LISA Symposium 2026 - Plenary 6 @LISAcommunity

Uploaded August 2026 | Updated September 2026, 2 hours ago

(Recorded on June 24, 2026)

Welcome to the sixth plenary session for the 16th LISA Symposium!

Presentations in this session:
00:00:20 - Standard sirens from ground- and space-based missions in the next decade - Hsin-Yu Chen
00:29:25 - Modeling gravitational wave signatures of supermassive black hole binary populations - Laura Blecha
01:00:45 - The Who What When Why and How of the LISA Global Fit - Tyson Littenberg

Session Chair: Arianna Renzini

Torsion pendulum testing for the LISA charge management system

LECSTalks! Quantum Neural Networks for LISA Low-Latency Data Analysis Pipelines by Maria Isfan

LISA Symposium XIV Parallel D EMRIs part 2

Status of the LISA Enhanced Temperature Subsystem (LETS)

Prospects for Detecting Exoplanets around Double White Dwarfs with LISA and Taiji

LISA Symposium XIV Parallel A Beyond LISA Part 2

$Numerical Relativity Surrogate model for eccentric binary black hole gravitational waveform Numerical Relativity Surrogate model for eccentric binary black hole gravitational waveform Tousif Islam, Vijay Varma, Jacqueline Lodman, Scott Field and Gaurav Khanna Though Numerical Relativity (NR) simulations provide the most accurate gravitational waveforms for binary black holes (BBHs), they are computationally expensive, taking days to weeks to generate one single waveform. NR surrogate waveform models are computationally cheaper without sacrificing accuracy. While surrogate models for non-spinning, aligned spin and precessing BBHs are quite reliable, efforts to build an eccentric NR surrogate model are still at an early stage. We provide detailed data decomposition and parameterization strategies to build an effective NR surrogate for eccentric BBHs waveforms. Based on the proposed framework, we then present a time domain, inspiral-merger-ringdown NR surrogate model for eccentric binary black holes for mass ratio $q=1$. We call it NRSur2dq1Ecc. The model includes the (l=2,m=2), (l=3,m=2) and (l=4,m=4) spin-weighted spherical harmonic modes. The odd $m$ modes are zero due to the symmetry of the system. We parameterize the effect of eccentricity via eccentric parameter $e_w$ and mean anomaly $l_w$. This model has been trained against 41 NR waveforms with mass ratio $q=1$, $e_wlt0.175$ and $0ltl_wlt2pi$ (as estimated at a reference time of $t_{ref} 4200M$); and uses Gaussian Process Regression to build the fits across parameter space. We show that our model can accurately predict NR waveforms with mismatches $approx 10^{-3}$ and can recover subtle effects like mode-mixing in the ringdown signal. The method proposed here would pave the way forward for constructing any future surrogate waveform model with eccentric binaries.$

IfoCAD simulations for TTL noise analyses in LISA

LISA Symposium XIV Parallel A LISA Instrumentation 3 Part 2