6 citations · 18 across the 17 of their papers we have counts for
17 papers
Distributionally Robust Circuit Design Optimization under Variation Shifts
Yifan Pan, Zichang He, Nanlin Guo +1
Due to the significant process variations, designers have to optimize the statistical performance distribution of nano-scale IC design in most cases. This problem has been investig…
Distributionally Robust Variational Quantum Algorithms with Shifted Noise
Zichang He, Bo Peng, Yuri Alexeev +1
Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been develo…
QuYBE -- An Algebraic Compiler for Quantum Circuit Compression
Sahil Gulania, Zichang He, Bo Peng +2
QuYBE is an open-source algebraic compiler for the compression of quantum circuits. It has been applied for the efficient simulation of the Heisenberg Hamiltonian on quantum comput…
Hybrid Gate-Pulse Model for Variational Quantum Algorithms
Zhiding Liang, Zhixin Song, Jinglei Cheng +8
Current quantum programs are mostly synthesized and compiled on the gate-level, where quantum circuits are composed of quantum gates. The gate-level workflow, however, introduces s…
Constructing Optimal Contraction Trees for Tensor Network Quantum Circuit Simulation
Cameron Ibrahim, Danylo Lykov, Zichang He +2
One of the key problems in tensor network based quantum circuit simulation is the construction of a contraction tree which minimizes the cost of the simulation, where the cost can…
Tensor Shape Search for Optimum Data Compression
Ryan Solgi, Zichang He, William Jiahua Liang +1
Various tensor decomposition methods have been proposed for data compression. In real world applications of the tensor decomposition, selecting the tensor shape for the given data…
PoBO: A Polynomial Bounding Method for Chance-Constrained Yield-Aware Optimization of Photonic ICs
Zichang He, Zheng Zhang
Conventional yield optimization algorithms try to maximize the success rate of a circuit under process variations. These methods often obtain a high yield but reach a design perfor…
High-Dimensional Uncertainty Quantification via Tensor Regression with Rank Determination and Adaptive Sampling
Zichang He, Zheng Zhang
Fabrication process variations can significantly influence the performance and yield of nano-scale electronic and photonic circuits. Stochastic spectral methods have achieved great…
Active Sampling for Accelerated MRI with Low-Rank Tensors
Zichang He, Bo Zhao, Zheng Zhang
Magnetic resonance imaging (MRI) is a powerful imaging modality that revolutionizes medicine and biology. The imaging speed of high-dimensional MRI is often limited, which constrai…
High-Dimensional Uncertainty Quantification via Active and Rank-Adaptive Tensor Regression
Zichang He, Zheng Zhang
Uncertainty quantification based on stochastic spectral methods suffers from the curse of dimensionality. This issue was mitigated recently by low-rank tensor methods. However, the…
Efficient Uncertainty Modeling for System Design via Mixed Integer Programming
Zichang He, Weilong Cui, Chunfeng Cui +2
The post-Moore era casts a shadow of uncertainty on many aspects of computer system design. Managing that uncertainty requires new algorithmic tools to make quantitative assessment…
An evidential Markov decision making model
Zichang He, Wen Jiang
The sure thing principle and the law of total probability are basic laws in classic probability theory. A disjunction fallacy leads to the violation of these two classical laws. In…
Quantum Mechanical Approach to Modelling Reliability of Sensor Reports
Zichang He, Wen Jiang
Dempster-Shafer evidence theory is wildly applied in multi-sensor data fusion. However, lots of uncertainty and interference exist in practical situation, especially in the battle…
A quantum dynamic belief model to explain the interference effects of categorization on decision making
Zichang He, Wen Jiang
Categorization is necessary for many decision making tasks. However, the categorization process may interfere the decision making result and the law of total probability can be vio…
A quantum dynamic belief decision making model
Zichang He, Wen Jiang
The sure thing principle and the law of total probability are basic laws in classic probability theory. A disjunction fallacy leads to the violation of these two classical probabil…
Evidential supplier selection based on interval data fusion
Zichang He, Wen Jiang
Supplier selection is a typical multi-criteria decision making (MCDM) problem and lots of uncertain information exist inevitably. To address this issue, a new method was proposed b…
A new belief Markov chain model and its application in inventory prediction
Zichang He, Wen Jiang
Markov chain model is widely applied in many fields, especially the field of prediction. The classical Discrete-time Markov chain(DTMC) is a widely used method for prediction. Howe…