Tyler Sachs

Undergraduate physicist specializing in computational and experimental applied physics, with hands-on experience in cryogenic systems, superconductivity, and data-driven modeling. Skilled in Python-based numerical simulation, data analysis, and instrumentation design, with a strong foundation in thermodynamics, electrodynamics, and quantum physics. Passionate about applying physics principles to complex systems through simulation, precision measurement, and collaborative research.

ONGOING:

Superconductivity Lab Design, Student Project Lead , Sep 2025 – present

• Collaborating with Dr. Galitzky to design and execute a low-temperature superconductivity experiment investigating Josephson junctions, persistent currents with hall probe, and distinctions between Type I and Type II superconductors.
• Operating a dilution refrigerator and cryogenic electronics to conduct measurements near 1 K, ensuring thermal stability and precise control of magnetic and current parameters.
• Developing a standardized experimental protocol to support future research and instructional use in superconductivity studies.

Computational Analysis of Josephson Dynamics, Research Team Member, Oct 2025 – present

• Collaborating in a team of three to perform a computational study of superconductivity and Josephson junction dynamics using RCSJ and Ginzburg–Landau–based models.
• Conducting parameter estimation and numerical simulation of current–voltage behavior and Shapiro steps using Python (NumPy, SciPy, Matplotlib, lmfit, QuTiP).
• Supplemented simulations with limited data from a dilution refrigerator system for comparison; the project otherwise remains fully independent of laboratory work.
• Focused on connecting theoretical models with measurable superconducting phenomena through data-driven analysis and simulation.

PAST:

Crime Trends with Weather and Housing in Austin, Project Leader, Jan 2025 – May 2025

• Analyzed crime in Austin using NIRBS data from Austin Open Data Portal, cross-referencing with Weather and residential information where applicable
• Utilized RStudio and Python to clean and visualize multiple data-frames with 20+ columns and nearly 500K rows
• Facilitated efficient group work and communications using collaborative software tools such as GitHub
• Presented findings to graduate students, professors, and employees of the city of Austin

150+ Hours:

• Botanical Gardens, Austin and Fort Worth
• Union Gospel Mission Lancaster Shelter, Fort Worth
• Austin Annual Book Festival, Austin
• Trinity River Trash Bash, Fort Worth
• NAMIWalks Mental Health, Austin