168 citations · 668 across the 22 of their papers we have counts for
22 papers
Blockchain with proof of quantum work
Mohammad H. Amin, Jack Raymond, Daniel Kinn +7
We propose a blockchain architecture in which mining requires a quantum computer. The consensus mechanism is based on proof of quantum work, a quantum-enhanced alternative to tradi…
Parallelized Computation and Backpropagation Under Angle-Parametrized Orthogonal Matrices
Firas Hamze
We present a methodology for parallel acceleration of learning in the presence of matrix orthogonality and unitarity constraints of interest in several branches of machine learning…
Chook -- A comprehensive suite for generating binary optimization problems with planted solutions
Dilina Perera, Inimfon Akpabio, Firas Hamze +4
We present Chook, an open-source Python-based tool to generate discrete optimization problems of tunable complexity with a priori known solutions. Chook provides a cross-platform u…
Computational hardness of spin-glass problems with tile-planted solutions
Dilina Perera, Firas Hamze, Jack Raymond +2
We investigate the computational hardness of spin-glass instances on a square lattice, generated via a recently introduced tunable and scalable approach for planting solutions. The…
The Wishart planted ensemble: A tunably-rugged pairwise Ising model with a first-order phase transition
Firas Hamze, Jack Raymond, Christopher A. Pattison +2
We propose the Wishart planted ensemble, a class of zero-field Ising models with tunable algorithmic hardness and specifiable (or planted) ground state. The problem class arises fr…
Learning to find order in disorder
Humberto Munoz-Bauza, Firas Hamze, Helmut G. Katzgraber
We introduce the use of neural networks as classifiers on classical disordered systems with no spatial ordering. In this study, we implement a convolutional neural network trained…
From Near to Eternity: Spin-glass planting, tiling puzzles, and constraint satisfaction problems
Firas Hamze, Darryl C. Jacob, Andrew J. Ochoa +3
We present a methodology for generating Ising Hamiltonians of tunable complexity and with a priori known ground states based on a decomposition of the model graph into edge-disjoin…
Discrete Equilibrium Sampling with Arbitrary Nonequilibrium Processes
Firas Hamze, Evgeny Andryash
We present a novel framework for performing statistical sampling, expectation estimation, and partition function approximation using \emph{arbitrary} heuristic stochastic processes…
Best-case performance of quantum annealers on native spin-glass benchmarks: How chaos can affect success probabilities
Zheng Zhu, Andrew J. Ochoa, Stefan Schnabel +2
Recent tests performed on the D-Wave Two quantum annealer have revealed no clear evidence of speedup over conventional silicon-based technologies. Here, we present results from cla…
Seeking Quantum Speedup Through Spin Glasses: The Good, the Bad, and the Ugly
Helmut G. Katzgraber, Firas Hamze, Zheng Zhu +2
There has been considerable progress in the design and construction of quantum annealing devices. However, a conclusive detection of quantum speedup over traditional silicon-based…
Erratum: Glassy Chimeras Could Be Blind to Quantum Speedup. . . [Phys. Rev. X 4, 021008 (2014)]
Martin Weigel, Helmut G. Katzgraber, Jonathan Machta +2
Erratum to Phys. Rev. X 4, 021008 (2014): The critical exponent associated with the ferromagnetic susceptibility was computed incorrectly. Furthermore, Ising ferromagnets on the Ch…
Glassy Chimeras could be blind to quantum speedup: Designing better benchmarks for quantum annealing machines
Helmut G. Katzgraber, Firas Hamze, Ruben S. Andrist
Recently, a programmable quantum annealing machine has been built that minimizes the cost function of hard optimization problems by adiabatically quenching quantum fluctuations. Te…
From Fields to Trees
Firas Hamze, Nando de Freitas
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demons…
Large-Flip Importance Sampling
Firas Hamze, Nando de Freitas
We propose a new Monte Carlo algorithm for complex discrete distributions. The algorithm is motivated by the N-Fold Way, which is an ingenious event-driven MCMC sampler that avoids…
Intracluster Moves for Constrained Discrete-Space MCMC
Firas Hamze, Nando de Freitas
This paper addresses the problem of sampling from binary distributions with constraints. In particular, it proposes an MCMC method to draw samples from a distribution of the set of…
Self-Avoiding Random Dynamics on Integer Complex Systems
Firas Hamze, Ziyu Wang, Nando de Freitas
This paper introduces a new specialized algorithm for equilibrium Monte Carlo sampling of binary-valued systems, which allows for large moves in the state space. This is achieved b…
Bayesian Optimization for Adaptive MCMC
Nimalan Mahendran, Ziyu Wang, Firas Hamze +1
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to non-differentiable objective functions and trades off explorat…
Investigating the Performance of an Adiabatic Quantum Optimization Processor
Kamran Karimi, Neil G. Dickson, Firas Hamze +6
Adiabatic quantum optimization offers a new method for solving hard optimization problems. In this paper we calculate median adiabatic times (in seconds) determined by the minimum…
A Performance Comparison of CUDA and OpenCL
Kamran Karimi, Neil G. Dickson, Firas Hamze
CUDA and OpenCL are two different frameworks for GPU programming. OpenCL is an open standard that can be used to program CPUs, GPUs, and other devices from different vendors, while…
Robust Parameter Selection for Parallel Tempering
Firas Hamze, Neil Dickson, Kamran Karimi
This paper describes an algorithm for selecting parameter values (e.g. temperature values) at which to measure equilibrium properties with Parallel Tempering Monte Carlo simulation…
Importance of Explicit Vectorization for CPU and GPU Software Performance
Neil G. Dickson, Kamran Karimi, Firas Hamze
Much of the current focus in high-performance computing is on multi-threading, multi-computing, and graphics processing unit (GPU) computing. However, vectorization and non-paralle…
High-Performance Physics Simulations Using Multi-Core CPUs and GPGPUs in a Volunteer Computing Context
Kamran Karimi, Neil G. Dickson, Firas Hamze
This paper presents two conceptually simple methods for parallelizing a Parallel Tempering Monte Carlo simulation in a distributed volunteer computing context, where computers belo…