Does science tell the truth?
It is impossible for science to arrive at ultimate truths, but functional truths are good enough.
Marcelo Gleiser is a professor of natural philosophy, physics, and astronomy at Dartmouth College. He is a Fellow of the American Physical Society, a recipient of the Presidential Faculty Fellows Award from the White House and NSF, and was awarded the 2019 Templeton Prize. Gleiser has authored five books and is the co-founder of 13.8, where he writes about science and culture with physicist Adam Frank.
- What is truth? This is a very tricky question, trickier than many would like to admit.
- Science does arrive at what we can call functional truth, that is, when it focuses on what something does as opposed to what something is. We know how gravity operates, but not what gravity is, a notion that has changed over time and will probably change again.
- The conclusion is that there are not absolute final truths, only functional truths that are agreed upon by consensus. The essential difference is that scientific truths are agreed upon by factual evidence, while most other truths are based on belief.
Does science tell the truth? The answer to this question is not as simple as it seems, and my 13.8 colleague Adam Frank took a look at it in his article about the complementarity of knowledge. There are many levels of complexity to what truth is or means to a person or a community. Why?
First, "truth" itself is hard to define or even to identify. How do you know for sure that someone is telling you the truth? Do you always tell the truth? In groups, what may be considered true to a culture with a given set of moral values may not be true in another. Examples are easy to come by: the death penalty, abortion rights, animal rights, environmentalism, the ethics of owning weapons, etc.
At the level of human relations, truth is very convoluted. Living in an age where fake news has taken center stage only corroborates this obvious fact. However, not knowing how to differentiate between what is true and what is not leads to fear, insecurity, and ultimately, to what could be called worldview servitude — the subservient adherence to a worldview proposed by someone in power. The results, as the history of the 20th century has shown extensively, can be catastrophic.
Proclamations of final or absolute truths, even in science, shouldn't be trusted.
The goal of science, at least on paper, is to arrive at the truth without recourse to any belief or moral system. Science aims to go beyond the human mess so as to be value-free. The premise here is that Nature doesn't have a moral dimension, and that the goal of science is to describe Nature the best possible way, to arrive at something we could call the "absolute truth." The approach is a typical heir to the Enlightenment notion that it is possible to take human complications out of the equation and have an absolute objective view of the world. However, this is a tall order.
It is tempting to believe that science is the best pathway to truth because, to a spectacular extent, science does triumph at many levels. You trust driving your car because the laws of mechanics and thermodynamics work. NASA scientists and engineers just managed to have the Ingenuity Mars Helicopter — the first man-made device to fly over another planet — hover above the Martian surface all by itself.
We can use the laws of physics to describe the results of countless experiments to amazing levels of accuracy, from the magnetic properties of materials to the position of your car in traffic using GPS locators. In this restricted sense, science does tell the truth. It may not be the absolute truth about Nature, but it's certainly a kind of pragmatic, functional truth at which the scientific community arrives by consensus based on the shared testing of hypotheses and results.
What is truth?
Credit: Sergey Nivens via Adobe Stock / 242235342
But at a deeper level of scrutiny, the meaning of truth becomes intangible, and we must agree with the pre-Socratic philosopher Democritus who declared, around 400 years BCE, that "truth is in the depths." (Incidentally, Democritus predicted the existence of the atom, something that certainly exists in the depths.)
A look at a dictionary reinforces this view. "Truth: the quality of being true." Now, that's a very circular definition. How do we know what is true? A second definition: "Truth: a fact or belief that is accepted as true." Acceptance is key here. A belief may be accepted to be true, as is the case with religious faith. There is no need for evidence to justify a belief. But note that a fact as well can be accepted as true, even if belief and facts are very different things. This illustrates how the scientific community arrives at a consensus of what is true by acceptance. Sufficient factual evidence supports that a statement is true. (Note that what defines sufficient factual evidence is also accepted by consensus.) At least until we learn more.
Take the example of gravity. We know that an object in free fall will hit the ground, and we can calculate when it does using Galileo's law of free fall (in the absence of friction). This is an example of "functional truth." If you drop one million rocks from the same height, the same law will apply every time, corroborating the factual acceptance of a functional truth, that all objects fall to the ground at the same rate irrespective of their mass (in the absence of friction).
But what if we ask, "What is gravity?" That's an ontological question about what gravity is and not what it does. And here things get trickier. To Galileo, it was an acceleration downward; to Newton a force between two or more massive bodies inversely proportional to the square of the distance between them; to Einstein the curvature of spacetime due to the presence of mass and/or energy. Does Einstein have the final word? Probably not.
Is there an ultimate scientific truth?
Final or absolute scientific truths assume that what we know of Nature can be final, that human knowledge can make absolute proclamations. But we know that this can't really work, for the very nature of scientific knowledge is that it is incomplete and contingent on the accuracy and depth with which we measure Nature with our instruments. The more accuracy and depth our measurements gain, the more they are able to expose the cracks in our current theories, as I illustrated last week with the muon magnetic moment experiments.
So, we must agree with Democritus, that truth is indeed in the depths and that proclamations of final or absolute truths, even in science, shouldn't be trusted. Fortunately, for all practical purposes — flying airplanes or spaceships, measuring the properties of a particle, the rates of chemical reactions, the efficacy of vaccines, or the blood flow in your brain — functional truths do well enough.
A new method could make holograms for virtual reality, 3D printing, and more. You can even run it can run on a smartphone.
Despite years of hype, virtual reality headsets have yet to topple TV or computer screens as the go-to devices for video viewing.
One reason: VR can make users feel sick. Nausea and eye strain can result because VR creates an illusion of 3D viewing although the user is in fact staring at a fixed-distance 2D display. The solution for better 3D visualization could lie in a 60-year-old technology remade for the digital world: holograms.
Holograms deliver an exceptional representation of 3D world around us. Plus, they're beautiful. (Go ahead — check out the holographic dove on your Visa card.) Holograms offer a shifting perspective based on the viewer's position, and they allow the eye to adjust focal depth to alternately focus on foreground and background.
Researchers have long sought to make computer-generated holograms, but the process has traditionally required a supercomputer to churn through physics simulations, which is time-consuming and can yield less-than-photorealistic results. Now, MIT researchers have developed a new way to produce holograms almost instantly — and the deep learning-based method is so efficient that it can run on a laptop in the blink of an eye, the researchers say.
"People previously thought that with existing consumer-grade hardware, it was impossible to do real-time 3D holography computations," says Liang Shi, the study's lead author and a PhD student in MIT's Department of Electrical Engineering and Computer Science (EECS). "It's often been said that commercially available holographic displays will be around in 10 years, yet this statement has been around for decades."
Shi believes the new approach, which the team calls "tensor holography," will finally bring that elusive 10-year goal within reach. The advance could fuel a spillover of holography into fields like VR and 3D printing.
Shi worked on the study, published today in Nature, with his advisor and co-author Wojciech Matusik. Other co-authors include Beichen Li of EECS and the Computer Science and Artificial Intelligence Laboratory at MIT, as well as former MIT researchers Changil Kim (now at Facebook) and Petr Kellnhofer (now at Stanford University).
The quest for better 3D
Courtesy of the researchers
A typical lens-based photograph encodes the brightness of each light wave — a photo can faithfully reproduce a scene's colors, but it ultimately yields a flat image.
In contrast, a hologram encodes both the brightness and phase of each light wave. That combination delivers a truer depiction of a scene's parallax and depth. So, while a photograph of Monet's "Water Lilies" can highlight the paintings' color palate, a hologram can bring the work to life, rendering the unique 3D texture of each brush stroke. But despite their realism, holograms are a challenge to make and share.
First developed in the mid-1900s, early holograms were recorded optically. That required splitting a laser beam, with half the beam used to illuminate the subject and the other half used as a reference for the light waves' phase. This reference generates a hologram's unique sense of depth. The resulting images were static, so they couldn't capture motion. And they were hard copy only, making them difficult to reproduce and share.
Computer-generated holography sidesteps these challenges by simulating the optical setup. But the process can be a computational slog. "Because each point in the scene has a different depth, you can't apply the same operations for all of them," says Shi. "That increases the complexity significantly." Directing a clustered supercomputer to run these physics-based simulations could take seconds or minutes for a single holographic image. Plus, existing algorithms don't model occlusion with photorealistic precision. So Shi's team took a different approach: letting the computer teach physics to itself.
They used deep learning to accelerate computer-generated holography, allowing for real-time hologram generation. The team designed a convolutional neural network — a processing technique that uses a chain of trainable tensors to roughly mimic how humans process visual information. Training a neural network typically requires a large, high-quality dataset, which didn't previously exist for 3D holograms.
The team built a custom database of 4,000 pairs of computer-generated images. Each pair matched a picture — including color and depth information for each pixel — with its corresponding hologram. To create the holograms in the new database, the researchers used scenes with complex and variable shapes and colors, with the depth of pixels distributed evenly from the background to the foreground, and with a new set of physics-based calculations to handle occlusion. That approach resulted in photorealistic training data. Next, the algorithm got to work.
By learning from each image pair, the tensor network tweaked the parameters of its own calculations, successively enhancing its ability to create holograms. The fully optimized network operated orders of magnitude faster than physics-based calculations. That efficiency surprised the team themselves.
"We are amazed at how well it performs," says Matusik. In mere milliseconds, tensor holography can craft holograms from images with depth information — which is provided by typical computer-generated images and can be calculated from a multicamera setup or LiDAR sensor (both are standard on some new smartphones). This advance paves the way for real-time 3D holography. What's more, the compact tensor network requires less than 1 MB of memory. "It's negligible, considering the tens and hundreds of gigabytes available on the latest cell phone," he says.
The research "shows that true 3D holographic displays are practical with only moderate computational requirements," says Joel Kollin, a principal optical architect at Microsoft who was not involved with the research. He adds that "this paper shows marked improvement in image quality over previous work," which will "add realism and comfort for the viewer." Kollin also hints at the possibility that holographic displays like this could even be customized to a viewer's ophthalmic prescription. "Holographic displays can correct for aberrations in the eye. This makes it possible for a display image sharper than what the user could see with contacts or glasses, which only correct for low order aberrations like focus and astigmatism."
"A considerable leap"
Real-time 3D holography would enhance a slew of systems, from VR to 3D printing. The team says the new system could help immerse VR viewers in more realistic scenery, while eliminating eye strain and other side effects of long-term VR use. The technology could be easily deployed on displays that modulate the phase of light waves. Currently, most affordable consumer-grade displays modulate only brightness, though the cost of phase-modulating displays would fall if widely adopted.
Three-dimensional holography could also boost the development of volumetric 3D printing, the researchers say. This technology could prove faster and more precise than traditional layer-by-layer 3D printing, since volumetric 3D printing allows for the simultaneous projection of the entire 3D pattern. Other applications include microscopy, visualization of medical data, and the design of surfaces with unique optical properties.
"It's a considerable leap that could completely change people's attitudes toward holography," says Matusik. "We feel like neural networks were born for this task."
The work was supported, in part, by Sony.
A new paper reveals that the Voyager 1 spacecraft detected a constant hum coming from outside our Solar System.
Voyager 1, humanity's most faraway spacecraft, has detected an unusual "hum" coming from outside our solar system. Fourteen billion miles away from Earth, the Voyager's instruments picked up a droning sound that may be caused by plasma (ionized gas) in the vast emptiness of interstellar space.
Launched in 1977, the Voyager 1 space probe — along with its twin Voyager 2 — has been traveling farther and farther into space for over 44 years. It has now breached the edge of our solar system, exiting the heliosphere, the bubble-like region of space influenced by the sun. Now, the spacecraft is moving through the "interstellar medium," where it recorded the peculiar sound.
Stella Koch Ocker, a doctoral student in astronomy at Cornell University, discovered the sound in the data from the Voyager's Plasma Wave System (PWS), which measures electron density. Ocker called the drone coming from plasma shock waves "very faint and monotone," likely due to the narrow bandwidth of its frequency.
While they think the persistent background hum may be coming from interstellar gas, the researchers don't yet know what exactly is causing it. It might be produced by "thermally excited plasma oscillations and quasi-thermal noise."
The new paper from Ocker and her colleagues at Cornell University and the University of Iowa, published in Nature Astronomy, also proposes that this is not the last we'll hear of the strange noise. The scientists write that "the emission's persistence suggests that Voyager 1 may be able to continue tracking the interstellar plasma density in the absence of shock-generated plasma oscillation events."
Voyager Captures Sounds of Interstellar Space www.youtube.com
The researchers think the droning sound may hold clues to how interstellar space and the heliopause, which can be thought of as the solar's system border, may be affecting each other. When it first entered interstellar space, the PWS instrument reported disturbances in the gas caused by the sun. But in between such eruptions is where the researchers spotted the steady signature made by the near-vacuum.
Senior author James Cordes, a professor of astronomy at Cornell, compared the interstellar medium to "a quiet or gentle rain," adding that "in the case of a solar outburst, it's like detecting a lightning burst in a thunderstorm and then it's back to a gentle rain."
More data from Voyager over the next few years may hold crucial information to the origins of the hum. The findings are already remarkable considering the space probe is functioning on technology from the mid-1970s. The craft has about 70 kilobytes of computer memory. It also carries a Golden Record created by a committee chaired by the late Carl Sagan, who taught at Cornell University. The 12-inch gold-plated copper disk record is essentially a time capsule, meant to tell the story of Earthlings to extraterrestrials. It contains sounds and images that showcase the diversity of Earth's life and culture.
A team of scientists managed to install onto a smartphone a spectrometer that's capable of identifying specific molecules — with cheap parts you can buy online.
- Spectroscopy provides a non-invasive way to study the chemical composition of matter.
- These techniques analyze the unique ways light interacts with certain materials.
- If spectrometers become a common feature of smartphones, it could someday potentially allow anyone to identify pathogens, detect impurities in food, and verify the authenticity of valuable minerals.
The quality of smartphone cameras has increased exponentially over the past decade. Today's smartphone cameras can not only capture photos that rival those of stand-alone camera systems but also offer practical applications, like heart-rate measurement, foreign-text translation, and augmented reality.
What's the next major functionality of smartphone cameras? It could be the ability to identify chemicals, drugs, and biological molecules, according to a new study published in the Review of Scientific Instruments.
The study describes how a team of scientists at Texas A&M turned a common smartphone into a "pocket-sized" Raman and emission spectral detector by modifying it with just $50 worth of extra equipment. With the added hardware, the smartphone was able to identify chemicals in the field within minutes.
The technology could have a wide range of applications, including diagnosing certain diseases, detecting the presence of pathogens and dangerous chemicals, identifying impurities in food, and verifying the authenticity of valuable artwork and minerals.
Raman and fluorescence spectroscopy
Raman and fluorescence spectroscopies are techniques for discerning the chemical composition of materials. Both strategies exploit the fact that light interacts with certain types of matter in unique ways. But there are some differences between the two techniques.
As the name suggests, fluorescence spectroscopy measures the fluorescence — that is, the light emitted by a substance when it absorbs light or other electromagnetic radiation — of a given material. It works by shining light on a material, which excites the electrons within the molecules of the material. The electrons then emit fluorescent light toward a filter that measures fluorescence.
The particular spectra of fluorescent light that's emitted can help scientists detect small concentrations of particular types of biological molecules within a material. But some biomolecules, such as RNA and DNA, don't emit fluorescent light, or they only do so at extremely low levels. That's where Raman spectroscopy comes into play.
Raman spectroscopy involves shooting a laser at a sample and observing how the light scatters. When light hits molecules, the atoms within the molecules vibrate and photons get scattered. Most of the scattered light is of the same wavelength and color as the original light, so it provides no information. But a tiny fraction of the light gets scattered differently; that is, the wavelength and color are different. Known as Raman scattering, this is extremely useful because it provides highly precise information about the chemical composition of the molecule. In other words, all molecules have a unique Raman "fingerprint."
Creating an affordable, pocket-sized spectrometer
To build the spectrometer, the researchers connected a smartphone to a laser and a series of plastic lenses. The smartphone camera was placed facing a transmission diffraction grating, which splits incoming light into its constituent wavelengths and colors. After a laser is fired into a sample, the scattered light is diffracted through this grating, and the smartphone camera analyzes the light on the other side.
Schematic diagram of the designed system.Credit: Dhankhar et al.
To test the spectrometer, the researchers analyzed a range of sample materials, including carrots and bacteria. The laser used in the spectrometer emits a wavelength that's readily absorbed by the pigments in carrots and bacteria, which is why these materials were chosen.
The results showed that the smartphone spectrometer was able to correctly identify the materials, but it wasn't quite as effective as the best commercially available Raman spectrometers. The researchers noted that their system might be improved by using specific High Dynamic Range (HDR) smartphone camera applications.
Ultimately, the study highlights how improving the fundamentals of a technology, like smartphone cameras, can lead to a surprisingly wide range of useful applications.
"This inexpensive yet accurate recording pocket Raman system has the potential of being an integral part of ubiquitous cell phones that will make it possible to identify chemical impurities and pathogens, in situ within minutes," the researchers concluded.
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