Quantum Computing for Natural Sciences (with IBM Quantum)

1. 00:00Hi everyone and welcome back to our course series on quantum computing applications in the natural sciences.
2. 00:06For this last video, we have planned something slightly different today.
3. 00:10We have brought in Dr Ivano Tavernelli.
4. 00:12Thank you a lot for joining us.
5. 00:15We have prepared a series of questions for you on the challenges and promises of this field to give our audience a little
6. 00:21bit of an idea of where we stand right now.
7. 00:25So I will dive straight in.
8. 00:27Could you summarize for us why you believe that quantum chemistry is such a promising field of application for quantum computers
9. 00:34Yes.
10. 00:35Thank you Laurin and hello everybody.
11. 00:37So in quantum chemistry, we are dealing with uh the solution of problems that are inherently quantum in nature.
12. 00:46And for instance, this could be the solution of the Schrödinger equation for a molecular system.
13. 00:52And this is exactly what Faymann has suggested already in the eighties.
14. 00:57This mean the solution of uh quantum problems using quantum technologies.
15. 01:04So in particular, this class of problems, so the solution of the Schroedinger equation can be very hard uh using classical
16. 01:12computer.
17. 01:12It can even have an exponential cost in the number of resources instead of using a quantum computer, we can reach the same
18. 01:21accuracy using only a polynomial number of resources.
19. 01:25So in this case, uh polynomial number of qubits.
20. 01:29So in this setting, what are the first concrete applications that you would envision where one might see something like a
21. 01:36quantum advantage?
22. 01:38Yes, indeed, as I mentioned before, in uh in quantum chemistry, there are problems that are uh really difficult, very hard
23. 01:47for uh classical calculations.
24. 01:50So in particular, I think here about uh strongly correlated systems but also the calculation of the interaction of a light
25. 01:59with a matter is another very difficult problem to solve classically.
26. 02:06And uh if uh the additional problems like um the calculation of excited states excited states properties uh and also quantum
27. 02:16dynamics that are particularly difficult uh using uh classical computing.
28. 02:23So these are very relevant topics that have uh implications in for instance, uh the conversion of solar light energy
29. 02:32right that we can use uh uh in technology for instance.
30. 02:37And um and in in this uh in this domain, a quantum computer can really bring to a breakthrough in in the future.
31. 02:47Well, this result sounds very promising and there's a quite a large spectrum of different applications.
32. 02:53So I mean, the entire field is wondering right now, what do you think are the biggest road blocks that might still be in
33. 03:00the way of truly achieving this full potential of quantum computers?
34. 03:04Yes.
35. 03:04So here we have to distinguish between a near term and fault tolerant quantum computing.
36. 03:09So in near term quantum computing, so we are dealing with a noisy devices and therefore we are limited in the number of qubits
37. 03:19and the number of gates that uh we can use in order to achieve our result.
38. 03:26So in a sense, the noise at a certain point will significantly affect the results of our calculations.
39. 03:34And therefore, we are currently limited to a few tens up to 100 qubits right
40. 03:41But we are also working on error mitigation schemes.
41. 03:45This will allow us to improve the fidelity of our gate operations, the fidelity of our read out operations, opening up a
42. 03:56new possibility for larger calculations and possibly also uh we will give us the possibility to achieve a quantum advantage
43. 04:07in the near future.
44. 04:09So then uh differently is the situation with fault tolerant quantum computing.
45. 04:15So um in this case, all the problems I mentioned before about the noise and the infidelity of the qubit operations will be
46. 04:26solved at once.
47. 04:28And then we will be able to implement more complex algorithms like for instance, Shore algorithm for the factorization , Groovers search
48. 04:38or algorithms like the H H L algorithm for the solution of linear algebra problems.
49. 04:45So when we envisioned as regimes of fault tolerant quantum computation, since you also have um a long research background
50. 04:54in classical computational techniques, where do you feel like the classical techniques will fall into place once quantum
51. 05:03computers hit their full potential, will they just become obsolete or what is their relationship going to be?
52. 05:09Yes.
53. 05:09So this is a very important question.
54. 05:11So I really believe that classical computers will keep their important role as a number crunching machines, right
55. 05:19For uh most floating point operation, we will still use high performance computing.
56. 05:25But on, on the other end, there is uh also a lot of potential for a combination of uh quantum and classical computing.
57. 05:34So I see in the future an hybrid quantum classical computational approach where the quantum computer can function as an accelerator
58. 05:46of a classical workflow.
59. 05:50Ivano
60. 05:50Thank you very much for joining us.
61. 05:52Um I hope you found these glimpses um as interesting as we did.
62. 05:57And with this, um we conclude our course, we thank you very much for your participation and thank you for joining.

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