arXiv subjects

Pranav Joshi

Publications and source records attributed to Pranav Joshi.

7 recordsLinked to original sources

arXiv2026

Study of discrete boundary layer suction for transition delay

In the present study we have assessed the effect of suction through discrete perforations on the transition of the Blasius boundary layer. In particular, the intermittency and the spectra of the streamwise velocity fluctuations, obtained using hot-wire anemometry, were used to evaluate the optimum suction, i.e., one that provides the greatest delay in transition. The displacement thickness Reynolds number at suction was varied between 1400 and 1600, while the number of rows of holes was either four or ten. The suction holes had diameter of the order of the displacement thickness of the boundary layer, a practical size from manufacturing and maintenance perspectives. As the suction strength was increased the transition front moved downstream, with the maximum delay in transition occurring at the optimum suction. When the suction was increased further, the transition front moved upstream again. The results, supported by a scaling analysis, showed that suction volume flow rate is a better indicator of the effects of suction on the transition delay than suction velocity. In particular, suction through different numbers of rows of perforations produces largely similar effects on the boundary layer transition, provided the suction volume flow rate remains the same. However, suction through fewer rows provided a slightly greater delay in transition in addition to a slightly lower optimum suction volume flow rate. The results also showed that suction applied at a lower Reynolds number provides a substantially greater transition delay but at slightly higher values of the normalized optimum suction volume flow rate.

physics.flu-dyn↗

arXiv2025

Efficient and rate-optimal list-decoding in the presence of minimal feedback: Weldon and Slepian-Wolf in sheep's clothing

Given a channel with length-$n$ inputs and outputs over the alphabet $\{0,1,\ldots,q-1\}$, and of which a fraction $\varrho \in (0,1-1/q)$ of symbols can be arbitrarily corrupted by an adversary, a fundamental problem is that of communicating at rates close to the information-theoretically optimal values, while ensuring the receiver can infer that the transmitter's message is from a ``small" set. While the existence of such codes is known, and constructions with computationally tractable encoding/decoding procedures are known for large $q$, we provide the first schemes that attain this performance for any $q \geq 2$, as long as low-rate feedback (asymptotically negligible relative to the number of transmissions) from the receiver to the transmitter is available. For any sufficiently small $\varepsilon > 0$ and $\varrho \in (1-{1}/{q}-\Theta(\sqrt{\varepsilon}))$ our minimal feedback scheme has the following parameters: Rate $1-H_q(\varrho) - \varepsilon$ (i.e., $\varepsilon$-close to information-theoretically optimal -- here $H_q(\varrho)$ is the $q$-ary entropy function), list-size $\exp\left(\mathcal{O}\left(\varepsilon^{-3/2}\log^2(1/\varepsilon)\right)\right)$, computational complexity of encoding/decoding $n^{\mathcal{O}(\varepsilon^{-1}\log(1/\varepsilon))}$, storage complexity $\mathcal{O}(n^{\eta+1}\log n)$ for a code design parameter $\eta>1$ that trades off storage complexity with the probability of error. The error probability is $\mathcal{O}(n^{-\eta})$, and the (vanishing) feedback rate is $\mathcal{O}({1}/{\sqrt{\log(n)}})$.

cs.IT↗

arXiv2025

Sampling-Based Estimation of Jaccard Containment and Similarity

This paper addresses the problem of estimating the containment and similarity between two sets using only random samples from each set, without relying on sketches of full sets. The study introduces a binomial model for predicting the overlap between samples, demonstrating that it is both accurate and practical when sample sizes are small compared to the original sets. The paper compares this model to previous approaches and shows that it provides better estimates under the considered conditions. It also analyzes the statistical properties of the estimator, including error bounds and sample size requirements needed to achieve a desired level of accuracy and confidence. The framework is extended to estimate set similarity, and the paper provides guidance for applying these methods in large scale data systems where only partial or sampled data is available.

stat.CO↗

arXiv2023

Critical Prandtl number for Heat Transfer Enhancement in Rotating Convection

Rotation, which stabilizes flow, can enhance the heat transfer in Rayleigh-B\'enard convection (RBC) through Ekman pumping. In this Letter, we present the results of our direct numerical simulations of rotating RBC, providing a comprehensive analysis of this heat transfer enhancement relative to non-rotating RBC in the parameter space of Rayleigh number ($Ra$), Prandtl number ($Pr$), and Taylor number ($Ta$). We show that for a given $Ra$, there exists a critical Prandtl number ($Pr_{cr}$) below which no significant heat transfer enhancement occurs at any rotation rate, and an optimal Prandtl number ($Pr_{opt}$) at which maximum heat transfer enhancement occurs at an optimal rotation rate ($Ta_{opt}$). Notably, $Pr_{cr}$, $Pr_{opt}$, $Ta_{opt}$, and the maximum heat transfer enhancement all increase with increasing $Ra$. We also demonstrate a significant heat transfer enhancement up to $Ra=2\times 10^{10}$ and predict that the enhancement would become even more pronounced at higher $Ra$, provided $Pr$ is also increased commensurately.

physics.flu-dyn↗

arXiv2023

Commitment over Gaussian Unfair Noisy Channels

Commitment is a key primitive which resides at the heart of several cryptographic protocols. Noisy channels can help realize information-theoretically secure commitment schemes, however, their imprecise statistical characterization can severely impair such schemes, especially their security guarantees. Keeping our focus on channel unreliability in this work, we study commitment over unreliable continuous alphabet channels called the Gaussian unfair noisy channels or Gaussian UNCs. We present the first results on the optimal throughput or commitment capacity of Gaussian UNCs. It is known that classical Gaussian channels have infinite commitment capacity, even under finite transmit power constraints. For unreliable Gaussian UNCs, we prove the surprising result that their commitment capacity may be finite, and in some cases, zero. When commitment is possible, we present achievable rate lower bounds by constructing positive - throughput protocols under given input power constraint, and (two-sided) channel elasticity at committer Alice and receiver Bob. Our achievability results establish an interesting fact - Gaussian UNCs with zero elasticity have infinite commitment capacity - which brings a completely new perspective to why classic Gaussian channels, i.e., Gaussian UNCs with zero elasticity, have infinite capacity. Finally, we precisely characterize the positive commitment capacity threshold for a Gaussian UNC in terms of the channel elasticity, when the transmit power tends to infinity.

cs.IT↗

arXiv2021

On Reverse Elastic Channels and the Asymmetry of Commitment Capacity under Channel Elasticity

Commitment is an important cryptographic primitive. It is well known that noisy channels are a promising resource to realize commitment in an information-theoretically secure manner. However, oftentimes, channel behaviour may be poorly characterized thereby limiting the commitment throughput and/or degrading the security guarantees; particularly problematic is when a dishonest party, unbeknown to the honest one, can maliciously alter the channel characteristics. Reverse elastic channels (RECs) are an interesting class of such unreliable channels, where only a dishonest committer, say, Alice can maliciously alter the channel. RECs have attracted recent interest in the study of several cryptographic primitives. Our principal contribution is the REC commitment capacity characterization; this proves a recent related conjecture. A key result is our tight converse which analyses a specific cheating strategy by Alice. RECs are closely related to the classic unfair noisy channels (UNCs); elastic channels (ECs), where only a dishonest receiver Bob can alter the channel, are similarly related. In stark contrast to UNCs, both RECs and ECs always exhibit positive commitment throughput for all non-trivial parameters. Interestingly, our results show that channels with exclusive one-sided elasticity for dishonest parties, exhibit a fundamental asymmetry where a committer with one-sided elasticity has a more debilitating effect on the commitment throughput than a receiver.

cs.IT↗

arXiv2018

Vision Based Dynamic Offside Line Marker for Soccer Games

Offside detection in soccer has emerged as one of the most important decisions with an average of 50 offside decisions every game. False detections and rash calls adversely affect game conditions and in many cases drastically change the outcome of the game. The human eye has finite precision and can only discern a limited amount of detail in a given instance. Current offside decisions are made manually by sideline referees and tend to remain controversial in many games. This calls for automated offside detection techniques in order to assist accurate refereeing. In this work, we have explicitly used computer vision and image processing techniques like Hough transform, color similarity (quantization), graph connected components, and vanishing point ideas to identify the probable offside regions. Keywords: Hough transform, connected components, KLT tracking, color similarity.

cs.CV↗