Oded Regev 
Computer Science Dept 
NYU  - Courant Institute 

*Person to talk to about PQC*

What can we do with quantum computers? 
- simulating natural systems 
- facotorng 
- finding new algorithms 


*Cryptography until 20th century*
- enigma machine boring! jk 
- secret key cryptography 

*Late 20th Century*: 
- Diffie Helman 


Public Key Encryption: 
- allows two parties to communciate securely over an insecure channel , without having to agree in advance on a secret

Factoring Integer 
- 15 = 5 * 3 
- 21 = 3 * 7 
- current world record is 2500 digits - took 2700 computer years
- very difficult task for computers - secure comms (web, phone, banks, governments) rely on this 
- based on assumption that this factoring is very hard 


Crisis in Cryptography 
- 199, Shor discussed factoring is easy for quantum computers 

Quantum Cryptography 
- allows uncontiionally secure, communcoation over a quantum channel (Weisman70, BenneetBressar84)
- real world implementatins 
- but rrequites dedicated infrastructure 



Post-quantum Cryptography 






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# Speaker 2 - SandboxAQ

Kahoot questions
1. What are the Z-basis states of a qubit
2. Which country is investing the most funds in quantum computing? 
3. The Z Gate only adds a phase to |0> and not |1>  TTrue/False ? --> FALSE 
4. Which gate us used to put a qubit in a super position 1/root2 >  H
5. A qubit in the state |0> is the SAME THING > **FALSE** it only has a flavor 
6. What gate would you add to this circuit > **CX(0,1)**
7. What is the most practical allowed error rate in quantum computing - Below 1%
8. What will the measurement read? > 00, 01, 10, 11 
9. Hackers can store RSA encryptedd data now, and decrypt it later when usedul quantum computing exists > True 
10. The following is a mult-contro, multitarget, MCMT, How many control, and target qubits are there > Control Target
11. Create the following superposition in cricuit qc using onel ine of code 1/v2 (|00) > qc.h(1)
12. where is the quantum processor? 


1. Rohan 
2. Ethan 
3. Bhavyansh S 

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# Speaker 3 - research scientist in AWS 


AWS - analog version with QuEra 
-qbraid powered by AWsS 


His interests: 
- pulse-level control 
- he works on compilation 
- first circuit level compilation 
- bosonic qubit architecture - 
	- GKB qubits - his favorite 
- Compilation for Hamiltonian Simulation 
	- prof at Upenn 
- Machine  Learning 
- Formal Verification for Quantum computing 


**Undergraduate Research Work **


Researchers! 
Sashad Anagolum 
Narges Alasvisami 
Poulami Das
Moin Kesslet 

Elivagar: efficient circuit search for QML 

Problems with current QML circuits 
- chosen arbitrary from a small set of tempaltes
- tempaltes do not incorpaorte any information about QML task or target device 
- choosing an ansatz is a very big thing / issue - a lot of people use templates which usually don't do work 
- people also quantum circuit search - based neural net search 
- inpired by classical Neural Architecture Search (NAS) 
- quantum NAS 


Differences between quantum and classical ML 

- they are different on all levels!! 


for quantum 
- how you embed is more flexibl 
- gradient compute is more expensive 
- big saearch space but as big in NISW
- SWAPS are expnsive 
- not all qubit/links are created ewual 



your classical RAM is so much easier to copy and move around
on the quantum side 


reach out - 
maya2newschool.edu



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QcraiD  

- EHNU6626
- 


Contact: 
akash@qbraid.com
pranet@qbraid.com 


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# NYU-HAQ 



- Quantum Chemistry problems - 
-  (MRSQK) algorithm - multireference selected quantum Krylov
	- https://arxiv.org/pdf/1911.05163 
	- [demo-notebook](https://colab.research.google.com/github/sandbox-quantum/Tangelo-Examples/blob/main/examples/chemistry/excited_states.ipynb#scrollTo=rpnEQfLZL8wx) - of the mrsqk algorithm 
	- get a molecule - find a ground state and find the excited state 
	- then evolve the hamiltonian 
	- what happens when you scale this? count the resources it takes - for example, the amount of gates it uses document how expensive it is 
		- or do circuit compilation 
		- biggest molecule with the smallest amount of resources 
		- do the first part in tangelo (ground state and excited state)


- Quantum Finance problems 
	- implement this algorithm using VQE
	- portfolio optimization 
	- take your algorithm and optimize it on the hardware 
	- do it to limit the computational cost 
	- compare it to classical algorithms 
	- run it on actual 

- DORA HACKS