85 citations · 86 across the 8 of their papers we have counts for
9 papers
EMBER: Predicting TCR--pMHC Binding Without a Docked Complex
Lin Ha, Chen Zhou, Haozheng Luo +3
We propose EMBER, a structure-based framework for TCR--pMHC binding prediction that eliminates the need for a predicted docked complex, and with it the placement error that dominat…
X-Z Round Scheduling for the Surface Code with Defects under Biased Noise
Lakshika Rathi, Pau Escofet, Joshua Viszlai +1
Fault-tolerant Quantum Computing (FTQC) relies on Quantum Error Correction (QEC) codes that encode logical qubits across many physical qubits to detect and correct errors. The surf…
An Analysis of Speculative Window Decoders for Quantum Error Correction
Jocelyn Li, Margaret Martonosi
Fault-tolerant quantum computing is essential for realizing the substantial computational speedups that quantum computing can bring, but it requires real-time error decoding with h…
PropHunt: Automated Optimization of Quantum Syndrome Measurement Circuits
Joshua Viszlai, Satvik Maurya, Swamit Tannu +2
Fault-Tolerant Quantum Computing (FTQC) relies on Quantum Error Correction (QEC) codes to reach error rates necessary for large scale quantum applications. At a physical level, QEC…
Statistical Assertions for Debugging Quantum Circuits and States in CUDA-Q
Jocelyn Li, Ella Rubinshtein, Margaret Martonosi
As quantum computing continues to mature, more developers are designing, coding, and simulating quantum circuits. A challenge exists, however, in debugging quantum circuits, partic…
TensorQC: Towards Scalable Distributed Quantum Computing via Tensor Networks
Wei Tang, Margaret Martonosi
A quantum processing unit (QPU) must contain a large number of high quality qubits to produce accurate results for problems at useful scales. In contrast, most scientific and indus…
Muchisim: A Simulation Framework for Design Exploration of Multi-Chip Manycore Systems
Marcelo Orenes-Vera, Esin Tureci, Margaret Martonosi +1
The design space exploration of scaled-out manycores for communication-intensive applications (e.g., graph analytics and sparse linear algebra) is hampered due to either lack of sc…
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Yuri Alexeev, Maximilian Amsler, Paul Baity +124
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…
21st Century Computer Architecture
Mark D. Hill, Sarita Adve, Luis Ceze +7
Because most technology and computer architecture innovations were (intentionally) invisible to higher layers, application and other software developers could reap the benefits of…