Modular Inversion Hidden Number Problem- A Lattice Approach

The Modular Inversion Hidden Number Problem (MIHNP) was introduced by Boneh, Halevi and Howgrave-Graham in Asiacrypt 2001 (BHH’01). They provided two heuristics - in Method I, two-third of the output bits are required to solve the problem, whereas the more efficient heuristic (Method II) requires only one-third of the bits of the output. After more than a decade, here Sarkar in [28] identified that the claim in Method II is actually not correct and a detailed calculation justified that this method too requires two-third of the bits of the output, contrary to the claim in BHH’01. He reconstructed the lattice and give a bound which heuristically solve with half of the output bits. Although J.Xu et al in [29] solved it with only one-third of the output bits asymptotically but that technique is difficult to understand and implement. Here we essentially use similar idea of [28] but in a clever way such that it is a better bound although we solve the problem heuristically with only half of the output bits in asymptotic sense. This is lot easier to understand and implement. Also experimental results support the claim corresponding to our heuristics. In the last section we actually talk about a variant of this which seems to be hard to solve under lattice attack

Deterministic Identity Testing Paradigms for Bounded Top-Fanin Depth-4 Circuits

Polynomial Identity Testing (PIT) is a fundamental computational problem. The famous depth-4 reduction (Agrawal & Vinay, FOCS\u2708) has made PIT for depth-4 circuits, an enticing pursuit. The largely open special-cases of sum-product-of-sum-of-univariates (?^[k] ? ? ?) and sum-product-of-constant-degree-polynomials (?^[k] ? ? ?^[?]), for constants k, ?, have been a source of many great ideas in the last two decades. For eg. depth-3 ideas (Dvir & Shpilka, STOC\u2705; Kayal & Saxena, CCC\u2706; Saxena & Seshadhri, FOCS\u2710, STOC\u2711); depth-4 ideas (Beecken, Mittmann & Saxena, ICALP\u2711; Saha,Saxena & Saptharishi, Comput.Compl.\u2713; Forbes, FOCS\u2715; Kumar & Saraf, CCC\u2716); geometric Sylvester-Gallai ideas (Kayal & Saraf, FOCS\u2709; Shpilka, STOC\u2719; Peleg & Shpilka, CCC\u2720, STOC\u2721). We solve two of the basic underlying open problems in this work. We give the first polynomial-time PIT for ?^[k] ? ? ?. Further, we give the first quasipolynomial time blackbox PIT for both ?^[k] ? ? ? and ?^[k] ? ? ?^[?]. No subexponential time algorithm was known prior to this work (even if k = ? = 3). A key technical ingredient in all the three algorithms is how the logarithmic derivative, and its power-series, modify the top ?-gate to ?

Electric Vehicle Battery Supply Chain and Critical Materials: A Brief Survey of State of the Art

Electric vehicles (EVs) have been garnering wide attention over conventional fossil fuel-based vehicles due to the serious concerns of environmental pollution and crude oil depletion. In this article, we have conducted a systematic literature survey to explore the battery raw material supply chain, material processing, and the economy behind the commodity price appreciation. We present significant areas of concern, including resource reserves, supply, demand, geographical distribution, battery reuse, and recycling industries. Furthermore, details of the battery supply chain and its associated steps are illustrated. The authors believe the presented study will be an information cornerstone in boosting manufacturing and understanding the key components and materials required to facilitate EV battery production. Further, this study discusses the major industries, and their policies and global market share in each material category