Module 6 of 7 · Pārāśara-rājamārga

अष्टकवर्ग-अध्यायः

Aṣṭakavarga-adhyāya

BPHS Ch. 23–26, 76 — The Aṣṭakavarga System

~90 min · 1 prerequisite(s)

Pārāśara's 8-source bindu (point) system — sarvāṣṭakavarga, bhinnāṣṭakavarga, trikoṇa-śodhana, ekādhipya-śodhana, piṇḍa-sādhana.

Viṣaya-sūcī · Topics
  • Aṣṭaka — 'eight' — eight sources (Sūrya, Candra, Maṅgala, Budha, Bṛhaspati, Śukra, Śani, lagna)
  • Bindu-allocation — each of the 8 sources allocates bindus (1 or 0) to each of 12 signs per graha
  • Bhinnāṣṭakavarga — separate aṣṭakavarga for each graha (7 grahas × 8 sources = 56 source-graha pairs)
  • Sarvāṣṭakavarga — sum across all 7 grahas (the 'all-aṣṭakavarga')
  • Two reductions — trikoṇa-śodhana and ekādhipya-śodhana — produce the piṇḍa
  • Transit application — bindu counts in the transiting graha's house signal the transit's quality

1. Saṃkṣepa

साराशं · विषय-विस्तारःSāra-aṃśa · Viṣaya-vistāraSummary — the topic unfolded

Aṣṭakavarga ('eight-source') is one of Pārāśara's most distinctive computational contributions. The idea: each of seven grahas (Sun through Saturn) is given a separate point-table, where each of eight sources (the seven grahas themselves plus the lagna) allocates one or zero bindus (points) to each of twelve signs, based on a fixed classical rule-set. The 56 sub-rules generate 12 bindus per graha-per-source; summed across the eight sources, you get the bhinnāṣṭakavarga of that graha — a 12-cell vector of point-totals indicating the favourability of each rāśi for that graha.

Summed further across all seven grahas, you get the sarvāṣṭakavarga (SAV) — a 12-cell vector of total bindus per rāśi (theoretical maximum 8 × 7 = 56 per cell; usual range 18 to 40). The SAV is one of the most-used transit-prediction inputs in classical practice. When a graha transits a sign with high SAV-bindus for that graha, the transit period tends to yield supportive effects; low bindus suggest a 'thin' transit.

The two reductions — trikoṇa-śodhana (Ch. 24) and ekādhipya-śodhana (Ch. 25) — strip out structural redundancies (triplicity overlaps and single-lordship overlaps), producing a refined piṇḍa value (Ch. 26). The piṇḍa feeds into longevity computation (piṇḍāyu) and other classical algorithms.

2. Śāstra-Pramāṇa

शास्त्र-प्रमाण · ग्रन्थ-निर्देशाःŚāstra-pramāṇa · Grantha-nirdeśāḥClassical anchors — textual references
BPHSCh. 23

Aṣṭakavarga-adhyāya — 8-source bindu (point) computation.

BPHSCh. 24

Trikoṇa-śodhanam — first reduction.

BPHSCh. 25

Ekādhipya-śodhanam — second reduction.

BPHSCh. 26

Piṇḍa-sādhanam — final piṇḍa-yoga (longevity input).

BPHSCh. 76

Aṣṭakavarga-gocara-phala — using bindu counts for transit interpretation.

All anchor references map to chapter structures in our annotated library at /library. We point to topics — the Jyotiṣī interprets, the substrate computes; we do not predict from these texts on your behalf.

3. Abhyāsa

अभ्यासः · प्रयोग-मार्गःAbhyāsa · Prayoga-mārgaPraxis — the path of application

Engine surfaces (substrate compute)

Exercises

  1. Computation

    Open /sarvashtaka for any chart. Identify the rāśi with the highest SAV-bindu total. According to Pārāśara, this is the most-supported rāśi for transits in general.

  2. Computation

    Open /bhinnashtaka. Look at Jupiter's bhinnāṣṭakavarga. Which rāśi has the highest bindu-total for Jupiter? When Jupiter transits that rāśi (every ~12 years), the classical tradition says the transit's effects are amplified.

4. Agrima

अग्रिमम् · पथः निरन्तरःAgrima · Pathaḥ nirantaraNext — the continuing path
ॐ सरस्वत्यै नमः · ॐ हयग्रीवाय नमः
KAAL Truth #5 · structured study · sources cited · the Jyotiṣī interprets