We discuss characterization of experimental quantum gates by the error matrix, which is similar to the standard process matrix χ in the Pauli basis, except the desired unitary operation is factored out, by formally placing it either before or after the error process. The error matrix has only one large element, which is equal to the process fidelity, while other elements are small and indicate ...

When a large body of data from diverse experiments is analyzed using a theoretical model with many parameters, the standard error matrix method and the general tools for evaluating the error may become inadequate. We present an iterative method that significantly improves the reliability, and hence the applicability, of the error matrix calculation. Also, to obtain more accurate estimates of th...

Some degree of error is inevitable in multi-agent bioassays regardless of design or measurement technology. Estimation error can be reduced post facto by exploiting the matrix partial ordering of the bioassay survival estimates. The standard method for this is order-restricted regression (ORR). If the joint action of the bioassay agents admits a tolerance-based interpretation, additional struct...

A new necessary and sufficient condition for the row W-property is given. By using this new condition and a special row rearrangement, we provide two global error bounds for the extended vertical linear complementarity problem under the row W-property, which extend the error bounds given in [2, 10] for the P-matrix linear complementarity problem, respectively. We show that one of the new error ...

Trapping sets have been identified as one of the main factors causing error floors of low-density parity-check (LDPC) codes at high SNR values. By adding several new rows to the original parity-check matrix, a novel method is proposed to eliminate small trapping sets in the LDPC code’s Tanner graph. Based on this parity-check matrix extension, we design new codes with low error floors from the ...

In this paper, we propose a new linear complementarity problem named as bi-linear complementarity problem (BLCP) and the method for solving BLCP. In addition, the algorithm for error estimation of BLCP is also given. Numerical experiments show that the algorithm is efficient. Keywords—Bi-linear complementarity problem, Linear complementarity problem, Extended linear complementarity problem, Err...

In this paper, new error bounds for the linear complementarity problem are obtained when the involved matrix is a weakly chained diagonally dominant B-matrix. The proposed error bounds are better than some existing results. The advantages of the results obtained are illustrated by numerical examples.

We study the stability vis a vis adversarial noise of matrix factorization algorithm for matrix completion. In particular, our results include: (I) we bound the gap between the solution matrix of the factorization method and the ground truth in terms of root mean square error; (II) we treat the matrix factorization as a subspace fitting problem and analyze the difference between the solution su...

Some connections between linear minimum mean square error estimators, maximum output SNR filters and the least square solutions are presented. The notes have been prepared to be distributed with EE 503 (METU, Electrical Engin.) lecture notes. 1 Linear Minimum Mean Square Error Estimators The following signal model is assumed: r = Hs + v (1) Here r is a N × 1 column vector denoting the observati...

Estimating and projecting population trends using population viability analysis (PVA) are central to identifying species at risk of extinction and for informing conservation management strategies. Models for PVA generally fall within two categories, scalar (count-based) or matrix (demographic). Model structure, process error, measurement error, and time series length all have known impacts in p...