Kevin Schultz
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View article: Sparse Non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations
Sparse Non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations Open
The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the eff…
View article: Mindfulness Practice Is Associated With Improved Well-Being and Reduced Injury Risk in Female NCAA Division I Athletes
Mindfulness Practice Is Associated With Improved Well-Being and Reduced Injury Risk in Female NCAA Division I Athletes Open
Background: Injury in sport is an inherent risk to participation, and it can have devastating consequences for the athlete, both mentally and physically. Previous research has found that impairments in well-being can increase the risk of i…
View article: Dynamically Generated Decoherence-Free Subspaces and Subsystems on Superconducting Qubits
Dynamically Generated Decoherence-Free Subspaces and Subsystems on Superconducting Qubits Open
Decoherence-free subspaces and subsystems (DFS) preserve quantum information by encoding it into symmetry-protected states unaffected by decoherence. An inherent DFS of a given experimental system may not exist; however, through the use of…
View article: Quantum Crosstalk Robust Quantum Control
Quantum Crosstalk Robust Quantum Control Open
The prevalence of quantum crosstalk in current quantum devices poses challenges for achieving high-fidelity quantum logic operations and reliable quantum processing. Through quantum control theory, we develop an analytical condition for ac…
View article: Bayesian optimization of distributed neurodynamical controller models for spatial navigation
Bayesian optimization of distributed neurodynamical controller models for spatial navigation Open
View article: Optimally Band-Limited Noise Filtering for Single Qubit Gates
Optimally Band-Limited Noise Filtering for Single Qubit Gates Open
We introduce a quantum control protocol that produces smooth, experimentally implementable control sequences optimized to combat temporally correlated noise for single qubit systems. The control ansatz is specifically chosen to be a functi…
View article: Provably Optimal Control for Multiplicative Amplitude Control Noise
Provably Optimal Control for Multiplicative Amplitude Control Noise Open
We provide a technique to obtain provably optimal control sequences for quantum systems under the influence of time-correlated multiplicative control noise. Utilizing the circuit-level noise model introduced in [Phys. Rev. Research 3, 0332…
View article: Universal-dephasing-noise injection via Schrödinger-wave autoregressive moving-average models
Universal-dephasing-noise injection via Schrödinger-wave autoregressive moving-average models Open
We present and validate a novel method for noise injection of arbitrary spectra in quantum circuits that can be applied to any system capable of executing arbitrary single qubit rotations, including cloud-based quantum processors. As the c…
View article: Analyzing the impact of time-correlated noise on zero-noise extrapolation
Analyzing the impact of time-correlated noise on zero-noise extrapolation Open
Zero-noise extrapolation is a quantum error mitigation technique that has typically been studied under the ideal approximation that the noise acting on a quantum device is not time-correlated. In this work, we investigate the feasibility a…
View article: Bayesian optimization of distributed neurodynamical controller models for spatial navigation
Bayesian optimization of distributed neurodynamical controller models for spatial navigation Open
Dynamical systems models for controlling multi-agent swarms have demonstrated advances toward resilient, decentralized navigation algorithms. We previously introduced the NeuroSwarms controller, in which agent-based interactions were model…
View article: Quantifying the Impact of Precision Errors on Quantum Approximate Optimization Algorithms
Quantifying the Impact of Precision Errors on Quantum Approximate Optimization Algorithms Open
The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm that seeks to achieve approximate solutions to optimization problems by iteratively alternating between intervals of controlled quantum evolution…
View article: Detecting Anomalous Swarming Agents With Graph Signal Processing
Detecting Anomalous Swarming Agents With Graph Signal Processing Open
Collective motion among biological organisms such as insects, fish, and birds has motivated considerable interest not only in biology but also in distributed robotic systems. In a robotic or biological swarm, anomalous agents (whether malf…
View article: Impact of correlations and heavy tails on quantum error correction
Impact of correlations and heavy tails on quantum error correction Open
We show that space- and time-correlated single-qubit rotation errors can lead\nto high-weight errors in a quantum circuit when the rotation angles are drawn\nfrom heavy-tailed distributions. This leads to a breakdown of quantum error\ncorr…
View article: Optimal control for quantum detectors
Optimal control for quantum detectors Open
Quantum systems are promising candidates for sensing of weak signals as they can be highly sensitive to external perturbations, thus providing excellent performance when estimating parameters of external fields. However, when trying to det…
View article: Analyzing Collective Motion Using Graph Fourier Analysis
Analyzing Collective Motion Using Graph Fourier Analysis Open
Collective motion in animal groups, such as swarms of insects, flocks of birds, and schools of fish, are some of the most visually striking examples of emergent behavior. Empirical analysis of these behaviors in experiment or computational…
View article: Graph Signal Processing for Infrastructure Resilience: Suitability and Future Directions
Graph Signal Processing for Infrastructure Resilience: Suitability and Future Directions Open
Graph signal processing (GSP) is an emerging field developed for analyzing signals defined on irregular spatial structures modeled as graphs. Given the considerable literature regarding the resilience of infrastructure networks using graph…
View article: Graph Signal Processing for Infrastructure Resilience: Suitability and\n Future Directions
Graph Signal Processing for Infrastructure Resilience: Suitability and\n Future Directions Open
Graph signal processing (GSP) is an emerging field developed for analyzing\nsignals defined on irregular spatial structures modeled as graphs. Given the\nconsiderable literature regarding the resilience of infrastructure networks\nusing gr…
View article: Graph Signal Processing of Indefinite and Complex Graphs using Directed Variation
Graph Signal Processing of Indefinite and Complex Graphs using Directed Variation Open
In the field of graph signal processing (GSP), directed graphs present a particular challenge for the "standard approaches" of GSP to due to their asymmetric nature. The presence of negative- or complex-weight directed edges, a graphical s…
View article: Graph Signal Processing of Indefinite and Complex Graphs using Directed\n Variation
Graph Signal Processing of Indefinite and Complex Graphs using Directed\n Variation Open
In the field of graph signal processing (GSP), directed graphs present a\nparticular challenge for the "standard approaches" of GSP to due to their\nasymmetric nature. The presence of negative- or complex-weight directed edges,\na graphica…
View article: An Exponential Family for Bayesian Process Tomography
An Exponential Family for Bayesian Process Tomography Open
By associating the Choi matrix form of a completely positive, trace preserving (CPTP) map with a particular space of matrices with orthonormal columns, called a Stiefel manifold, we present a particular probability distribution on the spac…
View article: Orientation Statistics and Quantum Information
Orientation Statistics and Quantum Information Open
Motivated by the engineering applications of uncertainty quantification, in this work we draw connections between the notions of random quantum states and operations in quantum information with probability distributions commonly encountere…