The traveling salesman problem is a classic mathematical problem and a combinatorial optimization problem. A new study by scientists at Freie Universität Berlin and the Helmholtz-Zentrum Berlin für Energie und Materialforschung (HZB) demonstrates that quantum computers can solve the traveling salesman problem more efficiently and faster than with conventional methods.
口语化英文：
Hey there! Let's talk about the Travelling Salesman Problem (TSP). It's like this: you have a bunch of cities to visit, and you want to find the shortest possible route to hit them all and get back where you started.
As easy as that sounds, TSP gets tough as the number of cities grows, and the time it takes to crunch the numbers explodes. It's a big deal because TSP represents a whole class of optimization problems that have major implications in the real world, like designing railroads, figuring out logistics, and even optimizing resources.
Now, here's the exciting part. A team led by Professor Jens Eisert from HZB (Helmholtz-Zentrum Berlin) has figured out a way to use quantum computers to tackle TSP and other optimization problems using pure analytical methods. They realized that they could adapt Shor's algorithm from cryptography to solve these headaches.
What this means is that instead of the time it takes to solve TSP exploding as cities increase, it only grows polynomially. Plus, the solutions they get this way are way better in quality than the "guesstimates" we get with traditional algorithms.
