575 research outputs found

    Approximation Algorithms for Complex-Valued Ising Models on Bounded Degree Graphs

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    We study the problem of approximating the Ising model partition function with complex parameters on bounded degree graphs. We establish a deterministic polynomial-time approximation scheme for the partition function when the interactions and external fields are absolutely bounded close to zero. Furthermore, we prove that for this class of Ising models the partition function does not vanish. Our algorithm is based on an approach due to Barvinok for approximating evaluations of a polynomial based on the location of the complex zeros and a technique due to Patel and Regts for efficiently computing the leading coefficients of graph polynomials on bounded degree graphs. Finally, we show how our algorithm can be extended to approximate certain output probability amplitudes of quantum circuits.Comment: 12 pages, 0 figures, published versio

    Commuting Quantum Circuits with Few Outputs are Unlikely to be Classically Simulatable

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    We study the classical simulatability of commuting quantum circuits with n input qubits and O(log n) output qubits, where a quantum circuit is classically simulatable if its output probability distribution can be sampled up to an exponentially small additive error in classical polynomial time. First, we show that there exists a commuting quantum circuit that is not classically simulatable unless the polynomial hierarchy collapses to the third level. This is the first formal evidence that a commuting quantum circuit is not classically simulatable even when the number of output qubits is exponentially small. Then, we consider a generalized version of the circuit and clarify the condition under which it is classically simulatable. Lastly, we apply the argument for the above evidence to Clifford circuits in a similar setting and provide evidence that such a circuit augmented by a depth-1 non-Clifford layer is not classically simulatable. These results reveal subtle differences between quantum and classical computation.Comment: 19 pages, 6 figures; v2: Theorems 1 and 3 improved, proofs modifie

    Achieving quantum supremacy with sparse and noisy commuting quantum computations

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    The class of commuting quantum circuits known as IQP (instantaneous quantum polynomial-time) has been shown to be hard to simulate classically, assuming certain complexity-theoretic conjectures. Here we study the power of IQP circuits in the presence of physically motivated constraints. First, we show that there is a family of sparse IQP circuits that can be implemented on a square lattice of n qubits in depth O(sqrt(n) log n), and which is likely hard to simulate classically. Next, we show that, if an arbitrarily small constant amount of noise is applied to each qubit at the end of any IQP circuit whose output probability distribution is sufficiently anticoncentrated, there is a polynomial-time classical algorithm that simulates sampling from the resulting distribution, up to constant accuracy in total variation distance. However, we show that purely classical error-correction techniques can be used to design IQP circuits which remain hard to simulate classically, even in the presence of arbitrary amounts of noise of this form. These results demonstrate the challenges faced by experiments designed to demonstrate quantum supremacy over classical computation, and how these challenges can be overcome.Comment: 23 pages, 1 figure; v4: uses standard journal styl

    Characterizing quantum supremacy in near-term devices

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    © 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. A critical question for quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond the capabilities of supercomputers. Such a demonstration of what is referred to as quantum supremacy requires a reliable evaluation of the resources required to solve tasks with classical approaches. Here, we propose the task of sampling from the output distribution of random quantum circuits as a demonstration of quantum supremacy. We extend previous results in computational complexity to argue that this sampling task must take exponential time in a classical computer. We introduce cross-entropy benchmarking to obtain the experimental fidelity of complex multiqubit dynamics. This can be estimated and extrapolated to give a success metric for a quantum supremacy demonstration. We study the computational cost of relevant classical algorithms and conclude that quantum supremacy can be achieved with circuits in a two-dimensional lattice of 7 × 7 qubits and around 40 clock cycles. This requires an error rate of around 0.5% for two-qubit gates (0.05% for one-qubit gates), and it would demonstrate the basic building blocks for a fault-tolerant quantum computer

    The Born supremacy: quantum advantage and training of an Ising Born machine

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    The search for an application of near-term quantum devices is widespread. Quantum Machine Learning is touted as a potential utilisation of such devices, particularly those which are out of the reach of the simulation capabilities of classical computers. In this work, we propose a generative Quantum Machine Learning Model, called the Ising Born Machine (IBM), which we show cannot, in the worst case, and up to suitable notions of error, be simulated efficiently by a classical device. We also show this holds for all the circuit families encountered during training. In particular, we explore quantum circuit learning using non-universal circuits derived from Ising Model Hamiltonians, which are implementable on near term quantum devices. We propose two novel training methods for the IBM by utilising the Stein Discrepancy and the Sinkhorn Divergence cost functions. We show numerically, both using a simulator within Rigetti's Forest platform and on the Aspen-1 16Q chip, that the cost functions we suggest outperform the more commonly used Maximum Mean Discrepancy (MMD) for differentiable training. We also propose an improvement to the MMD by proposing a novel utilisation of quantum kernels which we demonstrate provides improvements over its classical counterpart. We discuss the potential of these methods to learn `hard' quantum distributions, a feat which would demonstrate the advantage of quantum over classical computers, and provide the first formal definitions for what we call `Quantum Learning Supremacy'. Finally, we propose a novel view on the area of quantum circuit compilation by using the IBM to `mimic' target quantum circuits using classical output data only.Comment: v3 : Close to journal published version - significant text structure change, split into main text & appendices. See v2 for unsplit version; v2 : Typos corrected, figures altered slightly; v1 : 68 pages, 39 Figures. Comments welcome. Implementation at https://github.com/BrianCoyle/IsingBornMachin

    Fluoxetine: a case history of its discovery and preclinical development

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    Introduction: Depression is a multifactorial mood disorder with a high prevalence worldwide. Until now, treatments for depression have focused on the inhibition of monoaminergic reuptake sites, which augment the bioavailability of monoamines in the CNS. Advances in drug discovery have widened the therapeutic options with the synthesis of so-called selective serotonin reuptake inhibitors (SSRIs), such as fluoxetine. Areas covered: The aim of this case history is to describe and discuss the pharmacokinetic and pharmacodynamic profiles of fluoxetine, including its acute effects and the adaptive changes induced after long-term treatment. Furthermore, the authors review the effect of fluoxetine on neuroplasticity and adult neurogenesis. In addition, the article summarises the preclinical behavioural data available on fluoxetine’s effects on depressive-like behaviour, anxiety and cognition as well as its effects on other diseases. Finally, the article describes the seminal studies validating the antidepressant effects of fluoxetine. Expert opinion: Fluoxetine is the first selective SSRI that has a recognised clinical efficacy and safety profile. Since its discovery, other molecules that mimic its mechanism of action have been developed, commencing a new age in the treatment of depression. Fluoxetine has also demonstrated utility in the treatment of other disorders for which its prescription has now been approved

    Pixel and Voxel Representations of Graphs

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    We study contact representations for graphs, which we call pixel representations in 2D and voxel representations in 3D. Our representations are based on the unit square grid whose cells we call pixels in 2D and voxels in 3D. Two pixels are adjacent if they share an edge, two voxels if they share a face. We call a connected set of pixels or voxels a blob. Given a graph, we represent its vertices by disjoint blobs such that two blobs contain adjacent pixels or voxels if and only if the corresponding vertices are adjacent. We are interested in the size of a representation, which is the number of pixels or voxels it consists of. We first show that finding minimum-size representations is NP-complete. Then, we bound representation sizes needed for certain graph classes. In 2D, we show that, for kk-outerplanar graphs with nn vertices, Θ(kn)\Theta(kn) pixels are always sufficient and sometimes necessary. In particular, outerplanar graphs can be represented with a linear number of pixels, whereas general planar graphs sometimes need a quadratic number. In 3D, Θ(n2)\Theta(n^2) voxels are always sufficient and sometimes necessary for any nn-vertex graph. We improve this bound to Θ(n⋅τ)\Theta(n\cdot \tau) for graphs of treewidth τ\tau and to O((g+1)2nlog⁥2n)O((g+1)^2n\log^2n) for graphs of genus gg. In particular, planar graphs admit representations with O(nlog⁥2n)O(n\log^2n) voxels

    Realisation of a programmable two-qubit quantum processor

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    The universal quantum computer is a device capable of simulating any physical system and represents a major goal for the field of quantum information science. Algorithms performed on such a device are predicted to offer significant gains for some important computational tasks. In the context of quantum information, "universal" refers to the ability to perform arbitrary unitary transformations in the system's computational space. The combination of arbitrary single-quantum-bit (qubit) gates with an entangling two-qubit gate is a gate set capable of achieving universal control of any number of qubits, provided that these gates can be performed repeatedly and between arbitrary pairs of qubits. Although gate sets have been demonstrated in several technologies, they have as yet been tailored toward specific tasks, forming a small subset of all unitary operators. Here we demonstrate a programmable quantum processor that realises arbitrary unitary transformations on two qubits, which are stored in trapped atomic ions. Using quantum state and process tomography, we characterise the fidelity of our implementation for 160 randomly chosen operations. This universal control is equivalent to simulating any pairwise interaction between spin-1/2 systems. A programmable multi-qubit register could form a core component of a large-scale quantum processor, and the methods used here are suitable for such a device.Comment: 7 pages, 4 figure

    Understanding the threats posed by non-native species: public vs. conservation managers.

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    Public perception is a key factor influencing current conservation policy. Therefore, it is important to determine the influence of the public, end-users and scientists on the prioritisation of conservation issues and the direct implications for policy makers. Here, we assessed public attitudes and the perception of conservation managers to five non-native species in the UK, with these supplemented by those of an ecosystem user, freshwater anglers. We found that threat perception was not influenced by the volume of scientific research or by the actual threats posed by the specific non-native species. Media interest also reflected public perception and vice versa. Anglers were most concerned with perceived threats to their recreational activities but their concerns did not correspond to the greatest demonstrated ecological threat. The perception of conservation managers was an amalgamation of public and angler opinions but was mismatched to quantified ecological risks of the species. As this suggests that invasive species management in the UK is vulnerable to a knowledge gap, researchers must consider the intrinsic characteristics of their study species to determine whether raising public perception will be effective. The case study of the topmouth gudgeon Pseudorasbora parva reveals that media pressure and political debate has greater capacity to ignite policy changes and impact studies on non-native species than scientific evidence alone

    No imminent quantum supremacy by boson sampling

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    It is predicted that quantum computers will dramatically outperform their conventional counterparts. However, large-scale universal quantum computers are yet to be built. Boson sampling is a rudimentary quantum algorithm tailored to the platform of photons in linear optics, which has sparked interest as a rapid way to demonstrate this quantum supremacy. Photon statistics are governed by intractable matrix functions known as permanents, which suggests that sampling from the distribution obtained by injecting photons into a linear-optical network could be solved more quickly by a photonic experiment than by a classical computer. The contrast between the apparently awesome challenge faced by any classical sampling algorithm and the apparently near-term experimental resources required for a large boson sampling experiment has raised expectations that quantum supremacy by boson sampling is on the horizon. Here we present classical boson sampling algorithms and theoretical analyses of prospects for scaling boson sampling experiments, showing that near-term quantum supremacy via boson sampling is unlikely. While the largest boson sampling experiments reported so far are with 5 photons, our classical algorithm, based on Metropolised independence sampling (MIS), allowed the boson sampling problem to be solved for 30 photons with standard computing hardware. We argue that the impact of experimental photon losses means that demonstrating quantum supremacy by boson sampling would require a step change in technology.Comment: 25 pages, 9 figures. Comments welcom
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