Jitendra Gupta

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We present an N(5) scaling modification to the standard EOMEA-CCSD method, based on the matrix partitioning technique and perturbative approximations. The method has lower computational scaling and smaller storage requirements than the standard EOMEA-CCSD method and, therefore, can be used to calculate electron affinities of large molecules and clusters.(More)
In this paper, we present a formulation based on Lagrange multiplier approach for efficient evaluation of excited state energy derivatives in Fock space coupled cluster theory within the intermediate Hamiltonian framework. The formulation is applied to derive the explicit generic expressions up to second order energy derivatives for [1, 1] sector of Fock(More)
AbstractIn today’s world everyday a new technology which is faster, smaller and more complex than its predecessor is being developed. The increased number of transistors packed onto a chip of a conventional system results in increased power consumption that is why Reversible logic has drawn attention of Researchers due to its less heat dissipating(More)
In this paper we propose a novel clustering based multi-hop protection (referred to as CMHP) heuristic scheme to protect against single shared-risk link group (SRLG) failure in a long-reach passive optical network. We allocate the residual capacity of backup optical network units (ONUs) among the ONUs that require protection by employing bypass-based(More)
The next-generation passive optical networks (NG-PONs) are expected to offer very high data rate to large number of users. Long-reach passive optical network (LR-PON) is considered to be one of the most promising solutions for NG-PONs. Since providing full protection (i.e., 100 % reliability) to each user in LR-PON is complex and cost-prohibitive, we(More)
The Fock space multireference coupled cluster (FSMRCC) method provides an efficient approach for the direct calculation of excitation energies. In intermediate Hamiltonian (IH-FSMRCC) formulation, the method is free from intruder state problems and associated convergence difficulties, even with a large model space. In this paper, we demonstrate that the(More)
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