---
title: Young Supernova Experiment
url: https://www.emergentmind.com/topics/young-supernova-experiment
type: topic
---

# Young Supernova Experiment

The Young Supernova Experiment (YSE) is a large-scale, untargeted, multi-color time-domain optical survey designed to discover and characterize young, red, and rare supernovae (SNe) as well as other extragalactic transients. Utilizing the Pan-STARRS telescopes and coordinated with Zwicky Transient Facility (ZTF), YSE delivers high-cadence, deep, four-band ($griz$) imaging over a wide area, capturing the earliest phases of stellar explosions and generating well-calibrated low-redshift samples fundamental for cosmology, transient science, and the preparatory work required for the next generation of time-domain surveys such as the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope [2010.09724, 2211.07128].

## 1. Survey Design and Observational Strategy

YSE operates primarily with the Pan-STARRS1 (PS1) 1.8 m telescope and, as commissioning completes, the Pan-STARRS2 (PS2) twin. Each is equipped with a 1.4 Gpixel camera offering a 7 deg² field of view. The baseline survey cadence is every three days in two $griz$ filters, with alternating $g+r$/$g+i$ in dark time and $r+i$/$r+z$ in bright time. Typical single-epoch 5$\sigma$ depths are $g, r, i \approx 21.5$ mag and $z \approx 20.5$ mag (empirically up to $g\approx22.2$ mag), yielding sensitivity to transients out to $z \approx 0.5$ for SLSNe, and $z \approx 0.3$ for SNe Ia [2211.07128].

Coordination with ZTF (1.2 m Palomar Schmidt; 47 deg² camera, $g$, $r$ filters, $\sim2$ d cadence) enables sub-night and sub-two-day sampling. The effective combined YSE+ZTF cadence is median $\sim1.98$ d, essential for discovering fast transients and constraining explosion times with pre-discovery non-detections.

A fast-rise strategy is employed by flagging candidates with $>$1 mag brightening between YSE and ZTF epochs for rapid follow-up. Daily monitoring of cluster fields (e.g., Virgo) enables discovery of faint stellar outbursts and pre-explosion activity down to $M_i\sim-10$ mag [2010.09724].

## 2. Science Goals and Survey Scope

YSE is designed to address several central objectives:

1. **Early-Time Supernova Physics:** Detect SNe within hours to days of explosion, facilitating study of shock breakout, flash ionization, companion interaction, and circumstellar mass loss.
2. **Rare and Red Transients:** Expand the observational parameter space for faint ($M\gtrsim -16$), fast, and extremely red transients (including Ca-rich events, luminous red novae, fast blue optical transients, gravitationally lensed SNe, and SLSNe) by leveraging deep $i$ and $z$ imaging.
3. **Cosmology:** Provide a homogeneously calibrated anchor sample of several hundred SNe Ia at low redshift ($z\sim0.1$), with relative calibration better than 3 mmag, crucial for reducing systematic uncertainties in $H_0$ and $w$ in future cosmological analyses [2010.09724].
4. **Active Galactic Nuclei and Tidal Disruption Events:** Monitor tens of thousands of galaxies for nuclear variability, enabling discovery of TDEs and changing-look quasars.
5. **Rubin/Roman Pathfinder:** Build a comprehensive training set of multi-band transient light curves with selection functions and cadence closely matched to the next-generation time-domain surveys [2010.09724, 2211.07128].

## 3. Data Products, Photometric Classification, and Early Results

YSE Data Release 1 (YSE DR1) provides forced PSF photometry for 1,975 transients with accompanying host associations, redshifts (spectroscopic and photometric), and classifications using both spectroscopic and advanced photometric methods. The photometric classifier ParSNIP, a physics-enabled variational autoencoder with latent parameterization and a random-forest discriminator, achieves 82% overall accuracy on three-class (Ia, II, Ib/Ic) validation (94% completeness, 89% purity for SNe Ia). SuperRAENN, a recurrent autoencoder with random forest trained on interpolated light curves, achieves 75% tertiary accuracy and 90% Ia-CC binary separation [2211.07128].

Data products also include light-curve parameters, host galaxy cross-matches, and simulated light-curve injections using the SNANA framework, supporting classification algorithm development and robust derivation of volumetric SN rates.

Early YSE discoveries include prompt-phase SNe Ia (e.g., 2020pf, 2020fci), flash-ionized SNe II (e.g., 2020pni, 2020tlf), SNe Iax, super-Chandrasekhar SNe Ia, rare SNe IIb, and TDEs. The median discovery is $-6.4$ d before maximum light [2010.09724, 2211.07128]. 

## 4. Supernova Yields, Demographics, and Rates

Survey simulations predict $\sim$5000 SN detections per year (at full 1500 deg² coverage), subdivided as $\sim$3920 SNe Ia, $\sim$277 SNe Ib/c, $\sim$705 SNe II, and $\sim$67 SNe IIn for S/N$>$5 in at least three epochs [2010.09724].

Yearly yields from DR1 for magnitude-limited ($r<18.5$ mag) and volume-limited ($D<250$ Mpc) samples, with spectroscopic classification completeness up to 97%, are as follows:

| Sample Type         | SNe Ia         | SNe II        | SNe Ib/Ic        | SLSNe  |
|---------------------|---------------|--------------|------------------|--------|
| Magnitude-limited   | 0.682         | 0.239        | 0.074            | 0.006  |
| Volume-limited      | 0.438         | 0.438        | 0.123            | —      |

$R(c) = N_c / N_{\text{tot}}$; uncertainties are calculated via multinomial confidence intervals [2211.07128].

DR1’s photometric sample (ParSNIP labels) is 71% SNe Ia, 23% SNe II, 6% SNe Ib/Ic. The sample extends to $z\lesssim0.5$ (median $z\approx0.14$), with spectroscopic reach to $z\sim0.3$. Relative rates align with other untargeted transient surveys (ZTF BTS, ASAS-SN, LOSS) within uncertainties.

## 5. Diagnostic Experiments: Young SNe as Physics Laboratories

YSE's early detections of stripped-envelope SNe (IIb/Ib/Ic) are critical for probing nonthermal acceleration physics. Radio synchrotron emission in $\sim1$ yr-old SNe exhibits an electron energy index $p_\text{obs} \simeq 3.0\pm0.2$, significantly steeper than standard DSA predictions ($p_\mathrm{DSA}=2.0$ for $r=4$). This steepening diagnoses the pre-acceleration “injection” regime: radio emission arises from electrons below $E_\mathrm{break}\sim100$ MeV ($\gamma_{\rm br}\sim200$) where acceleration is inefficient [1211.5835].

The Young Supernova Experiment (in the sense of probing acceleration physics using early multi-wavelength data) employs:

- **mm/sub-mm (ALMA):** Multi-epoch (t=20, 50, 100, 200 days) monitoring across $\sim$100 GHz to track spectral breaks and infer $E_\mathrm{break}$ from SED features.
- **cm (Radio):** Constrains SSA turnover for magnetic field and shock radius.
- **X-ray (Chandra):** Observes IC and synchrotron emission to calibrate the transition from inefficient to efficient electron acceleration. Temporal and spectroscopic coverage (t$\sim$300, 500 days, 0.3–8 keV) probes slope hardening and slow decay ($F_X \propto t^{-0.3}$).

Key fitting parameters ($E_{\rm break}$, $p_{<}$, $p_{>}$, $\eta_e$, $A_*$, $\epsilon_B$) are determined through multi-band $\chi^2$ minimization, directly constraining DSA injection and acceleration efficiency for cosmic ray electron populations in young shocks [1211.5835].

## 6. Legacy and Role in Next-Generation Surveys

YSE serves as a Rubicon for time-domain survey methodology, providing a contiguous, multi-band, well-calibrated data set for training alert brokers and photometric classifiers in filters closely matched to Rubin ($grizy$) and Roman (NIR). The magnitude-limited, low-$z$ SN Ia anchor population is designed to replace legacy calibration samples, reducing systematic cross-survey uncertainties to $\sim$2–3 mmag.

Synergy with ZTF (joint fields, $\sim$1–2 d cadence) and preparations for data handoff and cadence supplementation with Rubin positions YSE as both scientific and logistical pathfinder. Deep stacked imaging (to $griz\approx23.6$–$24.2$ mag after several years) will support pre-explosion progenitor searches and facilitate studies of dust-enshrouded or ultra-faint transients [2010.09724].

YSE DR1 has already contributed a substantial increase in low-$z$ SNe Ia samples, improved transient anomaly detection pipelines, and validated machine-learning classifiers (ParSNIP, SuperRAENN) foundational for the LSST era [2211.07128].

## 7. Broader Scientific Applications

YSE DR1 supports:

- **Cosmology:** Robust anchor samples of SNe Ia for $H_0$ and $w$ measurements.
- **Transient Astrophysics:** Early-phase/fast SNe, classification of rare SNe (e.g. Ia–CSM, Iax, Ca-strong, LRNe, LBVs), and TDEs.
- **Survey Methodology:** Testbeds for cadence optimization, alert-broker architecture, and photometric pipeline scalability in preparation for future extremely large archives [2211.07128].
- **Core-Collapse SN Demographics:** Direct measurement of relative SN rates without the need for targeted host-galaxy catalogs.

YSE’s design, execution, and data releases exemplify the integration of optimized high-cadence survey strategy, advanced machine learning classification of time-domain events, and the broader community utility of large, homogeneous transient datasets.

Source: https://www.emergentmind.com/topics/young-supernova-experiment