Alex McCaskey
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View article: The generative quantum eigensolver (GQE) and its application for ground state search
The generative quantum eigensolver (GQE) and its application for ground state search Open
We introduce the generative quantum eigensolver (GQE), a new quantum computational framework that operates outside the variational quantum algorithm paradigm by applying classical generative models to quantum simulation. The GQE algorithm …
View article: Introduction to the Special Issue on Software Tools for Quantum Computing: Part 2
Introduction to the Special Issue on Software Tools for Quantum Computing: Part 2 Open
Quantum computing is emerging as a remarkable technology that offers the possibility of achieving major scientific breakthroughs in many areas. By leveraging the unique features of quantum mechanics, quantum computers may be instrumental i…
View article: Snowmass White Paper: Quantum Computing Systems and Software for High-energy Physics Research
Snowmass White Paper: Quantum Computing Systems and Software for High-energy Physics Research Open
Quantum computing offers a new paradigm for advancing high-energy physics research by enabling novel methods for representing and reasoning about fundamental quantum mechanical phenomena. Realizing these ideals will require the development…
View article: Enabling a Programming Environment for an Experimental Ion Trap Quantum Testbed
Enabling a Programming Environment for an Experimental Ion Trap Quantum Testbed Open
Ion trap quantum hardware promises to provide a computational advantage over classical computing for specific problem spaces while also providing an alternative hardware implementation path to cryogenic quantum systems as typified by IBM's…
View article: HEP ML/Optimization Go Quantum – QuantISED Pilot
HEP ML/Optimization Go Quantum – QuantISED Pilot Open
This poster includes sections on: Quantum annealers for classification, Quantum gate models for classification, Software and Workflows, and Quanutm optimization for LHC physics.
View article: Density matrix based perturbative corrections for improved quantum simulation accuracy
Density matrix based perturbative corrections for improved quantum simulation accuracy Open
We present error mitigation (EM) techniques for noisy intermediate-scale quantum computers (QC) based on density matrix purification and perturbative corrections to the target energy. We incorporate this scheme into the variational quantum…
View article: Scalar quantum field theories as a benchmark for near-term quantum computers
Scalar quantum field theories as a benchmark for near-term quantum computers Open
Quantum field theory (QFT) simulations are a potentially important application for noisy intermediate scale quantum (NISQ) computers. The ability of a quantum computer to emulate a QFT therefore constitutes a natural application-centric be…
View article: Quantum-classical computation of Schwinger model dynamics using quantum computers
Quantum-classical computation of Schwinger model dynamics using quantum computers Open
We present a quantum-classical algorithm to study the dynamics of the\ntwo-spatial-site Schwinger model on IBM's quantum computers. Using rotational\nsymmetries, total charge, and parity, the number of qubits needed to perform\ncomputation…
View article: Cloud Quantum Computing of an Atomic Nucleus
Cloud Quantum Computing of an Atomic Nucleus Open
We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary couple…
View article: Quantum-Classical Dynamical Calculations of the Schwinger Model using Quantum Computers
Quantum-Classical Dynamical Calculations of the Schwinger Model using Quantum Computers Open
We present a quantum-classical algorithm to study the dynamics of the two-spatial-site Schwinger model on IBM's quantum computers. Using rotational symmetries, total charge, and parity, the number of qubits needed to perform computation is…
View article: Recall Performance for Content-Addressable Memory Using Adiabatic Quantum Optimization
Recall Performance for Content-Addressable Memory Using Adiabatic Quantum Optimization Open
A content-addressable memory (CAM) stores key-value associations such that the key is recalled by providing its associated value. While CAM recall is traditionally performed using recurrent neural network models, we show how to solve this …
View article: Virtual Integrated Battery Environment (VIBE): Version 1.2 Release Documentation
Virtual Integrated Battery Environment (VIBE): Version 1.2 Release Documentation Open
As part of the CAEBAT (Computer Aided Engineering for Batteries) activities, ORNL developed a flexible, robust, and computationally scalable open-architecture framework that integrates multi-physics and multi-scale battery models. The phys…