B.S. Physics · UMass Amherst

Caleb Aiken

Experimental physics.
Instrumentation & scientific computing.

My undergraduate research combined cosmic-ray muon detection, detector electronics, signal processing, NI data acquisition, and Python analysis for a superfluid-helium experiment.

Explore my software projects
Two long scintillator paddle assemblies mounted outside the cylindrical cryostat, with cables leading to a NIM crate below.
Muon veto researchHertel Lab · UMass Amherst

Experimental research.

Detector integration, waveform analysis, and laboratory measurements.

01 /

Featured research · Hertel Lab

Muon detection for
superfluid helium research

An external coincidence veto to tag cosmic-ray muons in a cryogenic dark-matter experiment.

  • NI DAQ
  • NIM electronics
  • Python / HDF5
Read the research case study

My contribution

  • Integrated prebuilt Eljen Technologies PVT scintillator paddles, supplied with ET Enterprises PMTs already attached, into the veto system.
  • Connected high-voltage signal handling, NIM coincidence logic, and NI data acquisition; designed, soldered, and integrated an RC high-pass filter between the amplifier and discriminator.
  • Developed a Python/HDF5 workflow for waveform processing and event timing, with analysis ongoing.
Undergraduate thesis

Analysis and writing in progress

Connected NIM crate with amplifier, discriminator, coincidence and power modules, plus two external preamplifier boxes and a bench signal generator.
Signal processing on the benchThe connected NIM electronics used in the research setup. The photograph documents the integration and cabling, rather than a complete circuit schematic.

Signal processing on the bench

The connected NIM electronics used in the research setup. The photograph documents the integration and cabling, rather than a complete circuit schematic.

Oscilloscope display showing yellow and magenta negative-going pulses, with the original voltage scales and a 1 microsecond per division timebase visible.
Inspecting the signalsTwo-channel oscilloscope capture from laboratory signal checks. Original instrument scales are retained. This image is not presented as a calibrated before-and-after filter measurement or a final event-identification result.

Inspecting the signals

Two-channel oscilloscope capture from laboratory signal checks. Original instrument scales are retained. This image is not presented as a calibrated before-and-after filter measurement or a final event-identification result.

Engineering contribution

Signal conditioning I built.

I designed, soldered, and integrated an RC high-pass filter in the amplifier-to-discriminator path. The filter conditions the amplified detector waveform before the discriminator applies a threshold.

Explore the filter and signal chain
Thesis overview & methods

The muon veto system

Construction of Muon Veto System for Studying Excimer Triplet Dynamics in Superfluid Helium-4

Cosmic-ray muons can produce long-lived He2* excimers in superfluid helium. The external veto tags muon passages so their timing can be compared with the cryogenic detector response and delayed triplet signals.

I took responsibility for system integration, electronics, data acquisition, troubleshooting, and documentation under faculty supervision.

Working manuscript · Analysis and writing in progress

≈1 μs
Coincidence timing scale
≈10 mK
Helium detector environment
Python / HDF5
Event-data analysis

Objective

Isolate the timing of triplet signals

Correlate coincidence-tagged muons with detector events to study delayed excimer behavior.

Experimental system

Detector, electronics, and acquisition

Prebuilt Eljen Technologies PVT paddles with ET Enterprises PMTs already attached, integrated with NIM coincidence logic and NI DAQ. The veto sits outside the cryogenic system.

Analysis workflow

From waveforms to event timing

Baseline correction, pulse identification, nearest-event matching, and Δt distributions from multichannel HDF5 data.

Measurement chain

  1. Cosmic-ray muon
  2. Scintillator coincidence
  3. Waveform acquisition
  4. Triplet timing analysis

Software projects.

Personal projects in local AI, scientific computing, and game development.

Local AI · Windows desktop

Mu
AI Desktop Companion

Development prototype

A Windows-first companion with local AI chat, saved conversations, search and branching, rich text, and speech playback. An integrated Machine Learning Lab supports dataset inspection, CPU training, and experiment comparison.

My contribution
Product direction, feature requirements, testing, and iterative refinement through Codex/Claude-assisted development.
Current focus
Usability, resource limits, and release qualification. The application is still in development.
  • C# / .NET
  • WPF
  • Local AI
  • Python workers
Architecture & development boundaries

The WPF desktop composes separate Core, Application, and Infrastructure layers. Local Python workers support the ML Lab and optional speech. Chat history and ML artifacts have separate persistence rules.

The ML Lab is part of Mu. Model advice proposes actions for review before execution. Full local advisor inference, neural playback reuse, physical display testing, and resource qualification remain release work; no installer is published.

View Mu on GitHub

Scientific computing · Python

Physics
Simulation Engine

Ongoing personal project

An interactive Python desktop application for exploring projectile motion, orbital mechanics, and special relativity. Parameter controls connect numerical models with plots and visual outputs.

My contribution
Computational structure, parameter inputs, visualization, and interface behavior, with numerical output checked against expected physics.
  • Python
  • Tkinter
  • NumPy
  • Matplotlib

Interactive systems · Game development

Sightbreak

Development alpha

A Godot tactical FPS prototype with offline 5v5 matches, an original industrial arena, dedicated-server play, and a separate account and inventory backend.

Current stage
A playable development build. Physical-device testing, sustained performance, and production readiness remain open work.
  • Godot
  • GDScript
  • Python
  • PostgreSQL
Gameplay, networking & current limits

Offline rounds include purchasing equipment, planting or defusing an objective, and spectating after elimination. Dedicated-server practice and the separate Python/PostgreSQL account and inventory service form distinct development systems.

Development exports and automated fixtures do not establish mobile usability or production readiness. Production matchmaking, sustained device performance, and release security remain open work.

View Sightbreak on GitHub

Independent product concept

CONTINUUM Research Environment

A workspace concept bringing scientific reading, LaTeX authoring, computation, and AI-assisted research into connected academic workflows.

Scope Research workflows and AI-assisted prototyping.

  • Product design
  • Research tools
  • Prototyping

Experience & capabilities.

Research

Undergraduate Research Assistant

Hertel Lab · UMass Amherst
–

Integrated a muon-tagging system for superfluid-helium research, working across detector hardware, electronics, DAQ, testing, waveform analysis, and technical documentation.

  • Particle detection
  • Instrumentation
  • Python

Laboratory

Experimental Physics Laboratory

PHYS 440 · UMass Amherst
–

Investigated quantum transport in gold nanojunctions and high-temperature superconductivity, from signal conditioning and data acquisition to trace interpretation and manuscript preparation.

  • Quantum transport
  • Data analysis
  • RevTeX

Independent

Software & Product Exploration

Scientific computing · Local AI · Interactive systems

Explore software ideas through project requirements, interaction design, testing, and iterative refinement. Recent work includes a physics simulation tool, the Mu desktop companion, and Sightbreak.

  • Product architecture
  • Research workflows
  • Prototyping

Tools I use in practice

01 / Experimental systems

Build & troubleshoot

  • Scintillators and photomultiplier tubes
  • NIM electronics and coincidence logic
  • High-voltage signals and NI DAQ
  • Cryogenic research environments

02 / Scientific computing

Process & interpret

  • Python, NumPy, and pandas
  • Matplotlib and data visualization
  • HDF5 event-data workflows
  • Numerical and statistical analysis

03 / Research communication

Document & explain

  • LaTeX and RevTeX
  • Technical reports and manuscripts
  • Literature synthesis
  • Cross-disciplinary explanation

Additional programming experience

  • C++
  • Java
  • Git

About Caleb.

I'm a physicist by training and a builder by temperament. I enjoy problems that bring physical intuition, careful measurement, and code together.

My research at UMass Amherst taught me to learn unfamiliar hardware and analysis methods, troubleshoot patiently, and document work so others can build on it. I'm looking to bring that approach to a research, scientific software, or technical team.

Independent explorations

From physical models to testable questions

My interests include phenomenology: connecting mathematical models to observations that could support or rule them out. I’m also exploring questions about black-hole interiors, quantum extremal surfaces, and information in gravity.

  • Particle physics and physics beyond the Standard Model
  • Quantum gravity and emergent spacetime
  • Quantum sensing and detector technology
  • Scientific software and research infrastructure

Let's talk research.

I’m open to research, instrumentation, scientific software, and data-focused opportunities. Get in touch to discuss a role or a project.