arXiv subjects

Nikhil Kumar

Publications and source records attributed to Nikhil Kumar.

36 records · Page 2Linked to original sources

arXiv2024

A manufacturable platform for photonic quantum computing

Whilst holding great promise for low noise, ease of operation and networking, useful photonic quantum computing has been precluded by the need for beyond-state-of-the-art components, manufactured by the millions. Here we introduce a manufacturable platform for quantum computing with photons. We benchmark a set of monolithically-integrated silicon photonics-based modules to generate, manipulate, network, and detect photonic qubits, demonstrating dual-rail photonic qubits with $99.98\% \pm 0.01\%$ state preparation and measurement fidelity, Hong-Ou-Mandel quantum interference between independent photon sources with $99.50\%\pm0.25\%$ visibility, two-qubit fusion with $99.22\%\pm0.12\%$ fidelity, and a chip-to-chip qubit interconnect with $99.72\%\pm0.04\%$ fidelity, not accounting for loss. In addition, we preview a selection of next generation technologies, demonstrating low-loss silicon nitride waveguides and components, fabrication-tolerant photon sources, high-efficiency photon-number-resolving detectors, low-loss chip-to-fiber coupling, and barium titanate electro-optic phase shifters.

quant-ph↗

arXiv2024

Boosting Digital Safeguards: Blending Cryptography and Steganography

In today's digital age, the internet is essential for communication and the sharing of information, creating a critical need for sophisticated data security measures to prevent unauthorized access and exploitation. Cryptography encrypts messages into a cipher text that is incomprehensible to unauthorized readers, thus safeguarding data during its transmission. Steganography, on the other hand, originates from the Greek term for "covered writing" and involves the art of hiding data within another medium, thereby facilitating covert communication by making the message invisible. This proposed approach takes advantage of the latest advancements in Artificial Intelligence (AI) and Deep Learning (DL), especially through the application of Generative Adversarial Networks (GANs), to improve upon traditional steganographic methods. By embedding encrypted data within another medium, our method ensures that the communication remains hidden from prying eyes. The application of GANs enables a smart, secure system that utilizes the inherent sensitivity of neural networks to slight alterations in data, enhancing the protection against detection. By merging the encryption techniques of cryptography with the hiding capabilities of steganography, and augmenting these with the strengths of AI, we introduce a comprehensive security system designed to maintain both the privacy and integrity of information. This system is crafted not just to prevent unauthorized access or modification of data, but also to keep the existence of the data hidden. This fusion of technologies tackles the core challenges of data security in the current era of open digital communication, presenting an advanced solution with the potential to transform the landscape of information security.

cs.CR↗

arXiv2023

Small and Dim Target Detection in IR Imagery: A Review

While there has been significant progress in object detection using conventional image processing and machine learning algorithms, exploring small and dim target detection in the IR domain is a relatively new area of study. The majority of small and dim target detection methods are derived from conventional object detection algorithms, albeit with some alterations. The task of detecting small and dim targets in IR imagery is complex. This is because these targets often need distinct features, the background is cluttered with unclear details, and the IR signatures of the scene can change over time due to fluctuations in thermodynamics. The primary objective of this review is to highlight the progress made in this field. This is the first review in the field of small and dim target detection in infrared imagery, encompassing various methodologies ranging from conventional image processing to cutting-edge deep learning-based approaches. The authors have also introduced a taxonomy of such approaches. There are two main types of approaches: methodologies using several frames for detection, and single-frame-based detection techniques. Single frame-based detection techniques encompass a diverse range of methods, spanning from traditional image processing-based approaches to more advanced deep learning methodologies. Our findings indicate that deep learning approaches perform better than traditional image processing-based approaches. In addition, a comprehensive compilation of various available datasets has also been provided. Furthermore, this review identifies the gaps and limitations in existing techniques, paving the way for future research and development in this area.

cs.CV↗

arXiv2023

Exciting high-frequency short-wavelength spin waves using high harmonics of a magnonic cavity mode

Confined spin-wave modes are a promising object for studying nonlinear effects and future quantum technologies. Here, using micromagnetic simulations, we use a microwave magnetic field from a coplanar waveguide (CPW) to pump a standing spin-wave confined in the cavity of magnonic crystal. We find that the frequency of the fundamental cavity mode is equal to the ferromagnetic resonance frequency of the plane film and overlaps with the magnonic bandgap, allowing high magnetic field tunability. Multi-frequency harmonics of the cavity mode are generated once the microwave amplitude surpasses a certain threshold. Specifically, the second and third harmonics at 0.5 T equate to 48.6 and 72.9 GHz with wavelengths of 44 and 22 nm respectively, which propagate into the crystal. This effect reaches saturation when the CPW covers the entire cavity, making the system feasible for realization. These processes show potential for the advancement of magnonics at high-frequencies and very short-wavelengths.

cond-mat.mes-hall↗

arXiv2023

Decentralised Service Allocation using Blockchain

The growing demand for short-term property renting has led to the boom of a new category called PropTech (Property + Technology). Such a rise in demand attracted many entrepreneurs and investors leading to the inception of powerful and centralised players in the category (like Airbnb). Unfortunately, some big players are controlling the entire industry in a centralised way in turn, performing anti-competitive practices which leave no room for the small players. Such an ecosystem can be made more transparent and decentralised by executing transactions and order-fulfilment on a blockchain. To extend the functionality of the system, we can also perform the renting of small services and appliances via the integration of IoT. Implementing such a system will make the process more transparent, robust and decentralised.

cs.DC↗

arXiv2022

Approximate Max-Flow Min-Multicut Theorem for Graphs of Bounded Treewidth

We prove an approximate max-multiflow min-multicut theorem for bounded treewidth graphs. In particular, we show the following: Given a treewidth-$r$ graph, there exists a (fractional) multicommodity flow of value $f$, and a multicut of capacity $c$ such that $ f \leq c \leq \mathcal{O}(\ln (r+1)) \cdot f$. It is well known that the multiflow-multicut gap on an $r$-vertex (constant degree) expander graph can be $Ω(\ln r)$, and hence our result is tight up to constant factors. Our proof is constructive, and we also obtain a polynomial time $\mathcal{O}(\ln (r+1))$-approximation algorithm for the minimum multicut problem on treewidth-$r$ graphs. Our algorithm proceeds by rounding the optimal fractional solution to the natural linear programming relaxation of the multicut problem. We introduce novel modifications to the well-known region growing algorithm to facilitate the rounding while guaranteeing at most a logarithmic factor loss in the treewidth.

cs.DS↗

arXiv2021

Skeletons and Minimum Energy Scheduling

Consider the problem where $n$ jobs, each with a release time, a deadline and a required processing time are to be feasibly scheduled in a single- or multi-processor setting so as to minimize the total energy consumption of the schedule. A processor has two available states: a \emph{sleep state} where no energy is consumed but also no processing can take place, and an \emph{active state} which consumes energy at a rate of one, and in which jobs can be processed. Transitioning from the active to the sleep does not incur any further energy cost, but transitioning from the sleep to the active state requires $q$ energy units. Jobs may be preempted and (in the multi-processor case) migrated. The single-processor case of the problem is known to be solvable in polynomial time via an involved dynamic program, whereas the only known approximation algorithm for the multi-processor case attains an approximation factor of $3$ and is based on rounding the solution to a linear programming relaxation of the problem. In this work, we present efficient and combinatorial approximation algorithms for both the single- and the multi-processor setting. Before, only an algorithm based on linear programming was known for the multi-processor case. Our algorithms build upon the concept of a \emph{skeleton}, a basic (and not necessarily feasible) schedule that captures the fact that some processor(s) must be active at some time point during an interval. Finally, we further demonstrate the power of skeletons by providing an $2$-approximation algorithm for the multiprocessor case, thus improving upon the recent breakthrough $3$-approximation result. Our algorithm is based on a novel rounding scheme of a linear-programming relaxation of the problem which incorporates skeletons.

cs.DS↗

arXiv2020

Dual Half-integrality for Uncrossable Cut Cover and its Application to Maximum Half-Integral Flow

Given an edge weighted graph and a forest $F$, the $\textit{2-edge connectivity augmentation problem}$ is to pick a minimum weighted set of edges, $E'$, such that every connected component of $E'\cup F$ is 2-edge connected. Williamson et al. gave a 2-approximation algorithm (WGMV) for this problem using the primal-dual schema. We show that when edge weights are integral, the WGMV procedure can be modified to obtain a half-integral dual. The 2-edge connectivity augmentation problem has an interesting connection to routing flow in graphs where the union of supply and demand is planar. The half-integrality of the dual leads to a tight 2-approximate max-half-integral-flow min-multicut theorem.

cs.DS↗

arXiv2020

Multicommodity Flows in Planar Graphs with Demands on Faces

We consider the problem of multicommodity flows in planar graphs. Seymour showed that if the union of supply and demand graphs is planar, then the cut condition is sufficient for routing demands. Okamura-Seymour showed that if all demands are incident on one face, then again cut condition is sufficient for routing demands. We consider a common generalization of these settings where the end points of each demand are on the same face of the planar graph. We show that if the source sink pairs on each face of the graph are such that sources and sinks appear contiguously on the cycle bounding the face, then the flow cut gap is at most 3. We come up with a notion of approximating demands on a face by convex combination of laminar demands to prove this result.

cs.DS↗

arXiv2020

Integer Plane Multiflow Maximisation : Flow-Cut Gap and One-Quarter-Approximation

In this paper, we bound the integrality gap and the approximation ratio for maximum plane multiflow problems and deduce bounds on the flow-cut-gap. Planarity means here that the union of the supply and demand graph is planar. We first prove that there exists a multiflow of value at least half of the capacity of a minimum multicut. We then show how to convert any multiflow into a half-integer one of value at least half of the original multiflow. Finally, we round any half-integer multiflow into an integer multiflow, losing again at most half of the value, in polynomial time, achieving a $1/4$-approximation algorithm for maximum integer multiflows in the plane, and an integer-flow-cut gap of $8$.

cs.DS↗

arXiv2019

A Constant Factor Approximation for Capacitated Min-Max Tree Cover

Given a graph $G=(V,E)$ with non-negative real edge lengths and an integer parameter $k$, the Min-Max k-Tree Cover problem seeks to find a set of at most $k$ subtrees of $G$, such that the union of the trees is the vertex set $V$. The objective is to minimize the maximum length among all the trees. We give the first constant factor approximation for the hard uniform capacitated version of this problem, where, an input parameter $λ$ upper bounds the number of vertices that can be covered by any of the trees. Our result extends to the rooted version of the problem, where we are given a set of $k$ root vertices, $R$ and each of the covering trees is required to include a distinct vertex in $R$ as the root. Prior to our work, the only result known was a $(2k-1)$-approximation algorithm for the special case when the total number of vertices in the graph is $kλ$ [Guttmann-Beck and Hassin, J. of Algorithms, 1997]. Our technique circumvents the difficulty of using the minimum spanning tree of the graph as a lower bound, which is standard for the uncapacitated version of the problem [Even et al., OR Letters 2004] [Khani et al., Algorithmica 2010]. Instead, we use Steiner trees that cover $λ$ vertices along with an iterative refinement procedure that ensures that the output trees have low cost and the vertices are well distributed among the trees.

cs.DS↗

arXiv2019

Parallel Machine Scheduling to Minimize Energy Consumption

Given n jobs with release dates, deadlines and processing times we consider the problem of scheduling them on m parallel machines so as to minimize the total energy consumed. Machines can enter a sleep state and they consume no energy in this state. Each machine requires Q units of energy to awaken from the sleep state and in its active state the machine can process jobs and consumes a unit of energy per unit time. We allow for preemption and migration of jobs and provide the first constant approximation algorithm for this problem.

cs.DS↗

arXiv2016

Coherent microwave generation by spintronic feedback oscillator

The transfer of spin angular momentum to a nanomagnet from a spin polarized current provides an efficient means of controlling the magnetization direction in nanomagnets. A unique consequence of this spin torque is that the spontaneous oscillations of the magnetization can be induced by applying a combination of a dc bias current and a magnetic field. Here we experimentally demonstrate a different effect, which can drive a nanomagnet into spontaneous oscillations without the need of external spin torque injection. For the demonstration of this effect, we use a nano-pillar of magnetic tunnel junction (MTJ) powered by a dc current and connected to a coplanar waveguide (CPW) lying above the free layer of the MTJ. Any fluctuation of the free layer magnetization is converted into oscillating voltage via the tunneling magneto-resistance effect and is fed back into the MTJ by the CPW through inductive coupling. As a result of this feedback, the magnetization of the free layer can be driven into a continual precession. The combination of MTJ and CPW behaves similar to a laser system and outputs a stable rf power with quality factor exceeding 10,000.

cond-mat.mes-hall↗

arXiv2016

An Empirical Evaluation Of Social Influence Metrics

Predicting when an individual will adopt a new behavior is an important problem in application domains such as marketing and public health. This paper examines the perfor- mance of a wide variety of social network based measurements proposed in the literature - which have not been previously compared directly. We study the probability of an individual becoming influenced based on measurements derived from neigh- borhood (i.e. number of influencers, personal network exposure), structural diversity, locality, temporal measures, cascade mea- sures, and metadata. We also examine the ability to predict influence based on choice of classifier and how the ratio of positive to negative samples in both training and testing affect prediction results - further enabling practical use of these concepts for social influence applications.

cs.SI↗

arXiv2016

Substrate effect and nanoindentation fracture toughness based on pile up and failure

The effect of substrate was studied using nanoindentation on thin films. Soft films on hard substrate showed more pile up than usual which was attributed to the dislocation pile up at the film substrate interface. The effect of tip blunting on the load depth and hardness plots of nanoindentation was shown. The experimental date of variation of Vickers hardness with film thickness and loads were fitted and new parameters were analyzed. The delaminated area was analyzed using geometrical shapes using optical view of the failure region along with the load displacement Indentation fracture using Nanoindentation using Berkovich indenter has been studied. Indentation fracture toughness (KR) was analyzed based on computational programs. The contact mechanics during nanoindentation was studied with parameters related to indenter shape and tip sharpness. Elastic, plastic and total energies were computationally determined. The energy difference was related to shear stress being generated with elastic to plastic transition. Change in the nature of residual stress was related to film thickness.

cond-mat.mtrl-sci↗

arXiv2015

Controlling hysteresis in superconducting constrictions with a resistive shunt

We demonstrate control of the thermal hysteresis in superconducting constrictions by adding a resistive shunt. In order to prevent thermal relaxation oscillations, the shunt resistor is placed in close vicinity of the constriction, making the inductive current-switching time smaller than the thermal equilibration time. We investigate the current-voltage characteristics of the same constriction with and without the shunt-resistor. The widening of the hysteresis-free temperature range is explained on the basis of a simple model.

cond-mat.supr-con↗

arXiv2015

Reversibility of Superconducting Nb Weak Links Driven by the Proximity Effect in a Quantum Interference Device

We demonstrate the role of proximity effect in the thermal hysteresis of superconducting constrictions. From the analysis of successive thermal instabilities in the transport characteristics of micron-size superconducting quantum interference devices with a well-controlled geometry, we obtain a complete picture of the different thermal regimes. These determine whether the junctions are hysteretic or not. Below the superconductor critical temperature, the critical current switches from a classical weak-link behavior to one driven by the proximity effect. The associated small amplitude of the critical current makes it robust with respect to the heat generation by phase-slips, leading to a non-hysteretic behavior.

cond-mat.supr-con↗

arXiv2014

Temperature and phase dynamics in superconducting weak-link

A time dependent thermal model for a superconducting constriction based weak-link (WL) is discussed for investigating the deterministic dynamics of its temperature and phase. A new dynamic regime is found where a non-zero voltage exists across the WL and its temperature stabilizes between the bath temperature and superconductor's critical temperature. This regime exists over a limited bias current range and gives rise to a new hysteretic regime in current-voltage characteristics. We also discuss the effect of fluctuations on the current-voltage characteristics and experimental implications of this dynamic regime.

cond-mat.supr-con↗