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A composite quadric model (CQM) is an object modeled by piecewise linear or quadric patches. We study the continuous detection problem of a special type of CQM objects which are commonly used in CAD/CAM, that is, the boundary surfaces of…

Graphics · Computer Science 2013-12-02 Yi-King Choi , Wenping Wang , Bernard Mourrain , Changhe Tu , Xiaohong Jia , Feng Sun

We present efficient methods for calculating linear recurrences of hypergeometric double sums and, more generally, of multiple sums. In particular, we supplement this approach with the algorithmic theory of contiguous relations, which…

Symbolic Computation · Computer Science 2024-01-30 Peter Paule , Carsten Schneider

Most recently, learned image compression methods have outpaced traditional hand-crafted standard codecs. However, their inference typically requires to input the whole image at the cost of heavy computing resources, especially for…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Zifu Zhang , Shengxi Li , Henan Liu , Mai Xu , Ce Zhu

Besides tensor contractions, one of the most pronounced computational bottlenecks in the non-orthogonally spin-adapted forms of the quantum chemistry methods CCSDT and CCSDTQ, and their approximate forms---including CCSD(T) and…

Mathematical Software · Computer Science 2017-05-19 Paul Springer , Devin Matthews , Paolo Bientinesi

A novel electromagnetic quantitative inversion scheme for translationally moving targets via phase correlation registration of back-projection (BP) images is proposed. Based on a time division multiplexing multiple-input multiple-output…

Image and Video Processing · Electrical Eng. & Systems 2025-11-20 Yitao Lin , Dahai Dai , Shilong Sun , Yuchen Wu , Bo Pang

Compressive Sensing (CS) theory asserts that sparse signal reconstruction is possible from a small number of linear measurements. Although CS enables low-cost linear sampling, it requires non-linear and costly reconstruction. Recent…

Machine Learning · Computer Science 2018-10-16 Aysen Degerli , Sinem Aslan , Mehmet Yamac , Bulent Sankur , Moncef Gabbouj

A conjugate code pair is defined as a pair of linear codes either of which contains the dual of the other. A conjugate code pair represents the essential structure of the corresponding Calderbank-Shor-Steane (CSS) quantum code. It is known…

Quantum Physics · Physics 2007-05-23 Mitsuru Hamada

Clifford circuits -- i.e. circuits composed of only CNOT, Hadamard, and $\pi/4$ phase gates -- play a central role in the study of quantum computation. However, their computational power is limited: a well-known result of Gottesman and…

Quantum Physics · Physics 2018-06-21 Adam Bouland , Joseph F. Fitzsimons , Dax Enshan Koh

A conjugate code pair is defined as a pair of linear codes such that one contains the dual of the other. The conjugate code pair represents the essential structure of the corresponding Calderbank-Shor-Steane (CSS) quantum code. It is argued…

Quantum Physics · Physics 2009-01-21 Mitsuru Hamada

Compressive Sensing (CS) is a new technique for the efficient acquisition of signals, images, and other data that have a sparse representation in some basis, frame, or dictionary. By sparse we mean that the N-dimensional basis…

Information Theory · Computer Science 2015-05-18 Chinmay Hegde , Richard G. Baraniuk

Compressive sensing (CS) is a sampling technique designed for reducing the complexity of sparse data acquisition. One of the major obstacles for practical deployment of CS techniques is the signal reconstruction time and the high storage…

Information Theory · Computer Science 2011-07-12 Wei Dai , Olgica Milenkovic , Hoa Vin Pham

The same complex matrix model calculates both tachyon scattering for the c=1 non-critical string at the self-dual radius and certain correlation functions of half-BPS operators in N=4 super-Yang-Mills. It is dual to another complex matrix…

High Energy Physics - Theory · Physics 2011-10-11 T. W. Brown

Collision between rigid three-dimensional objects is a very common modelling problem in a wide spectrum of scientific disciplines, including Computer Science and Physics. It spans from realistic animation of polyhedral shapes for computer…

Computational Physics · Physics 2020-06-23 Luca Tonti , Alessandro Patti

We propose a notion of convergence-sensitive bisimulation that is built just over the notions of (internal) reduction and of (static) context. In the framework of timed CCS, we characterise this notion of `contextual' bisimulation via the…

Logic in Computer Science · Computer Science 2010-07-01 Roberto Amadio

We derive various interesting properties of complex equiangular cyclic frames for many pairs (n, k) using Gauss sums and number theory. We further use these results to study the random and burst errors of some special cases of complex…

Functional Analysis · Mathematics 2007-05-23 Deepti Kalra

It has been conjectured that the relative phase between strong and electromagnetic amplitudes is universally $-90^{\circ}$ in charmonium decays. $\psi^{\prime}$ decaying into pseudoscalar pair provides a possibility to test this conjecture.…

High Energy Physics - Phenomenology · Physics 2011-05-18 Wang Bo-Qun , Mo Xiao-Hu , Wang Ping , Ban Yong

The challenge of imbalanced learning lies not only in class imbalance problem, but also in the class overlapping problem which is complex. However, most of the existing algorithms mainly focus on the former. The limitation prevents the…

Machine Learning · Computer Science 2022-12-07 Fan Li , Bo Wang , Pin Wang , Yongming Li

We study pairing induced superconductivity in large $N$ strongly coupled systems at finite density using holography. In the weakly coupled dual gravitational theory the mechanism is conventional BCS theory. An IR hard wall cut-off is…

High Energy Physics - Theory · Physics 2015-06-19 Andrey Bagrov , Balazs Meszena , Koenraad Schalm

Snapshot compressed sensing (CS) refers to compressive imaging systems in which multiple frames are mapped into a single measurement frame. Each pixel in the acquired frame is a noisy linear mapping of the corresponding pixels in the frames…

Information Theory · Computer Science 2019-04-30 Shirin Jalali , Xin Yuan

A key challenge in spatial statistics is the analysis for massive spatially-referenced data sets. Such analyses often proceed from Gaussian process specifications that can produce rich and robust inference, but involve dense covariance…

Methodology · Statistics 2019-07-25 Shinichiro Shirota , Andrew O. Finley , Bruce D. Cook , Sudipto Banerjee