178 lines
4.4 KiB
Markdown
178 lines
4.4 KiB
Markdown
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Oded Regev
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Computer Science Dept
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NYU - Courant Institute
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*Person to talk to about PQC*
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What can we do with quantum computers?
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- simulating natural systems
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- facotorng
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- finding new algorithms
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*Cryptography until 20th century*
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- enigma machine boring! jk
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- secret key cryptography
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*Late 20th Century*:
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- Diffie Helman
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Public Key Encryption:
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- allows two parties to communciate securely over an insecure channel , without having to agree in advance on a secret
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Factoring Integer
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- 15 = 5 * 3
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- 21 = 3 * 7
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- current world record is 2500 digits - took 2700 computer years
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- very difficult task for computers - secure comms (web, phone, banks, governments) rely on this
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- based on assumption that this factoring is very hard
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Crisis in Cryptography
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- 199, Shor discussed factoring is easy for quantum computers
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Quantum Cryptography
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- allows uncontiionally secure, communcoation over a quantum channel (Weisman70, BenneetBressar84)
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- real world implementatins
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- but rrequites dedicated infrastructure
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Post-quantum Cryptography
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----
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# Speaker 2 - SandboxAQ
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Kahoot questions
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1. What are the Z-basis states of a qubit
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2. Which country is investing the most funds in quantum computing?
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3. The Z Gate only adds a phase to |0> and not |1> TTrue/False ? --> FALSE
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4. Which gate us used to put a qubit in a super position 1/root2 > H
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5. A qubit in the state |0> is the SAME THING > **FALSE** it only has a flavor
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6. What gate would you add to this circuit > **CX(0,1)**
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7. What is the most practical allowed error rate in quantum computing - Below 1%
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8. What will the measurement read? > 00, 01, 10, 11
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9. Hackers can store RSA encryptedd data now, and decrypt it later when usedul quantum computing exists > True
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10. The following is a mult-contro, multitarget, MCMT, How many control, and target qubits are there > Control Target
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11. Create the following superposition in cricuit qc using onel ine of code 1/v2 (|00) > qc.h(1)
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12. where is the quantum processor?
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1. Rohan
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2. Ethan
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3. Bhavyansh S
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---
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# Speaker 3 - research scientist in AWS
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AWS - analog version with QuEra
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-qbraid powered by AWsS
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His interests:
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- pulse-level control
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- he works on compilation
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- first circuit level compilation
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- bosonic qubit architecture -
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- GKB qubits - his favorite
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- Compilation for Hamiltonian Simulation
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- prof at Upenn
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- Machine Learning
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- Formal Verification for Quantum computing
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**Undergraduate Research Work **
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Researchers!
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Sashad Anagolum
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Narges Alasvisami
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Poulami Das
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Moin Kesslet
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Elivagar: efficient circuit search for QML
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Problems with current QML circuits
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- chosen arbitrary from a small set of tempaltes
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- tempaltes do not incorpaorte any information about QML task or target device
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- choosing an ansatz is a very big thing / issue - a lot of people use templates which usually don't do work
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- people also quantum circuit search - based neural net search
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- inpired by classical Neural Architecture Search (NAS)
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- quantum NAS
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Differences between quantum and classical ML
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- they are different on all levels!!
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for quantum
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- how you embed is more flexibl
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- gradient compute is more expensive
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- big saearch space but as big in NISW
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- SWAPS are expnsive
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- not all qubit/links are created ewual
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your classical RAM is so much easier to copy and move around
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on the quantum side
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reach out -
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maya2newschool.edu
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----
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QcraiD
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- EHNU6626
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-
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Contact:
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akash@qbraid.com
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pranet@qbraid.com
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---
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# NYU-HAQ
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- Quantum Chemistry problems -
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- (MRSQK) algorithm - multireference selected quantum Krylov
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- https://arxiv.org/pdf/1911.05163
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- [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
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- get a molecule - find a ground state and find the excited state
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- then evolve the hamiltonian
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- what happens when you scale this? count the resources it takes - for example, the amount of gates it uses document how expensive it is
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- or do circuit compilation
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- biggest molecule with the smallest amount of resources
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- do the first part in tangelo (ground state and excited state)
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- Quantum Finance problems
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- implement this algorithm using VQE
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- portfolio optimization
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- take your algorithm and optimize it on the hardware
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- do it to limit the computational cost
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- compare it to classical algorithms
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- run it on actual
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- DORA HACKS
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