Tameem Albash
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View article: Cost of emulating a small quantum annealing problem in the circuit model
Cost of emulating a small quantum annealing problem in the circuit model Open
Demonstrations of quantum advantage for certain sampling problems have generated considerable excitement for quantum computing and have further spurred the development of circuit-model quantum computers, which represent quantum programs as…
View article: Model validation and error attribution for a drifting qubit
Model validation and error attribution for a drifting qubit Open
Qubit performance is often reported in terms of a variety of single-value metrics, each providing a facet of the underlying noise mechanism limiting performance. However, the value of these metrics may drift over long timescales, and repor…
View article: Temporal Coarse Graining for Classical Stochastic Noise in Quantum Systems
Temporal Coarse Graining for Classical Stochastic Noise in Quantum Systems Open
Simulations of quantum systems with Hamiltonian classical stochastic noise can be challenging when the noise exhibits temporal correlations over a multitude of time scales, such as for $1/f$ noise in solid-state quantum information process…
View article: Macroproperties vs. microstates in the classical simulation of critical phenomena in quench dynamics of 1D Ising models
Macroproperties vs. microstates in the classical simulation of critical phenomena in quench dynamics of 1D Ising models Open
We study the tractability of classically simulating critical phenomena in the quench dynamics of one-dimensional transverse field Ising models (TFIMs) using highly truncated matrix product states (MPSs). We focus on two paradigmatic exampl…
View article: Model validation and error attribution for a drifting qubit
Model validation and error attribution for a drifting qubit Open
Qubit performance is often reported in terms of a variety of single-value metrics, each providing a facet of the underlying noise mechanism limiting performance. However, the value of these metrics may drift over long time-scales, and repo…
View article: Hamiltonian learning using machine-learning models trained with continuous measurements
Hamiltonian learning using machine-learning models trained with continuous measurements Open
Here, we build upon recent work on the use of machine-learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning,…
View article: Optimizing Temperature Distributions for Training Neural Quantum States using Parallel Tempering
Optimizing Temperature Distributions for Training Neural Quantum States using Parallel Tempering Open
Parameterized artificial neural networks (ANNs) can be very expressive ansatzes for variational algorithms, reaching state-of-the-art energies on many quantum many-body Hamiltonians. Nevertheless, the training of the ANN can be slow and st…
View article: On the emerging potential of quantum annealing hardware for combinatorial optimization
On the emerging potential of quantum annealing hardware for combinatorial optimization Open
Over the past decade, the usefulness of quantum annealing hardware for combinatorial optimization has been the subject of much debate. Thus far, experimental benchmarking studies have indicated that quantum annealing hardware does not prov…
View article: Hamiltonian Learning using Machine Learning Models Trained with Continuous Measurements
Hamiltonian Learning using Machine Learning Models Trained with Continuous Measurements Open
We build upon recent work on using Machine Learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning where the w…
View article: Cost of Emulating a Small Quantum Annealing Problem in the Circuit-Model
Cost of Emulating a Small Quantum Annealing Problem in the Circuit-Model Open
Demonstrations of quantum advantage for certain sampling problems have generated considerable excitement for quantum computing and have further spurred the development of circuit-model quantum computers, which represent quantum programs as…
View article: Decoherence limiting the cost to simulate an anharmonic oscillator
Decoherence limiting the cost to simulate an anharmonic oscillator Open
We study how decoherence increases the efficiency with which we can simulate the quantum dynamics of an anharmonic oscillator governed by the Kerr effect. As decoherence washes out the fine-grained sub-Planck structure associated with phas…
View article: Macroproperties vs. Microstates in the Classical Simulation of Critical Phenomena in Quench Dynamics of 1D Ising Models
Macroproperties vs. Microstates in the Classical Simulation of Critical Phenomena in Quench Dynamics of 1D Ising Models Open
We study the tractability of classically simulating critical phenomena in the quench dynamics of one-dimensional transverse field Ising models (TFIMs) using highly truncated matrix product states (MPS). We focus on two paradigmatic example…
View article: Diabatic quantum annealing for the frustrated ring model
Diabatic quantum annealing for the frustrated ring model Open
Quantum annealing (QA) is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare…
View article: Decoherence Limits the Cost to Simulate an Anharmonic Oscillator
Decoherence Limits the Cost to Simulate an Anharmonic Oscillator Open
We study how decoherence increases the efficiency with which we can simulate the quantum dynamics of an anharmonic oscillator, governed by the Kerr effect. As decoherence washes out the fine-grained subPlanck structure associated with phas…
View article: Quantum-inspired tempering for ground state approximation using artificial neural networks
Quantum-inspired tempering for ground state approximation using artificial neural networks Open
A large body of work has demonstrated that parameterized artificial neural networks (ANNs) can efficiently describe ground states of numerous interesting quantum many-body Hamiltonians. However, the standard variational algorithms used to …
View article: Signatures of Open and Noisy Quantum Systems in Single-Qubit Quantum Annealing
Signatures of Open and Noisy Quantum Systems in Single-Qubit Quantum Annealing Open
We propose a quantum annealing protocol that effectively probes the dynamics of a single qubit on D-Wave's quantum annealing hardware. This protocol uses D-Wave's $h$-gain schedule functionality, which allows the rapid suppression of the l…
View article: Data for "Diabatic Quantum Annealing for the Frustrated Ring Model"
Data for "Diabatic Quantum Annealing for the Frustrated Ring Model" Open
This repository contains data for the paper "Diabatic Quantum Annealing for the Frustrated Ring Model". In particular, the Jupyter notebook within the repository reproduces the figures that contain data in our paper. We also include a Qisk…
View article: Data for "Diabatic Quantum Annealing for the Frustrated Ring Model"
Data for "Diabatic Quantum Annealing for the Frustrated Ring Model" Open
This repository contains data for the paper "Diabatic Quantum Annealing for the Frustrated Ring Model". In particular, the Jupyter notebook within the repository reproduces the figures that contain data in our paper. We also include a Qisk…
View article: Master equation emulation and coherence preservation with classical control of a superconducting qubit
Master equation emulation and coherence preservation with classical control of a superconducting qubit Open
Open quantum systems are a topic of intense theoretical research. The use of master equations to model a system's evolution subject to an interaction with an external environment is one of the most successful theoretical paradigms. General…
View article: Report on 2210.11405v2
Report on 2210.11405v2 Open
A large body of work has demonstrated that parameterized artificial neural networks (ANNs) can efficiently describe ground states of numerous interesting quantum many-body Hamiltonians.However, the standard variational algorithms used to u…
View article: Diabatic Quantum Annealing for the Frustrated Ring Model
Diabatic Quantum Annealing for the Frustrated Ring Model Open
Quantum annealing is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare grou…
View article: Data for "Diabatic Quantum Annealing for the Frustrated Ring Model"
Data for "Diabatic Quantum Annealing for the Frustrated Ring Model" Open
This repository contains data for the paper "Diabatic Quantum Annealing for the Frustrated Ring Model". In particular, the Jupyter notebook within the repository reproduces the figures that contain data in our paper.
View article: Quantum-Inspired Tempering for Ground State Approximation using Artificial Neural Networks
Quantum-Inspired Tempering for Ground State Approximation using Artificial Neural Networks Open
A large body of work has demonstrated that parameterized artificial neural networks (ANNs) can efficiently describe ground states of numerous interesting quantum many-body Hamiltonians. However, the standard variational algorithms used to …
View article: On the Emerging Potential of Quantum Annealing Hardware for Combinatorial Optimization
On the Emerging Potential of Quantum Annealing Hardware for Combinatorial Optimization Open
Over the past decade, the usefulness of quantum annealing hardware for combinatorial optimization has been the subject of much debate. Thus far, experimental benchmarking studies have indicated that quantum annealing hardware does not prov…
View article: Signatures of Open and Noisy Quantum Systems in Single-Qubit Quantum Annealing
Signatures of Open and Noisy Quantum Systems in Single-Qubit Quantum Annealing Open
We propose a quantum annealing protocol that more effectively probes the dynamics of a single qubit on D-Wave’s quantum annealing hardware. This protocol uses D-Wave’s h-gain schedule functionality, which allows the rapid quenching of the …
View article: Signatures of Open and Noisy Quantum Systems in Single-Qubit Quantum Annealing
Signatures of Open and Noisy Quantum Systems in Single-Qubit Quantum Annealing Open
We propose a quantum annealing protocol that more effectively probes the dynamics of a single qubit on D-Wave's quantum annealing hardware. This protocol uses D-Wave's h-gain schedule functionality, which allows the rapid quenching of the …
View article: High-Quality Thermal Gibbs Sampling with Quantum Annealing Hardware
High-Quality Thermal Gibbs Sampling with Quantum Annealing Hardware Open
Quantum Annealing (QA) was originally intended for accelerating the solution of combinatorial optimization tasks that have natural encodings as Ising models. However, recent experiments on QA hardware platforms have demonstrated that, in t…
View article: Customized Quantum Annealing Schedules
Customized Quantum Annealing Schedules Open
In a typical quantum annealing protocol, the system starts with a transverse\nfield Hamiltonian which is gradually turned off and replaced by a longitudinal\nIsing Hamiltonian. The ground state of the Ising Hamiltonian encodes the\nsolutio…