Prediction of wavefronts in adaptive optics to reduce servo lag errors using data mining

Servo lag errors in adaptive optics lead to inaccurate compensation of wavefront distortions. An attempt has been made to predict future wavefronts using data mining on wavefronts of the immediate past to reduce these errors. Monte Carlo simulations were performed on experimentally obtained data that closely follows Kolmogorov phase characteristics. An improvement of 6% in wavefront correction is reported after data mining is performed. Data mining is performed in three steps (a) Data cube Segmentation (b) Polynomial Interpolation and (c) Wavefront Estimation. It is important to optimize the segment size that gives best prediction results. Optimization of the best predictable future helps in selecting a suitable exposure time.Comment: 4 pages, 7 figures, in proceedings of the International Conference on Optics and Photonics, 200

Lower bounds for multilinear bounded order ABPs

Proving super-polynomial size lower bounds for syntactic multilinear Algebraic Branching Programs(smABPs) computing an explicit polynomial is a challenging problem in Algebraic Complexity Theory. The order in which variables in $\{x_1,\ldots,x_n\}$ appear along source to sink paths in any smABP can be viewed as a permutation in $S_n$. In this article, we consider the following special classes of smABPs where the order of occurrence of variables along a source to sink path is restricted: Strict circular-interval ABPs: For every subprogram the index set of variables occurring in it is contained in some circular interval of $\{1,\ldots,n\}$. L-ordered ABPs: There is a set of L permutations of variables such that every source to sink path in the ABP reads variables in one of the L orders. We prove exponential lower bound for the size of a strict circular-interval ABP computing an explicit n-variate multilinear polynomial in VP. For the same polynomial, we show that any sum of L-ordered ABPs of small size will require exponential ($2^{n^{\Omega(1)}}$) many summands, when $L \leq 2^{n^{1/2-\epsilon}}, \epsilon>0$. At the heart of above lower bound arguments is a new decomposition theorem for smABPs: We show that any polynomial computable by an smABP of size S can be written as a sum of O(S) many multilinear polynomials where each summand is a product of two polynomials in at most 2n/3 variables computable by smABPs. As a corollary, we obtain a low bottom fan-in version of the depth reduction by Tavenas [MFCS 2013] in the case of smABPs. In particular, we show that a polynomial having size S smABPs can be expressed as a sum of products of multilinear polynomials on $O(\sqrt{n})$ variables, where the total number of summands is bounded by $2^{O(\sqrt{n}\log n \log S)}$. Additionally, we show that L-ordered ABPs can be transformed into L-pass smABPs with a polynomial blowup in size

Digital long focal length lenslet array using spatial light modulator

Under a thin lens and paraxial approximation, the phase transformation function of a lens was simulated on a Liquid Crystal (LC) based Spatial Light Modulator (SLM). The properties of an array of such lenses simulated on transmitting type and reflecting type SLMs were investigated and the limits of its operation in wavefront sensing applications are discussed.Comment: 4 pages, 7 figures, in proceedings of the International Conference on Optics and Photonics, 200

New Algorithms and Hard Instances for Non-Commutative Computation

Motivated by the recent developments on the complexity of non-com\-mu\-ta\-tive determinant and permanent [Chien et al.\ STOC 2011, Bl\"aser ICALP 2013, Gentry CCC 2014] we attempt at obtaining a tight characterization of hard instances of non-commutative permanent. We show that computing Cayley permanent and determinant on weight\-ed adjacency matrices of graphs of component size six is $\#{\sf P}$ complete on algebras that contain $2\times 2$ matrices and the permutation group $S_3$. Also, we prove a lower bound of $2^{\Omega(n)}$ on the size of branching programs computing the Cayley permanent on adjacency matrices of graphs with component size bounded by two. Further, we observe that the lower bound holds for almost all graphs of component size two. On the positive side, we show that the Cayley permanent on graphs of component size $c$ can be computed in time $n^{c{\sf poly}(t)}$, where $t$ is a parameter depending on the labels of the vertices. Finally, we exhibit polynomials that are equivalent to the Cayley permanent polynomial but are easy to compute over commutative domains.Comment: Submitted to a conferenc

Denoising Shack Hartmann Sensor spot pattern using Zernike Reconstructor

Shack Hartmann Sensor (SHS) is inflicted with significant background noise that deteriorates the wave-front reconstruction accuracy. In this paper, a simple method to remove the back ground noise with the use of Zernike polynomials is suggested. The images corresponding to individual array points of the SHS at the detector, placed at the focal plane are independently reconstructed using Zernike polynomials by the calculation of Zernike moments. Appropriate thresholding is applied on the images. It is shown with computational experiments that using Zernike Reconstructor along with usual thresholding improves the centroiding accuracy when compared to direct thresholding. A study was performed at different Signal to Noise ratio by changing the number of Zernike orders used for reconstruction. The analysis helps us in setting upper and lower bounds in the application of this denoising procedure.Comment: 9 figures, Proceedings of the International Conference on Advanced Computing, Cauvery College for Women & Bharathidasan University Technology Park, Tiruchirappalli, India. Aug 6-8, 2009, page 30

On the Complexity of Matroid Isomorphism Problem

We study the complexity of testing if two given matroids are isomorphic. The problem is easily seen to be in $\Sigma_2^p$. In the case of linear matroids, which are represented over polynomially growing fields, we note that the problem is unlikely to be $\Sigma_2^p$-complete and is \co\NP-hard. We show that when the rank of the matroid is bounded by a constant, linear matroid isomorphism, and matroid isomorphism are both polynomial time many-one equivalent to graph isomorphism. We give a polynomial time Turing reduction from graphic matroid isomorphism problem to the graph isomorphism problem. Using this, we are able to show that graphic matroid isomorphism testing for planar graphs can be done in deterministic polynomial time. We then give a polynomial time many-one reduction from bounded rank matroid isomorphism problem to graphic matroid isomorphism, thus showing that all the above problems are polynomial time equivalent. Further, for linear and graphic matroids, we prove that the automorphism problem is polynomial time equivalent to the corresponding isomorphism problems. In addition, we give a polynomial time membership test algorithm for the automorphism group of a graphic matroid

Linear Projections of the Vandermonde Polynomial

An n-variate Vandermonde polynomial is the determinant of the n x n matrix where the ith column is the vector (1, x_i, x_i^2, ...., x_i^{n-1})^T. Vandermonde polynomials play a crucial role in the theory of alternating polynomials and occur in Lagrangian polynomial interpolation as well as in the theory of error correcting codes. In this work we study structural and computational aspects of linear projections of Vandermonde polynomials. Firstly, we consider the problem of testing if a given polynomial is linearly equivalent to the Vandermonde polynomial. We obtain a deterministic polynomial time algorithm to test if the polynomial f is linearly equivalent to the Vandermonde polynomial when f is given as product of linear factors. In the case when the polynomial f is given as a black-box our algorithm runs in randomized polynomial time. Exploring the structure of projections of Vandermonde polynomials further, we describe the group of symmetries of a Vandermonde polynomial and show that the associated Lie algebra is simple.Comment: Submitted to a conferenc

Performance analysis of Fourier and Vector Matrix Multiply methods for phase reconstruction from slope measurements

The accuracy of wavefront reconstruction from discrete slope measurements depends on the sampling geometry, coherence length of the incoming wavefronts, wavefront sensor specifications and the accuracy of the reconstruction algorithm. Monte Carlo simulations were performed and a comparison of Fourier and Vector Matrix Multiply reconstruction methods was made with respect to these experimental and computational parameters. It was observed that although Fourier reconstruction gave consistent accuracy when coherence length of wavefronts is larger than the corresponding pitch on the wavefront sensor, VMM method gives even better accuracy when the coherence length closely matches with the wavefront sensor pitch.Comment: 4 pages, 6 figures, in proceedings of the International Conference on Optics and Photonics, 200

Regularity of Binomial Edge Ideals of Certain Block Graphs

We obtain an improved lower bound for the regularity of the binomial edge ideals of trees. We prove an upper bound for the regularity of the binomial edge ideals of certain subclass of block-graphs. As a consequence we obtain sharp upper and lower bounds for the regularity of binomial edge ideals of a class of trees called lobsters. We also obtain precise expressions for the regularities of binomial edge ideals of certain classes of trees and block graphs.Comment: Some more minor changes don

Parameterized Analogues of Probabilistic Computation

We study structural aspects of randomized parameterized computation. We introduce a new class ${\sf W[P]}$-${\sf PFPT}$ as a natural parameterized analogue of ${\sf PP}$. Our definition uses the machine based characterization of the parameterized complexity class ${\sf W[P]}$ obtained by Chen et.al [TCS 2005]. We translate most of the structural properties and characterizations of the class ${\sf PP}$ to the new class ${W[P]}$-${\sf PFPT}$. We study a parameterization of the polynomial identity testing problem based on the degree of the polynomial computed by the arithmetic circuit. We obtain a parameterized analogue of the well known Schwartz-Zippel lemma [Schwartz, JACM 80 and Zippel, EUROSAM 79]. Additionally, we introduce a parameterized variant of permanent, and prove its $\#W[1]$ completeness.Comment: Submitted to a conferenc