arXiv subjects

Rajan Walia

Publications and source records attributed to Rajan Walia.

4 recordsLinked to original sources

arXiv2026

Pressure induced electronic band evolution and observation of superconductivity in the Dirac semimetal ZrTe5

We report a comprehensive investigation of the pressure effects on the magnetotransport properties of the topological material ZrTe5 within 1 to 8 GPa pressure range. With increasing pressure, the characteristic peak (Tp) in its electrical resistivity first shifts to higher temperature and then moves quickly towards the lower temperature before disappearing eventually at 6 GPa. Beyond 6 GPa, the system exhibits metallic behavior across the entire temperature range, and superconductivity emerges below Tc = 1.8 K at 8 GPa. Based on the systematic magnetotransport measurement under pressure, we demonstrate that the superconductivity occurs following a significant electronic structure modulation possibly due to pressure induced structural changes near 6 GPa, which coincides with dramatic enhancement of the magnetoresistance (MR) reaching up to 1400 percent. Our experimental results are substantiated by density functional theory calculations as the application of pressure drastically alters the density of states near the Fermi level. Notably, multiple hole pockets emerge at the Fermi level from 4 GPa onward, and their contributions are further enhanced with increasing pressure. The combined experimental and theoretical investigation reveals a comprehensive evolution of electronic structure of Dirac semimetal ZrTe5 under pressure and suggest a possible link between the Fermi surface reconstruction in the pressure range of structural transition and emergence of superconductivity

cond-mat.mtrl-sci↗

arXiv2025

Effect of pressure on the transport properties and thermoelectric performance of Dirac semimetal ZrTe5

In this study, we have investigated and compared the effect of hydrostatic pressure up to ~20 kbar on the transport properties of ZrTe5 single crystals grown by chemical vapor transport (CVT) and flux methods. With the application of pressure, the electrical resistivity Rho(T) and thermopower S(T) of both crystals were found to increase in the whole temperature range unlike the other known thermoelectric materials, such as Bi2Te3, SnSe etc. This observation is supported by the complementary first-principles band structure calculation as the application of pressure widens the direct bandgap at Γ point. Moreover, the analysis of the pressure dependent magneto-transport and Shubnikov de-Hass oscillation results revealed an increase in carrier concentration and effective mass along with the reduction of mobility as pressure rises. Furthermore, with the application of pressure, the flux-grown ZrTe5 crystals display a transition from unipolar to bipolar charge transport as evidenced by the emergence of resistivity peak at T* under high pressure, unlike the CVT-grown ZrTe5 crystals where the bipolar charge transport near its characteristic resistivity peak (Tp) remains unaffected.

cond-mat.mtrl-sci↗

arXiv2021

Sham: A DSL for Fast DSLs

Domain-specific languages (DSLs) are touted as both easy to embed in programs and easy to optimize. Yet these goals are often in tension. Embedded or internal DSLs fit naturally with a host language, while inheriting the host's performance characteristics. External DSLs can use external optimizers and languages but sit apart from the host. We present Sham, a toolkit designed to enable internal DSLs with high performance. Sham provides a domain-specific language (embedded in Racket) for implementing other high-performance DSLs, with transparent compilation to assembly code at runtime. Sham is well suited as both a compilation target for other embedded DSLs and for transparently replacing DSL support code with faster versions. Sham provides seamless inter-operation with its host language without requiring any additional effort from its users. Sham also provides a framework for defining language syntax which implements Sham's own language interface as well. We validate Sham's design on a series of case studies, ranging from Krishnamurthi's classic automata DSL to a sound synthesis DSL and a probabilistic programming language. All of these are existing DSLs where we replaced the backend using Sham, resulting in major performance gains. We present an example-driven description of how Sham can smoothly enhance an existing DSL into a high-performance one. When compared to existing approaches for implementing high-performance DSLs, Sham's design aims for both simplicity and programmer control. This makes it easier to port our techniques to other languages and frameworks, or borrow Sham's innovations "à la carte" without adopting the whole approach. Sham builds a sophisticated and powerful DSL construction toolkit atop fundamental language features including higher-order functions, data structures, and a foreign-function interface (FFI), all readily available in other languages. Furthermore, Sham's approach allows DSL developers to simply write functions, either using Sham or generating Sham, without needing to work through complex staging or partial evaluation systems.

cs.PL↗

arXiv2019

From high-level inference algorithms to efficient code

Probabilistic programming languages are valuable because they allow domain experts to express probabilistic models and inference algorithms without worrying about irrelevant details. However, for decades there remained an important and popular class of probabilistic inference algorithms whose efficient implementation required manual low-level coding that is tedious and error-prone. They are algorithms whose idiomatic expression requires random array variables that are latent or whose likelihood is conjugate. Although that is how practitioners communicate and compose these algorithms on paper, executing such expressions requires eliminating the latent variables and recognizing the conjugacy by symbolic mathematics. Moreover, matching the performance of handwritten code requires speeding up loops by more than a constant factor. We show how probabilistic programs that directly and concisely express these desired inference algorithms can be compiled while maintaining efficiency. We introduce new transformations that turn high-level probabilistic programs with arrays into pure loop code. We then make great use of domain-specific invariants and norms to optimize the code, and to specialize and JIT-compile the code per execution. The resulting performance is competitive with manual implementations.

cs.PL↗