QuICS seminar

Quantum metrology, which studies parameter estimation in quantum systems, has many important applications in science and technology, ranging from frequency spectroscopy to gravitational wave detection. Quantum mechanics imposes a fundamental limit on the estimation precision, called the Heisenberg limit, which is achievable in noiseless quantum systems, but is in general not for noisy systems. This talk is a summary of some recent works by the speaker and collaborators on quantum metrology enhanced by quantum error correction.

Quantum error correction is expected to play an important role in the realization of large-scale quantum computers. At the lowest level, it takes advantage of embedding qubits in a larger Hilbert space, giving redundancy which allows measurements which preserve logical information while revealing the presence of errors. While many codes rely on multiple physical systems, Bosonic codes make use of the higher dimensional Hilbert space of a single harmonic oscillator mode.

To harness the potential of noisy intermediate-scale quantum devices, it is paramount to find the best type of circuits to run hybrid quantum-classical algorithms. Key candidates are parametrized quantum circuits that can be effectively implemented on current devices. Here, we evaluate the capacity and trainability of these circuits using the geometric structure of the parameter space via the effective quantum dimension [1]. We find that the capacity exhibits scaling laws and striking differences depending on the type of entangling gates used.

The main challenge for scaling up photonic quantum technologies is the lack of perfect quantum light sources. We have pushed the parametric down-conversion to its physical limit and produce two-photon source with simultaneously a collection efficiency of 97% and an indistinguishability of 96% between independent photons. Using a single quantum dot in microcavities, we have produced on-demand single photons with high purity (>99%), near-unity indistinguishability, and high extraction efficiency—all combined in a single device compatibly and simultaneously.

What does it mean to simulate a quantum field theory? This is a challenging question because a majority of the quantum field theories relevant to fundamental physics lack a fully rigourous mathematical definition. Thus it is impossible in general to compare the predictions of discretised theories with their continuum counterparts.

In this talk I will give an overview of various strategies we have developed for suppressing the inevitable errors occurring during quantum computations. These tools work at the gate level and thus can be effective even through a cloud API exposing only elementary gates to the end-user. I will demonstrate the effectiveness of these tools with experimental results across multiple hardware architectures.

Variational quantum algorithms are proposed to solve relevant computational problems on near term quantum devices. Popular versions are variational quantum eigensolvers and quantum approximate optimization algorithms that solve ground state problems from quantum chemistry and binary optimization problems, respectively. They are based on the idea of using a classical computer to train a parametrized quantum circuit. We show that the corresponding classical optimization problems are NP-hard.

Recent progress on noisy, intermediate scale quantum (NISQ) devices opens exciting opportunities for many-body physics. NISQ platforms are indeed not just computers, but also interesting laboratory systems in their own right, offering access to large Hilbert spaces with exceptional capabilities for control and measurement. I will argue that nonequilibrium phases in periodically-driven (Floquet) systems are a particularly good fit for such capabilities in the near term.

We show that every quantum computation can be described by a probabilistic update of a probability distribution on a finite phase space. Negativity in a quasiprobability function is not required in states or operations. Our result is consistent with Gleason’s theorem and the Pusey-Barrett-Rudolph theorem.

Joint work with: Michael Zurel and Cihan Okay
J-Ref: Phys. Rev. Lett. 125, 260404 (2020)

(Please note the earlier start time of 10:30 a.m. for this seminar.)

Near-term applications of early quantum devices, such as quantum simulations, rely on accurate estimates of expectation values to become relevant. Decoherence and gate errors lead to wrong estimates. This problem was, at least in theory, remedied with the advent of quantum error correction.