LightHit

LightHit computes the expected optical-module response to light propagating in a homogeneous scattering medium. It solves the time-dependent radiative transfer equation (RTE), including unscattered, once-scattered and multiply-scattered light, and returns expected photoelectrons per module and per time bin.

The medium, detector and source are ordinary Python objects. There is no global initialisation state, so several configurations can safely coexist in one program.

LightHit is currently an alpha release. Validate numerical settings for your medium and geometry before using its results in an analysis.

Installation

python -m pip install lighthit

Numba acceleration is strongly recommended for tracks, showers and large detector arrays:

python -m pip install 'lighthit[accelerate]'

Python 3.11 or newer is required.

Quick start

The example below defines a spectral medium, two optical modules and a monochromatic isotropic flash.

import numpy as np
import lighthit as lh

# Optical properties tabulated versus wavelength.
medium = lh.SpectralMedium(
    wavelength_nm=[400.0, 450.0, 500.0],
    absorption_per_m=[0.030, 0.020, 0.040],
    scattering_per_m=[0.030, 0.022, 0.017],
    phase_index=[1.344, 1.339, 1.336],
    group_index=[1.386, 1.374, 1.367],
    g=0.9,
)

# Response functions receive NumPy arrays and return arrays of the same shape.
def angular_acceptance(head_on_cosine):
    return np.ones_like(np.asarray(head_on_cosine, dtype=float))

def spectral_efficiency(wavelength_nm):
    return np.full_like(np.asarray(wavelength_nm, dtype=float), 0.20)

detector = lh.DetectorArray(
    positions_m=[[20.0, 0.0, 0.0], [35.0, 0.0, 0.0]],
    orientations=[[-1.0, 0.0, 0.0], [-1.0, 0.0, 0.0]],
    effective_area_m2=0.05,
    angular_acceptance=angular_acceptance,
    spectral_efficiency=spectral_efficiency,
)

source = lh.IsotropicFlash.monochromatic(
    position_m=[0.0, 0.0, 0.0],
    photons=1.0e8,
    wavelength_nm=450.0,
)

# build() returns a reusable kernel and prepares only the tables this source
# needs. The same kernel can then transport more compatible events.
kernel = lh.build(medium, detector, source)
response = kernel.transport(source)

print(response.charge_pe)   # integrated expected photoelectrons, one per OM
print(response.bins_pe)     # expected photoelectrons, shape (OM, time bin)

The first build may take noticeably longer than later event calculations. Set KernelConfig(cache_directory=...) to reuse transport tables across processes.

Sources

The high-level dispatcher accepts:

flash = lh.IsotropicFlash.monochromatic(
    position_m=[0, 0, 0], photons=1e8, wavelength_nm=450
)

track = lh.CherenkovTrack(
    start_m=[0, 0, -20],
    direction=[0.2, 0.1, 0.97],
    length_m=40,
    beta=1.0,
)

shower = lh.G4Shower.from_hdf5("event.h5", event=0)

For tracks and showers, kernel.transport(source) automatically selects the source engine and uses the detector's angular response. Research methods are never selected unless explicitly enabled.

Configuring the calculation

Numerical settings are collected in KernelConfig:

config = lh.KernelConfig(
    wavelength_nodes=9,
    threshold_pe=0.01,
    cache_directory="lighthit-cache",
)

kernel = lh.build(medium, detector, track, config=config)
response = kernel.transport(track)

Important inputs are explicit:

• SpectralMedium contains absorption and scattering coefficients in m⁻¹, phase and group refractive indices, and the Henyey–Greenstein parameter g.
• DetectorArray contains OM positions, orientations, effective areas, angular acceptance and wavelength-dependent detection efficiency.
• A detector orientation points from the OM toward a head-on source; angular_acceptance(+1) is the head-on response.
• spectral_efficiency should include all wavelength-dependent detection factors required by the application, such as quantum efficiency and optical transmission.

Reading the response

kernel.transport(...) returns a TransportResponse.

Absolute bin edges for every module are

absolute_edges_ns = (
    response.time_origin_ns[:, None]
    + response.relative_time_edges_ns[None, :]
)

The integrated charge is evaluated independently at zero frequency. A finite time window and a finite frequency grid mean that bins_pe.sum(axis=1) need not equal charge_pe exactly. Signed ringing is reported rather than silently clipped or renormalised.

Responses can be stored as compressed NumPy files:

response.save("response.npz")

Interactive viewer

Install the optional viewer dependency:

python -m pip install 'lighthit[viewer]'

Turn a response into a standalone interactive HTML file:

payload = lh.viewer_payload(
    response,
    source=source,
    event_id="flash-450nm",
    label="450 nm calibration flash",
)

viewer_path = lh.write_event_viewer(payload, "lighthit-viewer.html")
print(viewer_path)

Open lighthit-viewer.html in a web browser. It contains the detector geometry, integrated charge by scattering order, a selectable per-OM time histogram and a time animation. A portable lighthit-viewer.json companion is written beside the HTML file.

Scope

The current model assumes a homogeneous, unbounded medium with elastic Henyey–Greenstein scattering. It does not include boundaries, layered media, structural shadowing, polarisation, detector electronics, trigger or noise.

License

LightHit is distributed under the BSD 3-Clause License.