Talks

3:15PM Arnab Adhikary 3:18PM Anjishnu Bose 3:21PM Matthew Duschenes 3:24PM SangEun Han & Daniel Schultz 3:27PM Andrew Hardy 3:30PM Daniel Huerga 3:33PM Vedangi Pathak 3:36PM Shengqi Sang 3:39PM Joseph Tindall 3:42PM Tarun Tummuru 3:45PM Ryohei Weil 3:48PM Rui Wen 3:51PM Ye Weicheng 3:54PM Emily Zhang

Unlike the half spin Kitaev honeycomb model which can be solved by an exact parton construction, the higher spin analogue of it is not solvable and it is still controversial if it exhibits a quantum spin liquid phase. In this talk, I will present a generalized parton construction where each spin-S is represented by 8S Majorana fermions. This framework naturally leads to a Z2 spin liquid when S is a half integer and gives a trivial ground state when S is an integer. Particularly, in the Z2 spin liquid, the Z2 charge is carried by a product of 2S Majorana fermions. In the anisotropic limit, say the interaction on the z bond is much stronger than others, the charges are gapped and the higher spin Kitaev model is reduced to a Wen-plaquette model exhibiting Z2 topological order. However, it is expected that at certain interaction strength on the x,y,z bond, the charges become gapless which results in a gapless Z2 spin liquid.

A brief introduction to Celestial Holography

We introduce the origins of holography and illustrate in broad strokes the theory of celestial holography. We discuss the development of asymptotic symmetries from soft theorems and how these symmetries point to a codimension 2 boundary on which would live the dual CFT. We show the connection between predicted asymptotic symmetries and observable memory effects, completing the famous infrared triangle. We conclude with some applications and current problems we are thinking about, in particular with respect to bulk reconstruction.

I will discuss our recent work on the use of autoregressive neural networks for many-body physics. In particular, I will discuss two approaches to represent quantum states using these models and their applications to the reconstruction of quantum states, the simulation of real-time dynamics of open quantum systems, and the approximation of ground states of many-body systems displaying long-range order, frustration, and topological order. Finally, I will discuss how annealing in these systems can be used for combinatorial optimization where we observe solutions to problems that are orders of magnitude more accurate than simulated and simulated quantum annealing.

"The relatively weak van der Waals bond in 2D materials has ushered in a rich new era of stacking engineering. We recently found in rhombohedrally stacked MoS2, a Berry phase contrast between layers can induce an asymmetric interlayer coupling and an out-of-plane spontaneous electrical polarization (1). The polarization direction can be switched via interlayer sliding, forming a new type of ferroelectricity. In addition, we demonstrated that such a polarization can lead to a spontaneous photovoltaic effect without any pn junctions (2). Compared to conventional PV effects, our device shows a similar quantum efficiency with an ultrafast speed and potentially a programmable polarity. The rhombohedrally stacked transition metal dichalcogenides therefore provide a new platform for studying spontaneous polarization at the atomic scale. (1) Jing Liang, et al, arXiv:2209.06966 (2022). (2) Dongyang Yang, et al, Nature Photonics, 16, 469–474 (2022)."

Structures composed of two monolayer-thin d-wave superconductors with a twist angle close to 45° are predicted to form a robust, fully gapped topological superconducting phase with spontaneously broken time-reversal symmetry and protected chiral edge modes. In this talk I will briefly review the theory behind the topological phase and discuss recent experimental efforts to fabricate and probe twisted flakes of high-Tc cuprate Bi2Sr2CaCu2O8+δ. Signatures of d-wave symmetry and of spontaneous T-breaking are indeed visible in the device Josephson current response, as detected through Fraunhofer pattern and Shapiro step analysis, and, very recently, a pronounced superconducting diode effect observed in samples near 45° twist but absent in untwisted samples.

It is well known that quantum information can be strictly localized in quantum field theory. Similarly, one can also localize information in classical gravity up to quantities like the ADM mass which are fixed by the constraints of general relativity. On the other hand, the holographic nature of quantum gravity suggests that information can never be localized deep inside some spacetime region, and is always accessible from the boundary. This is meant to hold as a non-perturbative statement and it remains to be understood whether quantum information can be localized within G_N perturbation theory. In this talk, I will address this problem from the point of view of the AdS/CFT correspondence. I will construct candidate local operators that can be used to localize information deep inside the bulk. They have the following two properties: they act just like standard HKLL operators to leading order at large N, but commute with the CFT Hamiltonian to all orders in 1/N. These operators can only be constructed in a particular class of states which have a large energy variance, for example coherent states corresponding to semi-classical geometries. The interpretation of these operators is that they are dressed with respect to a feature of the state, rather than to the boundary. I will comment on connections with black holes and computations of the Page curve.

Zoom link: https://pitp.zoom.us/j/94678968773?pwd=NUJhOEJmRWxLa3pCVUtVVi9DdkE3QT09

In the early 1980s, axions and WIMPs were identified as promising dark matter candidates. The last forty years have seen a spectacularly successful experimental program attempting to discover the WIMPs, with sensitivity that has by now improved by many orders of magnitude compared to the earliest results. The parallel program to search for axions has made less progress and has reached the necessary sensitivity only over a very limited mass range. However, progress has recently accelerated, with the invention of many new axion detection techniques that may eventually provide a definitive answer to the question of whether the dark matter is made of axions. I will review some of these new developments with emphasis on Fermilab’s program, including ADMX- Extended Frequency Range and Broadband Reflector Experiment for Axion Detection (BREAD).

Zoom link:  https://pitp.zoom.us/j/97234421735?pwd=UGNJRWxYMkErRmdWSnJiWTdoOFNaZz09

In this talk, I describe our collaboration with VolunteerMatch (VM), the largest nationwide platform that connects nonprofits with volunteers. Through our work with VM, we have identified a key feature shared by many matching platforms (including Etsy, DonorsChoose, and VM): the supply side (e.g., nonprofits on the VM platform) not only relies on the platform’s internal recommendation algorithm to draw traffic but also utilizes other channels, such as social media, to attract external visitors. Such visitors arrive via direct links to their intended options, thus bypassing the platform’s recommendation algorithm. For example, of the 1.3 million monthly visitors to the VM platform, approximately 30% are external traffic directed to VM as a result of off-platform outreach activities, such as when nonprofits publicize volunteering opportunities on LinkedIn or Facebook. This motivated us to introduce the problem of online matching with multi-channel traffic, a variant of a canonical online matching problem. Taking a competitive analysis approach, we first demonstrate the shortcomings of a commonly-used algorithm that is optimal in the absence of external traffic. Then, we propose a new algorithm that achieves a near-optimal competitive ratio in certain regimes. Beyond theoretical guarantees, we demonstrate our algorithm’s practical effectiveness in simulations based on VM data. Time permitting, I will also report on implementing an improved recommendation algorithm on the VM platform and present data from our ensuing experimentation. (Joint work with Scott Rodilitz, Daniela Saban, and Akshaya Suresh)

I will describe a holographic model for the three dimensional de Sitter static patch where the boundary theory is the so called $T\bar{T}+\Lambda_2$ deformation of the conformal field theory dual to AdS_3 quantum gravity. This identification allows us to obtain the cosmic horizon entropy from a microstate count, and the microstates themselves are a dressed version of those that account for the entropy of certain black holes in AdS space. I will also show how the effect of this dressing at the cosmic horizon is to replace the spacetime dependence of the fields of the undeformed holographic CFT with dependence on the indices of large matrices.

Zoom link:  https://pitp.zoom.us/j/95396921570?pwd=NGFoOGlGY1ZDU2pnNFRwWit3b2w0Zz09

Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a variety of ad hoc border control protocols to allow for non-essential travel while safeguarding public health, from quarantining all travellers to restricting entry from select nations on the basis of population-level epidemiological metrics such as cases, deaths or testing positivity rates1,2. Here we report the design and performance of a reinforcement learning system, nicknamed Eva. In the summer of 2020, Eva was deployed across all Greek borders to limit the influx of asymptomatic travellers infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and to inform border policies through real-time estimates of COVID-19 prevalence. In contrast to country-wide protocols, Eva allocated Greece’s limited testing resources on the basis of incoming travellers’ demographic information and testing results from previous travellers. By comparing Eva’s performance against modelled counterfactual scenarios, we show that Eva identified 1.85 times as many asymptomatic, infected travellers as random surveillance testing, with up to 2–4 times as many during peak travel, and 1.25–1.45 times as many asymptomatic, infected travellers as testing policies that utilize only epidemiological metrics. We demonstrate that this latter benefit arises, at least partially, because population-level epidemiological metrics had limited predictive value for the actual prevalence of SARS-CoV-2 among asymptomatic travellers and exhibited strong country-specific idiosyncrasies in the summer of 2020. Our results raise serious concerns on the effectiveness of country-agnostic internationally proposed border control policies3 that are based on population-level epidemiological metrics. Instead, our work represents a successful example of the potential of reinforcement learning and real-time data for safeguarding public health.