Tag - Quantum computing

The 1-dimensional p-wave superconductor with boundary Majorana modes has attracted theoretical and experimental interest due to its potential application in topological quantum computation. Spin-1/2 Kitaev ladder systems with bond-dependent Ising interactions, featuring Majorana fermions coupled with Z₂ flux, can also exhibit boundary Majorana modes when they are in a topological phase. However, due to the ground state degeneracy, a superposition of the two states may annihilate the Majorana modes. Here we demonstrate a projective measurement that selects one of the degenerate Z₂ sectors, enabling the emergence of Majorana modes. We present the phase diagram across different flux configurations and interaction strengths using analytical and numerical analysis. Our study illustrates the appearance of Majorana modes at the interfaces of topological and non-topological phases, with each corresponding to different flux sectors for a given interaction strength. These modes, along with boundary Majorana modes, can be manipulated and fused by tuning the flux sectors achievable through applying local spin operators. We discuss the engineering of a trimmed Kitaev honeycomb ladder, along with its phase diagram and open questions for future studies.

It was once thought that if a probe quantum state exhibits high sensitivity to a particular transformation, this must come with the cost of decreased sensitivity to other transformations generated by non-commuting observables. However, particular classes of states exist that disprove this misconception, for example the 'compass state' and, more recently, generation of the 'tetrahedron state' was carried out in our group. The tetrahedron state is created in the symmetric subspace of four optical photons’ polarisation, and exhibits maximal sensitivity to arbitrary SU(2) rotations. In this presentation, I will talk about two quantum parameter estimation experiments, starting with the experimental generation of the tetrahedron state, the optimal four-photon state for estimating rotations. I will then discuss the experimental generation of the optimal two-photon state for simultaneous estimation of the parameters describing a rotation.

AI hardware needs are today the main driver of semiconductor industry processor chip developments and foundry progress, while quantum computing hardware is seeing unprecedented investment and interest. A critical need and missing need in computing of all kinds is movement of information, which now requires sophisticated optical interconnects. Such interconnects have provided the impetus for the development of advanced foundry platforms for electronic-photonic integrated circuits (EPICs). I will talk about the progress and applications of emerging capabilities in advanced electronic-photonic ICs.

I will review work carried out through my research group and through silicon-valley startup Ayar Labs on developing advanced-node 300mm CMOS platforms for monolithic electronics-photonics integration in commercial foundries. I will also describe using these platforms to develop classical, cryogenic and quantum interconnects on chip, and photonic sensing apertures. These platforms have allowed EPICs and systems on chip (SoCs) of unprecedented complexity and improved sensitivity. In the talk, I will describe the latest developments at Ayar Labs on Terabit scale I/O from a single processor package. I’ll talk about university research on cryogenic (4K) photonic data links that could address the I/O bottleneck of superconducting electronics and enable new future supercomputing platforms well suited to AI, and will summarize ongoing efforts on CMOS electronic-photonic quantum systems-on-chip (epQSoCs) for photonic quantum networks. Last, I will highlight recent research on efficient components, for example progress on a novel integrated photonic aperture, the serpentine optical phased array. One promising application is as a spectrometer design that improves over both bulk and integrated spectrometers by several orders of magnitude in key metrics such as resolving power and system volume. Photonic integrated circuits are at the brink of possible major impact in the semiconductor industry – for now, the first emerging commercial applications are optical interconnects, but it looks as though the semiconductor industry is starting to 'see the light'.

Dynamical probes and transport experiments are vital in deciphering quantum spin liquids, an exotic phase of matter with proposed applications in fault-tolerant quantum computing. However, experiments on candidate materials are usually performed at finite temperature away from perturbative regimes, evading analytical descriptions. Moreover, numerical simulations on the quantum Hamiltonians often suffer from finite size effects or short time evolution windows. In this talk, I provide an overview of my work involving classical numerical methods, specifically finite temperature Monte Carlo algorithms and Landau-Lifshitz Gilbert equations, to simulate dynamics in frustrated magnets. Using these methods, we offer insights into the finite-temperature crossover behaviour between the spin excitation continuum in a quantum spin liquid and topological magnons in the field-polarized state in various models with large Kitaev interactions.

One of the most promising applications of quantum computing is the simulation of quantum systems. The goal is to construct a quantum algorithm that closely approximates the solution to Schrödinger’s equation, which is a unitary propagator in time. Much attention has been given to this problem, and modern approaches provide a variety of highly efficient algorithms. The lesser-studied Lindblad equation generalizes the Schrödinger equation to quantum systems that undergo dissipation, leading to non-unitary dynamics that prevent a naïve application of state-of-the-art quantum algorithms. In this work, we utilize a correspondence between repeated interaction CPTP maps and Lindbladian dynamics to formulate an embedding of the non-unitary dynamics in a higher dimensional space that evolves under a Hamiltonian with low space overhead, which we can simulate with efficient quantum algorithms. In the process, we derive error bounds on the approximate correspondence and provide bounds on the computational complexity of the approach.

In this work, we present a super-polynomial improvement in the precision scaling of quantum simulations for coupled classical-quantum systems. Such systems are found, for example, in molecular dynamics simulations within the Born-Oppenheimer approximation. By employing a framework based on the Koopman-von Neumann formulation of classical mechanics, we express the Liouville equation of motion as unitary dynamics and utilize phase kickback from a dynamical quantum simulation to calculate the quantum forces acting on classical particles. This approach allows us to simulate the dynamics of these classical particles without the overheads associated with measuring gradients and solving the equations of motion on a classical computer, resulting in a super-polynomial advantage at the price of increased space complexity. We demonstrate that these simulations can be performed in both microcanonical and canonical ensembles, enabling the estimation of thermodynamic properties from the prepared probability density.

The steady states of Markovian processes can be written as extremal eigenvectors of a matrix (e.g., a quantum channel) that generates the dynamics. Unlike ground states of Hamiltonians, however, the gap of the channel does not necessarily control relaxation to the ground state. I will argue that this discrepancy is precisely what allows non-trivial gapped phases of Lindbladians to exist. I will discuss an alternative criterion for deciding whether two Lindbladians (and their steady states) are in the same phase. I will show that this criterion implies many of the properties one would naturally demand of a phase, such as the persistence of any long-range order and the analytic evolution of correlation functions within a phase.