying control over qubit interactions available in principle in most quantum hardware implementations.
Quantum Physics
no code implementations • 3 Oct 2019 • Johannes Bausch, Toby S. Cubitt, James D. Watson
The phase diagram of a material is of central importance to describe the properties and behaviour of a condensed matter system.
Quantum Physics Other Condensed Matter Mathematical Physics Mathematical Physics 03D35, 68Q17, 81V70, 82B26
2 code implementations • 1 Oct 2019 • Johannes Bausch, Felix Leditzky
The error thresholds of these tree graph states outperform repetition and cat codes in large regions of the Pauli simplex, and hence form a new code family with desirable error correction properties.
Quantum Physics Information Theory Information Theory 81P45, 94C15, 94B99, 94A17
no code implementations • 9 Sep 2019 • Johannes Bausch, Sathyawageeswar Subramanian, Stephen Piddock
Probabilistic language models, e. g. those based on an LSTM, often face the problem of finding a high probability prediction from a sequence of random variables over a set of tokens.
no code implementations • 2 Jul 2018 • Johannes Bausch
The goal of this work is to define a notion of a quantum neural network to classify data, which exploits the low energy spectrum of a local Hamiltonian.
no code implementations • 22 Jun 2018 • Johannes Bausch, Felix Leditzky
These codes outperform all other known codes for these channels, and cannot be found using a direct parametrization of the quantum state.