Researchers in Switzerland invent a new type of pixel 27%

By Sara Hashemi0%

7/5/2026, 3:04:00 PM

BS Summary: This article contains 15 faulty reasoning types, including Optimism Bias, Overconfidence Bias, and Burden of Proof, with Quote-first Misdirection as the most egregious example at 18.6% saturation with 77 hits. Analysis detected 388 faulty-reasoning hits from 414 analyzed words, generating a BS Score of 38.1% and a BS Rank of 27% (15,647 of 21,159 articles). This article is better (less manipulative) than 73.90% of the article peer group.

Every single day, we’re constantly looking at pixels. 
The tiny elements make up the displays on our phone screens and televisions, and allow us to capture images on digital cameras. 
Generally, a pixel works by either controlling light (think a computer) or analyzing it (like a camera sensor). 
Now, researchers writing in the journal Nature say they’ve created a pixel that can do both. 
Called a Fourier pixel, the new pixel tech is based on a fundamental principle of physics: interference. 
When light is scattered by a surface, the waves can overlap with each other, even if they originated from different points. 
When two or more light waves overlap, they reinforce each other. 
If the light waves are out of step, they cancel each other out. 
The new pixels use this phenomenon to control light with wave-shaped sculpted surfaces. 
The name Fourier pixel comes from Fourier analysis—a mathematical process that the team used to break down and understand how the waves behaved. 
Each patterned area, or pixel, turns light into a surface wave that travels along the chip’s surface. 
Then, in a different place within the pixel, the surface wave is scattered back out as a light wave. 
These scattered lightwaves can be used to generate colored images. 
In other words, the researchers carved tiny patterns into a chip that allows them to control how light waves combine. 
These patterns allowed them to create pixels that both steer and analyze light. 
“Thanks to the fact that the relevant surface profiles of the pixels can be determined using Fourier analysis, we can combine the control and analysis of amplitude, phase and polarisation on a single pixel,” said Sander Vonk, a study co-author and postdoctoral researcher at ETH Zurich, in a statement. 
He added that Fourier analysis is mathematically simple, and does not require complex models. 
The findings could have far-ranging technological applications in the future. 
“Our new pixels for control and analysis could, therefore, become a useful tool in many areas,” said David Norris, a study co-author and materials engineer at ETH Zurich. 
One day, we might even have pixels that both capture an image and process it without needing a computer. 
But in the short term, the team has more practical goals. 
They want to create a matrix of Fourier pixels that could be used to make more complex camera display devices. 
Still, you might have a future laptop screen capable of taking your photo. 
Article reasoning-pattern comparisonThis article: 3.1%Sara Hashemi: 1.7%Popular Science: 2.2%Confirmation Bias3.1%This article: 0.0%Sara Hashemi: 0.3%Popular Science: 0.8%Anchoring Bias0.0%This article: 1.9%Sara Hashemi: 2.5%Popular Science: 2.6%Availability Heuristic1.9%This article: 4.3%Sara Hashemi: 1.6%Popular Science: 1.2%Representativeness Heuristic4.3%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.5%Hindsight Bias0.0%This article: 15.2%Sara Hashemi: 5.4%Popular Science: 3.0%Overconfidence Bias15.2%This article: 2.7%Sara Hashemi: 2.3%Popular Science: 3.5%Framing Effect2.7%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.4%Loss Aversion0.0%This article: 0.0%Sara Hashemi: 0.4%Popular Science: 0.7%Status Quo Bias0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.1%Sunk Cost Effect0.0%This article: 16.9%Sara Hashemi: 12.2%Popular Science: 4.7%Optimism Bias16.9%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.7%Pessimism Bias0.0%This article: 0.0%Sara Hashemi: 1.4%Popular Science: 3.0%Negativity Bias0.0%This article: 0.0%Sara Hashemi: 0.5%Popular Science: 0.7%Self-Serving Bias0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.3%Fundamental Attribution Error0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Actor-Observer Bias0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.4%In-Group Bias0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.2%Out-Group Homogeneity Bias0.0%This article: 0.0%Sara Hashemi: 1.3%Popular Science: 2.1%Halo Effect0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Horn Effect0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.9%Recency Bias0.0%This article: 0.0%Sara Hashemi: 0.5%Popular Science: 0.3%Primacy Effect0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.1%Blind-Spot Bias0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Ad Hominem0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.1%Straw Man0.0%This article: 3.9%Sara Hashemi: 6.6%Popular Science: 4.3%Appeal to Authority3.9%This article: 0.0%Sara Hashemi: 0.7%Popular Science: 0.8%False Dilemma0.0%This article: 4.6%Sara Hashemi: 0.3%Popular Science: 0.3%Slippery Slope4.6%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.1%Circular Reasoning0.0%This article: 3.4%Sara Hashemi: 2.6%Popular Science: 4.2%Hasty Generalization3.4%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.1%Red Herring0.0%This article: 0.0%Sara Hashemi: 0.8%Popular Science: 0.5%Bandwagon0.0%This article: 3.1%Sara Hashemi: 3.0%Popular Science: 2.8%Appeal to Emotion3.1%This article: 0.0%Sara Hashemi: 0.2%Popular Science: 0.6%Begging the Question0.0%This article: 2.4%Sara Hashemi: 2.0%Popular Science: 2.3%Post Hoc (False Cause)2.4%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Tu Quoque0.0%This article: 6.8%Sara Hashemi: 0.4%Popular Science: 0.5%Burden of Proof6.8%This article: 4.1%Sara Hashemi: 0.7%Popular Science: 0.4%Appeal to Nature4.1%This article: 0.0%Sara Hashemi: 0.9%Popular Science: 0.4%Composition/Division0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 2.2%Anecdotal0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%No True Scotsman0.0%This article: 2.7%Sara Hashemi: 1.5%Popular Science: 2.1%Ambiguity (Equivocation)2.7%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.2%Middle Ground0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Personal Incredulity0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.2%Special Pleading0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.1%Genetic Fallacy0.0%This article: 0.0%Sara Hashemi: 0.8%Popular Science: 1.5%Unattributed Quote0.0%This article: 18.6%Sara Hashemi: 1.5%Popular Science: 0.8%Quote-first Misdirection18.6%This article: 0.0%Sara Hashemi: 2.2%Popular Science: 3.9%Biased Writer Voice0.0%This article: 0.0%Sara Hashemi: 0.3%Popular Science: 1.3%Indoctrination0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Politically Left Leaning Bias0.0%This article: 0.0%Sara Hashemi: 0.0%Popular Science: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Sara Hashemi: 0.3%Popular Science: 2.7%Attempt to Sell a Product or S…0.0%

414 words analyzed.

Speakers

3speakers26%attributed speech307writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageNature • 16 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageSander Vonk • 49 words • 100.0% coverageSander Vonk • 14 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageDavid Norris • 28 words • 100.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverage
Selected voice

David Norris

100%flagged-word coverage
28 attributed words26% of attributed speech39% writer coverage
0%50.0%100.0%Quote-first Misdirection+100.0 ptsWriter: 0.0%David Norris: 100.0%100.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.