arXiv subjects

M. Niranjan

Publications and source records attributed to M. Niranjan.

7 recordsLinked to original sources

arXiv2024

Associative ionization in a dilute ultracold $^7$Li gas probed with a hybrid trap

The formation of Li$_2^+$ and subsequently Li$^+$ ions, during the excitation of $^7$Li atoms to the $3S_{1/2}$ state in a $^7$Li magneto optical trap (MOT), is probed in an ion-atom hybrid trap. Associative ionization occurs during the collision of Li($2P_{3/2}$) and Li($3S_{1/2}$) ultracold atoms, creating Li$_2^+$ ions. Photodissociation of Li$_2^+$ by the MOT lasers is an active channel for the conversion of Li$_2^+$ to Li$^+$. A fraction of the Li$_2^+$ ions is long lived even in the presence of MOT light. Additionally, rapid formation of Li$^+$ from Li$_2^+$ in the absence of MOT light is observed. Resonant excitation of ultracold atoms, resulting in intricate molecular dynamics, reveals important processes in ultracold dilute gases.

physics.atom-ph↗

arXiv2022

Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications

Artificial Intelligence (AI) and its data-centric branch of machine learning (ML) have greatly evolved over the last few decades. However, as AI is used increasingly in real world use cases, the importance of the interpretability of and accessibility to AI systems have become major research areas. The lack of interpretability of ML based systems is a major hindrance to widespread adoption of these powerful algorithms. This is due to many reasons including ethical and regulatory concerns, which have resulted in poorer adoption of ML in some areas. The recent past has seen a surge in research on interpretable ML. Generally, designing a ML system requires good domain understanding combined with expert knowledge. New techniques are emerging to improve ML accessibility through automated model design. This paper provides a review of the work done to improve interpretability and accessibility of machine learning in the context of global problems while also being relevant to developing countries. We review work under multiple levels of interpretability including scientific and mathematical interpretation, statistical interpretation and partial semantic interpretation. This review includes applications in three areas, namely food processing, agriculture and health.

cs.LG↗

arXiv2022

Bichromatic state-dependent disordered potential for Anderson localization of ultracold atoms

The ability to load ultracold atoms at a well-defined energy in a disordered potential is a crucial tool to study quantum transport, and in particular Anderson localization. In this paper, we present a new method for achieving that goal by rf transfer of atoms of an atomic Bose-Einstein condensate from a disorder insensitive state to a disorder sensitive state. It is based on a bichromatic laser speckle pattern, produced by two lasers whose frequencies are chosen so that their light-shifts cancel each other in the first state and add-up in the second state. Moreover, the spontaneous scattering rate in the disorder-sensitive state is low enough to allow for long observation times of quantum transport in that state. We theoretically and experimentally study the characteristics of the resulting potential.

cond-mat.quant-gas↗

arXiv2020

Interaction potentials and ultracold scattering cross sections for the $^7$Li$^+$-$^7$Li ion-atom system

We calculate the isotope independent Li$^+$-Li potential energy curves for the electronic ground and first excited states. Scattering phase shifts and total scattering cross section for the $^7$Li$^+$-$^7$Li collision are calculated with emphasis on the ultra-low energy domain down to the $s$-wave regime. The effect of physically motivated alterations on the calculated potential energy curves is used to determine the bound of accuracy of the low-energy scattering parameters for the ion-atom system. It is found that the scattering length for the A$^2Σ_u^+$ state, $a_u$ = 1325 a$_0$, is positive and has well-constrained bounds. For the X$^2Σ_g^+$ state, the scattering length, $a_g$ = 20465 a$_0$ has a large magnitude as it is sensitive to the restrained change of the potential, due to the presence of a vibrational state in the vicinity of the dissociation limit.

physics.atom-ph↗

arXiv2014

A Structured Hardware Software Architecture for Peptide Based Diagnosis of Baylisascaris Procyonis Infection (ICIAfS14)

The problem of inferring proteins from complex peptide cocktails (digestion products of biological samples) in shotgun proteomic workflow sets extreme demands on computational resources in respect of the required very high processing throughputs, rapid processing rates and reliability of results. This is exacerbated by the fact that, in general, a given protein cannot be defined by a fixed sequence of amino acids due to the existence of splice variants and isoforms of that protein. Therefore, the problem of protein inference could be considered as one of identifying sequences of amino acids with some limited tolerance. In the current paper a model-based hardware acceleration of a structured and practical inference approach is developed and validated on a mass spectrometry experiment of realistic size. We have achieved 10 times maximum speed-up in the co-designed workflow compared to a similar software-only workflow run on the processor used for co-design.

cs.CE↗

arXiv2014

A Structured Hardware Software Architecture for Peptide Based Diagnosis - Sub-string Matching Problem with Limited Tolerance (ICIAfS14)

The problem of inferring proteins from complex peptide samples in shotgun proteomic workflow sets extreme demands on computational resources. This is exacerbated by the fact that, in general, a given protein cannot be defined by a fixed sequence of amino acids due to the existence of splice variants and isoforms of that protein. Therefore, the problem of protein inference could be considered as one of identifying sequences of amino acids with some limited tolerance. Two problems arise from this: a) due to these variations, the applicability of exact string matching methodologies could be questioned and b) the difficulty of defining a reference sequence for a particular set of proteins that are functionally indistinguishable, but with some variation in features. This paper presents a model-based inference approach that is developed and validated to solve the inference problem. Our approach starts from an examination of the known set of splice variants and isoforms of a target protein to identify the Greatest Common Stable Substring (GCSS) of amino acids and the Substrings Subjects to Limited Variation (SSLV) and their respective locations on the GCSS. Then we define and solve the Sub-string Matching Problem with Limited Tolerance (SMPLT). This approach is validated on identified peptides in a labelled and clustered data set from UNIPROT. Identification of Baylisascaris Procyonis infection was used as an application instance that achieved up to 70 times speedup compared to a software only system. This workflow can be generalised to any inexact multiple pattern matching application by replacing the patterns in a clustered and distributed environment which permits a distance between member strings to account for permitted deviations such as substitutions, insertions and deletions.

cs.CE↗

arXiv2014

Tile optimization for area in FPGA based hardware acceleration of peptide identification

Advances in life sciences over the last few decades have lead to the generation of a huge amount of biological data. Computing research has become a vital part in driving biological discovery where analysis and categorization of biological data are involved. String matching algorithms can be applied for protein/gene sequence matching and with the phenomenal increase in the size of string databases to be analyzed, software implementations of these algorithms seems to have hit a hard limit and hardware acceleration is increasingly being sought. Several hardware platforms such as Field Programmable Gate Arrays (FPGA), Graphics Processing Units (GPU) and Chip Multi Processors (CMP) are being explored as hardware platforms. In this paper, we give a comprehensive overview of the literature on hardware acceleration of string matching algorithms, we take an FPGA hardware exploration and expedite the design time by a design automation technique. Further, our design automation is also optimized for better hardware utilization through optimizing the number of peptides that can be represented in an FPGA tile. The results indicate significant improvements in design time and hardware utilization which are reported in this paper.

cs.CE↗