paper moved from private repo to PICA

Author: prathameshnium

docs/paper.md

@@ -1,48 +1,88 @@
 ---
-title: 'PICA: Python-based Instrument Control and Automation Software Suite'
+title: 'PICA: A Python-based Instrument Control and Automation Suite for Material Characterisation'
 tags:
-  - Python
-  - experimental physics
-  - laboratory automation
-  - instrument control
-  - materials science
-  - PyVISA
+  - python
+  - hardware control
+  - automation
+  - pyvisa
+  - condensed matter physics
+  - cryogenics
+  - scpi
 authors:
-  - name: Prathamesh Keshao Deshmukh
+  - name: Prathamesh Deshmukh
     orcid: 0009-0008-3278-0837
-    affiliation: 1
+    affiliation: "1,2"
+  - name: Srishti Kashyap
+    affiliation: "1,2"
+  - name: Swastika Mukherjee
+    affiliation: "1,2"
   - name: Sudip Mukherjee
-    affiliation: 1
+    orcid: 0000-0003-4734-9157
+    affiliation: "1,2"
+    corresponding: true
+    email: sudipm@csr.res.in
 affiliations:
  - name: UGC-DAE Consortium for Scientific Research, Mumbai Centre, India
    index: 1
-date: 21 November 2025
+ - name: Savitribai Phule Pune University, Pune, India
+   index: 2
+date: 27 November 2025
 bibliography: paper.bib
+
 ---
 
 # Summary
 
+PICA (Python-based Instrument Control and Automation) is a modular, open-source software suite designed to automate complex characterisation experiments in condensed matter physics. Developed to operate a custom laboratory-built measurement system, PICA provides a unified graphical user interface (GUI) for orchestrating high-precision instruments, specifically Keithley SourceMeters/Nanovoltmeters, Lakeshore Temperature Controllers, and Keysight LCR metres. The suite regulates the cryogenic environment to perform automated protocols such as temperature-dependent resistivity, current voltage (I-V) characteristics, and pyroelectric current measurement.
+
+<figure>
+<img src="pica-architecture-schematic.png" width="70%" />
+<figcaption>System architecture of PICA</figcaption>
+</figure>
+
+# Statement of need
+
+Advancements in experimental physics depend on the precise characterisation of material properties under extreme physical conditions. Researchers have to choose between expensive proprietary software like LabVIEW or developing a custom measurement script from scratch. While Python libraries such as PyVISA [] and PyMeasure [] provide excellent low-level driver support. They function as a primary developer toolkit. They often require significant boilerplate code to handle data visualisation and error handling, effectively forcing physicists to become software engineers.
+PICA fills this niche by providing a **"lab-ready" application layer** built on top of these libraries. It differentiates itself through.
+* **Accessibility:** A professional dashboard that allows researchers without coding experience to configure and run a complex measurement protocol immediately.
+* **Physical Validation:** Unlike general-purpose drivers, PICA's protocols are actively used for cryogenic transport measurements (80K - 320K) at the UGC DAE Consortium for Scientific Research, Mumbai Centre.Ensuring that the protocols are physically accurate and lab tested
+* **Process Isolation:** PICA deploys a `multiprocessing` architecture that runs instrumentation control logic in an isolated process. This ensures that hardware timeouts or driver crashes do not freeze the main dashboard, a common problem in single-threaded Python scripts.
+*  **Modular CLI Architecture:** As demonstrated in the repository, measurement modules also contain a CLI measurement module, which allows researchers to utilise PICA's measurement protocol and logic for headless automation or integration into other workflows without GUI overhead
+*  **Operational Transparency:** Unlike a Black box solution, PICA exposes the real-time command logs, aiding in debugging and ensuring scientific reproducibility.  
+
+
+# Design and Implementation
 
-[Your Summary Here]
+PICA is built on a modular architecture characterised by self-contained modules, ensuring future extensibility. This design allows individual measurement protocols to be modified independently or added without impacting the core system stability.
 
-# Statement of Need
+### Process Isolation and Concurrency 
 
-[Your Statement of Need Here]
+Unlike simple script-based automation, PICA decouples the User Interface (UI) from the instrumentation control logic. It utilises Python's standard 'multiprocessing' libraries to spawn isolated processes for measurement tasks.
+* **Stability:** If an instrument hangs or a communication bus times out, the isolated process can be terminated safely without freezing the main  GUI or losing previous data.
+* **Responsiveness:** The `tkinter`-based frontend remains responsive for live data plotting (using `matplotlib` [@hunter2007matplotlib] with blitting) even while the backend waits for hardware triggers.
+* **Data Integrity:** Experimental data integrity is prioritised through a "write on acquisition" strategy. Data is structured using `pandas` [@pandas2025] and is saved to a CSV file immediately after every acquisition point, preventing data loss in the event of a power failure or program/system crash.
 
-# Features
+### Hardware Abstraction Layer
 
+PICA utilises **PyVISA** [@grecco2023pyvisa] to abstract the low-level communication protocols (GPIB, USB, Ethernet). The software implements a strict initialisation routine:
+1. **Connection Verification:** A built-in "VISA Instrument Scanner" queries the bus ('*IDN?) to map the connected instrument addresses.
+2.  **State Sanitisation:** To eliminate the influence of all previous experiments, any stored data, cache in buffers, and existing settings or configurations, the instruments are explicitly reset (`*RST`) and buffers are cleared (`TRAC:CLE`), thereby providing a clean initial state before each measurement.
+3.  **Graceful Shutdown:** A "Safety Shutdown Routine" logic ensures that sources are ramped down to zero and heaters are disabled safely, even if the software is interrupted unexpectedly.
 
-[Your Features Here]
+### Operational Transparency
 
-# Software Architecture
+To support the scientific reproducibility of experimental results, PICA rejects hidden automation and replaces the "black box" paradigm with real-time console logs. Each measurement module has a console that records time-stamped actions (e.g., `[10:05:25] Keithley 6221: Ramping current to 10 mA`),
+ showing every command sent to the instrument. This allows researchers to verify measurement protocols and troubleshoot hardware instantly. 
 
+ ### Testing and Simulation
 
+To ensure measurement reliability, all of these modules were thoroughly tested with the corresponding hardware. Additionally, to facilitate development without constant access to physical instruments, PICA includes a testing suite that uses `pytest`. The suite employs `unittest.mock` to simulate VISA resources, allowing for the verification of backend logic streams, class structure, and command sequences in a continuous integration environment.
 
-[Your Architecture Description Here]
 
 # Acknowledgements
 
-We acknowledge the financial support provided under the SERB-CRG project grant No. CRG/2022/005676 from the Anusandhan National Research Foundation (ANRF), a statutory body of the Department of Science & Technology (DST), Government of India.
+We acknowledge the financial support provided under the SERB-GRG project grant No. CRG/2022/005676 from the Anusandhan National Research Foundation (ANRF), a statutory body of the Department of Science and Technology (DST), Government of India.
+PD would also like to thank Akshay Kamble for his valuable discussions on instrument control and for his effective assistance in resolving technical issues.
 
 # References