Researchers Hope to Virtually Unravel 2,000-Year-Old Scrolls

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Researchers Hope to Virtually Unravel 2,000-Year-Old Scrolls

 

Prof. Brent Seales, chairman of the computer science department at the University of Kentucky, and his team have proven that ancient documents that were once mysterious can be “virtually unraveled.” They used high-energy x-rays to “virtually unravel” a 1,700-year-old Hebrew parchment which was found in the holy ark of an Israeli synagogue in En-Gedi. This time, they will be trying to use the technique on 2,000-year-old scrolls. 

 

Photo Credit: All That's Interesting

 

In 1752, archaeologists discovered a collection of 1,800 carbonized scrolls at Herculaneum, a coastal town to the west of Vesuvius. It was believed that the scrolls were a library that burned due to the eruption of Mount Vesuvius in 79 A.D. According to All That’s Interesting, a site for curious people who want to know more about what they see on the news or read in history books, the collection is highly significant since it comprises the only intact library from antiquity – which is housed in the National Archaeological Museum in Naples.

 

Photo Credit: All That's Interesting

 

However, the scrolls have become difficult to read by now. Whatever ink left fades after exposure to the air and the scrolls themselves almost fall apart. Thus, the researchers decided to use cutting-edge technology that doesn’t risk destroying the precious scrolls, which can be a challenge as well. This is because the scrolls weren’t written with metal-based ink, unlike the Hebrew parchment. “Although you can see on every flake of papyrus that there is writing, to open it up would require that papyrus to be really limber and flexible — and it is not anymore,” Seales explained. 

 

Photo Credit: All That's Interesting

 

Thus, the researchers think the facility, called the Diamond Light Source, will provide key information about the Herculaneum scrolls. They will be using machine learning, a type of artificial intelligence, to detect hard-to-spot fractions of the ancient writings. “The machine learning tool we are developing will amplify that ink signal by training a computer algorithm to recognize it — pixel-by-pixel — from photographs of opened fragments that show exactly where the ink is — voxel-by-voxel — in the corresponding tomographic data of the fragments,” Seales said. 

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