Data Needs and Challenges of Quantum Dot Devices Automation: Workshop Report

Kavli Affiliate: Eliska Greplova | First 5 Authors: Justyna P. Zwolak, Jacob M. Taylor, Reed Andrews, Jared Benson, Garnett Bryant | Summary: Gate-defined quantum dots are a promising candidate system to realize scalable, coupled qubit systems and serve as a fundamental building block for quantum computers. However, present-day quantum dot devices suffer from imperfections that […]


Continue.. Data Needs and Challenges of Quantum Dot Devices Automation: Workshop Report

Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Akel Hashim, Arnaud Carignan-Dugas, Larry Chen, Christian Juenger, Neelay Fruitwala | Summary: Quantum measurements are a fundamental component of quantum computing. However, on modern-day quantum computers, measurements can be more error prone than quantum gates, and are susceptible to non-unital errors as well as non-local correlations due […]


Continue.. Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Akel Hashim, Arnaud Carignan-Dugas, Larry Chen, Christian Juenger, Neelay Fruitwala | Summary: Quantum measurements are a fundamental component of quantum computing. However, on modern-day quantum computers, measurements can be more error prone than quantum gates, and are susceptible to nonunital errors as well as non-local correlations due […]


Continue.. Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Akel Hashim, Arnaud Carignan-Dugas, Larry Chen, Christian Juenger, Neelay Fruitwala | Summary: Quantum measurements are a fundamental component of quantum computing. However, on modern-day quantum computers, measurements can be more error prone than quantum gates, and are susceptible to non-unital errors as well as non-local correlations due […]


Continue.. Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Akel Hashim, Arnaud Carignan-Dugas, Larry Chen, Christian Juenger, Neelay Fruitwala | Summary: Quantum measurements are a fundamental component of quantum computing. However, on modern-day quantum computers, measurements can be more error prone than quantum gates, and are susceptible to non-unital errors as well as non-local correlations due […]


Continue.. Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling

Morphologies of Bright Complex Fast Radio Bursts with CHIME/FRB Voltage Data

Kavli Affiliate: Kiyoshi W. Masui | First 5 Authors: Jakob T. Faber, Daniele Michilli, Ryan Mckinven, Jianing Su, Aaron B. Pearlman | Summary: We present the discovery of twelve thus far non-repeating fast radio burst (FRB) sources, detected by the Canadian Hydrogen Intensity Mapping Experiment (CHIME) telescope. These sources were selected from a database comprising […]


Continue.. Morphologies of Bright Complex Fast Radio Bursts with CHIME/FRB Voltage Data

Real-time Neural Network Inference on Extremely Weak Devices: Agile Offloading with Explainable AI

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Wei Gao, , , | Summary: With the wide adoption of AI applications, there is a pressing need of enabling real-time neural network (NN) inference on small embedded devices, but deploying NNs and achieving high performance of NN inference on these small devices is challenging […]


Continue.. Real-time Neural Network Inference on Extremely Weak Devices: Agile Offloading with Explainable AI

ElasticTrainer: Speeding Up On-Device Training with Runtime Elastic Tensor Selection

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Boyuan Yang, Wei Gao, , | Summary: On-device training is essential for neural networks (NNs) to continuously adapt to new online data, but can be time-consuming due to the device’s limited computing power. To speed up on-device training, existing schemes select trainable NN portion offline […]


Continue.. ElasticTrainer: Speeding Up On-Device Training with Runtime Elastic Tensor Selection

Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning

Kavli Affiliate: Yi Zhou | First 5 Authors: Desai Xie, Jiahao Li, Hao Tan, Xin Sun, Zhixin Shu | Summary: Multi-view diffusion models, obtained by applying Supervised Finetuning (SFT) to text-to-image diffusion models, have driven recent breakthroughs in text-to-3D research. However, due to the limited size and quality of existing 3D datasets, they still suffer […]


Continue.. Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning

Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning

Kavli Affiliate: Yi Zhou | First 5 Authors: Desai Xie, Jiahao Li, Hao Tan, Xin Sun, Zhixin Shu | Summary: Recent advancements in the text-to-3D task leverage finetuned text-to-image diffusion models to generate multi-view images, followed by NeRF reconstruction. Yet, existing supervised finetuned (SFT) diffusion models still suffer from multi-view inconsistency and the resulting NeRF […]


Continue.. Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning