arXiv subjects

Sarah Schneider

Publications and source records attributed to Sarah Schneider.

3 recordsLinked to original sources

arXiv2025

A SAT Encoding for Optimal Clifford Circuit Synthesis

Executing quantum algorithms on a quantum computer requires compilation to representations that conform to all restrictions imposed by the device. Due to devices' limited coherence times and gate fidelities, the compilation process has to be optimized as much as possible. To this end, an algorithm's description first has to be synthesized using the device's gate library. In this paper, we consider the optimal synthesis of Clifford circuits -- an important subclass of quantum circuits, with various applications. Such techniques are essential to establish lower bounds for (heuristic) synthesis methods and gauging their performance. Due to the huge search space, existing optimal techniques are practically limited to small qubit counts (around six qubits for typical instances). In this work, we propose an optimal synthesis method for Clifford circuits based on encoding the task as a satisfiability (SAT) problem and solving it using a SAT solver in conjunction with a binary search scheme. Experiments on random instances with up to 6 qubits demonstrate that state-of-the-art heuristics on average produce more than twice the number of gates necessary.

quant-ph↗

arXiv2023

NovelCraft: A Dataset for Novelty Detection and Discovery in Open Worlds

In order for artificial agents to successfully perform tasks in changing environments, they must be able to both detect and adapt to novelty. However, visual novelty detection research often only evaluates on repurposed datasets such as CIFAR-10 originally intended for object classification, where images focus on one distinct, well-centered object. New benchmarks are needed to represent the challenges of navigating the complex scenes of an open world. Our new NovelCraft dataset contains multimodal episodic data of the images and symbolic world-states seen by an agent completing a pogo stick assembly task within a modified Minecraft environment. In some episodes, we insert novel objects of varying size within the complex 3D scene that may impact gameplay. Our visual novelty detection benchmark finds that methods that rank best on popular area-under-the-curve metrics may be outperformed by simpler alternatives when controlling false positives matters most. Further multimodal novelty detection experiments suggest that methods that fuse both visual and symbolic information can improve time until detection as well as overall discrimination. Finally, our evaluation of recent generalized category discovery methods suggests that adapting to new imbalanced categories in complex scenes remains an exciting open problem.

cs.CV↗

arXiv2022

Limiting the Search Space in Optimal Quantum Circuit Mapping

Executing quantum circuits on currently available quantum computers requires compiling them to a representation that conforms to all restrictions imposed by the targeted architecture. Due to the limited connectivity of the devices' physical qubits, an important step in the compilation process is to map the circuit in such a way that all its gates are executable on the hardware. Existing solutions delivering optimal solutions to this task are severely challenged by the exponential complexity of the problem. In this paper, we show that the search space of the mapping problem can be limited drastically while still preserving optimality. The proposed strategies are generic, architecture-independent, and can be adapted to various mapping methodologies. The findings are backed by both, theoretical considerations and experimental evaluations. Results confirm that, by limiting the search space, optimal solutions can be determined for instances that timeouted before or speed-ups of up to three orders of magnitude can be achieved.

quant-ph↗