Guartester

Arduino® UNO R4 Minima

7 segment display

Arduino IDE

Black Potentiometer

White Push button

<html><body> <figure><img src="https://projects.arduinocontent.cc/8d78465f-1b43-4d6f-b7b0-8b39e1706632.png"/><figcaption>Guartester can use compatible with Arduino UNO R4 Minima or WiFI</figcaption></figure> This device has a simple purpose: to measure whether you can influence the generation of random numbers . More precisely, it explores whether human consciousness might influence physical systems. The project is inspired by experiments conducted by the Princeton Engineering Anomalies Research (PEAR) laboratory at Princeton University. It uses the Arduino UNO R4 Minima because of a relatively little-known feature: the SCE5 security engine, which provides access to a hardware true random number generator (TRNG). <figure><img src="https://projects.arduinocontent.cc/40655797-3820-4f6b-8707-951691b34102.jpg"/><figcaption></figcaption></figure><h3>True Random</h3>When we request a random number, most computers and development boards use a pseudorandom number generator (PRNG). This is a mathematical algorithm that uses an initial value, called a seed, to generate a deterministic sequence. Given the same seed and algorithm, the same sequence can be reproduced. Here is a basic Arduino pseudorandom number example: <pre>long randNumber; </pre><pre>void setup() { </pre><pre>	 Serial.begin(9600); </pre><pre>	 randomSeed(analogRead(0)); </pre><pre>} </pre><pre>void loop() { </pre><pre>	 randNumber = random(300); </pre><pre>	 Serial.println(randNumber); </pre><pre>	 delay(50); </pre><pre>} </pre>Reading an unconnected analog input can provide a variable seed, but it does not turn the pseudorandom generator into a true random number generator. A hardware true random number generator obtains randomness from a physical process. Its output is not reproduced simply by reusing a software seed. <figure><img src="https://projects.arduinocontent.cc/f533ec7a-7a92-40f2-b456-c5053f464287.png"/><figcaption></figcaption></figure> To access the UNO R4 Minima's hardware random number generator, this project uses the TRNG library: <a href="https://github.com/embarquech/trng">https://github.com/embarquech/trng </a>Example: <pre>TRNG.begin(); </pre><pre>uint32_t hardwareValue; </pre><pre>TRNG.random32(&amp;hardwareValue); </pre><pre>int finalNumber = (hardwareValue % 10) + 1; </pre><h3>The Enclosure</h3>A follower gave me an old handheld soil-testing device manufactured in Italy. I decided to reuse its enclosure for this project, adding a hole for the rotary sensor. I named the device GUAR, short for “Generador Uniforme de Anomalías Random.” Components <ol><li>- Arduino UNO R4 Minima </li><li>- HW-069 four-digit display based on the TM1637 driver </li><li>- DFRobot Gravity Analog Rotation Sensor DFR0054 </li><li>- Gravity digital push button </li><li>- Recycled enclosure from an old Italian soil-testing device </li><li>- Jumper wires and breadboard </li><li>- 9 V battery </li></ol><h3>Circuit Connections</h3><h3></h3><figure><img src="https://projects.arduinocontent.cc/e9d927ce-e30e-4942-a85e-24ae63c049b6.jpg"/><figcaption></figcaption></figure> TM1637 display - CLK: D2 - DIO: D3 - VCC: 5V - GND: GND Rotary sensor - Signal: A0 - VCC: 5V - GND: GND Push button - Signal: D4 - Other terminal: GND Battery - Positive: VIN - Negative: GND <h3>Installing the Software</h3><h3></h3><figure><img src="https://projects.arduinocontent.cc/54eab110-2219-4e45-8faa-3b753e66ad2c.png"/><figcaption></figcaption></figure> <ol><li>1. Install the Arduino IDE. </li><li>2. Install the TM1637 display library. </li><li>3. Install the TRNG library: https://github.com/embarquech/trng </li><li>4. Connect the Arduino UNO R4 Minima to your computer using a USB-C cable. </li><li>5. Open guarx.ino. </li><li>6. Select Arduino UNO R4 Minima as the board and choose the appropriate serial port. </li><li>7. Compile and upload the program. </li></ol><h3>Using GUAR Tester</h3><h3></h3><figure><img src="https://projects.arduinocontent.cc/b0707710-582b-48b1-a8b1-7834988b4c70.jpg"/><figcaption></figcaption></figure> Power the device using the 9 V battery and wait for the startup sequence. Use the rotary sensor to select one of three conditions: <ol><li>- LOW: Attempt to produce fewer 1s. </li><li>- BASELINE: Run the experiment without a specific intention. </li><li>- HIGH: Attempt to produce more 1s. </li></ol>Press the button to start the session. Maintain the selected intention while the device runs the experiment. Each session consists of 60 trials, with 200 bits per trial, for a total of 12,000 bits. For a perfectly balanced random sequence, each trial is expected to contain approximately 100 ones and 100 zeros. At the end of the session, the display shows the results and cumulative statistics. Changing the selected condition resets the accumulated statistics. Results stored in RAM are lost when the device is powered off, so save the serial output if you want to analyse it later. <figure><img src="https://projects.arduinocontent.cc/05fe39d0-11c8-4ef4-ac6c-fd1f13badae1.jpg"/><figcaption></figcaption></figure> <h3>Configuration Parameters</h3>The main configuration parameters are: <ol><li>- Bits per trial: 200 </li><li>- Trials per session: 60 </li><li>- Bits per session: 12,000 </li><li>- Z-score threshold: 1.645 </li><li>- Result display pause: 3,000 milliseconds </li><li>- Serial baud rate: 115200 </li><li>- Rotary sensor input: A0 </li><li>- Push button input: D4 </li></ol>The number of bits per trial determines how many random bits are evaluated in each trial. The number of trials determines how many measurements are performed during a session. The significance threshold is used to evaluate deviations from the expected distribution of zeros and ones. The display pause determines how long the results remain visible before the device returns to the condition selector. <figure><img src="https://projects.arduinocontent.cc/2e86833b-5bc0-4df7-8f2f-38a00b366005.png"/><figcaption></figcaption></figure> <h3>Analysing the Results</h3>Open the Arduino IDE Serial Monitor and set the baud rate to 115200. The serial output includes a CSV header and a data row for each completed trial, along with status messages. Copy the output, retain the header and data rows, remove status messages, and save the result as a CSV file.The CSV contains trial data and cumulative statistics. The available fields are listed in its header. <figure><img src="https://projects.arduinocontent.cc/88428621-a1c7-4c11-95ce-8fb4b6c69e56.png"/><figcaption>Guar Tester</figcaption></figure> <h3>Understanding the Statistics</h3>For a random sequence of independent bits, the expected probability of obtaining a 1 is 0.5. For a trial containing 200 bits, the expected number of ones is 100. The standard deviation is: <pre>SD = √(200 × 0.5 × 0.5) ≈ 7.07 </pre>Across a session of 12,000 bits, the expected number of ones is 6,000, with a standard deviation of approximately 54.77. A result of 6,001 ones and 5,999 zeros is only a one-bit deviation from the expected count and does not indicate a meaningful effect. <h3>Z-Score</h3>The Z-score measures how far the observed number of ones deviates from the expected number, expressed in standard deviations. <pre>Z = (X − N/2) / √(N/4) </pre>Where: <ol><li>- X is the observed number of ones. </li><li>- N is the total number of bits. </li></ol>A positive Z-score indicates more ones than expected. A negative Z-score indicates fewer ones than expected. A threshold of 1.645 corresponds to a one-sided significance level of approximately 5%. For a two-sided test at the 5% significance level, the corresponding thresholds are approximately −1.96 and +1.96. Compare results across repeated sessions under HIGH, LOW and BASELINE conditions. <h3>Demo</h3><h3><a href="https://www.youtube.com/shorts/uykwa75qbaQ">https://www.youtube.com/shorts/uykwa75qbaQ</a></h3><h3>Results and Observations</h3>I have obtained several runs in the intended direction: some attempts to produce more 1s resulted in a few dozen additional 1s, while attempts to produce fewer 1s sometimes resulted in fewer. So far, however, I have not obtained statistically significant results. <h3>Final Thoughts</h3>There is something fascinating about building an instrument to explore a question somewhere between electronics, probability, and the limits of our understanding. A discarded soil tester becomes a random event generator, a handful of bits becomes a measurement, and a small enclosure becomes a machine for asking unusual questions and discovering new things.<h3>References and further reading</h3>Princeton Engineering Anomalies Research — REG experiments<a href="https://phere.global-mind.org/reg.html">https://phere.global-mind.org/reg.html</a>Jahn &amp; Dunne, The PEAR Proposition (2007)<a href="https://pubmed.ncbi.nlm.nih.gov/17560342/">https://pubmed.ncbi.nlm.nih.gov/17560342/</a>PEAR REG experiments: equipment and design<a href="https://phere.global-mind.org/rdnelson/reg.html">https://phere.global-mind.org/rdnelson/reg.html</a>PEAR analysis of variance of REG experiments<a href="https://phere.global-mind.org/rdnelson/anova.html">https://phere.global-mind.org/rdnelson/anova.html</a>Princeton Engineering Anomalies Research — overview and history<a href="https://psi-encyclopedia.spr.ac.uk/articles/princeton-engineering-anomalies-research-pear/">https://psi-encyclopedia.spr.ac.uk/articles/princeton-engineering-anomalies-research-pear/</a>Arduino UNO R4 Minima — official documentation<a href="https://docs.arduino.cc/hardware/uno-r4-minima">https://docs.arduino.cc/hardware/uno-r4-minima</a>Renesas RA4M1 — official datasheet<a href="https://www.renesas.com/en/document/dst/ra4m1-group-datasheet">https://www.renesas.com/en/document/dst/ra4m1-group-datasheet</a></body></html>

Guartester

An experimental device designed to investigate whether human intention can influence number numbers