CANCELLED - Glasses: From Physical Hamiltonians to Neural Networks and Back
Abstract: This talk will review our recent work on classical and quantum glasses. I will start with a discussion of spin glasses from the perspective of chaos theory.
To be announced
The title and abstract for this talk are forthcoming.
*We strongly encourage attendees to use their full name (and if possible, their UMD credentials) to join the zoom session.*
To be annnounced
The title and abstract for this talk are forthcoming.
*We strongly encourage attendees to use their full name (and if possible, their UMD credentials) to join the zoom session.*
Optimization by Decoded Quantum Interferometry
In this talk I will describe Decoded Quantum Interferometry (DQI), a quantum algorithm for reducing classical optimization problems to classical decoding problems by exploiting structure in the Fourier spectrum of the objective function. (See: https://arxiv.org/abs/2408.08292.) For a regression problem called optimal polynomial intersection, which has been previously studied in the contexts of coding theory and cryptanalysis, we believe DQI achieves an exponential quantum speedup.
Quantum complexity in many-body physics: random circuits and thermodynamics
Quantum complexity is emerging as a key property of many-body systems, including black holes, topological materials, and early quantum computers. A state's complexity quantifies the number of computational gates required to prepare the state from a simple tensor product. I will discuss two approaches to better understand the role of quantum complexity in many-body physics. First, we'll consider random circuits, a model for chaotic dynamics. In such circuits, the quantum complexity grows linearly until it saturates at a value exponential in the system size.
Achieving low circuit depth with few qubits, for arithmetic and the QFT
In this work we present fast constructions for the quantum Fourier transform and quantum integer multiplication, using few ancilla qubits compared to the size of the input. For the approximate QFT we achieve depth O(log n) using only n + O(n / log n) total qubits, by applying a new technique we call "optimistic quantum circuits." To our knowledge this is the first circuit for the AQFT with space-time product O(n log n), matching a known lower bound.
Catalysis of quantum entanglement and entangled batteries
We discuss recent progress on entanglement catalysis, including the equivalence between catalytic and asymptotic transformations of quantum states and the impossibility to distill entanglement from states having positive partial transpose, even in the presence of a catalyst. A more general notion of catalysis is the concept of entanglement battery. In this framework, we show that a reversible manipulation of entangled states is possible. This establishes a second law of entanglement manipulation without relying on the generalized quantum Stein's lemma.
Information in a Photon
Light is quantum. Hence, quantifying and attaining fundamental limits of transmitting, processing and extracting information encoded in light must use quantum analyses. This talk is aimed at elucidating this using principles from information and estimation theories, and quantum modeling of light. We will discuss nuances of “informationally optimal” measurements on so-called Gaussian states of light in the contexts of a few different metrics.
Learning shallow quantum circuits and quantum states prepared by shallow circuits in polynomial time
In this talk we give polynomial time algorithms for the following two problems: (1) Given access to an unknown constant depth quantum circuit U on a finite-dimensional lattice, learn a constant depth circuit that approximates U to small diamond distance. (2) Given copies of an unknown quantum state |ψ>=U|0^n> that is prepared by an unknown constant depth circuit U on a finite-dimensional lattice, learn a constant depth circuit that prepares |ψ>. These algorithms extend to the case when the depth of U is polylog(n) with a quasi
QCVV: Making Quantum Computers Less Broken
Abstract: Quantum computing hardware capabilities have grown tremendously over the past decade, as evidenced by demonstrations of both quantum advantage and error-corrected logical qubits. These breakthroughs have been driven, in part, by advances in quantum characterization, verification, and validation (QCVV). I will discuss how QCVV provides a hardware-agnostic framework for assessing the performance of quantum computers; I will describe in detail how specific QCVV protocols (such as gate set tomography and robust phase estimation) have been used to characterize and sig