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STEM Talk at NI

Yesterday, I had the honor of presenting my experiences this past summer working on the Fermilab Holometer as well as my perspectives on STEM education at the high school level at National Instruments. Since my contribution to the Holometer project used National Instruments products and my family was vacationing in Austin, Texas, I offered to visit and share my experiences. I was a bit surprised when I was also asked to share my perspectives on STEM education in high school.

My presentation about the Holometer was pretty much the same as the one I gave the Global Physics Department. (I’ve written several posts about the Holometer.) I added more technical details on the NI products involved and how the signal analysis was performed to better match the audience.

At first, I didn’t feel qualified to address National Instruments employees, who work for a company that are amazing supporters of STEM in K-12 with their efforts with FIRST and LEGO. As a result, I started my presentation with disclaimers:

  • I do not have a master’s degree in STEM education
  • I am not a STEM education expert
  • I have not attended conferences and workshops in STEM education
  • I have taught at a one high school for five years

However, once I sat down and started thinking about what I would share, I realized that I, like most physics teachers, am qualified to at least share my perspective because:

every morning I get up and try to inspire students in science, technology, engineering, and mathematics by leveraging my experience as an engineer, an interviewer, a supervisor, and a teacher.

In my case, I specifically left National Instruments and software development to become a physics teacher to make some small contribution by inspiring students to pursue studies and careers in STEM-related fields.

I structured my presentation around three high-level themes which I elaborated with photos, videos, and stories:

Inspire Students with Experiences

I shared that few students are inspired because of something they only read or hear or see; they are inspired by their experience doing it. I shared the experiences of my FIRST Robotics Team, Science Olympiad Team, and Physics Club. Physics Club is an after school, student-driven, low-commitment group that allows all students opportunities to play, inquire, create, share, and explore. I shared our past experiences with near-space ballooning and the ping pong ball cannon. The second theme is:

Inspire Younger Students with Older Students

The main ideas for this theme are that students respond best to other students and students can loose interest in science during middle school. To address this, Physics Club and the FIRST Robotics Team perform outreach activities where younger students see projects done by the older students and build their own smaller-scale projects with the assistance of older students. The third theme is:

Inspire the other 98% in the Classroom

I was somewhat disappointed when I realized that all my efforts with FIRST Robotics, Science Olympiad, and Physics Club only involve 2% of the students at my school. I shared that this is a significant challenge but the most important theme. Many changes to a traditional classroom are required to inspire students about STEM:

  • Change Perceptions
  • Change Mindset
  • Change Pedagogy
  • Change Culture

I shared the importance of bring professionals into the classroom to share their experience and helping students appreciate that science is an active process done by real people. Despite significant local press about standards-based assessment and reporting, I shared how critical it is in my classrooms. I talked about Modeling Instruction, guided inquiry, project-based learning, and Project Lead the Way.

At the end, I felt compelled to take advantage of this opportunity to encourage those in attendance to help inspire students about STEM. I charged them to:

  • Be Aware
  • Promote Reform
  • Provide Support

I was honestly surprised at the level of interest in my presentation based on the attendance and the number of positive comments afterward. So, for those of you like me who are career changers, if the opportunity presents itself, share your experiences as a teacher with your former colleagues. We may gain more allies in the challenges that we face everyday.

Holometer: Computer-Based Measurements

As I described in the last post, the holographic noise can be detected if we measure the correlated noise between two adjacent interferometers. In order to do this effectively, the following requirements were specified:

  • Digitize two analog signals at 50 MS/s (50 mega-samples per second) from each interferometer. (This is faster than is actually required since we will be looking or the holographic noise near 4 MHz.)

  • stream all data to disk for offline analysis (2 channels at 50 MS/s = 200 MB/s). (This is critical for traceability and external verification of results.)

  • perform spectral analysis in real-time for experiment tuning. (Eliminating sources of noise and tuning the experiment will take considerable time and is only feasible if the effect of changes can be observed in near real-time.)

This last requirement is the kicker. Calculating power spectra and cross power spectra for multiple signals in software is time consuming. Today’s computers simply do not have the processing power to perform these calculations at a rate of 50 MS/s. In the past, if a software solution wasn’t possible, the only option was designing custom hardware which wasn’t feasible for most people and most projects. However, there is now a middle ground between software and hardware: Field Programmable Gate Arrays (FPGA). An FPGA is a hardware device that can take on multiple “personalities.” It consists of a variety of logic resources and the ability to interconnect these resources based on the specified description. While the tools to develop FPGAs have come a ways, they are still beyond the grasp of most scientists and engineers.

Let’s take a step back and look at this in a historical context. Fifteen years ago I was designing integrated circuits using VHDL (VHSIC (very-high-speed integrated circuit) description language) in a graduate class. If software wasn’t fast enough, you designed your own hardware. You would simulate and test your design and then send it off to be manufactured. Shortly thereafter, I started working in the field of computer-based measurements when I started at National Instruments developing driver software for DAQ (Data AcQuisition). At that time we just had started supporting the PCI bus along with NuBus (Mac), PCMCIA, and AT (Windows) as well as some other buses I would rather not mention. Our high-end DAQ card was a multifunction-card that could acquire analog signals at 20 kS/s.

Fast forward to the present. A lot of instrumentation is used in the development of this experiment:


However, almost all that is required to satisfy the above requirements in contained in just part of this PXIe chassis:

PXI Chassis

Slots 2 and 3 contain R-Series devices that are used to run control loops to keep the laser locked. While an incredibly interesting and sophisticated application, it is not related to the above requirements. Slot 6 contains an NI PXIe-5122 digitizer. It is a 2-channel, 14-bit digitizer that can sample at 100 MS/s. While we only need to sample at 50 MS/s, we actually run at 100 MS/s because that allows us to leverage the built-in 35 MHz antialiasing filter. The binary data is streamed from the digitizer, to the controller (slot 1), and then to the NI HDD-8265 12-drive RAID array (not pictured). These devices satisfy the first two requirements quite well. As I mentioned, the most challenging and interesting part of this application is computing the power spectra and cross power spectrum at 50 MS/s. In slot 7 is an NI PXIe-7965R FlexRIO device which contains the largest FPGA available from National Instruments. Often this device is used in conjunction with an analog front-end module. However, since we already had the 5122 and wanted to take advantage of the 5122’s calibration, filtering, and synchronization features; we used the 5122 as the analog front end for the FlexRIO device. The 5122 and the 7965R support peer-to-peer streaming. The controller isn’t involved in this streaming and the data doesn’t even leave the bus segment. I programmed the FPGA on the 7965R using the FPGA Toolkit for LabVIEW. This enabled me to write familiar looking LabVIEW code (within certain constraints) and then leverage the LabVIEW compiler and Xilinx tools to produce the FPGA bitfile. The FPGA calculates and accumulates the power spectra for the two channels and the cross power spectrum between them using an optimized and sophisticated algorithm based on the approach used for the GEO 600 experiment. We hope to publish this IP through National Instruments in some way to share it with the community. The accumulated power spectra and cross power spectrum are streamed from the FlexRIO to the controller for normalization, display, and logging.

This past Friday was my last day at Fermilab working on the Holometer experiment. It was quite satisfying to watch the noise floor of the cross power spectrum of the two photodiodes drop as the application ran. While I didn’t finish everything I wanted and expect there are certainly bugs left to find and fix, I at least left them with a solid application that satisfies the requirements. I look forward to stopping in over the next year and seeing their progress!

Disclaimer. I obviously used to work at National Instruments. I have a lot of friends who work at NI. As a shareholder, I want NI to be successful. This post may seem a bit evangelical, but you have to admit that it is pretty amazing what a high school teacher can do in six weeks with off-the-shelf hardware and software.

This post is one in a series about The Holometer experiment and my work at Fermilab in the Summer of 2011:

Holometer: Correlated Interferometers

In the previous post, I attempted to explain why an interferometer is susceptible to the holographic noise. However, this holographic noise is just one of many sources of noise that would be detected by the photodiode and digitizer. Some of these other sources of noise are more powerful than the holographic noise. Given that, how do we measure the holographic noise with an interferometer? We don’t. We measure the correlated noise between two adjacent interferometers. I previously explained how correlated noise that would otherwise be undetected can be measured by calculating a cross power spectrum. That is exactly how the Holometer, which is a pair of adjacent interferometers, measures the holographic noise.

The elephant in the room and, in my limited experience, the most challenging idea related to this experiment, is: why would the holographic noise from two adjacent interferometers be correlated? I’ve struggled trying to answer this question more than I’ve struggled with anything else this summer. I finally realized that one reason I was struggling so much is that I set myself up to fail from the start. I’ve been trying to explain this correlation from the perspective of quantum mechanics and general relativity. That approach is a nonstarter because quantum mechanics and general relativity don’t explain the holographic principle. This is New Physics, Planckian Physics! Another reason that I’ve struggled trying to answer this question is, quite simply, this is crazy stuff. Think about double-slit experiments with electrons, Bell Inequalities, the Einstein–Podolsky–Rosen experiment, or the Brown and Twiss interferometer. All of these are crazy. Most people wouldn’t believe them except for the fact that they have been demonstrated experimentally. The same can be said of the Holometer, most people may not believe that the holographic noise is present or is correlated until we measure it.

Let’s take a step back and take a look at light cones. A light cone contains the volume that defines the possible path of light, originating at some event, through space time. Two of the dimensions of the cone are spacial and the third is time. The upward opening cone is the future light cone that describes the potential paths of the light after the event and the downward opening cone is the past light cone. Only events within the past light cone can affect the event. This is called causality.


(figure 1: past and future light cones (source: Wikipedia))

The following diagram illustrates what is referred to as the causal diamond for an interferometer. The top half of the diamond is the past light cone of the beamsplitter reflection. The bottom-half of the diamond is the future light cone of another reflection from the beamsplitter. The causal diamond is the intersection of these light cones. The red lines are the arms of the interferometer.

inteferometer space-time diagram

(figure 2: interferometer causal diamond (source: Professor Craig Hogan))

This is the most important diagram of the experiment. Someone inscribed it on the concrete slab that will support one end of the interferometers:

causal diamond inscription

(figure 3: interferometer causal diamond preserved in concrete)

We are going to focus on the “wedge” of the causal diamond defined by the arms of the interferometer. The greater the overlap of these causal-diamond wedges for a pair of interferometers, the greater the correlated holographic noise. Therefore, these two adjacent interferometers would exhibit uncorrelated holographic noise:

uncorrelated interferometers

(figure 4: interferometer pair with non-overlapping causal diamonds)

While these two adjacent interferometers would exhibit highly correlated holographic noise:

correlated interferometers

(figure 5: interferometer pair with overlapping causal diamonds)

Why? The key idea is explained in the Holometer Proposal.

In the holographic effective theory built on light sheets, time and longitudinal position are identified. Measurement of a position at one point on a light sheet collapses the wavefunction at other points on the wavefront, even though they have spacelike separation. The apparent motion is thus in common across a significant transverse distance— not only across a macroscopic beamsplitter, say, but even between disconnected systems.

Let’s look at a top-view perspective of the two overlapping interferometers to examine this idea:

correlated wavefronts

(figure 6: wavefront in pair of correlated interferometers)

As the wavefront travels to the right in interferometer #1, the collapsing wave function results in a common motion of the two interferometers where their two causal diamonds overlap. The same occurs with the adjacent arms in the perpendicular direction. Therefore, these two interferometers will have highly correlated holographic noise. However for these two interferometers:

uncorrelated wavefronts

(figure 7: wavefront in pair of uncorrelated interferometers)

As the wavefront travels to the right in interferometer #1, the collapsing wave function doesn’t affect interferometer #2. There would not be any common motion between the arms in the x direction and, therefore, the two interferometers will have uncorrelated holographic noise.

The Holometer experiment tests the hypothesis illustrated by figures 6 and 7. We build a pair of interferometers as illustrated in figure 6. We then isolate the correlated holographic noise between the two interferometers. Then to prove that the noise is truly due to the Holographic Principle, we adjust the beam splitter to send the light down a fifth arm such that the experiment is arranged as illustrated in figure 7. We then are unable to identify correlated holographic noise between the two interferometers. QED.

All that is left for me to present is how we are going to measure the correlated holographic noise. That will be the topic of the final post. Ah, finally something in which I have some expertise!

This post is one in a series about The Holometer experiment and my work at Fermilab in the Summer of 2011:

Holometer: Transverse Jitter

Time to get serious. How does the Holometer, which is a pair of interferometers detect holographic noise? Fortunately, I met with Craig Hogan who is the Director of the Fermilab Center for Particle Astrophysics and a professor at University of Chicago since I wasn’t sure.

I’m going to attempt to explain why the holographic noise is measurable with the Holometer by way of analogy. In fact, there are several analogies that are applicable (Brownian motion, diffraction limits, black hole information theory, Heisenberg uncertainty principle). However, I want to be clear that we are talking about New Physics. You can’t explain this phenomenon using classical or quantum physics; it is not an application of any of the above phenomena; they serve only as analogies. That’s why it is New Physics. I’ve heard this New Physics referred in a couple of ways, but I like Planckian Physics best.

I know that we want to get to the Holometer, but first we need to introduce the Heisenberg uncertainty principle. Due to wave-particle duality, the Heisenberg uncertainty principles states that the more precisely we measure the position of a particle, the less precisely the momentum of that particle can be measured. (The uncertainty principle can also be presented in terms of energy and time, but we’ll stick with position and momentum.) While this inherent uncertainty is small, it is observable at the macroscopic level in some situations. For example, radioactive decay of a nucleus that ejects an alpha particle can only occur due to the uncertainty principle (from an energy and time perspective) via a process called tunneling. Classically, alpha decay violates conservation of energy.

Planckian Physics states that, in the same way that measuring position and momentum result in uncertainty, measuring position in perpendicular directions result in uncertainty. That is, the more precisely we measure the position of a particle in one direction, the less precisely we can measure the position of the particle in a perpendicular direction. Stated another way, precisely measuring the position of a particle in one directions results in transverse jitter in the position of the particle. This jitter is the holographic noise.

Hopefully, this explains why it is not possible to measure the holographic noise in a single dimension. For example, bouncing a photon off of a mirror and measuring when it returns cannot measure the holographic noise because this measurement only results in a transverse jitter (i.e., motion perpendicular to the motion of the photon) which would not affect the measurement.

Therefore, we need to employ an interferometer. When the position of a photon along one arm of the interferometer is precisely measured, the transverse jitter of the beam splitter results in noise in the interference measured by the photodiode.

transverse jitter of beam splitter

(diagram from Professor Craig Hogan)

The beam splitter executes a random walk of one Planck length per Planck time as the photon travels the length of the arm. This answers two of the questions from the previous post: why are the Holometer arms 40-m long and why do we look for the holographic noise at 4 MHz? It takes a photon 267 ns to travel 80 m (40 m down and 40 m back). While 267 ns may not seem like long, it is 5 x 1036 Planck times. That means that, if the beam splitter may move a Planck length (1.6 x 10-35 m) for each Planck time, the beam splitter’s transverse jitter (due to the random walk) is on the order of 10-17 m which can be measured by an interferometer with clever spectral analysis. The holographic noise is present at all frequencies, but we are most sensitive to it at 4 MHz because that is the . and nearly constant from 0 Hz to near 3.75 MHz, where it drops off to zero (3.75 MHz is the frequency at which photos return to the beam splitter (the speed of light divided by 80 m)). (Revised Mon Jul 18 23:01:57 CDT 2011)

I haven’t yet explained why the Holometer consists of a pair of interferometers and why the theory predicts that the holographic noise of the two interferometers will be correlated if their space-time overlap and the holographic noise will not be correlated if their space-time does not overlap. Honestly, I don’t understand this aspect of the experiment yet. That’s okay because I get to meet with Professor Hogan again next week. I’m hoping to clarify my understanding by proposing several thought experiments and seeing if I can connect the resulting explanations. I think that the fact that the photons traveling down the arms are entangled is key. I proposed an experiment where two coherent photons are shot down each arm at exactly the same time and the resulting interference is measured. I would expect that the holographic noise would not be present since the photons are not entangled. However, I’m not sure if this thought experiment is possible to execute without entangling the photons in some manner. I’m going to study up on collapsing wave functions before our next meeting. If you have any questions, please comment!

This post is one in a series about The Holometer experiment and my work at Fermilab in the Summer of 2011:

Holometer: Spectral Analysis

This post introduces some of the concepts that are important when analyzing the data measured from the Holometer. The last post introduced the concept of an interferometer. In the Holometer, the photodiodes measure the intensity of the laser at the dark port. As described in the previous post, if everything was perfectly aligned and nothing moved, the dark port would be completely dark. However, in reality, everything is moving a bit and the intensity of laser at the dark port varies. The photodiode produces a voltage corresponding to the intensity of the laser which is sampled by a computer-based measurement system. (I’ll write much more about the computer-based measurement system later since it is the one part of this experiment with which I have expertise.) If this voltage is plotted over time, it looks like noise. That is, there is no discernible pattern to the voltages. Here is an example (not from a photodiode, but a simulated signal):


It is very difficult to see repeating patterns in a signal when there are either multiple patterns present or there is significant random noise. In order to see these repeating patterns we travel to a parallel universe of sorts. In this parallel universe we observe the signal in the frequency domain (amplitude as a function of frequency) instead of in the time domain (amplitude as a function of time). This is done with a Fourier transform. I’m not going to focus on how to calculate Fourier transforms of signals, but I do want to describe Fourier transforms conceptually.

Let’s start with a sine wave with a frequency of 4 Hz, an amplitude of 1 V, and a phase of 0 degrees. Frequency is how many cycles of the sine wave are in every second; amplitude is the difference in volts from the equilibrium position (0 V in this case) to the maximum voltage; and phase is where the sine wave starts at time 0 s. I’m not going to worry about the phase at all. It looks like this in the time-domain (graph of amplitude in Volts vs. time in seconds):

4-Hz, 1-V sine wave in time domain

It could also be described in the frequency domain (amplitude in Vrms vs. time in seconds):

4-Hz, 1-V sine wave in frequency domain

The amplitude of the signal in the frequency domain is zero everywhere except at 4 Hz, where it is 0.7 V (Vrms value of an 1-V amplitude sine wave). (For those of you wondering, I’m not going to discuss the phase information in the frequency domain.)

What if our signal is the combination of two sine waves? Let’s add a second sine wave with a frequency of 10 Hz, an amplitude of 1.5 V, and a phase of 0 degrees. The signal still looks like a repeating pattern, but is more complicated:

two sine waves in time domain

However, the signal is easily described in the frequency domain:

two sine waves in frequency domain

The amplitude of the signal in the frequency domain is zero everywhere except at 4 Hz and 10 Hz.

The idea behind a frequency-domain representation of a signal is that any signal can be represented as a combination of sine waves of various frequencies, amplitudes, and phases. Here’s an example of a signal that is a combination of five different sine waves of various frequency and amplitudes:

multiple sine waves in time domain

and here are the five frequencies clearly shown in the frequency domain:

multiple sine waves in frequency domain

Good luck determining that the time-domain graph was comprised of five sine waves of frequency 4 Hz, 10 Hz, 13 Hz, 15 Hz, and 18 Hz.

Let’s go back and look at the original signal in the frequency domain:

noise in frequency domain

It is now evident that what appeared to be random noise is composed of a 60 Hz signal. The signal to noise ratio for this example was worse than 1/50. That is, the amplitude of the noise was more than 50 times greater than that of the 60 Hz signal. This is the power of analyzing signals in the frequency domain. When performing this analysis, the Fourier transform is calculated multiple times and the results are averaged together. This reduces the influence of the random noise and makes the repeating signal more apparent. There are other techniques besides averaging to improve the measurement such as windowing, but we aren’t going to worry about that for now.

There are many things that contribute to the noise measured by the photodiode in the interferometer. A truck driving by, seismic activity, vibrations due to a fan, 60 Hz AC power, and the digitizer itself are all possibilities. In addition, the holographic noise presented in the first post in this series is also present. If the two interferometers which make up the Holometer are isolated from each other, than much of their noise will be uncorrelated, that is, not related to each other. Some sources of noise would be correlated, such as seismic activity and a truck driving near the experiment. However, these sources of noise occur at much lower frequencies that the holographic noise. If the two interferometers overlap in their space-time (I’ll explain this more later), than the holographic noise should be correlated. We can remove uncorrelated signals between two signals by calculating the cross power spectrum. As an example, suppose I have two signals:

first signal

second signal

We can filter out uncorrelated signals by calculating the cross-power spectrum for the two signals (again, just focus on the concept and not how the calculation is done). The graph of the resulting cross-power spectrum for these two signals is:

cross-power spectrum

Whoa! There is a 60 Hz correlated signal between the two signals. This signal was lost in the noise when looking at the individual signals in the frequency domain because it was so much weaker than the other components (unless you look really carefully). However, by minimizing the uncorrelated frequencies between the two signals, the 60 Hz correlated signal becomes more apparent. (The uncorrelated 80-Hz and 110-Hz signals are not completely eliminated, but they are minimized.)

The Holometer experiment uses these techniques to search for the correlated holographic noise signal between two adjacent interferometers.

I have the opportunity to meet with Craig Hogan this week and ask him some of my questions which should help me more clearly explain the ideas of the holographic principle, in general, and the Holometer experiment, in particular. I hope to have clear answers for questions such as:

  • Why is the interferometer 40-m long?
  • Given the incredible small scale of the Planck length, how to the two adjacent interferometers “share” the same space-time?
  • What is the connection between the holographic information principle and the Planck length?
  • Why is the holographic noise expected to be around 4 MHz?
  • What’s up with this?

What questions do you have?

This post is one in a series about The Holometer experiment and my work at Fermilab in the Summer of 2011:

Holometer: Interferometer

This is my second post in my Holometer series. The first one provided some background information on the Holographic Principle.

The Holometer experiment consists of a pair of 40-m-long interferometers. I don’t yet fully understand why there are two or why they are 40-m long; so, I’ll address the design of the experiment later. For now, I’ll provide some background on interferometers in general.

When discussing interferometers, I have to start with the one of the most important failed experiments: the Michelson–Morley experiment. This is especially the case since it was conducted at my alma matter, Case Western Reserve University. In his efforts to detect the ether, Michelson developed the interferometer:

(Michelson interferometer; source: wikipedia)

An interferometer has two perpendicular arms. Light is directed at a beam splitter (half-silvered mirror in the diagram) and is split down each arm. While the diagram refers to coherent light, and the Holometer does use a laser, coherent light is not required (and certainly not used by Michelson). The light travels the length of each arm, is reflected off mirrors at the end of each arm, and passes back through/off the beam splitter to the detector.

I’m assuming that you are familiar with the concept of interference. Interference of waves is evident when playing with slinkies, dropping a pair of pebbles in a pond, or listening to two tones close in frequency (i.e., beats). Perhaps the most famous example of interference of light is Young’s Double Slit experiment. In essence, when two waves of light meet, they interfere. If two peaks or two troughs of these waves align (i.e., are in phase), they constructively interfere and the detector measures a brighter light. If a peak aligns with a trough (i.e., out of phase), they destructively interfere and, if aligned exactly, the detector measures no light.

(constructive and destructive interference; source: wikipedia)

Michelson and Morely measured the effect of the ether on the speed of light by observing the interference patterns as their interferometer was rotated. While they didn’t know the direction of the ether, by rotating their interferometer, they were assured that at times one beam would be in the same direction as the ether while the other was perpendicular to it. If the light traveled different speeds based on its direction relative to that of the ether, the interference patterns produced by the interferometer would change as it is rotated. The interference pattern didn’t change since there was no ether and light travels at a constant speed in a given medium regardless of direction.

Given that light does travel at a constant speed, an interferometer is useful for measuring very small differences in length. If the two arms of the interferometer are exactly the same length, the two waves will constructively interfere. However, if one arm is a quarter-of-a-wavelength longer than the other, one wave will travel a total of an extra half-a-wavelength compared to the other, and the two waves will destructively interfere. Given the very small wavelength of light, this makes an interferometer a very sensitive instrument. The Holometer is designed such that one arm is a quarter-of-a-wavelength longer than the other. If this distance was exact, and nothing moved, the detector would measure no light (in fact, it is referred to it as the dark port).

However, in order for the Holometer experiment to eventually make sense, we need to look at the light in an interferometer from a different perspective: light as a particle. When a photon (i.e., particle of light) hits the beam splitter, quantum mechanics tells us that the photon travels down both arms at the same time. Don’t think too hard about that; just drink the kool-aid and move on. This particle perspective is key because it illustrates that, since the same photon travels down each arm and reflects back, the photon interferes with itself. This is a very important characteristic to which we will return later.

So, at this point we’ve described a very sensitive instrument – the interferometer. It can measure differences in length of an order smaller than the wavelength of light (400 nm – 750 nm). The realization that you may have at this point is that there is a huge difference in magnitude between the wavelength of light (7.5 x 10-7 m) and Planck’s length (1.6 x 10-35 m). How can the Holometer measure anything on the order of the holographic noise? We’ll tackle that next as we explore spectral analysis and correlation.

This post is one in a series about The Holometer experiment and my work at Fermilab in the Summer of 2011:

Holometer: Holographic Noise

This summer I am working at Fermi National Accelerator Laboratory as a Teacher Research Associate as part of the TRAC program. I plan on writing a series of posts about my experiences and, specifically, about the experiment with which I’m involved: the holometer. Before describing my specific contributions to the experiment, I think I should start with the theory that led to holometer experiment. One of my goals this summer is to be able to explain this experiment and the theory that it is testing in a way that can be understood by my students. This will take several revisions and this post is my first draft.

The theorist involved with this experiment is Craig Hogan and the holometer is designed to test the the holographic principle. What is the holographic principle? Some describe this theory as claiming that the reality that we perceive is actually a three-dimensional projection from the two-dimensional reality at the edge of the universe. While that sounds cool and sci-fi, I have no idea what it means.

An analogy that I think helps explain the holographic principle is that of graphics on a computer screen. When you play Angry Birds, the bird flies across the screen in an apparently smooth path:

Angry Birds

However, if you zoom in and look more closely, you’ll see that the bird cannot follow an arbitrarily smooth path since the screen is made of pixels. As the bird flies across the screen, it must move in discrete intervals horizontally and vertically. That is, its location on the screen is quantized. What appears to be smooth movement, is actually the bird jumping from one pixel to the next. The minimum distance the bird can move is the width of one pixel. A pixel’s width is sufficiently small that we don’t notice these jumps as we play the game.


How does this analogy apply to the holographic principle? Space-time is the screen; we are the Angry Birds; and the Planck length is the width of a pixel. To elaborate, as we move through space-time, our movement is not perfectly smooth but, rather, jumpy because the smallest distance we can move is the Planck length (1.6 x 10-35 m)1. Similarly to how, if we zoom in on the computer screen, we can observe the jumpiness of the Angry Bird, through an analogous magnification we should be able to observe the jumpiness, or jitter, of our movement through space-time. This jitter is the focus of Hogan’s research and is called holographic noise. The holometer experiment is designed to measure this phenomenon. How can we build an apparatus that can measure this holographic noise when the Planck length is so incredibly small? Stay tuned for the next post in this series!

Does this make any sense? Feedback is most welcome!

This post is one in a series about The Holometer experiment and my work at Fermilab in the Summer of 2011:

1 The Planck length was derived from fundamental physical constants (speed of light, gravitational constant, and Planck constant) by Max Planck.