Matthias Troyer

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Troyer

First Name

Matthias

ORCID

0000-0002-1469-9444

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Publications 1 - 10 of 63

Quantifying the Loss of Coral from a Bleaching Event Using Underwater Photogrammetry and AI-Assisted Image Segmentation
Kopecky, Kai L.; Pavoni, Gaia; Nocerino, Erica; et al. (2023)
Remote Sensing
Detecting the impacts of natural and anthropogenic disturbances that cause declines in organisms or changes in community composition has long been a focus of ecology. However, a tradeoff often exists between the spatial extent over which relevant data can be collected, and the resolution of those data. Recent advances in underwater photogrammetry, as well as computer vision and machine learning tools that employ artificial intelligence (AI), offer potential solutions with which to resolve this tradeoff. Here, we coupled a rigorous photogrammetric survey method with novel AI-assisted image segmentation software in order to quantify the impact of a coral bleaching event on a tropical reef, both at an ecologically meaningful spatial scale and with high spatial resolution. In addition to outlining our workflow, we highlight three key results: (1) dramatic changes in the three-dimensional surface areas of live and dead coral, as well as the ratio of live to dead colonies before and after bleaching; (2) a size-dependent pattern of mortality in bleached corals, where the largest corals were disproportionately affected, and (3) a significantly greater decline in the surface area of live coral, as revealed by our approximation of the 3D shape compared to the more standard planar area (2D) approach. The technique of photogrammetry allows us to turn 2D images into approximate 3D models in a flexible and efficient way. Increasing the resolution, accuracy, spatial extent, and efficiency with which we can quantify effects of disturbances will improve our ability to understand the ecological consequences that cascade from small to large scales, as well as allow more informed decisions to be made regarding the mitigation of undesired impacts.
Advantages of a modular high-level quantum programming framework
Steiger, Damian S.; Häner, Thomas; Troyer, Matthias (2019)
Microprocessors and Microsystems
Supersolid Hard-Core Bosons on the Triangular Lattice
Wessel, Stefan; Troyer, Matthias (2005)
Physical Review Letters
Embedding Overhead Scaling of Optimization Problems in Quantum Annealing
Könz, Mario S.; Lechner, Wolfgang; Katzgraber, Helmut G.; et al. (2021)
PRX Quantum
In order to treat all-to-all-connected quadratic binary optimization problems (QUBOs) with hard- ware quantum annealers, an embedding of the original problem is required due to the sparsity of the topology of the hardware. The embedding of fully connected graphs-typically found in industrial applications incurs a quadratic space overhead and thus a significant overhead in the time to solution. Here, we investigate this embedding penalty of established planar embedding schemes such as square-lattice embedding, embedding on a chimera lattice, and the Lechner-Hauke-Zoller scheme, using simulated quantum annealing on classical hardware. Large-scale quantum Monte Carlo simulation suggests a polynomial time-to-solution overhead. Our results demonstrate that standard analog quantum annealing hardware is at a disadvantage in comparison to classical digital annealers, as well as gate-model quantum annealers, and could also serve as a benchmark for improvements of the standard quantum annealing protocol.
Distributed quantum computing with qmpi
Häner, Thomas; Steiger, Damian S.; Hoefler, Torsten; et al. (2021)
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '21)
Practical applications of quantum computers require millions of physical qubits and it will be challenging for individual quantum processors to reach such qubit numbers. It is therefore timely to investigate the resource requirements of quantum algorithms in a distributed setting, where multiple quantum processors are interconnected by a coherent network. We introduce an extension of the Message Passing Interface (MPI) to enable high-performance implementations of distributed quantum algorithms. In turn, these implementations can be used for testing, debugging, and resource estimation. In addition to a prototype implementation of quantum MPI, we present a performance model for distributed quantum computing, SENDQ. The model is inspired by the classical LogP model, making it useful to inform algorithmic decisions when programming distributed quantum computers. Specifically, we consider several optimizations of two quantum algorithms for problems in physics and chemistry, and we detail their effects on performance in the SENDQ model.
Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium
Davies, Neil; Field, Dawn; Gavaghan, David; et al. (2016)
GigaScience
Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine–terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions.
Thermodynamics and Magnetic Properties of the Anisotropic 3D Hubbard Model
Imriška, Jakub; Iazzi, Mauro; Wang, Lei; et al. (2014)
Physical Review Letters
Fermionic quantum critical point of spinless fermions on a honeycomb lattice
Wang, Lei; Corboz, Philippe; Troyer, Matthias (2014)
New Journal of Physics
Spinless fermions on a honeycomb lattice provide a minimal realization of lattice Dirac fermions. Repulsive interactions between nearest neighbors drive a quantum phase transition from a Dirac semimetal to a charge-density-wave state through a fermionic quantum critical point, where the coupling of the Ising order parameter to the Dirac fermions at low energy drastically affects the quantum critical behavior. Encouraged by a recent discovery (Huffman and Chandrasekharan 2014 Phys. Rev. B 89 111101) of the absence of the fermion sign problem in this model, we study the fermionic quantum critical point using the continuous-time quantum Monte Carlo method with a worm-sampling technique. We estimate the transition point $V/t=1.356(1)$ with the critical exponents $\nu =0.80(3)$ and $\eta =0.302(7)$. Compatible results for the transition point are also obtained with infinite projected entangled-pair states.
Solving the quantum many-body problem with artificial neural networks
Carleo, Giuseppe; Troyer, Matthias (2017)
Science
The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in the exponential complexity of the many-body wave function. Here we demonstrate that systematic machine learning of the wave function can reduce this complexity to a tractable computational form for some notable cases of physical interest. We introduce a variational representation of quantum states based on artificial neural networks with a variable number of hidden neurons. A reinforcement-learning scheme we demonstrate is capable of both finding the ground state and describing the unitary time evolution of complex interacting quantum systems. Our approach achieves high accuracy in describing prototypical interacting spins models in one and two dimensions.
Independent quality assessment of a commercial quantum random number generator
Petrov, Mikhail; Radchenko, Igor; Steiger, Damian; et al. (2022)
EPJ Quantum Technology
We reverse-engineer, test and analyse hardware and firmware of the commercial quantum-optical random number generator Quantis from ID Quantique. We show that > 99% of its output data originates in physically random processes: random timing of photon absorption in a semiconductor material, and random growth of avalanche owing to impact ionisation. Under a strong assumption that these processes correspond to a measurement of an initially pure state of the components, our analysis implies the unpredictability of the generated randomness. We have also found minor non-random contributions from imperfections in detector electronics and an internal processing algorithm, specific to this particular device. Our work shows that the design quality of a commercial quantum-optical randomness source can be verified without cooperation of the manufacturer and without access to the engineering documentation.

Publications 1 - 10 of 63

Matthias Troyer

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