Harvard Quantum Initiative Special Seminar
Monday, January 7
10:00 AM
Jefferson 356
Saeed Mehraban, MIT
The complexity of sampling from a weak quantum computer
This is an exciting time for quantum computing. Over the next few years, intermediate-scale quantum computers with ~50-100 qubits are expected to become practical. These computers are too small to do error correction and they may not capture the full power of a universal quantum computer. A major theoretical challenge is to understand the capabilities and limitations of these devices. In order to approach this challenge, quantum supremacy experiments have been proposed as a near-term milestone. The objective of quantum supremacy is to find computational problems that are feasible on a small-scale quantum computer but are hard to simulate classically. Even though a quantum supremacy experiment may not have practical applications, achieving it will demonstrate that quantum computers can outperform classical ones. Among other proposals, over the recent years, two sampling based quantum supremacy experiments have been proposed:
(1) The first one is based on sampling from the output of a random circuit applied to a square grid of qubits. The Google quantum AI group is planning to implement this task on a processor composed of a few (~50-100) superconducting qubits. In order to argue that this sampling task is hard, building on previous works of Aaronson, Arkhipov, and others, they conjectured that the output distribution of a low-depth (O(sqrt n) depth in particular) circuit is anti-concentrated meaning that it has nearly maximal entropy.
(2) The second proposal, known as Boson Sampling (Aaronson Arkhipov ’10), is based on linear optical experiments. A baseline conjecture of Boson Sampling is that it is #P-hard to approximate the permanent of a Gaussian matrix with zero mean and unit variance with high probability.
In this talk, I first explain a joint work with Aram Harrow (QIP 2019) which proves the mentioned anti-concentration conjecture. This result also finds efficient ways to generate pseudo-random quantum states (known as t-designs), which have vast applications in quantum communication, algorithms, and cryptography. I then explain how the permanent of Gaussian matrices can be approximated in quasi-polynomial with high probability if instead of zero mean we consider a nonzero but vanishing mean Gaussian matrix. This result finds, to the best of our knowledge, the first example of a natural counting problem that is #P-hard to compute exactly on average and #P-hard to approximate in the worst case but becomes easy only when approximation and average case are combined. This result is based on joint work with Lior Eldar (FOCS 2018).
In the end, I introduce some intermediate scale models of quantum computation based on exactly solvable models in mathematical physics and argue that, even though they are very simple in the sense of solvability, they still cannot be simulated on a classical computer assuming plausible conjectures. I also explain how these models can be simulated by another intermediate model known as the one-clean qubit model. This result is based on joint work with Aaronson, Bouland, and Kuperberg (STOC 2017).
Special ITAMP Talk
Monday, January 7, 2019
11:00 am, 60 Garden Street, B-105
Valentin Walther (Aarhus University)
Title: Long-ranged interaction effects with excitons and atoms
Samantha Dakoulas
Faculty Assistant to Professors Lukin & Greiner & their groups
Department of Physics
17 Oxford St., Lyman 324A
Cambridge, MA 02138
P. (617) 496-2544
*Speaker: *Yehuda B. Band (Ben-Gurion University)
*Date:* Thursday, Jan 10th
*Time:* 12:00-1:00 pm
Includes Pizza.
*Title: * Quantum Rotors: Magnetometers and Accelerometers
*Abstract: *In a cold atom gas subject to a spin-dependent 2D optical
lattice potential with hexagonal symmetry, trapped atoms undergo orbital
motion around the minima of the optical lattice potential. Such atoms are
elementary quantum rotors (QRs). The theory of an atomic QR is developed.
Wave functions, energies, and degeneracies are determined for both bosonic
and fermionic QRs, as well as magnetic dipole transitions between ground
and spin-excited states. QRs in optical lattices with precisely one atom
per site can be used as a magnetometer or as an accelerometer; such devices
can have unprecedented accuracy.
Harvard Quantum Initiative Special Seminar
Monday, January 7
10:00 AM
Jefferson 356
Saeed Mehraban, MIT
The complexity of sampling from a weak quantum computer
This is an exciting time for quantum computing. Over the next few years, intermediate-scale quantum computers with ~50-100 qubits are expected to become practical. These computers are too small to do error correction and they may not capture the full power of a universal quantum computer. A major theoretical challenge is to understand the capabilities and limitations of these devices. In order to approach this challenge, quantum supremacy experiments have been proposed as a near-term milestone. The objective of quantum supremacy is to find computational problems that are feasible on a small-scale quantum computer but are hard to simulate classically. Even though a quantum supremacy experiment may not have practical applications, achieving it will demonstrate that quantum computers can outperform classical ones. Among other proposals, over the recent years, two sampling based quantum supremacy experiments have been proposed:
(1) The first one is based on sampling from the output of a random circuit applied to a square grid of qubits. The Google quantum AI group is planning to implement this task on a processor composed of a few (~50-100) superconducting qubits. In order to argue that this sampling task is hard, building on previous works of Aaronson, Arkhipov, and others, they conjectured that the output distribution of a low-depth (O(sqrt n) depth in particular) circuit is anti-concentrated meaning that it has nearly maximal entropy.
(2) The second proposal, known as Boson Sampling (Aaronson Arkhipov ’10), is based on linear optical experiments. A baseline conjecture of Boson Sampling is that it is #P-hard to approximate the permanent of a Gaussian matrix with zero mean and unit variance with high probability.
In this talk, I first explain a joint work with Aram Harrow (QIP 2019) which proves the mentioned anti-concentration conjecture. This result also finds efficient ways to generate pseudo-random quantum states (known as t-designs), which have vast applications in quantum communication, algorithms, and cryptography. I then explain how the permanent of Gaussian matrices can be approximated in quasi-polynomial with high probability if instead of zero mean we consider a nonzero but vanishing mean Gaussian matrix. This result finds, to the best of our knowledge, the first example of a natural counting problem that is #P-hard to compute exactly on average and #P-hard to approximate in the worst case but becomes easy only when approximation and average case are combined. This result is based on joint work with Lior Eldar (FOCS 2018).
In the end, I introduce some intermediate scale models of quantum computation based on exactly solvable models in mathematical physics and argue that, even though they are very simple in the sense of solvability, they still cannot be simulated on a classical computer assuming plausible conjectures. I also explain how these models can be simulated by another intermediate model known as the one-clean qubit model. This result is based on joint work with Aaronson, Bouland, and Kuperberg (STOC 2017).
Dear Quanta
If anyone is interested in participating in QISkit camp, please
email Liz Durst @ IBM (cc-ed here):
*https://qiskit.camp/* <https://qiskit.camp/>
It might require a nomination and deadline is soon.
Best,
--
Ramis
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qip(a)mit.edu
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Dear all,
Saeed Mehraban’s talk has been postponed until Monday, January 7. A new announcement will be sent once the talk time is finalized.
_________________
Harvard Quantum Initiative Special Seminar
*Will be held Monday, January 7, time TBA*
Saeed Mehraban, MIT
The complexity of sampling from a weak quantum computer
This is an exciting time for quantum computing. Over the next few years, intermediate-scale quantum computers with ~50-100 qubits are expected to become practical. These computers are too small to do error correction and they may not capture the full power of a universal quantum computer. A major theoretical challenge is to understand the capabilities and limitations of these devices. In order to approach this challenge, quantum supremacy experiments have been proposed as a near-term milestone. The objective of quantum supremacy is to find computational problems that are feasible on a small-scale quantum computer but are hard to simulate classically. Even though a quantum supremacy experiment may not have practical applications, achieving it will demonstrate that quantum computers can outperform classical ones. Among other proposals, over the recent years, two sampling based quantum supremacy experiments have been proposed:
(1) The first one is based on sampling from the output of a random circuit applied to a square grid of qubits. The Google quantum AI group is planning to implement this task on a processor composed of a few (~50-100) superconducting qubits. In order to argue that this sampling task is hard, building on previous works of Aaronson, Arkhipov, and others, they conjectured that the output distribution of a low-depth (O(sqrt n) depth in particular) circuit is anti-concentrated meaning that it has nearly maximal entropy.
(2) The second proposal, known as Boson Sampling (Aaronson Arkhipov ’10), is based on linear optical experiments. A baseline conjecture of Boson Sampling is that it is #P-hard to approximate the permanent of a Gaussian matrix with zero mean and unit variance with high probability.
In this talk, I first explain a joint work with Aram Harrow (QIP 2019) which proves the mentioned anti-concentration conjecture. This result also finds efficient ways to generate pseudo-random quantum states (known as t-designs), which have vast applications in quantum communication, algorithms, and cryptography. I then explain how the permanent of Gaussian matrices can be approximated in quasi-polynomial with high probability if instead of zero mean we consider a nonzero but vanishing mean Gaussian matrix. This result finds, to the best of our knowledge, the first example of a natural counting problem that is #P-hard to compute exactly on average and #P-hard to approximate in the worst case but becomes easy only when approximation and average case are combined. This result is based on joint work with Lior Eldar (FOCS 2018).
In the end, I introduce some intermediate scale models of quantum computation based on exactly solvable models in mathematical physics and argue that, even though they are very simple in the sense of solvability, they still cannot be simulated on a classical computer assuming plausible conjectures. I also explain how these models can be simulated by another intermediate model known as the one-clean qubit model. This result is based on joint work with Aaronson, Bouland, and Kuperberg (STOC 2017).
--
Clare Ploucha
Administrative Program Manager
Max Planck/Harvard Research Center for Quantum Optics
Department of Physics
17 Oxford Street, Jefferson 357
Cambridge, MA 02138
P: 617-495-3388
*PLEASE NOTE ROOM CHANGE*
Harvard Quantum Initiative Special Seminar
Friday, January 4
12:00 PM
Jefferson 250
Ilya Esterlis, Stanford
Title: Reconsidering the electron-phonon problem
Abstract: The electron-phonon interactions determine many of the salient features of “conventional” metals including their transport properties (e.g. resistivity) at most temperatures and, famously, their superconducting transition temperature, Tc. As the electron-phonon coupling is not small, perturbation theory is not applicable. However, a 60 year old “theorem” by Migdal was generally thought to solve this problem, allowing results to all orders in perturbation theory to be summed using the ratio of the electron mass to the ion mass as a small parameter. We have revisited this problem by studying a paradigmatic model problem (the “Holstein model”) using the Migdal approach, a strong coupling expansion, and exact numerical methods. We show that Migdal’s theorem isn’t (a theorem); results based on the Migdal-Eliashberg “approximation” are found to be amazingly accurate for a range of couplings, but break down quantitatively and qualitatively (in a regime where the Migdal theorem is still nominally applicable) at a point of crossover to strong-coupling physics. These results give a new perspective (including an upper bound on Tc) on the hunt for high temperature conventional superconductors.
--
Clare Ploucha
Administrative Program Manager
Max Planck/Harvard Research Center for Quantum Optics
Department of Physics
17 Oxford Street, Jefferson 357
Cambridge, MA 02138
P: 617-495-3388
Harvard Quantum Initiative Special Seminar
Friday, January 4
4:00 PM
Jefferson 356
Saeed Mehraban, MIT
The complexity of sampling from a weak quantum computer
This is an exciting time for quantum computing. Over the next few years, intermediate-scale quantum computers with ~50-100 qubits are expected to become practical. These computers are too small to do error correction and they may not capture the full power of a universal quantum computer. A major theoretical challenge is to understand the capabilities and limitations of these devices. In order to approach this challenge, quantum supremacy experiments have been proposed as a near-term milestone. The objective of quantum supremacy is to find computational problems that are feasible on a small-scale quantum computer but are hard to simulate classically. Even though a quantum supremacy experiment may not have practical applications, achieving it will demonstrate that quantum computers can outperform classical ones. Among other proposals, over the recent years, two sampling based quantum supremacy experiments have been proposed:
(1) The first one is based on sampling from the output of a random circuit applied to a square grid of qubits. The Google quantum AI group is planning to implement this task on a processor composed of a few (~50-100) superconducting qubits. In order to argue that this sampling task is hard, building on previous works of Aaronson, Arkhipov, and others, they conjectured that the output distribution of a low-depth (O(sqrt n) depth in particular) circuit is anti-concentrated meaning that it has nearly maximal entropy.
(2) The second proposal, known as Boson Sampling (Aaronson Arkhipov ’10), is based on linear optical experiments. A baseline conjecture of Boson Sampling is that it is #P-hard to approximate the permanent of a Gaussian matrix with zero mean and unit variance with high probability.
In this talk, I first explain a joint work with Aram Harrow (QIP 2019) which proves the mentioned anti-concentration conjecture. This result also finds efficient ways to generate pseudo-random quantum states (known as t-designs), which have vast applications in quantum communication, algorithms, and cryptography. I then explain how the permanent of Gaussian matrices can be approximated in quasi-polynomial with high probability if instead of zero mean we consider a nonzero but vanishing mean Gaussian matrix. This result finds, to the best of our knowledge, the first example of a natural counting problem that is #P-hard to compute exactly on average and #P-hard to approximate in the worst case but becomes easy only when approximation and average case are combined. This result is based on joint work with Lior Eldar (FOCS 2018).
In the end, I introduce some intermediate scale models of quantum computation based on exactly solvable models in mathematical physics and argue that, even though they are very simple in the sense of solvability, they still cannot be simulated on a classical computer assuming plausible conjectures. I also explain how these models can be simulated by another intermediate model known as the one-clean qubit model. This result is based on joint work with Aaronson, Bouland, and Kuperberg (STOC 2017).
--
Clare Ploucha
Administrative Program Manager
Max Planck/Harvard Research Center for Quantum Optics
Department of Physics
17 Oxford Street, Jefferson 357
Cambridge, MA 02138
P: 617-495-3388
Harvard Quantum Initiative Special Seminar
Friday, January 4
12:00 PM
Jefferson 356
Ilya Esterlis, Stanford
Title: Reconsidering the electron-phonon problem
Abstract: The electron-phonon interactions determine many of the salient features of “conventional” metals including their transport properties (e.g. resistivity) at most temperatures and, famously, their superconducting transition temperature, Tc. As the electron-phonon coupling is not small, perturbation theory is not applicable. However, a 60 year old “theorem” by Migdal was generally thought to solve this problem, allowing results to all orders in perturbation theory to be summed using the ratio of the electron mass to the ion mass as a small parameter. We have revisited this problem by studying a paradigmatic model problem (the “Holstein model”) using the Migdal approach, a strong coupling expansion, and exact numerical methods. We show that Migdal’s theorem isn’t (a theorem); results based on the Migdal-Eliashberg “approximation” are found to be amazingly accurate for a range of couplings, but break down quantitatively and qualitatively (in a regime where the Migdal theorem is still nominally applicable) at a point of crossover to strong-coupling physics. These results give a new perspective (including an upper bound on Tc) on the hunt for high temperature conventional superconductors.
--
Clare Ploucha
Administrative Program Manager
Max Planck/Harvard Research Center for Quantum Optics
Department of Physics
17 Oxford Street, Jefferson 357
Cambridge, MA 02138
P: 617-495-3388
Since we've just finished the holidays, let's skip the group meeting
tomorrow. But let's have one next week, on the 11th. Then we'll skip the
18th because of QIP, and have one on the 25th.
Happy New Year everybody!
Peter
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