Amenti LabsAmenti Labs
active investigation

Reproducing PEAR Lab Experiments

Modern reproductions of the Princeton Engineering Anomalies Research laboratory's consciousness-machine interaction experiments.

This page is a project summary for work in progress rather than a finished public report. learn more / contact

contributors: Amenti Labs
PEAR Lab Archive ↗OpenEntropy ↗

Overview

The Princeton Engineering Anomalies Research (PEAR) laboratory operated from 1979 to 2007 at Princeton University. Over 28 years, the lab ran millions of trials testing whether human consciousness can shift the behavior of random physical systems. This project reproduces those experiments with modern hardware and statistics.

Background

PEAR researchers reported that human operators could produce small but statistically detectable deviations in random event generator (REG) outputs through conscious intention. They published findings across dozens of peer-reviewed papers. Independent replications have been inconsistent, which makes modern reproduction with better tools a worthwhile effort.

The original experiments used electronic noise diodes and other hardware RNGs from the 1980s and 1990s. Our reproductions use hardware QRNGs based on photonic quantum noise, plus dozens of unconventional entropy sources from modern computing hardware. We pair these with automated collection, calibration, and analysis.

Apparatus

The experimental apparatus runs on OpenEntropy, a Rust-based entropy harvesting system that pulls raw, unconditioned randomness from 63 physical noise sources inside computers. Unlike random number APIs that run output through deterministic algorithms (DRBGs), OpenEntropy preserves the actual hardware signal. Detecting the micro-biases PEAR's work hypothesized requires an unfiltered signal.

Entropy Sources

OpenEntropy collects from 13 categories of physical noise: clock jitter and PLL phase noise, branch predictor state and cache timing, crystal oscillator beats and PCIe PHY jitter, Metal shader thread divergence, microphone ADC thermal noise, camera sensor dark current, Bluetooth RF environment, and more.

The QCicada photonic QRNG serves as the main source for PEAR reproductions, producing true quantum randomness from vacuum fluctuations in a photonic beam splitter. The other 62 sources provide cross-correlation baselines and control channels.

Raw Mode

Most QRNG APIs only expose post-DRBG output. SHA-256 conditioning destroys the raw hardware signal before the user sees it. OpenEntropy's raw mode bypasses all conditioning, delivering XOR-combined bytes straight from the hardware. Here is why that matters: if intention produces a micro-bias in the physical noise, conditioning would erase it.

Three output modes are available:

  • Raw. Unconditioned bytes for signal analysis.
  • Von Neumann. Debiasing only. Removes first-order bias while preserving higher-order structure.
  • SHA-256. Full cryptographic conditioning for control trials.

Calibration

Before any recording session, OpenEntropy runs calibration checks: terminal z-score within ±2.0, bit-level bias below 0.005, Shannon entropy above 7.9 bits per byte, and z-score standard deviation between 0.85 and 1.15. Recording is blocked if any check fails. This prevents weak sources from confounding results, a control PEAR's original apparatus lacked.

Trial Methodology

OpenEntropy implements the PEAR trial analysis method. Let's break it down:

  1. Trial slicing. Raw entropy is divided into fixed-length trials (default: 200 bits each).
  2. Per-trial statistics. Each trial produces a 1-bit count, z-score deviation from the expected mean (N/2), and running cumulative deviation.
  3. Terminal z-score. The cumulative deviation is normalized: Z = cumulative_deviation / sqrt(num_trials * N/4). This is the same statistic PEAR reported across their 28 years of data.
  4. Effect size. Computed as terminal_z / sqrt(num_trials), allowing direct comparison to PEAR's published values.
  5. Multi-session composition. Stouffer's method combines z-scores across sessions with sqrt(N) weighting.

Statistical Validation

Each session runs through 31 tests derived from NIST SP 800-22: frequency and runs tests, serial and spectral analysis, cross-correlation between sources, stationarity testing, autocorrelation profiling, and bit-by-bit bias analysis. Optional system telemetry (CPU load, thermal state, power mode) is recorded alongside entropy data.

Experimental Protocol

Sessions follow a three-condition design:

  • Intention (high). Participant directs intention toward increasing bit count above the expected mean.
  • Intention (low). Participant directs intention toward decreasing bit count below the expected mean.
  • Baseline. No intention directive. Participant is present but does not try to influence output.

Each session starts with calibration, runs trials across all three conditions in counterbalanced order, and ends with a full analysis pass.

Status

Hardware and software are operational. The QCicada QRNG and OpenEntropy are collecting data. We are developing the formal reproduction protocols.

Sources

  • Jahn, R.G. & Dunne, B.J. "Margins of Reality: The Role of Consciousness in the Physical World." Harcourt Brace Jovanovich, 1987.
  • Jahn, R.G. et al. "Correlations of Random Binary Sequences with Pre-Stated Operator Intention." Journal of Scientific Exploration, Vol. 11, No. 3, 1997. https://www.scientificexploration.org/docs/11/jse_11_3_jahn.pdf
  • PEAR Lab. "PEAR Proposition." Princeton University, 2007. https://pear-lab.com
  • National Institute of Standards and Technology. "A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications." NIST SP 800-22 Rev. 1a, 2010.