Light Solvers LPU100 is based on “quantum inspired” technology. Start-up Light Solvers has developed a PC sized optical computer that uses an array of 100 lasers to perform complex calculations through a process called laser interference.
This capability is implemented using a device called a programmable spatial light modulator. This can be used to solve a complex optimization problem by:
- Encoding the problem unto physical obstacles on the lasers’ paths using a programmable spatial light modulator.
- “These obstacles prompt the lasers to adjust their behavior to minimize energy loss.”
- The lasers adjust their behavior to minimize energy loss.
- The lasers achieve a state of minimum energy loss.
- The LPU 100 uses cameras to detect the laser states where they are interpreted.
- The LPU100 translates them into a mathematical solution to the original optimization problem.
NP hard optimization problems:
Claims that complex optimization problems such as vector matrix multiplication problems can be solved within 10 nanoseconds. Also researchers at Cornell University found the LPU100 outperformed traditional GPUs in the used for testing the efficiency of logic-solving algorithms via the Max-2-Sat Challenges as well as the test for evaluating the performance of algorithms used for large combinatorial sorts via Regular 3-XORSAT problem.
Does not use quantum technology, instead “it borrows the principle of processing multiple operations simultaneously at very high speeds.”
Specifically, “the LPU100’s laser array can handle 100 continuous variables, theoretically allowing it to address computational problems involving an astronomically large number of variable combinations (120 to the power of 100).”
This computing power can be applied to cryptologic problems utilizing optimization such as those described in Logic Minimization Techniques with Applications to Cryptology.
Sources:
Livescience.com:
For more info read:
Logic Minimization Techniques with Applications to Cryptology
Published: April 1, 2013
Citation: Journal of Cryptology vol. 26, no. 2, (April 2013) pp. 280-312
Authors Joan Boyar (University of Southern Denmark), Philip Matthews (Aarhus University), Rene Peralta (NIST)