Harold Erbin
@harolderbin.bsky.social
Physicist working on string theory, machine learning and quantum computing. Other interests: climate crisis, ethics, Buddhism, HEMA, vegan Asian cooking. Currently @CEA-IPHT, previously @MIT
https://harolderbin.com
https://harolderbin.com
Yesterday, I gave a talk at the Mitchell Institute (@tamu.bsky.social) entitled:
“Cubic string field theory using auxiliary fields”
“Cubic string field theory using auxiliary fields”
February 4, 2025 at 2:10 PM
Yesterday, I gave a talk at the Mitchell Institute (@tamu.bsky.social) entitled:
“Cubic string field theory using auxiliary fields”
“Cubic string field theory using auxiliary fields”
It did rain a bit in @lamayenne.bsky.social
140 mm in 20 days (weather station got installed on the 11th), against 70-80 on average.
140 mm in 20 days (weather station got installed on the 11th), against 70-80 on average.
February 1, 2025 at 2:34 PM
It did rain a bit in @lamayenne.bsky.social
140 mm in 20 days (weather station got installed on the 11th), against 70-80 on average.
140 mm in 20 days (weather station got installed on the 11th), against 70-80 on average.
During my spare time, I cook Asian vegan food (notably Indian), read fantasy and science-fiction, and practice #HEMA (historical European martial arts = medieval fencing). My favorite weapons: German longsword, sword and buckler and Destreza.
January 27, 2025 at 8:02 PM
During my spare time, I cook Asian vegan food (notably Indian), read fantasy and science-fiction, and practice #HEMA (historical European martial arts = medieval fencing). My favorite weapons: German longsword, sword and buckler and Destreza.
My research spans several directions, including string theory, black holes, quantum field theory and simulations. One recent highlight is how machine learning can be used to solve mathematical problems in physics, but also how physics can help to understand AI.
January 27, 2025 at 8:02 PM
My research spans several directions, including string theory, black holes, quantum field theory and simulations. One recent highlight is how machine learning can be used to solve mathematical problems in physics, but also how physics can help to understand AI.