PyNomo software dataset for sciences and engineering nomogram construction.

This article examines different python-based codes to be run under PyNomo nomographer software to represent alignment charts or nomograms for formulas commonly used in sciences and engineering studies. PyNomo nomographer supports nine basic types of nomograms based on the format of the mathematical equation. The examined PyNomo codes cover the construction of the following types of nomogram: type 1, type 2, type 7, type 8, type 9, and type 10. Each PyNomo script includes some background and the underlying mathematics for the nomogram construction and how to implement each code into PyNomo software. Potential users can use these PyNomo codes, as template scripts, to customize and construct their own nomograms for a variety of technical applications. That is especially true since a considerable number of science and engineering equations fall into one of these covered nomogram types depending on the equation form involved.

Nomography: A renewed pedagogical tool to sciences and engineering high-education studies.

Nomography is defined as a branch of mathematics in which methods of graphical representation of functional dependencies are studied. The resulting graphs are called nomograms, alignment charts, or abacs. Along the past century, this science branch experienced extensive development and use in many contexts to support scientists and engineers with accurate and fast calculations of complex formulas to a practical precision. However, nomography declined by the end of the twentieth century with the development and popularisation of more capable and powerful personal computers and handheld calculators. Despite this context, nomography remains attractive due to its potential for rapid and accurate graphical calculations contributing to a better understanding of complex formulas. Thus, this work defines the alignment charts and their capabilities to justify their importance as graphical tools in sciences and engineering studies. Also, PyNomo software is introduced to build vector-based and scalable nomograms. Then, this work emphasizes the importance of including nomography as a valuable and renewed computational tool, in conjunction with PyNomo software, in an academic context. In line with that, several nomograms, which have been obtained with PyNomo software, are examined to grasp the true importance of this science branch and its capabilities in an educational context.

Characterizing cryogenic amplifiers with a matched temperature-variable noise source.

We present a cryogenic microwave noise source with a characteristic impedance of 50 Ω, which can be installed in a coaxial line of a cryostat. The bath temperature of the noise source is continuously variable between 0.1 K and 5 K without causing significant back-action heating on the sample space. As a proof-of-concept experiment, we perform Y-factor measurements of an amplifier cascade that includes a traveling wave parametric amplifier and a commercial high electron mobility transistor amplifier. We observe system noise temperatures as low as 680-200 +20 mK at 5.7 GHz corresponding to 1.5-0.7 +0.1 excess photons. The system we present has immediate applications in the validation of solid-state qubit readout lines.

Inductive single-electron transistor.

We demonstrate a sensitive method of charge detection based on radio-frequency readout of the Josephson inductance of a superconducting single-electron transistor. Charge sensitivity 1.4 x 10(-4) e/square root Hz, limited by a preamplifier, is achieved in an operation mode which takes advantage of the nonlinearity of the Josephson potential. Owing to reactive readout, our setup has more than 2 orders of magnitude lower dissipation than the existing method of radio-frequency electrometry. With an optimized sample, we expect uncoupled energy sensitivity below variant Planck's over h in the same experimental scheme.