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Moritz Schmidt

Publications and source records attributed to Moritz Schmidt.

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Resource-adaptive distributed fault tolerance with very noisy Bell pairs

Distributed architectures have been proposed as a pathway to large-scale quantum computers. Combined with the need for fault-tolerance, such architectures require distributed quantum error correction (DQEC) and distributed logical gates. An important challenge is how to realize DQEC primitives in the setting where interaction between modules is restricted to shared Bell pairs that are significantly noisier than on-chip operations. We extend the framework known as fault tolerance by construction to this setting, deriving different strategies for handling the additional noise. Through fault-improvement we recover conventional entanglement distillation, and also find more dynamical protocols that enable space-time trade-offs. We show that integrated decoding halves the required distillation code distance compared to entanglement distillation implemented using separate decoding, thus requiring significantly fewer Bell pairs. As a main focus of the work, we synthesize efficient circuits for an important primitive in distributed fault tolerance: distributed stabilizer measurements. These circuits can be adapted to resource constraints, e.g. on the Bell pair generation rate or the space available for on-chip auxiliary qubits. Noting that full local fault-tolerance is not always needed to preserve the correct scaling of logical error rates, we further optimize the circuits depending on the surrounding context. We consider in particular the surface code and the color code, both as distributed memories and in the case of lattice surgery across separate modules. Here, robustness to certain hook and readout errors reduces the number of required Bell pairs even further, compared to the context-free setting. We numerically benchmark the resulting implementations under circuit level noise with additional interconnect noise.

quant-ph

Exploration of Design Alternatives for Reducing Idle Time in Shor's Algorithm: A Study on Monolithic and Distributed Quantum Systems

Shor's algorithm is one of the most prominent quantum algorithms, yet finding efficient implementations remains an active research challenge. While many approaches focus on low-level modular arithmetic optimizations, a broader perspective can provide additional opportunities for improvement. By adopting a mid-level abstraction, we analyze the algorithm as a sequence of computational tasks, enabling systematic identification of idle time and optimization of execution flow. Building on this perspective, we first introduce an alternating design approach to minimize idle time while preserving qubit efficiency in Shor's algorithm. By strategically reordering tasks for simultaneous execution, we achieve a substantial reduction in overall execution time. Extending this approach to distributed implementations, we demonstrate how task rearrangement enhances execution efficiency in the presence of multiple distribution channels. Furthermore, to effectively evaluate the impact of design choices, we employ static timing analysis (STA) -- a technique from classical circuit design -- to analyze circuit delays while accounting for hardware-specific execution characteristics, such as measurement and reset delays in monolithic architectures and ebit generation time in distributed settings. Finally, we validate our approach by integrating modular exponentiation circuits from QRISP and constructing circuits for factoring numbers up to 64 bits. Through an extensive study across neutral atom, superconducting, and ion trap quantum computing platforms, we analyze circuit delays, highlighting trade-offs between qubit efficiency and execution time. Our findings provide a structured framework for optimizing compiled quantum circuits for Shor's algorithm, tailored to specific hardware constraints.

quant-ph

A Concept for User-Centered Delegation of Abstract High-Level Tasks to Cobots for Flexible Lot Sizes

Technical advances in collaborative robots (cobots) are making them increasingly attractive to companies. However, many human operators are not trained to program complex machines. Instead, humans are used to communicating with each other on a task-based level rather than through specific instructions, as is common with machines. The gap between low-level instruction-based and high-level task-based communication leads to low values for usability scores of teach pendant programming. As a solution, we propose a task-based interaction concept that allows human operators to delegate a complex task to a machine without programming by specifying a task via triplets. The concept is based on task decomposition and a reasoning system using a cognitive architecture. The approach is evaluated in an industrial use case where mineral cast basins have to be sanded by a cobot in a crafts enterprise.

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