Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Gnanasekaran, Abeynaya"'
Autor:
Surana, Amit, Gnanasekaran, Abeynaya
We present a novel variational quantum framework for linear partial differential equation (PDE) constrained optimization problems. Such problems arise in many scientific and engineering domains. For instance, in aerodynamics, the PDE constraints are
Externí odkaz:
http://arxiv.org/abs/2405.16651
Autor:
Gnanasekaran, Abeynaya, Surana, Amit
We develop a novel approach for efficiently applying variational quantum linear solver (VQLS) in context of structured sparse matrices. Such matrices frequently arise during numerical solution of partial differential equations which are ubiquitous in
Externí odkaz:
http://arxiv.org/abs/2404.16991
Autor:
Sahai, Tuhin, Gnanasekaran, Abeynaya
The Unique Games Conjecture (UGC) constitutes a highly dynamic subarea within computational complexity theory, intricately linked to the outstanding P versus NP problem. Despite multiple insightful results in the past few years, a proof for the conje
Externí odkaz:
http://arxiv.org/abs/2404.16024
In this paper, we propose efficient quantum algorithms for solving nonlinear stochastic differential equations (SDE) via the associated Fokker-Planck equation (FPE). We discretize the FPE in space and time using two well-known numerical schemes, name
Externí odkaz:
http://arxiv.org/abs/2303.02463
We present an efficient quantum algorithm to simulate nonlinear differential equations with polynomial vector fields of arbitrary degree on quantum platforms. Models of physical systems that are governed by ordinary differential equations (ODEs) or p
Externí odkaz:
http://arxiv.org/abs/2212.10775
Autor:
Gnanasekaran, Abeynaya, Darve, Eric
In this work, we develop a fast hierarchical solver for solving large, sparse least squares problems. We build upon the algorithm, spaQR (sparsified QR), that was developed by the authors to solve large sparse linear systems. Our algorithm is built o
Externí odkaz:
http://arxiv.org/abs/2102.09878
Autor:
Gnanasekaran, Abeynaya, Darve, Eric
In this work, we develop a new fast algorithm, spaQR -- sparsified QR, for solving large, sparse linear systems. The key to our approach is using low-rank approximations to sparsify the separators in a Nested Dissection based Householder QR factoriza
Externí odkaz:
http://arxiv.org/abs/2010.06807
Akademický článek
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Autor:
Vasudevan, Varun1 devan@stanford.edu, Gnanasekaran, Abeynaya1, Sankar, Varsha2, Vasudevan, Siddarth A.3, Zou, James4
Publikováno v:
BMC Public Health. 7/16/2021, Vol. 21 Issue 1, p1-12. 12p. 2 Diagrams, 1 Chart, 2 Graphs, 1 Map.
Akademický článek
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