QuICS seminar

The presence of noise is currently one of the main obstacles to achieving large-scale quantum computation. Strategies to characterise and understand noise processes in quantum hardware are a critical part of mitigating it, especially as the overhead of full error correction and fault-tolerance is beyond the reach of current hardware. Non-Markovian effects are a particularly unfavorable type of noise, being both harder to analyse using standard techniques and more difficult to control using error correction.

The quantum circuit model is the de-facto way of designing quantum algorithms. Yet any level of abstraction away from the underlying hardware incurs overhead. In the era of near-term, noisy, intermediate-scale quantum (NISQ) hardware with severely restricted resources, this overhead may be unjustifiable. We develop quantum algorithms for Hamiltonian simulation "one level below" the circuit model, exploiting the underlying control over qubit interactions available in most quantum hardware implementations.

The typical model for measurement noise in quantum error correction is to randomly flip the binary measurement outcome. In experiments, measurements yield much richer information - e.g., continuous current values, discrete photon counts - which is then mapped into binary outcomes by discarding some of this information. In this work, we consider methods to incorporate all of this richer information, typically called soft information, into the decoding of the surface code.

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.

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.

Abstract: Modern quantum algorithms originate historically from three disparate origins: simulation, search, and factoring.  Today, we can now understand and appreciate all of these as being instances of a single framework, and remarkably, the essence is how the rotations of a single quantum bit can be transformed non-linearly by a simple sequence of operations.  On the face of it, this is physically non-intuitive, because quantum mechanics is linear.  The key is to think not about eigenvalues and closed systems, but instead, about singular values and subsystem dynamics.

Abstract: 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.

Abstract: 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. I will discuss these challenges and advocate the use of the recently introduced operator algebraic renormalization (OAR) as a means to provide both classical and quantum simulations of quantum field theories, in particular, conformal theories.

Abstract: 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.