No Arabic abstract
A simple protocol based on low-weight Pauli Hamiltonians is introduced for performing quantum gates that are robust to control noise. Gates are implemented by an adiabatic sequence of single-qubit fields and two-qubit interactions with a single ancillary qubit, whereas related techniques require three-qubit interactions, perturbation gadgets, higher dimensional subsystems, and/or more ancilla qubits. Low-weight interactions and low qubit overhead open a viable path to experimental investigation, while operation in a degenerate ground space allows for physical qubit designs that are immune to energy relaxation. Simulations indicate that two-qubit gate error due to control noise can be as low as $10^{-5}$, for realizable coupling strengths and time-scales, with low-frequency noise that is as high as 15% of the control pulse amplitude.
Quantum gates induced by geometric phases are intrinsically robust against noise due to their global properties of the evolution paths. Compared to conventional nonadiabatic geometric quantum computation (NGQC), the recently proposed nonadiabatic noncyclic geometric quantum computation (NNGQC) works in a faster fashion, while still remaining the robust feature of the geometric operations. Here, we experimentally implement the NNGQC in a single trapped ultracold $^{40}$Ca$^{+}$ ion for verifying the noise-resilient and fast feature. By performing unitary operations under imperfect conditions, we witness the advantages of the NNGQC with measured fidelities by quantum process tomography in comparison with other two quantum gates by conventional NGQC and by straightforwardly dynamical evolution. Our results provide the first evidence confirming the possibility of accelerated quantum information processing with limited systematic errors even in the imperfect situation.
Noise mitigation and reduction will be crucial for obtaining useful answers from near-term quantum computers. In this work, we present a general framework based on machine learning for reducing the impact of quantum hardware noise on quantum circuits. Our method, called noise-aware circuit learning (NACL), applies to circuits designed to compute a unitary transformation, prepare a set of quantum states, or estimate an observable of a many-qubit state. Given a task and a device model that captures information about the noise and connectivity of qubits in a device, NACL outputs an optimized circuit to accomplish this task in the presence of noise. It does so by minimizing a task-specific cost function over circuit depths and circuit structures. To demonstrate NACL, we construct circuits resilient to a fine-grained noise model derived from gate set tomography on a superconducting-circuit quantum device, for applications including quantum state overlap, quantum Fourier transform, and W-state preparation.
Realistic quantum computing is subjected to noise. A most important frontier in research of quantum computing is to implement noise-resilient quantum control over qubits. Dynamical decoupling can protect coherence of qubits. Here we demonstrate non-trivial quantum evolution steered by dynamical decoupling control, which automatically suppresses the noise effect. We designed and implemented a self-protected controlled-NOT gate on the electron spin of a nitrogen-vacancy centre and a nearby carbon-13 nuclear spin in diamond at room temperature, by employing an engineered dynamical decoupling control on the electron spin. Final state fidelities of 0.91 and 0.88 were observed even with imperfect initial states. In the mean time, the qubit coherence time has been elongated by at least 30 folds. The design scheme does not require that the dynamical decoupling control commute with the qubit interaction and works for general systems. This work marks a step toward realistic quantum computing.
Variational algorithms are a promising paradigm for utilizing near-term quantum devices for modeling electronic states of molecular systems. However, previous bounds on the measurement time required have suggested that the application of these techniques to larger molecules might be infeasible. We present a measurement strategy based on a low rank factorization of the two-electron integral tensor. Our approach provides a cubic reduction in term groupings over prior state-of-the-art and enables measurement times three orders of magnitude smaller than those suggested by commonly referenced bounds for the largest systems we consider. Although our technique requires execution of a linear-depth circuit prior to measurement, this is compensated for by eliminating challenges associated with sampling non-local Jordan-Wigner transformed operators in the presence of measurement error, while enabling a powerful form of error mitigation based on efficient postselection. We numerically characterize these benefits with noisy quantum circuit simulations for ground state energies of strongly correlated electronic systems.
We propose and demonstrate a quantum control scheme for hybrid quantum registers that can reduce the operation time, and therefore the effects of relaxation, compared to existing implementations. It combines resonant excitation pulses with periods of free precession under the internal Hamiltonian of the qubit system. We use this scheme to implement quantum gates like controlled-NOT operations on electronic and nuclear spins of the nitrogen-vacancy center in diamond. As a specific application, we transfer population between electronic and nuclear spin qubits and use it to measure the Rabi oscillations of a nuclear spin in a system with multiple coupled spins.