Gate-set evaluation metrics for closed-loop optimal control on nitrogen-vacancy center ensembles in diamond

Philipp J. Vetter, Thomas Reisser, Maximilian G. Hirsch, Tommaso Calarco, Felix Motzoi, Fedor Jelezko and Matthias M. Muller. A recurring challenge in quantum science and technology is the precise control of their underlying dynamics that lead to the desired quantum operations, often described by a set of quantum gates. These gates can be subject to application-specific errors, leading to a…

Reinforcement learning pulses for transmon qubit entangling gates

Ho Nam Nguyen, Felix Motzoi, Mekena Metcalf, K. Birgitta Whaley, Marin Bukov, Markus Schmitt. The utility of a quantum computer depends heavily on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular interest to explore model-free approaches, since their quality is not constrained by the limited accuracy of theoretical models for…

Experimental error suppression in Cross-Resonance gates via multi-derivative pulse shaping

Boxi Li, Tommaso Calarco and Felix Motzoi. While quantum circuits are reaching impressive widths in the hundreds of qubits, their depths have not been able to keep pace. In particular, cloud computing gates based on fixed-frequency superconducting architectures have stalled, hovering on average around the 1% error range for half a decade, considerably underutilizing the potential offered by their coherence…

Hamiltonian and Liouvillian learning in weakly-dissipative quantum many-body systems

Tobias Olsacher, Tristan Kraft, Christian Kokail, Barbara Kraus, Peter Zoller. We discuss Hamiltonian and Liouvillian learning for analog quantum simulation from non-equilibrium quench dynamics in the limit of weakly dissipative many-body systems. We present various strategies to learn the operator content of the Hamiltonian and the Lindblad operators of the Liouvillian. We compare different ansätze based on an experimentally accessible…

Unsupervised learning of quantum many-body scars using intrinsic dimension

Harvey Cao, Dimitris G. Angelakis, Daniel Leykam. Quantum many-body scarred systems contain both thermal and non-thermal scar eigenstates in their spectra. When these systems are quenched from special initial states which share high overlap with scar eigenstates, the system undergoes dynamics with atypically slow relaxation and periodic revival. This scarring phenomenon poses a potential avenue for circumventing decoherence in various…

Landscape approximation of low energy solutions to binary optimization problems

Benjamin Y.L. Tan, Beng Yee Gan, Daniel Leykam, and Dimitris G. Angelakis. We show how the localization landscape, originally introduced to bound low energy eigenstates of disordered wave media and many-body quantum systems, can form the basis for hardware efficient quantum algorithms for solving binary optimization problems. Many binary optimization problems can be cast as finding low-energy eigenstates of Ising…

Nonlinear Quantum Dynamics in Superconducting NISQ Processors

Muhammad Umer, Eleftherios Mastorakis, Sofia Evangelou, Dimitris G. Angelakis. A recently proposed variational quantum algorithm has expanded the horizon of variational quantum computing to nonlinear physics and fluid dynamics. In this work, we employ this algorithm to find the ground state of the nonlinear Schrödinger equation with a quadratic potential and implement it on the cloud superconducting quantum processors. We…

Partitioned Quantum Subspace Expansion

Tom O'Leary, Lewis W. Anderson, Dieter Jaksch, Martin Kiffner. We present an iterative generalisation of the quantum subspace expansion algorithm used with a Krylov basis. The iterative construction connects a sequence of subspaces via their lowest energy states. Diagonalising a Hamiltonian in a given Krylov subspace requires the same quantum resources in both the single step and sequential cases. We…

Boundary Treatment for Variational Quantum Simulations of Partial Differential Equations on Quantum Computers

Paul Over, Sergio Bengoechea, Thomas Rung, Francesco Clerici, Leonardo Scandurra, Eugene de Villiers, Dieter Jaksch. The paper presents a variational quantum algorithm to solve initial-boundary value problems described by second-order partial differential equations. The approach uses hybrid classical/quantum hardware that is well suited for quantum computers of the current noisy intermediate-scale quantum era. The partial differential equation is initially translated into an optimal control problem with…

Shallow quantum circuits for efficient preparation of Slater determinants and correlated states on a quantum computer

Chong Hian Chee, Daniel Leykam, Adrian M. Mak, and Dimitris G. Angelakis. Fermionic Ansatz state preparation is a critical subroutine in many quantum algorithms such as the variational quantum eigensolver for quantum chemistry and condensed-matter applications. The shallowest circuit depth needed to prepare Slater determinants and correlated states to date scales at least linearly with respect to the system size \(N\). Inspired by…
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The QCFD (Quantum Computational Fluid Dynamics) project is funded under the European Union’s Horizon Programme (HORIZON-CL4-2021-DIGITAL-EMERGING-02-10), Grant Agreement 101080085 QCFD.