peterzoller starred hmlongco/Factory: A modern approach to Container-Based Dependency Injection for Swift and SwiftUI.
A modern approach to Container-Based Dependency Injection for Swift and SwiftUI.. Stars: 2806
Chronological feed of everything captured from Peter Zoller.
A modern approach to Container-Based Dependency Injection for Swift and SwiftUI.. Stars: 2806
Declarative list views for iOS apps.. Stars: 214
CryptoSwift is a growing collection of standard and secure cryptographic algorithms implemented in Swift. Stars: 10541
An exhaustive expansion of the standard SwiftUI library.. Stars: 8023
A Backend for ACRA written in Kotlin using Spring Boot, Vaadin and MySQL. Stars: 227
Acknowledgements screen displaying a list of licenses, for example from CocoaPods and Swift Package Manager dependencies.. Stars: 880
Coordinators in SwiftUI. Simple, powerful and elegant.. Stars: 960
A highly customizable calendar view and compose library for Android and Kotlin Multiplatform.. Stars: 5512
A tool to identify unused code in Swift projects.. Stars: 6071
☠️ An elegant way to show users that something is happening and also prepare them to which contents they are awaiting. Stars: 12865
The Swift (and Objective-C) testing framework.. Stars: 9832
A Matcher Framework for Swift and Objective-C. Stars: 4842
The Swift Programming Language. Stars: 69899
💧 A server-side Swift HTTP web framework.. Stars: 26023
Bitcoin Core integration/staging tree. Stars: 88798
A Flash Player emulator written in Rust. Stars: 17947
This paper introduces a bounded-error quantum simulation framework that quantifies uncertainties in predictions from analog quantum simulators. It combines Hamiltonian and Lindbladian Learning to infer coherent and dissipative dynamics, propagating their uncertainties to simulated observables. This approach enables rigorous uncertainty bounds, transforming quantum simulators into quantitative scientific tools capable of addressing complex many-body problems with verifiable accuracy, bridging the gap between experimental platforms and predictive many-body physics, including digital quantum simulation.
A novel protocol uses global time evolution and Loschmidt echo measurements to estimate ground-state energies and other observables in quantum many-body systems. This method bypasses the need for controlled operations, making it applicable to analog simulators. The approach demonstrates significantly improved precision over direct energy measurements and maintains accuracy even with hundreds of modes and experimental imperfections.
The proposed architecture leverages entangled atomic ensembles and optical clock qubits to emulate non-local mass superpositions across a programmable quantum network. By distributing Bell-type seed states via photonic channels and employing collective internal state addressing, the system creates a non-local Ramsey interferometer sensitive to gravitational redshift. This approach bypasses the spatial limitations of conventional interferometry while maintaining scalability to large atom numbers.
This work introduces a protocol for learning matrix-product operator (MPO) representations of experimentally prepared quantum states using classical shadows from local randomized measurements. The tensor optimization proceeds sequentially, analogous to DMRG, and is provably efficient for short-range correlated and noisy states. The method was experimentally validated on a superconducting processor with up to 96 qubits, marking a significant scaling milestone for quantum state tomography in realistic hardware settings.