High-Level Methods for Quantum Computation and Information

A research programme is set out for developing the use of high-level methods for quantum computation and information, based on the categorical formulation of quantum mechanics introduced by the author and Bob Coecke.Comment: 5 page

Getting the public involved in Quantum Error Correction

The Decodoku project seeks to let users get hands-on with cutting-edge quantum research through a set of simple puzzle games. The design of these games is explicitly based on the problem of decoding qudit variants of surface codes. This problem is presented such that it can be tackled by players with no prior knowledge of quantum information theory, or any other high-level physics or mathematics. Methods devised by the players to solve the puzzles can then directly be incorporated into decoding algorithms for quantum computation. In this paper we give a brief overview of the novel decoding methods devised by players, and provide short postmortem for Decodoku v1.0-v4.1.Comment: Extended version of article in the proceedings of the GSGS'17 conference (see https://gsgs.ch/gsgs17/

Online Scheduled Execution of Quantum Circuits Protected by Surface Codes

Quantum circuits are the preferred formalism for expressing quantum information processing tasks. Quantum circuit design automation methods mostly use a waterfall approach and consider that high level circuit descriptions are hardware agnostic. This assumption has lead to a static circuit perspective: the number of quantum bits and quantum gates is determined before circuit execution and everything is considered reliable with zero probability of failure. Many different schemes for achieving reliable fault-tolerant quantum computation exist, with different schemes suitable for different architectures. A number of large experimental groups are developing architectures well suited to being protected by surface quantum error correcting codes. Such circuits could include unreliable logical elements, such as state distillation, whose failure can be determined only after their actual execution. Therefore, practical logical circuits, as envisaged by many groups, are likely to have a dynamic structure. This requires an online scheduling of their execution: one knows for sure what needs to be executed only after previous elements have finished executing. This work shows that scheduling shares similarities with place and route methods. The work also introduces the first online schedulers of quantum circuits protected by surface codes. The work also highlights scheduling efficiency by comparing the new methods with state of the art static scheduling of surface code protected fault-tolerant circuits.Comment: accepted in QI

Efficient, low noise, mode-selective quantum memory

Photonic quantum information processing is a key element for scalable quantum technologies, and has applications in secure long-distance quantum communication and connecting nodes of a quantum computation network. However, logical photon-photon gates and state-of-the-art single photon sources rely on probabilistic processes. Quantum memories are devices that enable storage and on-demand recall of quantum states of light, and have been highlighted as a vital component in photonic networks to overcome the scaling problem by synchronising probabilistic processes. The Raman memory has a large storage bandwidth and high synchronising capacity, and is an ideal candidate for local synchronisation. However, previous demonstrations of the Raman memory suffer from four-wave mixing noise, which prohibits quantum level operation. In this thesis I investigate methods to increase the signal to noise ratio in the Raman memory. I investigate increasing the light-matter coupling strength to boost the memory efficiency, and then explore two different methods to suppress four-wave mixing noise. I demonstrate that operating the Raman memory in a cavity is successful in reducing four-wave mixing, but it is technically challenging to maintain a high memory efficiency. I investigate a new method of noise suppression by introducing an absorption feature at the frequency of the unwanted noise field. This technically simple method is successful in reducing the noise by an order of magnitude, and will be applicable to many quantum memory protocols. In the final section of this thesis I explore the temporal mode properties of the Raman memory. I demonstrate that the Raman memory is single mode and can be used to separate and manipulate temporal modes of light. This positions the Raman memory as a key device for enabling high-dimensional photonic quantum information processing, and enhancing light-matter interactions. These results pave the way towards an efficient, low-noise, mode-selective quantum memory.Open Acces

Optimized Surface Code Communication in Superconducting Quantum Computers

Quantum computing (QC) is at the cusp of a revolution. Machines with 100 quantum bits (qubits) are anticipated to be operational by 2020 [googlemachine,gambetta2015building], and several-hundred-qubit machines are around the corner. Machines of this scale have the capacity to demonstrate quantum supremacy, the tipping point where QC is faster than the fastest classical alternative for a particular problem. Because error correction techniques will be central to QC and will be the most expensive component of quantum computation, choosing the lowest-overhead error correction scheme is critical to overall QC success. This paper evaluates two established quantum error correction codes---planar and double-defect surface codes---using a set of compilation, scheduling and network simulation tools. In considering scalable methods for optimizing both codes, we do so in the context of a full microarchitectural and compiler analysis. Contrary to previous predictions, we find that the simpler planar codes are sometimes more favorable for implementation on superconducting quantum computers, especially under conditions of high communication congestion.Comment: 14 pages, 9 figures, The 50th Annual IEEE/ACM International Symposium on Microarchitectur

Algorithmic Cooling of Spins: A Practicable Method for Increasing Polarization

An efficient technique to generate ensembles of spins that are highly polarized by external magnetic fields is the Holy Grail in Nuclear Magnetic Resonance (NMR) spectroscopy. Since spin-half nuclei have steady-state polarization biases that increase inversely with temperature, spins exhibiting high polarization biases are considered cool, even when their environment is warm. Existing spin-cooling techniques are highly limited in their efficiency and usefulness. Algorithmic cooling is a promising new spin-cooling approach that employs data compression methods in open systems. It reduces the entropy of spins on long molecules to a point far beyond Shannon's bound on reversible entropy manipulations (an information-theoretic version of the 2nd Law of Thermodynamics), thus increasing their polarization. Here we present an efficient and experimentally feasible algorithmic cooling technique that cools spins to very low temperatures even on short molecules. This practicable algorithmic cooling could lead to breakthroughs in high-sensitivity NMR spectroscopy in the near future, and to the development of scalable NMR quantum computers in the far future. Moreover, while the cooling algorithm itself is classical, it uses quantum gates in its implementation, thus representing the first short-term application of quantum computing devices.Comment: 24 pages (with annexes), 3 figures (PS). This version contains no major content changes: fixed bibliography & figures, modified acknowledgement