arXiv subjects

Ana Tudor

Publications and source records attributed to Ana Tudor.

3 recordsLinked to original sources

arXiv2023

Inclusive Study Group Formation At Scale

Underrepresented students face many significant challenges in their education. In particular, they often have a harder time than their peers from majority groups in building long-term high-quality study groups. This challenge is exacerbated in remote-learning scenarios, where students are unable to meet face-to-face and must rely on pre-existing networks for social support. We present a scalable system that removes structural obstacles faced by underrepresented students and supports all students in building inclusive and flexible study groups. One of our main goals is to make the traditionally informal and unstructured process of finding study groups for homework more equitable by providing a uniform but lightweight structure. We aim to provide students from underrepresented groups an experience that is similar in quality to that of students from majority groups. Our process is unique in that it allows students the opportunity to request group reassignments during the semester if they wish. Unlike other collaboration tools our system is not mandatory and does not use peer-evaluation. We trialed our approach in a 1000+ student introductory Engineering and Computer Science course that was conducted entirely online during the COVID-19 pandemic. We find that students from underrepresented backgrounds were more likely to ask for group-matching support compared to students from majority groups. At the same time, underrepresented students that we matched into study groups had group experiences that were comparable to students we matched from majority groups. B-range students in high-comfort and high-quality groups had improved learning outcomes.

cs.CY↗

arXiv2021

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices

We present a collection of optimizers tuned for usage on Noisy Intermediate-Scale Quantum (NISQ) devices. Optimizers have a range of applications in quantum computing, including the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization (QAOA) algorithms. They are also used for calibration tasks, hyperparameter tuning, in machine learning, etc. We analyze the efficiency and effectiveness of different optimizers in a VQE case study. VQE is a hybrid algorithm, with a classical minimizer step driving the next evaluation on the quantum processor. While most results to date concentrated on tuning the quantum VQE circuit, we show that, in the presence of quantum noise, the classical minimizer step needs to be carefully chosen to obtain correct results. We explore state-of-the-art gradient-free optimizers capable of handling noisy, black-box, cost functions and stress-test them using a quantum circuit simulation environment with noise injection capabilities on individual gates. Our results indicate that specifically tuned optimizers are crucial to obtaining valid science results on NISQ hardware, and will likely remain necessary even for future fault tolerant circuits.

quant-ph↗

arXiv2019

Heuristics for Quantum Compiling with a Continuous Gate Set

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As accurate CNOT gates are hard for the foreseeable Noisy- Intermediate-Scale Quantum devices era, our A* inspired algorithm attempts to minimize their count, while accounting for connectivity. We discuss the search strategy together with metrics to expand the solution frontier. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4x average (up to 5.3x) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set, while obtaining similar quality results. We believe that empirical tools like ours can facilitate algorithmic exploration, gate set discovery for quantum processor designers, as well as providing useful optimization blocks within the quantum compilation tool-chain.

cs.ET↗