activity
20182026
most citedFrom pulses to circuits and back again: A quantum optimal control perspective on variational quantum algorithms

105 citations · 407 across the 23 of their papers we have counts for

collaborators

24 papers

quant-ph2026

A Model Predictive Control-Inspired Quantum Algorithm

Dominic Messina, Alicia B. Magann, Mohan Sarovar +1

We introduce a new hybrid quantum-classical algorithm inspired by an advanced control strategy known as model predictive control (MPC). This algorithm unifies the optimization-base…

quant-ph2026

Trajectory-independent speed limits for controlled open quantum systems

James B. Larsen, Tameem Albash, Alicia B. Magann +1

Existing quantum speed limits for controlled open quantum systems depend on the specified trajectory. For example, lower bounds on quantum annealing times in the presence of dissip…

quant-ph2026

Learning parameter curves in feedback-based quantum algorithms

Vicente Peña Pérez, Matthew D. Grace, Christian Arenz +1

Feedback-based quantum algorithms (FQAs) operate by iteratively growing a quantum circuit to optimize a given task. At each step, feedback from qubit measurements is used to inform…

quant-ph2025

Fast-feedback protocols for calibration and drift control in quantum computers

Alicia B. Magann, Nathan E. Miller, Robin Blume-Kohout +2

We introduce two classes of lightweight, adaptive calibration protocols for quantum computers that leverage fast feedback. The first enables shot-by-shot updates to device paramete…

quant-ph2025

Platform Architecture for Tight Coupling of High-Performance Computing with Quantum Processors

Shane A. Caldwell, Moein Khazraee, Elena Agostini +27

We propose an architecture, called NVQLink, for connecting high-performance computing (HPC) resources to the control system of a quantum processing unit (QPU) to accelerate workloa…

quant-ph2024

Non-Variational ADAPT algorithm for quantum simulations

Ho Lun Tang, Yanzhu Chen, Prakriti Biswas +3

We explore a non-variational quantum state preparation approach combined with the ADAPT operator selection strategy in the application of preparing the ground state of a desired ta…

quant-ph2024

Hamiltonian simulation in Zeno subspaces

Kasra Rajabzadeh Dizaji, Ariq Haqq, Alicia B. Magann +1

We investigate the quantum Zeno effect as a framework for designing and analyzing quantum algorithms for Hamiltonian simulation. We show that frequent projective measurements of an…

quant-ph2024★ 1 cited

Requirements for building effective Hamiltonians using quantum-enhanced density matrix downfolding

Shivesh Pathak, Antonio E. Russo, Stefan Seritan +4

Density matrix downfolding (DMD) is a technique for regressing low-energy effective Hamiltonians from quantum many-body Hamiltonians. One limiting factor in the accuracy of classic…

quant-ph2024★ 1 cited

Quantum Dynamical Emulation of Imaginary Time Evolution

Jacob M. Leamer, Alicia B. Magann, Denys I. Bondar +1

We introduce a constructive method for mapping non-unitary dynamics to a weighted set of unitary operations. We utilize this construction to derive a new correspondence between rea…

quant-ph2024★ 4 cited

Spectral gaps of two- and three-dimensional many-body quantum systems in the thermodynamic limit

Illya V. Lukin, Andrii G. Sotnikov, Jacob M. Leamer +2

We present an expression for the spectral gap, opening up new possibilities for performing and accelerating spectral calculations of quantum many-body systems. We develop and demon…

quant-ph2023★ 19 cited

HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware

Nicolas PD Sawaya, Daniel Marti-Dafcik, Yang Ho +13

In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum co…

quant-ph2023

Feedback-based quantum algorithms for ground state preparation

James B. Larsen, Matthew D. Grace, Andrew D. Baczewski +1

The ground state properties of quantum many-body systems are a subject of interest across chemistry, materials science, and physics. Thus, algorithms for finding ground states can…

quant-ph2023

Spectral Gaps via Imaginary Time

Jacob M. Leamer, Alicia B. Magann, Gerard McCaul +1

The spectral gap occupies a role of central importance in many open problems in physics. We present an approach for evaluating the spectral gap of a Hamiltonian from a simple ratio…

quant-ph2023★ 5 cited

Quantum tracking control of the orientation of symmetric top molecules

Alicia B. Magann, Tak-San Ho, Christian Arenz +1

The goal of quantum tracking control is to identify shaped fields to steer observable expectation values along designated time-dependent tracks. The fields are determined via an it…

quant-ph2023★ 13 cited

Randomized adaptive quantum state preparation

Alicia B. Magann, Sophia E. Economou, Christian Arenz

We develop an adaptive method for quantum state preparation that utilizes randomness as an essential component and that does not require classical optimization. Instead, a cost fun…

quant-ph2022★ 30 cited

Self-healing of Trotter error in digital adiabatic state preparation

Lucas K. Kovalsky, Fernando A. Calderon-Vargas, Matthew D. Grace +4

Adiabatic time evolution can be used to prepare a complicated quantum many-body state from one that is easier to synthesize and Trotterization can be used to implement such an evol…

quant-ph2021★ 37 cited

Lyapunov control-inspired strategies for quantum combinatorial optimization

Alicia B. Magann, Kenneth M. Rudinger, Matthew D. Grace +1

The prospect of using quantum computers to solve combinatorial optimization problems via the quantum approximate optimization algorithm (QAOA) has attracted considerable interest i…

quant-ph2021★ 45 cited

Progress toward favorable landscapes in quantum combinatorial optimization

Juneseo Lee, Alicia B. Magann, Herschel A. Rabitz +1

The performance of variational quantum algorithms relies on the success of using quantum and classical computing resources in tandem. Here, we study how these quantum and classical…

quant-ph2021★ 64 cited

Feedback-based quantum optimization

Alicia B. Magann, Kenneth M. Rudinger, Matthew D. Grace +1

It is hoped that quantum computers will offer advantages over classical computers for combinatorial optimization. Here, we introduce a feedback-based strategy for quantum optimizat…

quant-ph2020★ 11 cited

Sequential optical response suppression for chemical mixture characterization

Alicia B. Magann, Gerard McCaul, Herschel A. Rabitz +1

The characterization of mixtures of non-interacting, spectroscopically similar quantum components has important applications in chemistry, biology, and materials science. We introd…

quant-ph2020★ 105 cited

From pulses to circuits and back again: A quantum optimal control perspective on variational quantum algorithms

Alicia B. Magann, Christian Arenz, Matthew D. Grace +5

The last decade has witnessed remarkable progress in the development of quantum technologies. Although fault-tolerant devices likely remain years away, the noisy intermediate-scale…

quant-ph2020★ 39 cited

Digital quantum simulation of molecular dynamics and control

Alicia B. Magann, Matthew D. Grace, Herschel A. Rabitz +1

Optimally-shaped electromagnetic fields have the capacity to coherently control the dynamics of quantum systems and thus offer a promising means for controlling molecular transform…

quant-ph2018★ 8 cited

Optimal control of interacting quantum systems based on the first-order Magnus approximation: Application to multiple dipole-dipole coupled molecular rotors

Andrew Ma, Alicia B. Magann, Tak-San Ho +1

We develop a methodology for performing approximate optimal control simulations for quantum systems with multiple interacting degrees of freedom. The quantum dynamics are modeled u…

quant-ph2018★ 25 cited

Singularity-free quantum tracking control of molecular rotor orientation

Alicia Magann, Tak-San Ho, Herschel Rabitz

Quantum tracking control aims to identify applied fields to steer the expectation values of particular observables along desired paths in time. The associated temporal fields can b…